Annotation of imach/src/imach.c, revision 1.281
1.281 ! brouard 1: /* $Id: imach.c,v 1.280 2018/02/21 07:58:13 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.281 ! brouard 4: Revision 1.280 2018/02/21 07:58:13 brouard
! 5: Summary: 0.99r15
! 6:
! 7: New Makefile with recent VirtualBox 5.26. Bug in sqrt negatve in imach.c
! 8:
1.280 brouard 9: Revision 1.279 2017/07/20 13:35:01 brouard
10: Summary: temporary working
11:
1.279 brouard 12: Revision 1.278 2017/07/19 14:09:02 brouard
13: Summary: Bug for mobil_average=0 and prevforecast fixed(?)
14:
1.278 brouard 15: Revision 1.277 2017/07/17 08:53:49 brouard
16: Summary: BOM files can be read now
17:
1.277 brouard 18: Revision 1.276 2017/06/30 15:48:31 brouard
19: Summary: Graphs improvements
20:
1.276 brouard 21: Revision 1.275 2017/06/30 13:39:33 brouard
22: Summary: Saito's color
23:
1.275 brouard 24: Revision 1.274 2017/06/29 09:47:08 brouard
25: Summary: Version 0.99r14
26:
1.274 brouard 27: Revision 1.273 2017/06/27 11:06:02 brouard
28: Summary: More documentation on projections
29:
1.273 brouard 30: Revision 1.272 2017/06/27 10:22:40 brouard
31: Summary: Color of backprojection changed from 6 to 5(yellow)
32:
1.272 brouard 33: Revision 1.271 2017/06/27 10:17:50 brouard
34: Summary: Some bug with rint
35:
1.271 brouard 36: Revision 1.270 2017/05/24 05:45:29 brouard
37: *** empty log message ***
38:
1.270 brouard 39: Revision 1.269 2017/05/23 08:39:25 brouard
40: Summary: Code into subroutine, cleanings
41:
1.269 brouard 42: Revision 1.268 2017/05/18 20:09:32 brouard
43: Summary: backprojection and confidence intervals of backprevalence
44:
1.268 brouard 45: Revision 1.267 2017/05/13 10:25:05 brouard
46: Summary: temporary save for backprojection
47:
1.267 brouard 48: Revision 1.266 2017/05/13 07:26:12 brouard
49: Summary: Version 0.99r13 (improvements and bugs fixed)
50:
1.266 brouard 51: Revision 1.265 2017/04/26 16:22:11 brouard
52: Summary: imach 0.99r13 Some bugs fixed
53:
1.265 brouard 54: Revision 1.264 2017/04/26 06:01:29 brouard
55: Summary: Labels in graphs
56:
1.264 brouard 57: Revision 1.263 2017/04/24 15:23:15 brouard
58: Summary: to save
59:
1.263 brouard 60: Revision 1.262 2017/04/18 16:48:12 brouard
61: *** empty log message ***
62:
1.262 brouard 63: Revision 1.261 2017/04/05 10:14:09 brouard
64: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
65:
1.261 brouard 66: Revision 1.260 2017/04/04 17:46:59 brouard
67: Summary: Gnuplot indexations fixed (humm)
68:
1.260 brouard 69: Revision 1.259 2017/04/04 13:01:16 brouard
70: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
71:
1.259 brouard 72: Revision 1.258 2017/04/03 10:17:47 brouard
73: Summary: Version 0.99r12
74:
75: Some cleanings, conformed with updated documentation.
76:
1.258 brouard 77: Revision 1.257 2017/03/29 16:53:30 brouard
78: Summary: Temp
79:
1.257 brouard 80: Revision 1.256 2017/03/27 05:50:23 brouard
81: Summary: Temporary
82:
1.256 brouard 83: Revision 1.255 2017/03/08 16:02:28 brouard
84: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
85:
1.255 brouard 86: Revision 1.254 2017/03/08 07:13:00 brouard
87: Summary: Fixing data parameter line
88:
1.254 brouard 89: Revision 1.253 2016/12/15 11:59:41 brouard
90: Summary: 0.99 in progress
91:
1.253 brouard 92: Revision 1.252 2016/09/15 21:15:37 brouard
93: *** empty log message ***
94:
1.252 brouard 95: Revision 1.251 2016/09/15 15:01:13 brouard
96: Summary: not working
97:
1.251 brouard 98: Revision 1.250 2016/09/08 16:07:27 brouard
99: Summary: continue
100:
1.250 brouard 101: Revision 1.249 2016/09/07 17:14:18 brouard
102: Summary: Starting values from frequencies
103:
1.249 brouard 104: Revision 1.248 2016/09/07 14:10:18 brouard
105: *** empty log message ***
106:
1.248 brouard 107: Revision 1.247 2016/09/02 11:11:21 brouard
108: *** empty log message ***
109:
1.247 brouard 110: Revision 1.246 2016/09/02 08:49:22 brouard
111: *** empty log message ***
112:
1.246 brouard 113: Revision 1.245 2016/09/02 07:25:01 brouard
114: *** empty log message ***
115:
1.245 brouard 116: Revision 1.244 2016/09/02 07:17:34 brouard
117: *** empty log message ***
118:
1.244 brouard 119: Revision 1.243 2016/09/02 06:45:35 brouard
120: *** empty log message ***
121:
1.243 brouard 122: Revision 1.242 2016/08/30 15:01:20 brouard
123: Summary: Fixing a lots
124:
1.242 brouard 125: Revision 1.241 2016/08/29 17:17:25 brouard
126: Summary: gnuplot problem in Back projection to fix
127:
1.241 brouard 128: Revision 1.240 2016/08/29 07:53:18 brouard
129: Summary: Better
130:
1.240 brouard 131: Revision 1.239 2016/08/26 15:51:03 brouard
132: Summary: Improvement in Powell output in order to copy and paste
133:
134: Author:
135:
1.239 brouard 136: Revision 1.238 2016/08/26 14:23:35 brouard
137: Summary: Starting tests of 0.99
138:
1.238 brouard 139: Revision 1.237 2016/08/26 09:20:19 brouard
140: Summary: to valgrind
141:
1.237 brouard 142: Revision 1.236 2016/08/25 10:50:18 brouard
143: *** empty log message ***
144:
1.236 brouard 145: Revision 1.235 2016/08/25 06:59:23 brouard
146: *** empty log message ***
147:
1.235 brouard 148: Revision 1.234 2016/08/23 16:51:20 brouard
149: *** empty log message ***
150:
1.234 brouard 151: Revision 1.233 2016/08/23 07:40:50 brouard
152: Summary: not working
153:
1.233 brouard 154: Revision 1.232 2016/08/22 14:20:21 brouard
155: Summary: not working
156:
1.232 brouard 157: Revision 1.231 2016/08/22 07:17:15 brouard
158: Summary: not working
159:
1.231 brouard 160: Revision 1.230 2016/08/22 06:55:53 brouard
161: Summary: Not working
162:
1.230 brouard 163: Revision 1.229 2016/07/23 09:45:53 brouard
164: Summary: Completing for func too
165:
1.229 brouard 166: Revision 1.228 2016/07/22 17:45:30 brouard
167: Summary: Fixing some arrays, still debugging
168:
1.227 brouard 169: Revision 1.226 2016/07/12 18:42:34 brouard
170: Summary: temp
171:
1.226 brouard 172: Revision 1.225 2016/07/12 08:40:03 brouard
173: Summary: saving but not running
174:
1.225 brouard 175: Revision 1.224 2016/07/01 13:16:01 brouard
176: Summary: Fixes
177:
1.224 brouard 178: Revision 1.223 2016/02/19 09:23:35 brouard
179: Summary: temporary
180:
1.223 brouard 181: Revision 1.222 2016/02/17 08:14:50 brouard
182: Summary: Probably last 0.98 stable version 0.98r6
183:
1.222 brouard 184: Revision 1.221 2016/02/15 23:35:36 brouard
185: Summary: minor bug
186:
1.220 brouard 187: Revision 1.219 2016/02/15 00:48:12 brouard
188: *** empty log message ***
189:
1.219 brouard 190: Revision 1.218 2016/02/12 11:29:23 brouard
191: Summary: 0.99 Back projections
192:
1.218 brouard 193: Revision 1.217 2015/12/23 17:18:31 brouard
194: Summary: Experimental backcast
195:
1.217 brouard 196: Revision 1.216 2015/12/18 17:32:11 brouard
197: Summary: 0.98r4 Warning and status=-2
198:
199: Version 0.98r4 is now:
200: - displaying an error when status is -1, date of interview unknown and date of death known;
201: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
202: Older changes concerning s=-2, dating from 2005 have been supersed.
203:
1.216 brouard 204: Revision 1.215 2015/12/16 08:52:24 brouard
205: Summary: 0.98r4 working
206:
1.215 brouard 207: Revision 1.214 2015/12/16 06:57:54 brouard
208: Summary: temporary not working
209:
1.214 brouard 210: Revision 1.213 2015/12/11 18:22:17 brouard
211: Summary: 0.98r4
212:
1.213 brouard 213: Revision 1.212 2015/11/21 12:47:24 brouard
214: Summary: minor typo
215:
1.212 brouard 216: Revision 1.211 2015/11/21 12:41:11 brouard
217: Summary: 0.98r3 with some graph of projected cross-sectional
218:
219: Author: Nicolas Brouard
220:
1.211 brouard 221: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 222: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 223: Summary: Adding ftolpl parameter
224: Author: N Brouard
225:
226: We had difficulties to get smoothed confidence intervals. It was due
227: to the period prevalence which wasn't computed accurately. The inner
228: parameter ftolpl is now an outer parameter of the .imach parameter
229: file after estepm. If ftolpl is small 1.e-4 and estepm too,
230: computation are long.
231:
1.209 brouard 232: Revision 1.208 2015/11/17 14:31:57 brouard
233: Summary: temporary
234:
1.208 brouard 235: Revision 1.207 2015/10/27 17:36:57 brouard
236: *** empty log message ***
237:
1.207 brouard 238: Revision 1.206 2015/10/24 07:14:11 brouard
239: *** empty log message ***
240:
1.206 brouard 241: Revision 1.205 2015/10/23 15:50:53 brouard
242: Summary: 0.98r3 some clarification for graphs on likelihood contributions
243:
1.205 brouard 244: Revision 1.204 2015/10/01 16:20:26 brouard
245: Summary: Some new graphs of contribution to likelihood
246:
1.204 brouard 247: Revision 1.203 2015/09/30 17:45:14 brouard
248: Summary: looking at better estimation of the hessian
249:
250: Also a better criteria for convergence to the period prevalence And
251: therefore adding the number of years needed to converge. (The
252: prevalence in any alive state shold sum to one
253:
1.203 brouard 254: Revision 1.202 2015/09/22 19:45:16 brouard
255: Summary: Adding some overall graph on contribution to likelihood. Might change
256:
1.202 brouard 257: Revision 1.201 2015/09/15 17:34:58 brouard
258: Summary: 0.98r0
259:
260: - Some new graphs like suvival functions
261: - Some bugs fixed like model=1+age+V2.
262:
1.201 brouard 263: Revision 1.200 2015/09/09 16:53:55 brouard
264: Summary: Big bug thanks to Flavia
265:
266: Even model=1+age+V2. did not work anymore
267:
1.200 brouard 268: Revision 1.199 2015/09/07 14:09:23 brouard
269: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
270:
1.199 brouard 271: Revision 1.198 2015/09/03 07:14:39 brouard
272: Summary: 0.98q5 Flavia
273:
1.198 brouard 274: Revision 1.197 2015/09/01 18:24:39 brouard
275: *** empty log message ***
276:
1.197 brouard 277: Revision 1.196 2015/08/18 23:17:52 brouard
278: Summary: 0.98q5
279:
1.196 brouard 280: Revision 1.195 2015/08/18 16:28:39 brouard
281: Summary: Adding a hack for testing purpose
282:
283: After reading the title, ftol and model lines, if the comment line has
284: a q, starting with #q, the answer at the end of the run is quit. It
285: permits to run test files in batch with ctest. The former workaround was
286: $ echo q | imach foo.imach
287:
1.195 brouard 288: Revision 1.194 2015/08/18 13:32:00 brouard
289: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
290:
1.194 brouard 291: Revision 1.193 2015/08/04 07:17:42 brouard
292: Summary: 0.98q4
293:
1.193 brouard 294: Revision 1.192 2015/07/16 16:49:02 brouard
295: Summary: Fixing some outputs
296:
1.192 brouard 297: Revision 1.191 2015/07/14 10:00:33 brouard
298: Summary: Some fixes
299:
1.191 brouard 300: Revision 1.190 2015/05/05 08:51:13 brouard
301: Summary: Adding digits in output parameters (7 digits instead of 6)
302:
303: Fix 1+age+.
304:
1.190 brouard 305: Revision 1.189 2015/04/30 14:45:16 brouard
306: Summary: 0.98q2
307:
1.189 brouard 308: Revision 1.188 2015/04/30 08:27:53 brouard
309: *** empty log message ***
310:
1.188 brouard 311: Revision 1.187 2015/04/29 09:11:15 brouard
312: *** empty log message ***
313:
1.187 brouard 314: Revision 1.186 2015/04/23 12:01:52 brouard
315: Summary: V1*age is working now, version 0.98q1
316:
317: Some codes had been disabled in order to simplify and Vn*age was
318: working in the optimization phase, ie, giving correct MLE parameters,
319: but, as usual, outputs were not correct and program core dumped.
320:
1.186 brouard 321: Revision 1.185 2015/03/11 13:26:42 brouard
322: Summary: Inclusion of compile and links command line for Intel Compiler
323:
1.185 brouard 324: Revision 1.184 2015/03/11 11:52:39 brouard
325: Summary: Back from Windows 8. Intel Compiler
326:
1.184 brouard 327: Revision 1.183 2015/03/10 20:34:32 brouard
328: Summary: 0.98q0, trying with directest, mnbrak fixed
329:
330: We use directest instead of original Powell test; probably no
331: incidence on the results, but better justifications;
332: We fixed Numerical Recipes mnbrak routine which was wrong and gave
333: wrong results.
334:
1.183 brouard 335: Revision 1.182 2015/02/12 08:19:57 brouard
336: Summary: Trying to keep directest which seems simpler and more general
337: Author: Nicolas Brouard
338:
1.182 brouard 339: Revision 1.181 2015/02/11 23:22:24 brouard
340: Summary: Comments on Powell added
341:
342: Author:
343:
1.181 brouard 344: Revision 1.180 2015/02/11 17:33:45 brouard
345: Summary: Finishing move from main to function (hpijx and prevalence_limit)
346:
1.180 brouard 347: Revision 1.179 2015/01/04 09:57:06 brouard
348: Summary: back to OS/X
349:
1.179 brouard 350: Revision 1.178 2015/01/04 09:35:48 brouard
351: *** empty log message ***
352:
1.178 brouard 353: Revision 1.177 2015/01/03 18:40:56 brouard
354: Summary: Still testing ilc32 on OSX
355:
1.177 brouard 356: Revision 1.176 2015/01/03 16:45:04 brouard
357: *** empty log message ***
358:
1.176 brouard 359: Revision 1.175 2015/01/03 16:33:42 brouard
360: *** empty log message ***
361:
1.175 brouard 362: Revision 1.174 2015/01/03 16:15:49 brouard
363: Summary: Still in cross-compilation
364:
1.174 brouard 365: Revision 1.173 2015/01/03 12:06:26 brouard
366: Summary: trying to detect cross-compilation
367:
1.173 brouard 368: Revision 1.172 2014/12/27 12:07:47 brouard
369: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
370:
1.172 brouard 371: Revision 1.171 2014/12/23 13:26:59 brouard
372: Summary: Back from Visual C
373:
374: Still problem with utsname.h on Windows
375:
1.171 brouard 376: Revision 1.170 2014/12/23 11:17:12 brouard
377: Summary: Cleaning some \%% back to %%
378:
379: The escape was mandatory for a specific compiler (which one?), but too many warnings.
380:
1.170 brouard 381: Revision 1.169 2014/12/22 23:08:31 brouard
382: Summary: 0.98p
383:
384: Outputs some informations on compiler used, OS etc. Testing on different platforms.
385:
1.169 brouard 386: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 387: Summary: update
1.169 brouard 388:
1.168 brouard 389: Revision 1.167 2014/12/22 13:50:56 brouard
390: Summary: Testing uname and compiler version and if compiled 32 or 64
391:
392: Testing on Linux 64
393:
1.167 brouard 394: Revision 1.166 2014/12/22 11:40:47 brouard
395: *** empty log message ***
396:
1.166 brouard 397: Revision 1.165 2014/12/16 11:20:36 brouard
398: Summary: After compiling on Visual C
399:
400: * imach.c (Module): Merging 1.61 to 1.162
401:
1.165 brouard 402: Revision 1.164 2014/12/16 10:52:11 brouard
403: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
404:
405: * imach.c (Module): Merging 1.61 to 1.162
406:
1.164 brouard 407: Revision 1.163 2014/12/16 10:30:11 brouard
408: * imach.c (Module): Merging 1.61 to 1.162
409:
1.163 brouard 410: Revision 1.162 2014/09/25 11:43:39 brouard
411: Summary: temporary backup 0.99!
412:
1.162 brouard 413: Revision 1.1 2014/09/16 11:06:58 brouard
414: Summary: With some code (wrong) for nlopt
415:
416: Author:
417:
418: Revision 1.161 2014/09/15 20:41:41 brouard
419: Summary: Problem with macro SQR on Intel compiler
420:
1.161 brouard 421: Revision 1.160 2014/09/02 09:24:05 brouard
422: *** empty log message ***
423:
1.160 brouard 424: Revision 1.159 2014/09/01 10:34:10 brouard
425: Summary: WIN32
426: Author: Brouard
427:
1.159 brouard 428: Revision 1.158 2014/08/27 17:11:51 brouard
429: *** empty log message ***
430:
1.158 brouard 431: Revision 1.157 2014/08/27 16:26:55 brouard
432: Summary: Preparing windows Visual studio version
433: Author: Brouard
434:
435: In order to compile on Visual studio, time.h is now correct and time_t
436: and tm struct should be used. difftime should be used but sometimes I
437: just make the differences in raw time format (time(&now).
438: Trying to suppress #ifdef LINUX
439: Add xdg-open for __linux in order to open default browser.
440:
1.157 brouard 441: Revision 1.156 2014/08/25 20:10:10 brouard
442: *** empty log message ***
443:
1.156 brouard 444: Revision 1.155 2014/08/25 18:32:34 brouard
445: Summary: New compile, minor changes
446: Author: Brouard
447:
1.155 brouard 448: Revision 1.154 2014/06/20 17:32:08 brouard
449: Summary: Outputs now all graphs of convergence to period prevalence
450:
1.154 brouard 451: Revision 1.153 2014/06/20 16:45:46 brouard
452: Summary: If 3 live state, convergence to period prevalence on same graph
453: Author: Brouard
454:
1.153 brouard 455: Revision 1.152 2014/06/18 17:54:09 brouard
456: Summary: open browser, use gnuplot on same dir than imach if not found in the path
457:
1.152 brouard 458: Revision 1.151 2014/06/18 16:43:30 brouard
459: *** empty log message ***
460:
1.151 brouard 461: Revision 1.150 2014/06/18 16:42:35 brouard
462: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
463: Author: brouard
464:
1.150 brouard 465: Revision 1.149 2014/06/18 15:51:14 brouard
466: Summary: Some fixes in parameter files errors
467: Author: Nicolas Brouard
468:
1.149 brouard 469: Revision 1.148 2014/06/17 17:38:48 brouard
470: Summary: Nothing new
471: Author: Brouard
472:
473: Just a new packaging for OS/X version 0.98nS
474:
1.148 brouard 475: Revision 1.147 2014/06/16 10:33:11 brouard
476: *** empty log message ***
477:
1.147 brouard 478: Revision 1.146 2014/06/16 10:20:28 brouard
479: Summary: Merge
480: Author: Brouard
481:
482: Merge, before building revised version.
483:
1.146 brouard 484: Revision 1.145 2014/06/10 21:23:15 brouard
485: Summary: Debugging with valgrind
486: Author: Nicolas Brouard
487:
488: Lot of changes in order to output the results with some covariates
489: After the Edimburgh REVES conference 2014, it seems mandatory to
490: improve the code.
491: No more memory valgrind error but a lot has to be done in order to
492: continue the work of splitting the code into subroutines.
493: Also, decodemodel has been improved. Tricode is still not
494: optimal. nbcode should be improved. Documentation has been added in
495: the source code.
496:
1.144 brouard 497: Revision 1.143 2014/01/26 09:45:38 brouard
498: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
499:
500: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
501: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
502:
1.143 brouard 503: Revision 1.142 2014/01/26 03:57:36 brouard
504: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
505:
506: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
507:
1.142 brouard 508: Revision 1.141 2014/01/26 02:42:01 brouard
509: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
510:
1.141 brouard 511: Revision 1.140 2011/09/02 10:37:54 brouard
512: Summary: times.h is ok with mingw32 now.
513:
1.140 brouard 514: Revision 1.139 2010/06/14 07:50:17 brouard
515: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
516: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
517:
1.139 brouard 518: Revision 1.138 2010/04/30 18:19:40 brouard
519: *** empty log message ***
520:
1.138 brouard 521: Revision 1.137 2010/04/29 18:11:38 brouard
522: (Module): Checking covariates for more complex models
523: than V1+V2. A lot of change to be done. Unstable.
524:
1.137 brouard 525: Revision 1.136 2010/04/26 20:30:53 brouard
526: (Module): merging some libgsl code. Fixing computation
527: of likelione (using inter/intrapolation if mle = 0) in order to
528: get same likelihood as if mle=1.
529: Some cleaning of code and comments added.
530:
1.136 brouard 531: Revision 1.135 2009/10/29 15:33:14 brouard
532: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
533:
1.135 brouard 534: Revision 1.134 2009/10/29 13:18:53 brouard
535: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
536:
1.134 brouard 537: Revision 1.133 2009/07/06 10:21:25 brouard
538: just nforces
539:
1.133 brouard 540: Revision 1.132 2009/07/06 08:22:05 brouard
541: Many tings
542:
1.132 brouard 543: Revision 1.131 2009/06/20 16:22:47 brouard
544: Some dimensions resccaled
545:
1.131 brouard 546: Revision 1.130 2009/05/26 06:44:34 brouard
547: (Module): Max Covariate is now set to 20 instead of 8. A
548: lot of cleaning with variables initialized to 0. Trying to make
549: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
550:
1.130 brouard 551: Revision 1.129 2007/08/31 13:49:27 lievre
552: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
553:
1.129 lievre 554: Revision 1.128 2006/06/30 13:02:05 brouard
555: (Module): Clarifications on computing e.j
556:
1.128 brouard 557: Revision 1.127 2006/04/28 18:11:50 brouard
558: (Module): Yes the sum of survivors was wrong since
559: imach-114 because nhstepm was no more computed in the age
560: loop. Now we define nhstepma in the age loop.
561: (Module): In order to speed up (in case of numerous covariates) we
562: compute health expectancies (without variances) in a first step
563: and then all the health expectancies with variances or standard
564: deviation (needs data from the Hessian matrices) which slows the
565: computation.
566: In the future we should be able to stop the program is only health
567: expectancies and graph are needed without standard deviations.
568:
1.127 brouard 569: Revision 1.126 2006/04/28 17:23:28 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: Version 0.98h
574:
1.126 brouard 575: Revision 1.125 2006/04/04 15:20:31 lievre
576: Errors in calculation of health expectancies. Age was not initialized.
577: Forecasting file added.
578:
579: Revision 1.124 2006/03/22 17:13:53 lievre
580: Parameters are printed with %lf instead of %f (more numbers after the comma).
581: The log-likelihood is printed in the log file
582:
583: Revision 1.123 2006/03/20 10:52:43 brouard
584: * imach.c (Module): <title> changed, corresponds to .htm file
585: name. <head> headers where missing.
586:
587: * imach.c (Module): Weights can have a decimal point as for
588: English (a comma might work with a correct LC_NUMERIC environment,
589: otherwise the weight is truncated).
590: Modification of warning when the covariates values are not 0 or
591: 1.
592: Version 0.98g
593:
594: Revision 1.122 2006/03/20 09:45:41 brouard
595: (Module): Weights can have a decimal point as for
596: English (a comma might work with a correct LC_NUMERIC environment,
597: otherwise the weight is truncated).
598: Modification of warning when the covariates values are not 0 or
599: 1.
600: Version 0.98g
601:
602: Revision 1.121 2006/03/16 17:45:01 lievre
603: * imach.c (Module): Comments concerning covariates added
604:
605: * imach.c (Module): refinements in the computation of lli if
606: status=-2 in order to have more reliable computation if stepm is
607: not 1 month. Version 0.98f
608:
609: Revision 1.120 2006/03/16 15:10:38 lievre
610: (Module): refinements in the computation of lli if
611: status=-2 in order to have more reliable computation if stepm is
612: not 1 month. Version 0.98f
613:
614: Revision 1.119 2006/03/15 17:42:26 brouard
615: (Module): Bug if status = -2, the loglikelihood was
616: computed as likelihood omitting the logarithm. Version O.98e
617:
618: Revision 1.118 2006/03/14 18:20:07 brouard
619: (Module): varevsij Comments added explaining the second
620: table of variances if popbased=1 .
621: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
622: (Module): Function pstamp added
623: (Module): Version 0.98d
624:
625: Revision 1.117 2006/03/14 17:16:22 brouard
626: (Module): varevsij Comments added explaining the second
627: table of variances if popbased=1 .
628: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
629: (Module): Function pstamp added
630: (Module): Version 0.98d
631:
632: Revision 1.116 2006/03/06 10:29:27 brouard
633: (Module): Variance-covariance wrong links and
634: varian-covariance of ej. is needed (Saito).
635:
636: Revision 1.115 2006/02/27 12:17:45 brouard
637: (Module): One freematrix added in mlikeli! 0.98c
638:
639: Revision 1.114 2006/02/26 12:57:58 brouard
640: (Module): Some improvements in processing parameter
641: filename with strsep.
642:
643: Revision 1.113 2006/02/24 14:20:24 brouard
644: (Module): Memory leaks checks with valgrind and:
645: datafile was not closed, some imatrix were not freed and on matrix
646: allocation too.
647:
648: Revision 1.112 2006/01/30 09:55:26 brouard
649: (Module): Back to gnuplot.exe instead of wgnuplot.exe
650:
651: Revision 1.111 2006/01/25 20:38:18 brouard
652: (Module): Lots of cleaning and bugs added (Gompertz)
653: (Module): Comments can be added in data file. Missing date values
654: can be a simple dot '.'.
655:
656: Revision 1.110 2006/01/25 00:51:50 brouard
657: (Module): Lots of cleaning and bugs added (Gompertz)
658:
659: Revision 1.109 2006/01/24 19:37:15 brouard
660: (Module): Comments (lines starting with a #) are allowed in data.
661:
662: Revision 1.108 2006/01/19 18:05:42 lievre
663: Gnuplot problem appeared...
664: To be fixed
665:
666: Revision 1.107 2006/01/19 16:20:37 brouard
667: Test existence of gnuplot in imach path
668:
669: Revision 1.106 2006/01/19 13:24:36 brouard
670: Some cleaning and links added in html output
671:
672: Revision 1.105 2006/01/05 20:23:19 lievre
673: *** empty log message ***
674:
675: Revision 1.104 2005/09/30 16:11:43 lievre
676: (Module): sump fixed, loop imx fixed, and simplifications.
677: (Module): If the status is missing at the last wave but we know
678: that the person is alive, then we can code his/her status as -2
679: (instead of missing=-1 in earlier versions) and his/her
680: contributions to the likelihood is 1 - Prob of dying from last
681: health status (= 1-p13= p11+p12 in the easiest case of somebody in
682: the healthy state at last known wave). Version is 0.98
683:
684: Revision 1.103 2005/09/30 15:54:49 lievre
685: (Module): sump fixed, loop imx fixed, and simplifications.
686:
687: Revision 1.102 2004/09/15 17:31:30 brouard
688: Add the possibility to read data file including tab characters.
689:
690: Revision 1.101 2004/09/15 10:38:38 brouard
691: Fix on curr_time
692:
693: Revision 1.100 2004/07/12 18:29:06 brouard
694: Add version for Mac OS X. Just define UNIX in Makefile
695:
696: Revision 1.99 2004/06/05 08:57:40 brouard
697: *** empty log message ***
698:
699: Revision 1.98 2004/05/16 15:05:56 brouard
700: New version 0.97 . First attempt to estimate force of mortality
701: directly from the data i.e. without the need of knowing the health
702: state at each age, but using a Gompertz model: log u =a + b*age .
703: This is the basic analysis of mortality and should be done before any
704: other analysis, in order to test if the mortality estimated from the
705: cross-longitudinal survey is different from the mortality estimated
706: from other sources like vital statistic data.
707:
708: The same imach parameter file can be used but the option for mle should be -3.
709:
1.133 brouard 710: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 711: former routines in order to include the new code within the former code.
712:
713: The output is very simple: only an estimate of the intercept and of
714: the slope with 95% confident intervals.
715:
716: Current limitations:
717: A) Even if you enter covariates, i.e. with the
718: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
719: B) There is no computation of Life Expectancy nor Life Table.
720:
721: Revision 1.97 2004/02/20 13:25:42 lievre
722: Version 0.96d. Population forecasting command line is (temporarily)
723: suppressed.
724:
725: Revision 1.96 2003/07/15 15:38:55 brouard
726: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
727: rewritten within the same printf. Workaround: many printfs.
728:
729: Revision 1.95 2003/07/08 07:54:34 brouard
730: * imach.c (Repository):
731: (Repository): Using imachwizard code to output a more meaningful covariance
732: matrix (cov(a12,c31) instead of numbers.
733:
734: Revision 1.94 2003/06/27 13:00:02 brouard
735: Just cleaning
736:
737: Revision 1.93 2003/06/25 16:33:55 brouard
738: (Module): On windows (cygwin) function asctime_r doesn't
739: exist so I changed back to asctime which exists.
740: (Module): Version 0.96b
741:
742: Revision 1.92 2003/06/25 16:30:45 brouard
743: (Module): On windows (cygwin) function asctime_r doesn't
744: exist so I changed back to asctime which exists.
745:
746: Revision 1.91 2003/06/25 15:30:29 brouard
747: * imach.c (Repository): Duplicated warning errors corrected.
748: (Repository): Elapsed time after each iteration is now output. It
749: helps to forecast when convergence will be reached. Elapsed time
750: is stamped in powell. We created a new html file for the graphs
751: concerning matrix of covariance. It has extension -cov.htm.
752:
753: Revision 1.90 2003/06/24 12:34:15 brouard
754: (Module): Some bugs corrected for windows. Also, when
755: mle=-1 a template is output in file "or"mypar.txt with the design
756: of the covariance matrix to be input.
757:
758: Revision 1.89 2003/06/24 12:30:52 brouard
759: (Module): Some bugs corrected for windows. Also, when
760: mle=-1 a template is output in file "or"mypar.txt with the design
761: of the covariance matrix to be input.
762:
763: Revision 1.88 2003/06/23 17:54:56 brouard
764: * 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.
765:
766: Revision 1.87 2003/06/18 12:26:01 brouard
767: Version 0.96
768:
769: Revision 1.86 2003/06/17 20:04:08 brouard
770: (Module): Change position of html and gnuplot routines and added
771: routine fileappend.
772:
773: Revision 1.85 2003/06/17 13:12:43 brouard
774: * imach.c (Repository): Check when date of death was earlier that
775: current date of interview. It may happen when the death was just
776: prior to the death. In this case, dh was negative and likelihood
777: was wrong (infinity). We still send an "Error" but patch by
778: assuming that the date of death was just one stepm after the
779: interview.
780: (Repository): Because some people have very long ID (first column)
781: we changed int to long in num[] and we added a new lvector for
782: memory allocation. But we also truncated to 8 characters (left
783: truncation)
784: (Repository): No more line truncation errors.
785:
786: Revision 1.84 2003/06/13 21:44:43 brouard
787: * imach.c (Repository): Replace "freqsummary" at a correct
788: place. It differs from routine "prevalence" which may be called
789: many times. Probs is memory consuming and must be used with
790: parcimony.
791: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
792:
793: Revision 1.83 2003/06/10 13:39:11 lievre
794: *** empty log message ***
795:
796: Revision 1.82 2003/06/05 15:57:20 brouard
797: Add log in imach.c and fullversion number is now printed.
798:
799: */
800: /*
801: Interpolated Markov Chain
802:
803: Short summary of the programme:
804:
1.227 brouard 805: This program computes Healthy Life Expectancies or State-specific
806: (if states aren't health statuses) Expectancies from
807: cross-longitudinal data. Cross-longitudinal data consist in:
808:
809: -1- a first survey ("cross") where individuals from different ages
810: are interviewed on their health status or degree of disability (in
811: the case of a health survey which is our main interest)
812:
813: -2- at least a second wave of interviews ("longitudinal") which
814: measure each change (if any) in individual health status. Health
815: expectancies are computed from the time spent in each health state
816: according to a model. More health states you consider, more time is
817: necessary to reach the Maximum Likelihood of the parameters involved
818: in the model. The simplest model is the multinomial logistic model
819: where pij is the probability to be observed in state j at the second
820: wave conditional to be observed in state i at the first
821: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
822: etc , where 'age' is age and 'sex' is a covariate. If you want to
823: have a more complex model than "constant and age", you should modify
824: the program where the markup *Covariates have to be included here
825: again* invites you to do it. More covariates you add, slower the
1.126 brouard 826: convergence.
827:
828: The advantage of this computer programme, compared to a simple
829: multinomial logistic model, is clear when the delay between waves is not
830: identical for each individual. Also, if a individual missed an
831: intermediate interview, the information is lost, but taken into
832: account using an interpolation or extrapolation.
833:
834: hPijx is the probability to be observed in state i at age x+h
835: conditional to the observed state i at age x. The delay 'h' can be
836: split into an exact number (nh*stepm) of unobserved intermediate
837: states. This elementary transition (by month, quarter,
838: semester or year) is modelled as a multinomial logistic. The hPx
839: matrix is simply the matrix product of nh*stepm elementary matrices
840: and the contribution of each individual to the likelihood is simply
841: hPijx.
842:
843: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 844: of the life expectancies. It also computes the period (stable) prevalence.
845:
846: Back prevalence and projections:
1.227 brouard 847:
848: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
849: double agemaxpar, double ftolpl, int *ncvyearp, double
850: dateprev1,double dateprev2, int firstpass, int lastpass, int
851: mobilavproj)
852:
853: Computes the back prevalence limit for any combination of
854: covariate values k at any age between ageminpar and agemaxpar and
855: returns it in **bprlim. In the loops,
856:
857: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
858: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
859:
860: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 861: Computes for any combination of covariates k and any age between bage and fage
862: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
863: oldm=oldms;savm=savms;
1.227 brouard 864:
1.267 brouard 865: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 866: Computes the transition matrix starting at age 'age' over
867: 'nhstepm*hstepm*stepm' months (i.e. until
868: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 869: nhstepm*hstepm matrices.
870:
871: Returns p3mat[i][j][h] after calling
872: p3mat[i][j][h]=matprod2(newm,
873: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
874: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
875: oldm);
1.226 brouard 876:
877: Important routines
878:
879: - func (or funcone), computes logit (pij) distinguishing
880: o fixed variables (single or product dummies or quantitative);
881: o varying variables by:
882: (1) wave (single, product dummies, quantitative),
883: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
884: % fixed dummy (treated) or quantitative (not done because time-consuming);
885: % varying dummy (not done) or quantitative (not done);
886: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
887: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
888: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
889: o There are 2*cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
890: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 891:
1.226 brouard 892:
893:
1.133 brouard 894: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
895: Institut national d'études démographiques, Paris.
1.126 brouard 896: This software have been partly granted by Euro-REVES, a concerted action
897: from the European Union.
898: It is copyrighted identically to a GNU software product, ie programme and
899: software can be distributed freely for non commercial use. Latest version
900: can be accessed at http://euroreves.ined.fr/imach .
901:
902: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
903: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
904:
905: **********************************************************************/
906: /*
907: main
908: read parameterfile
909: read datafile
910: concatwav
911: freqsummary
912: if (mle >= 1)
913: mlikeli
914: print results files
915: if mle==1
916: computes hessian
917: read end of parameter file: agemin, agemax, bage, fage, estepm
918: begin-prev-date,...
919: open gnuplot file
920: open html file
1.145 brouard 921: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
922: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
923: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
924: freexexit2 possible for memory heap.
925:
926: h Pij x | pij_nom ficrestpij
927: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
928: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
929: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
930:
931: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
932: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
933: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
934: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
935: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
936:
1.126 brouard 937: forecasting if prevfcast==1 prevforecast call prevalence()
938: health expectancies
939: Variance-covariance of DFLE
940: prevalence()
941: movingaverage()
942: varevsij()
943: if popbased==1 varevsij(,popbased)
944: total life expectancies
945: Variance of period (stable) prevalence
946: end
947: */
948:
1.187 brouard 949: /* #define DEBUG */
950: /* #define DEBUGBRENT */
1.203 brouard 951: /* #define DEBUGLINMIN */
952: /* #define DEBUGHESS */
953: #define DEBUGHESSIJ
1.224 brouard 954: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 955: #define POWELL /* Instead of NLOPT */
1.224 brouard 956: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 957: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
958: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.126 brouard 959:
960: #include <math.h>
961: #include <stdio.h>
962: #include <stdlib.h>
963: #include <string.h>
1.226 brouard 964: #include <ctype.h>
1.159 brouard 965:
966: #ifdef _WIN32
967: #include <io.h>
1.172 brouard 968: #include <windows.h>
969: #include <tchar.h>
1.159 brouard 970: #else
1.126 brouard 971: #include <unistd.h>
1.159 brouard 972: #endif
1.126 brouard 973:
974: #include <limits.h>
975: #include <sys/types.h>
1.171 brouard 976:
977: #if defined(__GNUC__)
978: #include <sys/utsname.h> /* Doesn't work on Windows */
979: #endif
980:
1.126 brouard 981: #include <sys/stat.h>
982: #include <errno.h>
1.159 brouard 983: /* extern int errno; */
1.126 brouard 984:
1.157 brouard 985: /* #ifdef LINUX */
986: /* #include <time.h> */
987: /* #include "timeval.h" */
988: /* #else */
989: /* #include <sys/time.h> */
990: /* #endif */
991:
1.126 brouard 992: #include <time.h>
993:
1.136 brouard 994: #ifdef GSL
995: #include <gsl/gsl_errno.h>
996: #include <gsl/gsl_multimin.h>
997: #endif
998:
1.167 brouard 999:
1.162 brouard 1000: #ifdef NLOPT
1001: #include <nlopt.h>
1002: typedef struct {
1003: double (* function)(double [] );
1004: } myfunc_data ;
1005: #endif
1006:
1.126 brouard 1007: /* #include <libintl.h> */
1008: /* #define _(String) gettext (String) */
1009:
1.251 brouard 1010: #define MAXLINE 2048 /* Was 256 and 1024. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 1011:
1012: #define GNUPLOTPROGRAM "gnuplot"
1013: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
1014: #define FILENAMELENGTH 132
1015:
1016: #define GLOCK_ERROR_NOPATH -1 /* empty path */
1017: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
1018:
1.144 brouard 1019: #define MAXPARM 128 /**< Maximum number of parameters for the optimization */
1020: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 1021:
1022: #define NINTERVMAX 8
1.144 brouard 1023: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
1024: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
1025: #define NCOVMAX 20 /**< Maximum number of covariates, including generated covariates V1*V2 */
1.197 brouard 1026: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 1027: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
1028: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.126 brouard 1029: #define MAXN 20000
1.144 brouard 1030: #define YEARM 12. /**< Number of months per year */
1.218 brouard 1031: /* #define AGESUP 130 */
1032: #define AGESUP 150
1.268 brouard 1033: #define AGEINF 0
1.218 brouard 1034: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1035: #define AGEBASE 40
1.194 brouard 1036: #define AGEOVERFLOW 1.e20
1.164 brouard 1037: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1038: #ifdef _WIN32
1039: #define DIRSEPARATOR '\\'
1040: #define CHARSEPARATOR "\\"
1041: #define ODIRSEPARATOR '/'
1042: #else
1.126 brouard 1043: #define DIRSEPARATOR '/'
1044: #define CHARSEPARATOR "/"
1045: #define ODIRSEPARATOR '\\'
1046: #endif
1047:
1.281 ! brouard 1048: /* $Id: imach.c,v 1.280 2018/02/21 07:58:13 brouard Exp $ */
1.126 brouard 1049: /* $State: Exp $ */
1.196 brouard 1050: #include "version.h"
1051: char version[]=__IMACH_VERSION__;
1.224 brouard 1052: char copyright[]="February 2016,INED-EUROREVES-Institut de longevite-Japan Society for the Promotion of Science (Grant-in-Aid for Scientific Research 25293121), Intel Software 2015-2018";
1.281 ! brouard 1053: char fullversion[]="$Revision: 1.280 $ $Date: 2018/02/21 07:58:13 $";
1.126 brouard 1054: char strstart[80];
1055: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1056: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.187 brouard 1057: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.145 brouard 1058: /* Number of covariates model=V2+V1+ V3*age+V2*V4 */
1059: int cptcovn=0; /**< cptcovn number of covariates added in the model (excepting constant and age and age*product) */
1060: int cptcovt=0; /**< cptcovt number of covariates added in the model (excepting constant and age) */
1.225 brouard 1061: int cptcovs=0; /**< cptcovs number of simple covariates in the model V2+V1 =2 */
1062: int cptcovsnq=0; /**< cptcovsnq number of simple covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1063: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1064: int cptcovprodnoage=0; /**< Number of covariate products without age */
1065: int cptcoveff=0; /* Total number of covariates to vary for printing results */
1.233 brouard 1066: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1067: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.232 brouard 1068: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (dummy of quantitative) in the model */
1.234 brouard 1069: int nsd=0; /**< Total number of single dummy variables (output) */
1070: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1071: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1072: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1073: int ntveff=0; /**< ntveff number of effective time varying variables */
1074: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1075: int cptcov=0; /* Working variable */
1.218 brouard 1076: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.126 brouard 1077: int npar=NPARMAX;
1078: int nlstate=2; /* Number of live states */
1079: int ndeath=1; /* Number of dead states */
1.130 brouard 1080: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.223 brouard 1081: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable */
1.126 brouard 1082: int popbased=0;
1083:
1084: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1085: int maxwav=0; /* Maxim number of waves */
1086: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1087: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1088: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 1089: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1090: int mle=1, weightopt=0;
1.126 brouard 1091: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1092: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1093: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1094: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1095: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1096: int selected(int kvar); /* Is covariate kvar selected for printing results */
1097:
1.130 brouard 1098: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1099: double **matprod2(); /* test */
1.126 brouard 1100: double **oldm, **newm, **savm; /* Working pointers to matrices */
1101: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1102: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1103:
1.136 brouard 1104: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1105: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1106: FILE *ficlog, *ficrespow;
1.130 brouard 1107: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1108: double fretone; /* Only one call to likelihood */
1.130 brouard 1109: long ipmx=0; /* Number of contributions */
1.126 brouard 1110: double sw; /* Sum of weights */
1111: char filerespow[FILENAMELENGTH];
1112: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1113: FILE *ficresilk;
1114: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1115: FILE *ficresprobmorprev;
1116: FILE *fichtm, *fichtmcov; /* Html File */
1117: FILE *ficreseij;
1118: char filerese[FILENAMELENGTH];
1119: FILE *ficresstdeij;
1120: char fileresstde[FILENAMELENGTH];
1121: FILE *ficrescveij;
1122: char filerescve[FILENAMELENGTH];
1123: FILE *ficresvij;
1124: char fileresv[FILENAMELENGTH];
1.269 brouard 1125:
1.126 brouard 1126: char title[MAXLINE];
1.234 brouard 1127: char model[MAXLINE]; /**< The model line */
1.217 brouard 1128: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1129: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1130: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1131: char command[FILENAMELENGTH];
1132: int outcmd=0;
1133:
1.217 brouard 1134: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1135: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1136: char filelog[FILENAMELENGTH]; /* Log file */
1137: char filerest[FILENAMELENGTH];
1138: char fileregp[FILENAMELENGTH];
1139: char popfile[FILENAMELENGTH];
1140:
1141: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1142:
1.157 brouard 1143: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1144: /* struct timezone tzp; */
1145: /* extern int gettimeofday(); */
1146: struct tm tml, *gmtime(), *localtime();
1147:
1148: extern time_t time();
1149:
1150: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1151: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1152: struct tm tm;
1153:
1.126 brouard 1154: char strcurr[80], strfor[80];
1155:
1156: char *endptr;
1157: long lval;
1158: double dval;
1159:
1160: #define NR_END 1
1161: #define FREE_ARG char*
1162: #define FTOL 1.0e-10
1163:
1164: #define NRANSI
1.240 brouard 1165: #define ITMAX 200
1166: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1167:
1168: #define TOL 2.0e-4
1169:
1170: #define CGOLD 0.3819660
1171: #define ZEPS 1.0e-10
1172: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1173:
1174: #define GOLD 1.618034
1175: #define GLIMIT 100.0
1176: #define TINY 1.0e-20
1177:
1178: static double maxarg1,maxarg2;
1179: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1180: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1181:
1182: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1183: #define rint(a) floor(a+0.5)
1.166 brouard 1184: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1185: #define mytinydouble 1.0e-16
1.166 brouard 1186: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1187: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1188: /* static double dsqrarg; */
1189: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1190: static double sqrarg;
1191: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1192: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1193: int agegomp= AGEGOMP;
1194:
1195: int imx;
1196: int stepm=1;
1197: /* Stepm, step in month: minimum step interpolation*/
1198:
1199: int estepm;
1200: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1201:
1202: int m,nb;
1203: long *num;
1.197 brouard 1204: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1205: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1206: covariate for which somebody answered excluding
1207: undefined. Usually 2: 0 and 1. */
1208: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1209: covariate for which somebody answered including
1210: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1211: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1212: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1213: double ***mobaverage, ***mobaverages; /* New global variable */
1.126 brouard 1214: double *ageexmed,*agecens;
1215: double dateintmean=0;
1216:
1217: double *weight;
1218: int **s; /* Status */
1.141 brouard 1219: double *agedc;
1.145 brouard 1220: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1221: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1222: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1223: double **coqvar; /* Fixed quantitative covariate nqv */
1224: double ***cotvar; /* Time varying covariate ntv */
1.225 brouard 1225: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1226: double idx;
1227: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.234 brouard 1228: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1229: /*k 1 2 3 4 5 6 7 8 9 */
1230: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 */
1231: /* Tndvar[k] 1 2 3 4 5 */
1232: /*TDvar 4 3 6 7 1 */ /* For outputs only; combination of dummies fixed or varying */
1233: /* Tns[k] 1 2 2 4 5 */ /* Number of single cova */
1234: /* TvarsD[k] 1 2 3 */ /* Number of single dummy cova */
1235: /* TvarsDind 2 3 9 */ /* position K of single dummy cova */
1236: /* TvarsQ[k] 1 2 */ /* Number of single quantitative cova */
1237: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1238: /* Tprod[i]=k 4 7 */
1239: /* Tage[i]=k 5 8 */
1240: /* */
1241: /* Type */
1242: /* V 1 2 3 4 5 */
1243: /* F F V V V */
1244: /* D Q D D Q */
1245: /* */
1246: int *TvarsD;
1247: int *TvarsDind;
1248: int *TvarsQ;
1249: int *TvarsQind;
1250:
1.235 brouard 1251: #define MAXRESULTLINES 10
1252: int nresult=0;
1.258 brouard 1253: int parameterline=0; /* # of the parameter (type) line */
1.235 brouard 1254: int TKresult[MAXRESULTLINES];
1.237 brouard 1255: int Tresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */
1256: int Tinvresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */
1.235 brouard 1257: int Tvresult[MAXRESULTLINES][NCOVMAX]; /* For dummy variable , variable # (output) */
1258: double Tqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */
1.237 brouard 1259: double Tqinvresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */
1.235 brouard 1260: int Tvqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , variable # (output) */
1261:
1.234 brouard 1262: /* 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 1263: 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 */
1264: 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 */
1265: 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 */
1266: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1267: 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 */
1268: 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 1269: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1270: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1271: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1272: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1273: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1274: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1275: 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 */
1276: 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 */
1277:
1.230 brouard 1278: int *Tvarsel; /**< Selected covariates for output */
1279: double *Tvalsel; /**< Selected modality value of covariate for output */
1.226 brouard 1280: int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.227 brouard 1281: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1282: 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 1283: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1284: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1285: int *Tage;
1.227 brouard 1286: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1287: 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 1288: 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*/
1289: 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 1290: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1291: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1292: int **Tvard;
1293: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1294: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1295: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1296: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1297: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1298: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1299: double *lsurv, *lpop, *tpop;
1300:
1.231 brouard 1301: #define FD 1; /* Fixed dummy covariate */
1302: #define FQ 2; /* Fixed quantitative covariate */
1303: #define FP 3; /* Fixed product covariate */
1304: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1305: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1306: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1307: #define VD 10; /* Varying dummy covariate */
1308: #define VQ 11; /* Varying quantitative covariate */
1309: #define VP 12; /* Varying product covariate */
1310: #define VPDD 13; /* Varying product dummy*dummy covariate */
1311: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1312: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1313: #define APFD 16; /* Age product * fixed dummy covariate */
1314: #define APFQ 17; /* Age product * fixed quantitative covariate */
1315: #define APVD 18; /* Age product * varying dummy covariate */
1316: #define APVQ 19; /* Age product * varying quantitative covariate */
1317:
1318: #define FTYPE 1; /* Fixed covariate */
1319: #define VTYPE 2; /* Varying covariate (loop in wave) */
1320: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1321:
1322: struct kmodel{
1323: int maintype; /* main type */
1324: int subtype; /* subtype */
1325: };
1326: struct kmodel modell[NCOVMAX];
1327:
1.143 brouard 1328: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1329: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1330:
1331: /**************** split *************************/
1332: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1333: {
1334: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1335: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1336: */
1337: char *ss; /* pointer */
1.186 brouard 1338: int l1=0, l2=0; /* length counters */
1.126 brouard 1339:
1340: l1 = strlen(path ); /* length of path */
1341: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1342: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1343: if ( ss == NULL ) { /* no directory, so determine current directory */
1344: strcpy( name, path ); /* we got the fullname name because no directory */
1345: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1346: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1347: /* get current working directory */
1348: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1349: #ifdef WIN32
1350: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1351: #else
1352: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1353: #endif
1.126 brouard 1354: return( GLOCK_ERROR_GETCWD );
1355: }
1356: /* got dirc from getcwd*/
1357: printf(" DIRC = %s \n",dirc);
1.205 brouard 1358: } else { /* strip directory from path */
1.126 brouard 1359: ss++; /* after this, the filename */
1360: l2 = strlen( ss ); /* length of filename */
1361: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1362: strcpy( name, ss ); /* save file name */
1363: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1364: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1365: printf(" DIRC2 = %s \n",dirc);
1366: }
1367: /* We add a separator at the end of dirc if not exists */
1368: l1 = strlen( dirc ); /* length of directory */
1369: if( dirc[l1-1] != DIRSEPARATOR ){
1370: dirc[l1] = DIRSEPARATOR;
1371: dirc[l1+1] = 0;
1372: printf(" DIRC3 = %s \n",dirc);
1373: }
1374: ss = strrchr( name, '.' ); /* find last / */
1375: if (ss >0){
1376: ss++;
1377: strcpy(ext,ss); /* save extension */
1378: l1= strlen( name);
1379: l2= strlen(ss)+1;
1380: strncpy( finame, name, l1-l2);
1381: finame[l1-l2]= 0;
1382: }
1383:
1384: return( 0 ); /* we're done */
1385: }
1386:
1387:
1388: /******************************************/
1389:
1390: void replace_back_to_slash(char *s, char*t)
1391: {
1392: int i;
1393: int lg=0;
1394: i=0;
1395: lg=strlen(t);
1396: for(i=0; i<= lg; i++) {
1397: (s[i] = t[i]);
1398: if (t[i]== '\\') s[i]='/';
1399: }
1400: }
1401:
1.132 brouard 1402: char *trimbb(char *out, char *in)
1.137 brouard 1403: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1404: char *s;
1405: s=out;
1406: while (*in != '\0'){
1.137 brouard 1407: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1408: in++;
1409: }
1410: *out++ = *in++;
1411: }
1412: *out='\0';
1413: return s;
1414: }
1415:
1.187 brouard 1416: /* char *substrchaine(char *out, char *in, char *chain) */
1417: /* { */
1418: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1419: /* char *s, *t; */
1420: /* t=in;s=out; */
1421: /* while ((*in != *chain) && (*in != '\0')){ */
1422: /* *out++ = *in++; */
1423: /* } */
1424:
1425: /* /\* *in matches *chain *\/ */
1426: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1427: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1428: /* } */
1429: /* in--; chain--; */
1430: /* while ( (*in != '\0')){ */
1431: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1432: /* *out++ = *in++; */
1433: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1434: /* } */
1435: /* *out='\0'; */
1436: /* out=s; */
1437: /* return out; */
1438: /* } */
1439: char *substrchaine(char *out, char *in, char *chain)
1440: {
1441: /* Substract chain 'chain' from 'in', return and output 'out' */
1442: /* in="V1+V1*age+age*age+V2", chain="age*age" */
1443:
1444: char *strloc;
1445:
1446: strcpy (out, in);
1447: strloc = strstr(out, chain); /* strloc points to out at age*age+V2 */
1448: printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out);
1449: if(strloc != NULL){
1450: /* will affect out */ /* strloc+strlenc(chain)=+V2 */ /* Will also work in Unicode */
1451: memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1);
1452: /* strcpy (strloc, strloc +strlen(chain));*/
1453: }
1454: printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out);
1455: return out;
1456: }
1457:
1458:
1.145 brouard 1459: char *cutl(char *blocc, char *alocc, char *in, char occ)
1460: {
1.187 brouard 1461: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.145 brouard 1462: and alocc starts after first occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1.187 brouard 1463: gives blocc="abcdef" and alocc="ghi2j".
1.145 brouard 1464: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1465: */
1.160 brouard 1466: char *s, *t;
1.145 brouard 1467: t=in;s=in;
1468: while ((*in != occ) && (*in != '\0')){
1469: *alocc++ = *in++;
1470: }
1471: if( *in == occ){
1472: *(alocc)='\0';
1473: s=++in;
1474: }
1475:
1476: if (s == t) {/* occ not found */
1477: *(alocc-(in-s))='\0';
1478: in=s;
1479: }
1480: while ( *in != '\0'){
1481: *blocc++ = *in++;
1482: }
1483:
1484: *blocc='\0';
1485: return t;
1486: }
1.137 brouard 1487: char *cutv(char *blocc, char *alocc, char *in, char occ)
1488: {
1.187 brouard 1489: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1490: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1491: gives blocc="abcdef2ghi" and alocc="j".
1492: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1493: */
1494: char *s, *t;
1495: t=in;s=in;
1496: while (*in != '\0'){
1497: while( *in == occ){
1498: *blocc++ = *in++;
1499: s=in;
1500: }
1501: *blocc++ = *in++;
1502: }
1503: if (s == t) /* occ not found */
1504: *(blocc-(in-s))='\0';
1505: else
1506: *(blocc-(in-s)-1)='\0';
1507: in=s;
1508: while ( *in != '\0'){
1509: *alocc++ = *in++;
1510: }
1511:
1512: *alocc='\0';
1513: return s;
1514: }
1515:
1.126 brouard 1516: int nbocc(char *s, char occ)
1517: {
1518: int i,j=0;
1519: int lg=20;
1520: i=0;
1521: lg=strlen(s);
1522: for(i=0; i<= lg; i++) {
1.234 brouard 1523: if (s[i] == occ ) j++;
1.126 brouard 1524: }
1525: return j;
1526: }
1527:
1.137 brouard 1528: /* void cutv(char *u,char *v, char*t, char occ) */
1529: /* { */
1530: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1531: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1532: /* gives u="abcdef2ghi" and v="j" *\/ */
1533: /* int i,lg,j,p=0; */
1534: /* i=0; */
1535: /* lg=strlen(t); */
1536: /* for(j=0; j<=lg-1; j++) { */
1537: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1538: /* } */
1.126 brouard 1539:
1.137 brouard 1540: /* for(j=0; j<p; j++) { */
1541: /* (u[j] = t[j]); */
1542: /* } */
1543: /* u[p]='\0'; */
1.126 brouard 1544:
1.137 brouard 1545: /* for(j=0; j<= lg; j++) { */
1546: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1547: /* } */
1548: /* } */
1.126 brouard 1549:
1.160 brouard 1550: #ifdef _WIN32
1551: char * strsep(char **pp, const char *delim)
1552: {
1553: char *p, *q;
1554:
1555: if ((p = *pp) == NULL)
1556: return 0;
1557: if ((q = strpbrk (p, delim)) != NULL)
1558: {
1559: *pp = q + 1;
1560: *q = '\0';
1561: }
1562: else
1563: *pp = 0;
1564: return p;
1565: }
1566: #endif
1567:
1.126 brouard 1568: /********************** nrerror ********************/
1569:
1570: void nrerror(char error_text[])
1571: {
1572: fprintf(stderr,"ERREUR ...\n");
1573: fprintf(stderr,"%s\n",error_text);
1574: exit(EXIT_FAILURE);
1575: }
1576: /*********************** vector *******************/
1577: double *vector(int nl, int nh)
1578: {
1579: double *v;
1580: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
1581: if (!v) nrerror("allocation failure in vector");
1582: return v-nl+NR_END;
1583: }
1584:
1585: /************************ free vector ******************/
1586: void free_vector(double*v, int nl, int nh)
1587: {
1588: free((FREE_ARG)(v+nl-NR_END));
1589: }
1590:
1591: /************************ivector *******************************/
1592: int *ivector(long nl,long nh)
1593: {
1594: int *v;
1595: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
1596: if (!v) nrerror("allocation failure in ivector");
1597: return v-nl+NR_END;
1598: }
1599:
1600: /******************free ivector **************************/
1601: void free_ivector(int *v, long nl, long nh)
1602: {
1603: free((FREE_ARG)(v+nl-NR_END));
1604: }
1605:
1606: /************************lvector *******************************/
1607: long *lvector(long nl,long nh)
1608: {
1609: long *v;
1610: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
1611: if (!v) nrerror("allocation failure in ivector");
1612: return v-nl+NR_END;
1613: }
1614:
1615: /******************free lvector **************************/
1616: void free_lvector(long *v, long nl, long nh)
1617: {
1618: free((FREE_ARG)(v+nl-NR_END));
1619: }
1620:
1621: /******************* imatrix *******************************/
1622: int **imatrix(long nrl, long nrh, long ncl, long nch)
1623: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
1624: {
1625: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
1626: int **m;
1627:
1628: /* allocate pointers to rows */
1629: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
1630: if (!m) nrerror("allocation failure 1 in matrix()");
1631: m += NR_END;
1632: m -= nrl;
1633:
1634:
1635: /* allocate rows and set pointers to them */
1636: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
1637: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1638: m[nrl] += NR_END;
1639: m[nrl] -= ncl;
1640:
1641: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
1642:
1643: /* return pointer to array of pointers to rows */
1644: return m;
1645: }
1646:
1647: /****************** free_imatrix *************************/
1648: void free_imatrix(m,nrl,nrh,ncl,nch)
1649: int **m;
1650: long nch,ncl,nrh,nrl;
1651: /* free an int matrix allocated by imatrix() */
1652: {
1653: free((FREE_ARG) (m[nrl]+ncl-NR_END));
1654: free((FREE_ARG) (m+nrl-NR_END));
1655: }
1656:
1657: /******************* matrix *******************************/
1658: double **matrix(long nrl, long nrh, long ncl, long nch)
1659: {
1660: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
1661: double **m;
1662:
1663: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1664: if (!m) nrerror("allocation failure 1 in matrix()");
1665: m += NR_END;
1666: m -= nrl;
1667:
1668: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1669: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1670: m[nrl] += NR_END;
1671: m[nrl] -= ncl;
1672:
1673: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1674: return m;
1.145 brouard 1675: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
1676: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
1677: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 1678: */
1679: }
1680:
1681: /*************************free matrix ************************/
1682: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
1683: {
1684: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1685: free((FREE_ARG)(m+nrl-NR_END));
1686: }
1687:
1688: /******************* ma3x *******************************/
1689: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
1690: {
1691: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
1692: double ***m;
1693:
1694: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1695: if (!m) nrerror("allocation failure 1 in matrix()");
1696: m += NR_END;
1697: m -= nrl;
1698:
1699: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1700: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1701: m[nrl] += NR_END;
1702: m[nrl] -= ncl;
1703:
1704: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1705:
1706: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
1707: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
1708: m[nrl][ncl] += NR_END;
1709: m[nrl][ncl] -= nll;
1710: for (j=ncl+1; j<=nch; j++)
1711: m[nrl][j]=m[nrl][j-1]+nlay;
1712:
1713: for (i=nrl+1; i<=nrh; i++) {
1714: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
1715: for (j=ncl+1; j<=nch; j++)
1716: m[i][j]=m[i][j-1]+nlay;
1717: }
1718: return m;
1719: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
1720: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
1721: */
1722: }
1723:
1724: /*************************free ma3x ************************/
1725: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
1726: {
1727: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
1728: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1729: free((FREE_ARG)(m+nrl-NR_END));
1730: }
1731:
1732: /*************** function subdirf ***********/
1733: char *subdirf(char fileres[])
1734: {
1735: /* Caution optionfilefiname is hidden */
1736: strcpy(tmpout,optionfilefiname);
1737: strcat(tmpout,"/"); /* Add to the right */
1738: strcat(tmpout,fileres);
1739: return tmpout;
1740: }
1741:
1742: /*************** function subdirf2 ***********/
1743: char *subdirf2(char fileres[], char *preop)
1744: {
1745:
1746: /* Caution optionfilefiname is hidden */
1747: strcpy(tmpout,optionfilefiname);
1748: strcat(tmpout,"/");
1749: strcat(tmpout,preop);
1750: strcat(tmpout,fileres);
1751: return tmpout;
1752: }
1753:
1754: /*************** function subdirf3 ***********/
1755: char *subdirf3(char fileres[], char *preop, char *preop2)
1756: {
1757:
1758: /* Caution optionfilefiname is hidden */
1759: strcpy(tmpout,optionfilefiname);
1760: strcat(tmpout,"/");
1761: strcat(tmpout,preop);
1762: strcat(tmpout,preop2);
1763: strcat(tmpout,fileres);
1764: return tmpout;
1765: }
1.213 brouard 1766:
1767: /*************** function subdirfext ***********/
1768: char *subdirfext(char fileres[], char *preop, char *postop)
1769: {
1770:
1771: strcpy(tmpout,preop);
1772: strcat(tmpout,fileres);
1773: strcat(tmpout,postop);
1774: return tmpout;
1775: }
1.126 brouard 1776:
1.213 brouard 1777: /*************** function subdirfext3 ***********/
1778: char *subdirfext3(char fileres[], char *preop, char *postop)
1779: {
1780:
1781: /* Caution optionfilefiname is hidden */
1782: strcpy(tmpout,optionfilefiname);
1783: strcat(tmpout,"/");
1784: strcat(tmpout,preop);
1785: strcat(tmpout,fileres);
1786: strcat(tmpout,postop);
1787: return tmpout;
1788: }
1789:
1.162 brouard 1790: char *asc_diff_time(long time_sec, char ascdiff[])
1791: {
1792: long sec_left, days, hours, minutes;
1793: days = (time_sec) / (60*60*24);
1794: sec_left = (time_sec) % (60*60*24);
1795: hours = (sec_left) / (60*60) ;
1796: sec_left = (sec_left) %(60*60);
1797: minutes = (sec_left) /60;
1798: sec_left = (sec_left) % (60);
1799: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
1800: return ascdiff;
1801: }
1802:
1.126 brouard 1803: /***************** f1dim *************************/
1804: extern int ncom;
1805: extern double *pcom,*xicom;
1806: extern double (*nrfunc)(double []);
1807:
1808: double f1dim(double x)
1809: {
1810: int j;
1811: double f;
1812: double *xt;
1813:
1814: xt=vector(1,ncom);
1815: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
1816: f=(*nrfunc)(xt);
1817: free_vector(xt,1,ncom);
1818: return f;
1819: }
1820:
1821: /*****************brent *************************/
1822: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 1823: {
1824: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
1825: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
1826: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
1827: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
1828: * returned function value.
1829: */
1.126 brouard 1830: int iter;
1831: double a,b,d,etemp;
1.159 brouard 1832: double fu=0,fv,fw,fx;
1.164 brouard 1833: double ftemp=0.;
1.126 brouard 1834: double p,q,r,tol1,tol2,u,v,w,x,xm;
1835: double e=0.0;
1836:
1837: a=(ax < cx ? ax : cx);
1838: b=(ax > cx ? ax : cx);
1839: x=w=v=bx;
1840: fw=fv=fx=(*f)(x);
1841: for (iter=1;iter<=ITMAX;iter++) {
1842: xm=0.5*(a+b);
1843: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
1844: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
1845: printf(".");fflush(stdout);
1846: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 1847: #ifdef DEBUGBRENT
1.126 brouard 1848: 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);
1849: 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);
1850: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
1851: #endif
1852: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
1853: *xmin=x;
1854: return fx;
1855: }
1856: ftemp=fu;
1857: if (fabs(e) > tol1) {
1858: r=(x-w)*(fx-fv);
1859: q=(x-v)*(fx-fw);
1860: p=(x-v)*q-(x-w)*r;
1861: q=2.0*(q-r);
1862: if (q > 0.0) p = -p;
1863: q=fabs(q);
1864: etemp=e;
1865: e=d;
1866: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 1867: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 1868: else {
1.224 brouard 1869: d=p/q;
1870: u=x+d;
1871: if (u-a < tol2 || b-u < tol2)
1872: d=SIGN(tol1,xm-x);
1.126 brouard 1873: }
1874: } else {
1875: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1876: }
1877: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
1878: fu=(*f)(u);
1879: if (fu <= fx) {
1880: if (u >= x) a=x; else b=x;
1881: SHFT(v,w,x,u)
1.183 brouard 1882: SHFT(fv,fw,fx,fu)
1883: } else {
1884: if (u < x) a=u; else b=u;
1885: if (fu <= fw || w == x) {
1.224 brouard 1886: v=w;
1887: w=u;
1888: fv=fw;
1889: fw=fu;
1.183 brouard 1890: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 1891: v=u;
1892: fv=fu;
1.183 brouard 1893: }
1894: }
1.126 brouard 1895: }
1896: nrerror("Too many iterations in brent");
1897: *xmin=x;
1898: return fx;
1899: }
1900:
1901: /****************** mnbrak ***********************/
1902:
1903: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
1904: double (*func)(double))
1.183 brouard 1905: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
1906: the downhill direction (defined by the function as evaluated at the initial points) and returns
1907: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
1908: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
1909: */
1.126 brouard 1910: double ulim,u,r,q, dum;
1911: double fu;
1.187 brouard 1912:
1913: double scale=10.;
1914: int iterscale=0;
1915:
1916: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
1917: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
1918:
1919:
1920: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
1921: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
1922: /* *bx = *ax - (*ax - *bx)/scale; */
1923: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
1924: /* } */
1925:
1.126 brouard 1926: if (*fb > *fa) {
1927: SHFT(dum,*ax,*bx,dum)
1.183 brouard 1928: SHFT(dum,*fb,*fa,dum)
1929: }
1.126 brouard 1930: *cx=(*bx)+GOLD*(*bx-*ax);
1931: *fc=(*func)(*cx);
1.183 brouard 1932: #ifdef DEBUG
1.224 brouard 1933: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
1934: 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 1935: #endif
1.224 brouard 1936: 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 1937: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 1938: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 1939: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 1940: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
1941: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
1942: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 1943: fu=(*func)(u);
1.163 brouard 1944: #ifdef DEBUG
1945: /* f(x)=A(x-u)**2+f(u) */
1946: double A, fparabu;
1947: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
1948: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 1949: 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);
1950: 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 1951: /* And thus,it can be that fu > *fc even if fparabu < *fc */
1952: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
1953: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
1954: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 1955: #endif
1.184 brouard 1956: #ifdef MNBRAKORIGINAL
1.183 brouard 1957: #else
1.191 brouard 1958: /* if (fu > *fc) { */
1959: /* #ifdef DEBUG */
1960: /* printf("mnbrak4 fu > fc \n"); */
1961: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
1962: /* #endif */
1963: /* /\* 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 *\\/ *\/ */
1964: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
1965: /* dum=u; /\* Shifting c and u *\/ */
1966: /* u = *cx; */
1967: /* *cx = dum; */
1968: /* dum = fu; */
1969: /* fu = *fc; */
1970: /* *fc =dum; */
1971: /* } else { /\* end *\/ */
1972: /* #ifdef DEBUG */
1973: /* printf("mnbrak3 fu < fc \n"); */
1974: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
1975: /* #endif */
1976: /* dum=u; /\* Shifting c and u *\/ */
1977: /* u = *cx; */
1978: /* *cx = dum; */
1979: /* dum = fu; */
1980: /* fu = *fc; */
1981: /* *fc =dum; */
1982: /* } */
1.224 brouard 1983: #ifdef DEBUGMNBRAK
1984: double A, fparabu;
1985: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
1986: fparabu= *fa - A*(*ax-u)*(*ax-u);
1987: 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);
1988: 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 1989: #endif
1.191 brouard 1990: dum=u; /* Shifting c and u */
1991: u = *cx;
1992: *cx = dum;
1993: dum = fu;
1994: fu = *fc;
1995: *fc =dum;
1.183 brouard 1996: #endif
1.162 brouard 1997: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 1998: #ifdef DEBUG
1.224 brouard 1999: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
2000: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 2001: #endif
1.126 brouard 2002: fu=(*func)(u);
2003: if (fu < *fc) {
1.183 brouard 2004: #ifdef DEBUG
1.224 brouard 2005: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2006: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2007: #endif
2008: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
2009: SHFT(*fb,*fc,fu,(*func)(u))
2010: #ifdef DEBUG
2011: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 2012: #endif
2013: }
1.162 brouard 2014: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 2015: #ifdef DEBUG
1.224 brouard 2016: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
2017: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 2018: #endif
1.126 brouard 2019: u=ulim;
2020: fu=(*func)(u);
1.183 brouard 2021: } else { /* u could be left to b (if r > q parabola has a maximum) */
2022: #ifdef DEBUG
1.224 brouard 2023: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
2024: 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 2025: #endif
1.126 brouard 2026: u=(*cx)+GOLD*(*cx-*bx);
2027: fu=(*func)(u);
1.224 brouard 2028: #ifdef DEBUG
2029: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2030: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2031: #endif
1.183 brouard 2032: } /* end tests */
1.126 brouard 2033: SHFT(*ax,*bx,*cx,u)
1.183 brouard 2034: SHFT(*fa,*fb,*fc,fu)
2035: #ifdef DEBUG
1.224 brouard 2036: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2037: 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 2038: #endif
2039: } /* 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 2040: }
2041:
2042: /*************** linmin ************************/
1.162 brouard 2043: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2044: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2045: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2046: the value of func at the returned location p . This is actually all accomplished by calling the
2047: routines mnbrak and brent .*/
1.126 brouard 2048: int ncom;
2049: double *pcom,*xicom;
2050: double (*nrfunc)(double []);
2051:
1.224 brouard 2052: #ifdef LINMINORIGINAL
1.126 brouard 2053: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2054: #else
2055: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2056: #endif
1.126 brouard 2057: {
2058: double brent(double ax, double bx, double cx,
2059: double (*f)(double), double tol, double *xmin);
2060: double f1dim(double x);
2061: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2062: double *fc, double (*func)(double));
2063: int j;
2064: double xx,xmin,bx,ax;
2065: double fx,fb,fa;
1.187 brouard 2066:
1.203 brouard 2067: #ifdef LINMINORIGINAL
2068: #else
2069: double scale=10., axs, xxs; /* Scale added for infinity */
2070: #endif
2071:
1.126 brouard 2072: ncom=n;
2073: pcom=vector(1,n);
2074: xicom=vector(1,n);
2075: nrfunc=func;
2076: for (j=1;j<=n;j++) {
2077: pcom[j]=p[j];
1.202 brouard 2078: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2079: }
1.187 brouard 2080:
1.203 brouard 2081: #ifdef LINMINORIGINAL
2082: xx=1.;
2083: #else
2084: axs=0.0;
2085: xxs=1.;
2086: do{
2087: xx= xxs;
2088: #endif
1.187 brouard 2089: ax=0.;
2090: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2091: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2092: /* 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)) */
2093: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2094: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2095: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2096: /* 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 2097: #ifdef LINMINORIGINAL
2098: #else
2099: if (fx != fx){
1.224 brouard 2100: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2101: printf("|");
2102: fprintf(ficlog,"|");
1.203 brouard 2103: #ifdef DEBUGLINMIN
1.224 brouard 2104: 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 2105: #endif
2106: }
1.224 brouard 2107: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2108: #endif
2109:
1.191 brouard 2110: #ifdef DEBUGLINMIN
2111: 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 2112: 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 2113: #endif
1.224 brouard 2114: #ifdef LINMINORIGINAL
2115: #else
2116: if(fb == fx){ /* Flat function in the direction */
2117: xmin=xx;
2118: *flat=1;
2119: }else{
2120: *flat=0;
2121: #endif
2122: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2123: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2124: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2125: /* fmin = f(p[j] + xmin * xi[j]) */
2126: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2127: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2128: #ifdef DEBUG
1.224 brouard 2129: 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);
2130: 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);
2131: #endif
2132: #ifdef LINMINORIGINAL
2133: #else
2134: }
1.126 brouard 2135: #endif
1.191 brouard 2136: #ifdef DEBUGLINMIN
2137: printf("linmin end ");
1.202 brouard 2138: fprintf(ficlog,"linmin end ");
1.191 brouard 2139: #endif
1.126 brouard 2140: for (j=1;j<=n;j++) {
1.203 brouard 2141: #ifdef LINMINORIGINAL
2142: xi[j] *= xmin;
2143: #else
2144: #ifdef DEBUGLINMIN
2145: if(xxs <1.0)
2146: printf(" before xi[%d]=%12.8f", j,xi[j]);
2147: #endif
2148: 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) */
2149: #ifdef DEBUGLINMIN
2150: if(xxs <1.0)
2151: 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 );
2152: #endif
2153: #endif
1.187 brouard 2154: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2155: }
1.191 brouard 2156: #ifdef DEBUGLINMIN
1.203 brouard 2157: printf("\n");
1.191 brouard 2158: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2159: 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 2160: for (j=1;j<=n;j++) {
1.202 brouard 2161: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2162: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2163: if(j % ncovmodel == 0){
1.191 brouard 2164: printf("\n");
1.202 brouard 2165: fprintf(ficlog,"\n");
2166: }
1.191 brouard 2167: }
1.203 brouard 2168: #else
1.191 brouard 2169: #endif
1.126 brouard 2170: free_vector(xicom,1,n);
2171: free_vector(pcom,1,n);
2172: }
2173:
2174:
2175: /*************** powell ************************/
1.162 brouard 2176: /*
2177: Minimization of a function func of n variables. Input consists of an initial starting point
2178: p[1..n] ; an initial matrix xi[1..n][1..n] , whose columns contain the initial set of di-
2179: rections (usually the n unit vectors); and ftol , the fractional tolerance in the function value
2180: such that failure to decrease by more than this amount on one iteration signals doneness. On
2181: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2182: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2183: */
1.224 brouard 2184: #ifdef LINMINORIGINAL
2185: #else
2186: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2187: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2188: #endif
1.126 brouard 2189: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2190: double (*func)(double []))
2191: {
1.224 brouard 2192: #ifdef LINMINORIGINAL
2193: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2194: double (*func)(double []));
1.224 brouard 2195: #else
1.241 brouard 2196: void linmin(double p[], double xi[], int n, double *fret,
2197: double (*func)(double []),int *flat);
1.224 brouard 2198: #endif
1.239 brouard 2199: int i,ibig,j,jk,k;
1.126 brouard 2200: double del,t,*pt,*ptt,*xit;
1.181 brouard 2201: double directest;
1.126 brouard 2202: double fp,fptt;
2203: double *xits;
2204: int niterf, itmp;
1.224 brouard 2205: #ifdef LINMINORIGINAL
2206: #else
2207:
2208: flatdir=ivector(1,n);
2209: for (j=1;j<=n;j++) flatdir[j]=0;
2210: #endif
1.126 brouard 2211:
2212: pt=vector(1,n);
2213: ptt=vector(1,n);
2214: xit=vector(1,n);
2215: xits=vector(1,n);
2216: *fret=(*func)(p);
2217: for (j=1;j<=n;j++) pt[j]=p[j];
1.202 brouard 2218: rcurr_time = time(NULL);
1.126 brouard 2219: for (*iter=1;;++(*iter)) {
1.187 brouard 2220: fp=(*fret); /* From former iteration or initial value */
1.126 brouard 2221: ibig=0;
2222: del=0.0;
1.157 brouard 2223: rlast_time=rcurr_time;
2224: /* (void) gettimeofday(&curr_time,&tzp); */
2225: rcurr_time = time(NULL);
2226: curr_time = *localtime(&rcurr_time);
2227: printf("\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout);
2228: fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog);
2229: /* fprintf(ficrespow,"%d %.12f %ld",*iter,*fret,curr_time.tm_sec-start_time.tm_sec); */
1.192 brouard 2230: for (i=1;i<=n;i++) {
1.126 brouard 2231: fprintf(ficrespow," %.12lf", p[i]);
2232: }
1.239 brouard 2233: fprintf(ficrespow,"\n");fflush(ficrespow);
2234: printf("\n#model= 1 + age ");
2235: fprintf(ficlog,"\n#model= 1 + age ");
2236: if(nagesqr==1){
1.241 brouard 2237: printf(" + age*age ");
2238: fprintf(ficlog," + age*age ");
1.239 brouard 2239: }
2240: for(j=1;j <=ncovmodel-2;j++){
2241: if(Typevar[j]==0) {
2242: printf(" + V%d ",Tvar[j]);
2243: fprintf(ficlog," + V%d ",Tvar[j]);
2244: }else if(Typevar[j]==1) {
2245: printf(" + V%d*age ",Tvar[j]);
2246: fprintf(ficlog," + V%d*age ",Tvar[j]);
2247: }else if(Typevar[j]==2) {
2248: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2249: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2250: }
2251: }
1.126 brouard 2252: printf("\n");
1.239 brouard 2253: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2254: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2255: fprintf(ficlog,"\n");
1.239 brouard 2256: for(i=1,jk=1; i <=nlstate; i++){
2257: for(k=1; k <=(nlstate+ndeath); k++){
2258: if (k != i) {
2259: printf("%d%d ",i,k);
2260: fprintf(ficlog,"%d%d ",i,k);
2261: for(j=1; j <=ncovmodel; j++){
2262: printf("%12.7f ",p[jk]);
2263: fprintf(ficlog,"%12.7f ",p[jk]);
2264: jk++;
2265: }
2266: printf("\n");
2267: fprintf(ficlog,"\n");
2268: }
2269: }
2270: }
1.241 brouard 2271: if(*iter <=3 && *iter >1){
1.157 brouard 2272: tml = *localtime(&rcurr_time);
2273: strcpy(strcurr,asctime(&tml));
2274: rforecast_time=rcurr_time;
1.126 brouard 2275: itmp = strlen(strcurr);
2276: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2277: strcurr[itmp-1]='\0';
1.162 brouard 2278: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2279: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.126 brouard 2280: for(niterf=10;niterf<=30;niterf+=10){
1.241 brouard 2281: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2282: forecast_time = *localtime(&rforecast_time);
2283: strcpy(strfor,asctime(&forecast_time));
2284: itmp = strlen(strfor);
2285: if(strfor[itmp-1]=='\n')
2286: strfor[itmp-1]='\0';
2287: 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);
2288: 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 2289: }
2290: }
1.187 brouard 2291: for (i=1;i<=n;i++) { /* For each direction i */
2292: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2293: fptt=(*fret);
2294: #ifdef DEBUG
1.203 brouard 2295: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2296: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2297: #endif
1.203 brouard 2298: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2299: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2300: #ifdef LINMINORIGINAL
1.188 brouard 2301: linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.224 brouard 2302: #else
2303: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2304: flatdir[i]=flat; /* Function is vanishing in that direction i */
2305: #endif
2306: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2307: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2308: /* because that direction will be replaced unless the gain del is small */
2309: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2310: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2311: /* with the new direction. */
2312: del=fabs(fptt-(*fret));
2313: ibig=i;
1.126 brouard 2314: }
2315: #ifdef DEBUG
2316: printf("%d %.12e",i,(*fret));
2317: fprintf(ficlog,"%d %.12e",i,(*fret));
2318: for (j=1;j<=n;j++) {
1.224 brouard 2319: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2320: printf(" x(%d)=%.12e",j,xit[j]);
2321: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2322: }
2323: for(j=1;j<=n;j++) {
1.225 brouard 2324: printf(" p(%d)=%.12e",j,p[j]);
2325: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2326: }
2327: printf("\n");
2328: fprintf(ficlog,"\n");
2329: #endif
1.187 brouard 2330: } /* end loop on each direction i */
2331: /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
1.188 brouard 2332: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.187 brouard 2333: /* New value of last point Pn is not computed, P(n-1) */
1.224 brouard 2334: for(j=1;j<=n;j++) {
1.225 brouard 2335: if(flatdir[j] >0){
2336: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2337: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2338: }
2339: /* printf("\n"); */
2340: /* fprintf(ficlog,"\n"); */
2341: }
1.243 brouard 2342: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
2343: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2344: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2345: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2346: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2347: /* decreased of more than 3.84 */
2348: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2349: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2350: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2351:
1.188 brouard 2352: /* Starting the program with initial values given by a former maximization will simply change */
2353: /* the scales of the directions and the directions, because the are reset to canonical directions */
2354: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2355: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2356: #ifdef DEBUG
2357: int k[2],l;
2358: k[0]=1;
2359: k[1]=-1;
2360: printf("Max: %.12e",(*func)(p));
2361: fprintf(ficlog,"Max: %.12e",(*func)(p));
2362: for (j=1;j<=n;j++) {
2363: printf(" %.12e",p[j]);
2364: fprintf(ficlog," %.12e",p[j]);
2365: }
2366: printf("\n");
2367: fprintf(ficlog,"\n");
2368: for(l=0;l<=1;l++) {
2369: for (j=1;j<=n;j++) {
2370: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2371: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2372: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2373: }
2374: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2375: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2376: }
2377: #endif
2378:
1.224 brouard 2379: #ifdef LINMINORIGINAL
2380: #else
2381: free_ivector(flatdir,1,n);
2382: #endif
1.126 brouard 2383: free_vector(xit,1,n);
2384: free_vector(xits,1,n);
2385: free_vector(ptt,1,n);
2386: free_vector(pt,1,n);
2387: return;
1.192 brouard 2388: } /* enough precision */
1.240 brouard 2389: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2390: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2391: ptt[j]=2.0*p[j]-pt[j];
2392: xit[j]=p[j]-pt[j];
2393: pt[j]=p[j];
2394: }
1.181 brouard 2395: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2396: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2397: if (*iter <=4) {
1.225 brouard 2398: #else
2399: #endif
1.224 brouard 2400: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2401: #else
1.161 brouard 2402: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2403: #endif
1.162 brouard 2404: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2405: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2406: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2407: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2408: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2409: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2410: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2411: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2412: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2413: /* Even if f3 <f1, directest can be negative and t >0 */
2414: /* mu² and del² are equal when f3=f1 */
2415: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2416: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2417: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2418: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2419: #ifdef NRCORIGINAL
2420: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2421: #else
2422: 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 2423: t= t- del*SQR(fp-fptt);
1.183 brouard 2424: #endif
1.202 brouard 2425: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2426: #ifdef DEBUG
1.181 brouard 2427: 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);
2428: 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 2429: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2430: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2431: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2432: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2433: 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);
2434: 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);
2435: #endif
1.183 brouard 2436: #ifdef POWELLORIGINAL
2437: if (t < 0.0) { /* Then we use it for new direction */
2438: #else
1.182 brouard 2439: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2440: 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 2441: 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 2442: 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 2443: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2444: }
1.181 brouard 2445: if (directest < 0.0) { /* Then we use it for new direction */
2446: #endif
1.191 brouard 2447: #ifdef DEBUGLINMIN
1.234 brouard 2448: printf("Before linmin in direction P%d-P0\n",n);
2449: for (j=1;j<=n;j++) {
2450: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2451: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2452: if(j % ncovmodel == 0){
2453: printf("\n");
2454: fprintf(ficlog,"\n");
2455: }
2456: }
1.224 brouard 2457: #endif
2458: #ifdef LINMINORIGINAL
1.234 brouard 2459: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2460: #else
1.234 brouard 2461: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2462: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2463: #endif
1.234 brouard 2464:
1.191 brouard 2465: #ifdef DEBUGLINMIN
1.234 brouard 2466: for (j=1;j<=n;j++) {
2467: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2468: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2469: if(j % ncovmodel == 0){
2470: printf("\n");
2471: fprintf(ficlog,"\n");
2472: }
2473: }
1.224 brouard 2474: #endif
1.234 brouard 2475: for (j=1;j<=n;j++) {
2476: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2477: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2478: }
1.224 brouard 2479: #ifdef LINMINORIGINAL
2480: #else
1.234 brouard 2481: for (j=1, flatd=0;j<=n;j++) {
2482: if(flatdir[j]>0)
2483: flatd++;
2484: }
2485: if(flatd >0){
1.255 brouard 2486: printf("%d flat directions: ",flatd);
2487: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 2488: for (j=1;j<=n;j++) {
2489: if(flatdir[j]>0){
2490: printf("%d ",j);
2491: fprintf(ficlog,"%d ",j);
2492: }
2493: }
2494: printf("\n");
2495: fprintf(ficlog,"\n");
2496: }
1.191 brouard 2497: #endif
1.234 brouard 2498: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2499: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2500:
1.126 brouard 2501: #ifdef DEBUG
1.234 brouard 2502: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2503: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2504: for(j=1;j<=n;j++){
2505: printf(" %lf",xit[j]);
2506: fprintf(ficlog," %lf",xit[j]);
2507: }
2508: printf("\n");
2509: fprintf(ficlog,"\n");
1.126 brouard 2510: #endif
1.192 brouard 2511: } /* end of t or directest negative */
1.224 brouard 2512: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2513: #else
1.234 brouard 2514: } /* end if (fptt < fp) */
1.192 brouard 2515: #endif
1.225 brouard 2516: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2517: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2518: #else
1.224 brouard 2519: #endif
1.234 brouard 2520: } /* loop iteration */
1.126 brouard 2521: }
1.234 brouard 2522:
1.126 brouard 2523: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 2524:
1.235 brouard 2525: 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 2526: {
1.279 brouard 2527: /**< Computes the prevalence limit in each live state at age x and for covariate combination ij
2528: * (and selected quantitative values in nres)
2529: * by left multiplying the unit
2530: * matrix by transitions matrix until convergence is reached with precision ftolpl
2531: * Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I
2532: * Wx is row vector: population in state 1, population in state 2, population dead
2533: * or prevalence in state 1, prevalence in state 2, 0
2534: * newm is the matrix after multiplications, its rows are identical at a factor.
2535: * Inputs are the parameter, age, a tolerance for the prevalence limit ftolpl.
2536: * Output is prlim.
2537: * Initial matrix pimij
2538: */
1.206 brouard 2539: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2540: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2541: /* 0, 0 , 1} */
2542: /*
2543: * and after some iteration: */
2544: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2545: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2546: /* 0, 0 , 1} */
2547: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2548: /* {0.51571254859325999, 0.4842874514067399, */
2549: /* 0.51326036147820708, 0.48673963852179264} */
2550: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 2551:
1.126 brouard 2552: int i, ii,j,k;
1.209 brouard 2553: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 2554: /* double **matprod2(); */ /* test */
1.218 brouard 2555: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 2556: double **newm;
1.209 brouard 2557: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 2558: int ncvloop=0;
1.169 brouard 2559:
1.209 brouard 2560: min=vector(1,nlstate);
2561: max=vector(1,nlstate);
2562: meandiff=vector(1,nlstate);
2563:
1.218 brouard 2564: /* Starting with matrix unity */
1.126 brouard 2565: for (ii=1;ii<=nlstate+ndeath;ii++)
2566: for (j=1;j<=nlstate+ndeath;j++){
2567: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2568: }
1.169 brouard 2569:
2570: cov[1]=1.;
2571:
2572: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 2573: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 2574: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 2575: ncvloop++;
1.126 brouard 2576: newm=savm;
2577: /* Covariates have to be included here again */
1.138 brouard 2578: cov[2]=agefin;
1.187 brouard 2579: if(nagesqr==1)
2580: cov[3]= agefin*agefin;;
1.234 brouard 2581: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2582: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2583: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.235 brouard 2584: /* 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 2585: }
2586: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2587: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
1.235 brouard 2588: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2589: /* 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 2590: }
1.237 brouard 2591: for (k=1; k<=cptcovage;k++){ /* For product with age */
1.234 brouard 2592: if(Dummy[Tvar[Tage[k]]]){
2593: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
2594: } else{
1.235 brouard 2595: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
1.234 brouard 2596: }
1.235 brouard 2597: /* 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 2598: }
1.237 brouard 2599: for (k=1; k<=cptcovprod;k++){ /* For product without age */
1.235 brouard 2600: /* 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 2601: if(Dummy[Tvard[k][1]==0]){
2602: if(Dummy[Tvard[k][2]==0]){
2603: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2604: }else{
2605: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2606: }
2607: }else{
2608: if(Dummy[Tvard[k][2]==0]){
2609: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2610: }else{
2611: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2612: }
2613: }
1.234 brouard 2614: }
1.138 brouard 2615: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2616: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2617: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 2618: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2619: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2620: /* age and covariate values of ij are in 'cov' */
1.142 brouard 2621: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 2622:
1.126 brouard 2623: savm=oldm;
2624: oldm=newm;
1.209 brouard 2625:
2626: for(j=1; j<=nlstate; j++){
2627: max[j]=0.;
2628: min[j]=1.;
2629: }
2630: for(i=1;i<=nlstate;i++){
2631: sumnew=0;
2632: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
2633: for(j=1; j<=nlstate; j++){
2634: prlim[i][j]= newm[i][j]/(1-sumnew);
2635: max[j]=FMAX(max[j],prlim[i][j]);
2636: min[j]=FMIN(min[j],prlim[i][j]);
2637: }
2638: }
2639:
1.126 brouard 2640: maxmax=0.;
1.209 brouard 2641: for(j=1; j<=nlstate; j++){
2642: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
2643: maxmax=FMAX(maxmax,meandiff[j]);
2644: /* 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 2645: } /* j loop */
1.203 brouard 2646: *ncvyear= (int)age- (int)agefin;
1.208 brouard 2647: /* 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 2648: if(maxmax < ftolpl){
1.209 brouard 2649: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
2650: free_vector(min,1,nlstate);
2651: free_vector(max,1,nlstate);
2652: free_vector(meandiff,1,nlstate);
1.126 brouard 2653: return prlim;
2654: }
1.169 brouard 2655: } /* age loop */
1.208 brouard 2656: /* After some age loop it doesn't converge */
1.209 brouard 2657: 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 2658: 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 2659: /* 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); */
2660: free_vector(min,1,nlstate);
2661: free_vector(max,1,nlstate);
2662: free_vector(meandiff,1,nlstate);
1.208 brouard 2663:
1.169 brouard 2664: return prlim; /* should not reach here */
1.126 brouard 2665: }
2666:
1.217 brouard 2667:
2668: /**** Back Prevalence limit (stable or period prevalence) ****************/
2669:
1.218 brouard 2670: /* 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) */
2671: /* 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 2672: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 2673: {
1.264 brouard 2674: /* 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 2675: matrix by transitions matrix until convergence is reached with precision ftolpl */
2676: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
2677: /* Wx is row vector: population in state 1, population in state 2, population dead */
2678: /* or prevalence in state 1, prevalence in state 2, 0 */
2679: /* newm is the matrix after multiplications, its rows are identical at a factor */
2680: /* Initial matrix pimij */
2681: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2682: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2683: /* 0, 0 , 1} */
2684: /*
2685: * and after some iteration: */
2686: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2687: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2688: /* 0, 0 , 1} */
2689: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2690: /* {0.51571254859325999, 0.4842874514067399, */
2691: /* 0.51326036147820708, 0.48673963852179264} */
2692: /* If we start from prlim again, prlim tends to a constant matrix */
2693:
2694: int i, ii,j,k;
1.247 brouard 2695: int first=0;
1.217 brouard 2696: double *min, *max, *meandiff, maxmax,sumnew=0.;
2697: /* double **matprod2(); */ /* test */
2698: double **out, cov[NCOVMAX+1], **bmij();
2699: double **newm;
1.218 brouard 2700: double **dnewm, **doldm, **dsavm; /* for use */
2701: double **oldm, **savm; /* for use */
2702:
1.217 brouard 2703: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
2704: int ncvloop=0;
2705:
2706: min=vector(1,nlstate);
2707: max=vector(1,nlstate);
2708: meandiff=vector(1,nlstate);
2709:
1.266 brouard 2710: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
2711: oldm=oldms; savm=savms;
2712:
2713: /* Starting with matrix unity */
2714: for (ii=1;ii<=nlstate+ndeath;ii++)
2715: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 2716: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2717: }
2718:
2719: cov[1]=1.;
2720:
2721: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
2722: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 2723: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
2724: for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 2725: ncvloop++;
1.218 brouard 2726: newm=savm; /* oldm should be kept from previous iteration or unity at start */
2727: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 2728: /* Covariates have to be included here again */
2729: cov[2]=agefin;
2730: if(nagesqr==1)
2731: cov[3]= agefin*agefin;;
1.242 brouard 2732: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2733: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2734: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.264 brouard 2735: /* 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 2736: }
2737: /* for (k=1; k<=cptcovn;k++) { */
2738: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
2739: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
2740: /* /\* 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])]); *\/ */
2741: /* } */
2742: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2743: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
2744: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2745: /* 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]); */
2746: }
2747: /* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; */
2748: /* for (k=1; k<=cptcovprod;k++) /\* Useless *\/ */
2749: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\/ */
2750: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */
2751: for (k=1; k<=cptcovage;k++){ /* For product with age */
2752: if(Dummy[Tvar[Tage[k]]]){
2753: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
2754: } else{
2755: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
2756: }
2757: /* 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]); */
2758: }
2759: for (k=1; k<=cptcovprod;k++){ /* For product without age */
2760: /* 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]); */
2761: if(Dummy[Tvard[k][1]==0]){
2762: if(Dummy[Tvard[k][2]==0]){
2763: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2764: }else{
2765: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2766: }
2767: }else{
2768: if(Dummy[Tvard[k][2]==0]){
2769: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2770: }else{
2771: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2772: }
2773: }
1.217 brouard 2774: }
2775:
2776: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2777: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2778: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
2779: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2780: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2781: /* ij should be linked to the correct index of cov */
2782: /* age and covariate values ij are in 'cov', but we need to pass
2783: * ij for the observed prevalence at age and status and covariate
2784: * number: prevacurrent[(int)agefin][ii][ij]
2785: */
2786: /* 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 *\/ */
2787: /* 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 *\/ */
2788: 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 2789: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 2790: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
2791: /* for(i=1; i<=nlstate+ndeath; i++) { */
2792: /* printf("%d newm= ",i); */
2793: /* for(j=1;j<=nlstate+ndeath;j++) { */
2794: /* printf("%f ",newm[i][j]); */
2795: /* } */
2796: /* printf("oldm * "); */
2797: /* for(j=1;j<=nlstate+ndeath;j++) { */
2798: /* printf("%f ",oldm[i][j]); */
2799: /* } */
1.268 brouard 2800: /* printf(" bmmij "); */
1.266 brouard 2801: /* for(j=1;j<=nlstate+ndeath;j++) { */
2802: /* printf("%f ",pmmij[i][j]); */
2803: /* } */
2804: /* printf("\n"); */
2805: /* } */
2806: /* } */
1.217 brouard 2807: savm=oldm;
2808: oldm=newm;
1.266 brouard 2809:
1.217 brouard 2810: for(j=1; j<=nlstate; j++){
2811: max[j]=0.;
2812: min[j]=1.;
2813: }
2814: for(j=1; j<=nlstate; j++){
2815: for(i=1;i<=nlstate;i++){
1.234 brouard 2816: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
2817: bprlim[i][j]= newm[i][j];
2818: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
2819: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 2820: }
2821: }
1.218 brouard 2822:
1.217 brouard 2823: maxmax=0.;
2824: for(i=1; i<=nlstate; i++){
2825: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column */
2826: maxmax=FMAX(maxmax,meandiff[i]);
2827: /* 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 2828: } /* i loop */
1.217 brouard 2829: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 2830: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 2831: if(maxmax < ftolpl){
1.220 brouard 2832: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 2833: free_vector(min,1,nlstate);
2834: free_vector(max,1,nlstate);
2835: free_vector(meandiff,1,nlstate);
2836: return bprlim;
2837: }
2838: } /* age loop */
2839: /* After some age loop it doesn't converge */
1.247 brouard 2840: if(first){
2841: first=1;
2842: 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\
2843: 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);
2844: }
2845: 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 2846: 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);
2847: /* 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); */
2848: free_vector(min,1,nlstate);
2849: free_vector(max,1,nlstate);
2850: free_vector(meandiff,1,nlstate);
2851:
2852: return bprlim; /* should not reach here */
2853: }
2854:
1.126 brouard 2855: /*************** transition probabilities ***************/
2856:
2857: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
2858: {
1.138 brouard 2859: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 2860: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 2861: model to the ncovmodel covariates (including constant and age).
2862: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
2863: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
2864: ncth covariate in the global vector x is given by the formula:
2865: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
2866: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
2867: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
2868: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 2869: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 2870: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 2871: Sum on j ps[i][j] should equal to 1.
1.138 brouard 2872: */
2873: double s1, lnpijopii;
1.126 brouard 2874: /*double t34;*/
1.164 brouard 2875: int i,j, nc, ii, jj;
1.126 brouard 2876:
1.223 brouard 2877: for(i=1; i<= nlstate; i++){
2878: for(j=1; j<i;j++){
2879: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2880: /*lnpijopii += param[i][j][nc]*cov[nc];*/
2881: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
2882: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2883: }
2884: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2885: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2886: }
2887: for(j=i+1; j<=nlstate+ndeath;j++){
2888: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2889: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
2890: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
2891: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
2892: }
2893: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2894: }
2895: }
1.218 brouard 2896:
1.223 brouard 2897: for(i=1; i<= nlstate; i++){
2898: s1=0;
2899: for(j=1; j<i; j++){
2900: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2901: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2902: }
2903: for(j=i+1; j<=nlstate+ndeath; j++){
2904: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2905: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2906: }
2907: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
2908: ps[i][i]=1./(s1+1.);
2909: /* Computing other pijs */
2910: for(j=1; j<i; j++)
2911: ps[i][j]= exp(ps[i][j])*ps[i][i];
2912: for(j=i+1; j<=nlstate+ndeath; j++)
2913: ps[i][j]= exp(ps[i][j])*ps[i][i];
2914: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
2915: } /* end i */
1.218 brouard 2916:
1.223 brouard 2917: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
2918: for(jj=1; jj<= nlstate+ndeath; jj++){
2919: ps[ii][jj]=0;
2920: ps[ii][ii]=1;
2921: }
2922: }
1.218 brouard 2923:
2924:
1.223 brouard 2925: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
2926: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
2927: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
2928: /* } */
2929: /* printf("\n "); */
2930: /* } */
2931: /* printf("\n ");printf("%lf ",cov[2]);*/
2932: /*
2933: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 2934: goto end;*/
1.266 brouard 2935: return ps; /* Pointer is unchanged since its call */
1.126 brouard 2936: }
2937:
1.218 brouard 2938: /*************** backward transition probabilities ***************/
2939:
2940: /* 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 ) */
2941: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
2942: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
2943: {
1.266 brouard 2944: /* Computes the backward probability at age agefin and covariate combination ij. In fact cov is already filled and x too.
2945: * 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 2946: */
1.218 brouard 2947: int i, ii, j,k;
1.222 brouard 2948:
2949: double **out, **pmij();
2950: double sumnew=0.;
1.218 brouard 2951: double agefin;
1.268 brouard 2952: 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 2953: double **dnewm, **dsavm, **doldm;
2954: double **bbmij;
2955:
1.218 brouard 2956: doldm=ddoldms; /* global pointers */
1.222 brouard 2957: dnewm=ddnewms;
2958: dsavm=ddsavms;
2959:
2960: agefin=cov[2];
1.268 brouard 2961: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 2962: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 2963: the observed prevalence (with this covariate ij) at beginning of transition */
2964: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 2965:
2966: /* P_x */
1.266 brouard 2967: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm */
1.268 brouard 2968: /* outputs pmmij which is a stochastic matrix in row */
2969:
2970: /* Diag(w_x) */
2971: /* Problem with prevacurrent which can be zero */
2972: sumnew=0.;
1.269 brouard 2973: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 2974: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.269 brouard 2975: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 2976: sumnew+=prevacurrent[(int)agefin][ii][ij];
2977: }
2978: if(sumnew >0.01){ /* At least some value in the prevalence */
2979: for (ii=1;ii<=nlstate+ndeath;ii++){
2980: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 2981: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 2982: }
2983: }else{
2984: for (ii=1;ii<=nlstate+ndeath;ii++){
2985: for (j=1;j<=nlstate+ndeath;j++)
2986: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
2987: }
2988: /* if(sumnew <0.9){ */
2989: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
2990: /* } */
2991: }
2992: k3=0.0; /* We put the last diagonal to 0 */
2993: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
2994: doldm[ii][ii]= k3;
2995: }
2996: /* End doldm, At the end doldm is diag[(w_i)] */
2997:
2998: /* left Product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm) */
2999: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* Bug Valgrind */
3000:
3001: /* Diag(Sum_i w^i_x p^ij_x */
3002: /* 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 3003: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 3004: sumnew=0.;
1.222 brouard 3005: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 3006: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 3007: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 3008: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 3009: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 3010: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 3011: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3012: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 3013: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3014: /* }else */
1.268 brouard 3015: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
3016: } /*End ii */
3017: } /* 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 */
3018:
3019: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* Bug Valgrind */
3020: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 3021: /* end bmij */
1.266 brouard 3022: return ps; /*pointer is unchanged */
1.218 brouard 3023: }
1.217 brouard 3024: /*************** transition probabilities ***************/
3025:
1.218 brouard 3026: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 3027: {
3028: /* According to parameters values stored in x and the covariate's values stored in cov,
3029: computes the probability to be observed in state j being in state i by appying the
3030: model to the ncovmodel covariates (including constant and age).
3031: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3032: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3033: ncth covariate in the global vector x is given by the formula:
3034: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3035: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3036: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3037: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
3038: Outputs ps[i][j] the probability to be observed in j being in j according to
3039: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
3040: */
3041: double s1, lnpijopii;
3042: /*double t34;*/
3043: int i,j, nc, ii, jj;
3044:
1.234 brouard 3045: for(i=1; i<= nlstate; i++){
3046: for(j=1; j<i;j++){
3047: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3048: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3049: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3050: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3051: }
3052: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3053: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3054: }
3055: for(j=i+1; j<=nlstate+ndeath;j++){
3056: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3057: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3058: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3059: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3060: }
3061: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3062: }
3063: }
3064:
3065: for(i=1; i<= nlstate; i++){
3066: s1=0;
3067: for(j=1; j<i; j++){
3068: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3069: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3070: }
3071: for(j=i+1; j<=nlstate+ndeath; j++){
3072: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3073: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3074: }
3075: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3076: ps[i][i]=1./(s1+1.);
3077: /* Computing other pijs */
3078: for(j=1; j<i; j++)
3079: ps[i][j]= exp(ps[i][j])*ps[i][i];
3080: for(j=i+1; j<=nlstate+ndeath; j++)
3081: ps[i][j]= exp(ps[i][j])*ps[i][i];
3082: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3083: } /* end i */
3084:
3085: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3086: for(jj=1; jj<= nlstate+ndeath; jj++){
3087: ps[ii][jj]=0;
3088: ps[ii][ii]=1;
3089: }
3090: }
3091: /* Added for backcast */ /* Transposed matrix too */
3092: for(jj=1; jj<= nlstate+ndeath; jj++){
3093: s1=0.;
3094: for(ii=1; ii<= nlstate+ndeath; ii++){
3095: s1+=ps[ii][jj];
3096: }
3097: for(ii=1; ii<= nlstate; ii++){
3098: ps[ii][jj]=ps[ii][jj]/s1;
3099: }
3100: }
3101: /* Transposition */
3102: for(jj=1; jj<= nlstate+ndeath; jj++){
3103: for(ii=jj; ii<= nlstate+ndeath; ii++){
3104: s1=ps[ii][jj];
3105: ps[ii][jj]=ps[jj][ii];
3106: ps[jj][ii]=s1;
3107: }
3108: }
3109: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3110: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3111: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3112: /* } */
3113: /* printf("\n "); */
3114: /* } */
3115: /* printf("\n ");printf("%lf ",cov[2]);*/
3116: /*
3117: for(i=1; i<= npar; i++) printf("%f ",x[i]);
3118: goto end;*/
3119: return ps;
1.217 brouard 3120: }
3121:
3122:
1.126 brouard 3123: /**************** Product of 2 matrices ******************/
3124:
1.145 brouard 3125: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 3126: {
3127: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
3128: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
3129: /* in, b, out are matrice of pointers which should have been initialized
3130: before: only the contents of out is modified. The function returns
3131: a pointer to pointers identical to out */
1.145 brouard 3132: int i, j, k;
1.126 brouard 3133: for(i=nrl; i<= nrh; i++)
1.145 brouard 3134: for(k=ncolol; k<=ncoloh; k++){
3135: out[i][k]=0.;
3136: for(j=ncl; j<=nch; j++)
3137: out[i][k] +=in[i][j]*b[j][k];
3138: }
1.126 brouard 3139: return out;
3140: }
3141:
3142:
3143: /************* Higher Matrix Product ***************/
3144:
1.235 brouard 3145: 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 3146: {
1.218 brouard 3147: /* Computes the transition matrix starting at age 'age' and combination of covariate values corresponding to ij over
1.126 brouard 3148: 'nhstepm*hstepm*stepm' months (i.e. until
3149: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3150: nhstepm*hstepm matrices.
3151: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3152: (typically every 2 years instead of every month which is too big
3153: for the memory).
3154: Model is determined by parameters x and covariates have to be
3155: included manually here.
3156:
3157: */
3158:
3159: int i, j, d, h, k;
1.131 brouard 3160: double **out, cov[NCOVMAX+1];
1.126 brouard 3161: double **newm;
1.187 brouard 3162: double agexact;
1.214 brouard 3163: double agebegin, ageend;
1.126 brouard 3164:
3165: /* Hstepm could be zero and should return the unit matrix */
3166: for (i=1;i<=nlstate+ndeath;i++)
3167: for (j=1;j<=nlstate+ndeath;j++){
3168: oldm[i][j]=(i==j ? 1.0 : 0.0);
3169: po[i][j][0]=(i==j ? 1.0 : 0.0);
3170: }
3171: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3172: for(h=1; h <=nhstepm; h++){
3173: for(d=1; d <=hstepm; d++){
3174: newm=savm;
3175: /* Covariates have to be included here again */
3176: cov[1]=1.;
1.214 brouard 3177: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3178: cov[2]=agexact;
3179: if(nagesqr==1)
1.227 brouard 3180: cov[3]= agexact*agexact;
1.235 brouard 3181: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
3182: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
3183: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3184: /* 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)); */
3185: }
3186: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3187: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3188: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3189: /* 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]); */
3190: }
3191: for (k=1; k<=cptcovage;k++){
3192: if(Dummy[Tvar[Tage[k]]]){
3193: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
3194: } else{
3195: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3196: }
3197: /* 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]); */
3198: }
3199: for (k=1; k<=cptcovprod;k++){ /* */
3200: /* 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]); */
3201: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
3202: }
3203: /* for (k=1; k<=cptcovn;k++) */
3204: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3205: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3206: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3207: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3208: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3209:
3210:
1.126 brouard 3211: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3212: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.218 brouard 3213: /* right multiplication of oldm by the current matrix */
1.126 brouard 3214: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3215: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3216: /* if((int)age == 70){ */
3217: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3218: /* for(i=1; i<=nlstate+ndeath; i++) { */
3219: /* printf("%d pmmij ",i); */
3220: /* for(j=1;j<=nlstate+ndeath;j++) { */
3221: /* printf("%f ",pmmij[i][j]); */
3222: /* } */
3223: /* printf(" oldm "); */
3224: /* for(j=1;j<=nlstate+ndeath;j++) { */
3225: /* printf("%f ",oldm[i][j]); */
3226: /* } */
3227: /* printf("\n"); */
3228: /* } */
3229: /* } */
1.126 brouard 3230: savm=oldm;
3231: oldm=newm;
3232: }
3233: for(i=1; i<=nlstate+ndeath; i++)
3234: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 3235: po[i][j][h]=newm[i][j];
3236: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3237: }
1.128 brouard 3238: /*printf("h=%d ",h);*/
1.126 brouard 3239: } /* end h */
1.267 brouard 3240: /* printf("\n H=%d \n",h); */
1.126 brouard 3241: return po;
3242: }
3243:
1.217 brouard 3244: /************* Higher Back Matrix Product ***************/
1.218 brouard 3245: /* 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 3246: 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 3247: {
1.266 brouard 3248: /* For a combination of dummy covariate ij, computes the transition matrix starting at age 'age' over
1.217 brouard 3249: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3250: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3251: nhstepm*hstepm matrices.
3252: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3253: (typically every 2 years instead of every month which is too big
1.217 brouard 3254: for the memory).
1.218 brouard 3255: Model is determined by parameters x and covariates have to be
1.266 brouard 3256: included manually here. Then we use a call to bmij(x and cov)
3257: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 3258: */
1.217 brouard 3259:
3260: int i, j, d, h, k;
1.266 brouard 3261: double **out, cov[NCOVMAX+1], **bmij();
3262: double **newm, ***newmm;
1.217 brouard 3263: double agexact;
3264: double agebegin, ageend;
1.222 brouard 3265: double **oldm, **savm;
1.217 brouard 3266:
1.266 brouard 3267: newmm=po; /* To be saved */
3268: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 3269: /* Hstepm could be zero and should return the unit matrix */
3270: for (i=1;i<=nlstate+ndeath;i++)
3271: for (j=1;j<=nlstate+ndeath;j++){
3272: oldm[i][j]=(i==j ? 1.0 : 0.0);
3273: po[i][j][0]=(i==j ? 1.0 : 0.0);
3274: }
3275: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3276: for(h=1; h <=nhstepm; h++){
3277: for(d=1; d <=hstepm; d++){
3278: newm=savm;
3279: /* Covariates have to be included here again */
3280: cov[1]=1.;
1.271 brouard 3281: agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 3282: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
3283: cov[2]=agexact;
3284: if(nagesqr==1)
1.222 brouard 3285: cov[3]= agexact*agexact;
1.266 brouard 3286: for (k=1; k<=cptcovn;k++){
3287: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3288: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
3289: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3290: /* 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)); */
3291: }
1.267 brouard 3292: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3293: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3294: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3295: /* 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]); */
3296: }
3297: for (k=1; k<=cptcovage;k++){ /* Should start at cptcovn+1 */
3298: if(Dummy[Tvar[Tage[k]]]){
3299: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
3300: } else{
3301: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3302: }
3303: /* 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]); */
3304: }
3305: for (k=1; k<=cptcovprod;k++){ /* Useless because included in cptcovn */
1.222 brouard 3306: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.267 brouard 3307: }
1.217 brouard 3308: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3309: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.267 brouard 3310:
1.218 brouard 3311: /* Careful transposed matrix */
1.266 brouard 3312: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 3313: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3314: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3315: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.222 brouard 3316: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);
1.217 brouard 3317: /* if((int)age == 70){ */
3318: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3319: /* for(i=1; i<=nlstate+ndeath; i++) { */
3320: /* printf("%d pmmij ",i); */
3321: /* for(j=1;j<=nlstate+ndeath;j++) { */
3322: /* printf("%f ",pmmij[i][j]); */
3323: /* } */
3324: /* printf(" oldm "); */
3325: /* for(j=1;j<=nlstate+ndeath;j++) { */
3326: /* printf("%f ",oldm[i][j]); */
3327: /* } */
3328: /* printf("\n"); */
3329: /* } */
3330: /* } */
3331: savm=oldm;
3332: oldm=newm;
3333: }
3334: for(i=1; i<=nlstate+ndeath; i++)
3335: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 3336: po[i][j][h]=newm[i][j];
1.268 brouard 3337: /* if(h==nhstepm) */
3338: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 3339: }
1.268 brouard 3340: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 3341: } /* end h */
1.268 brouard 3342: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 3343: return po;
3344: }
3345:
3346:
1.162 brouard 3347: #ifdef NLOPT
3348: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
3349: double fret;
3350: double *xt;
3351: int j;
3352: myfunc_data *d2 = (myfunc_data *) pd;
3353: /* xt = (p1-1); */
3354: xt=vector(1,n);
3355: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
3356:
3357: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
3358: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
3359: printf("Function = %.12lf ",fret);
3360: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
3361: printf("\n");
3362: free_vector(xt,1,n);
3363: return fret;
3364: }
3365: #endif
1.126 brouard 3366:
3367: /*************** log-likelihood *************/
3368: double func( double *x)
3369: {
1.226 brouard 3370: int i, ii, j, k, mi, d, kk;
3371: int ioffset=0;
3372: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
3373: double **out;
3374: double lli; /* Individual log likelihood */
3375: int s1, s2;
1.228 brouard 3376: 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 3377: double bbh, survp;
3378: long ipmx;
3379: double agexact;
3380: /*extern weight */
3381: /* We are differentiating ll according to initial status */
3382: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3383: /*for(i=1;i<imx;i++)
3384: printf(" %d\n",s[4][i]);
3385: */
1.162 brouard 3386:
1.226 brouard 3387: ++countcallfunc;
1.162 brouard 3388:
1.226 brouard 3389: cov[1]=1.;
1.126 brouard 3390:
1.226 brouard 3391: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3392: ioffset=0;
1.226 brouard 3393: if(mle==1){
3394: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3395: /* Computes the values of the ncovmodel covariates of the model
3396: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
3397: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
3398: to be observed in j being in i according to the model.
3399: */
1.243 brouard 3400: ioffset=2+nagesqr ;
1.233 brouard 3401: /* Fixed */
1.234 brouard 3402: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */
3403: 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)*/
3404: }
1.226 brouard 3405: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
3406: is 6, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]
3407: has been calculated etc */
3408: /* For an individual i, wav[i] gives the number of effective waves */
3409: /* We compute the contribution to Likelihood of each effective transition
3410: mw[mi][i] is real wave of the mi th effectve wave */
3411: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
3412: s2=s[mw[mi+1][i]][i];
3413: And the iv th varying covariate is the cotvar[mw[mi+1][i]][iv][i]
3414: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
3415: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
3416: */
3417: for(mi=1; mi<= wav[i]-1; mi++){
1.234 brouard 3418: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 3419: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
3420: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
1.234 brouard 3421: }
3422: for (ii=1;ii<=nlstate+ndeath;ii++)
3423: for (j=1;j<=nlstate+ndeath;j++){
3424: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3425: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3426: }
3427: for(d=0; d<dh[mi][i]; d++){
3428: newm=savm;
3429: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3430: cov[2]=agexact;
3431: if(nagesqr==1)
3432: cov[3]= agexact*agexact; /* Should be changed here */
3433: for (kk=1; kk<=cptcovage;kk++) {
1.242 brouard 3434: if(!FixedV[Tvar[Tage[kk]]])
1.234 brouard 3435: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
1.242 brouard 3436: else
3437: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
1.234 brouard 3438: }
3439: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3440: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3441: savm=oldm;
3442: oldm=newm;
3443: } /* end mult */
3444:
3445: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
3446: /* But now since version 0.9 we anticipate for bias at large stepm.
3447: * If stepm is larger than one month (smallest stepm) and if the exact delay
3448: * (in months) between two waves is not a multiple of stepm, we rounded to
3449: * the nearest (and in case of equal distance, to the lowest) interval but now
3450: * we keep into memory the bias bh[mi][i] and also the previous matrix product
3451: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
3452: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 3453: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
3454: * -stepm/2 to stepm/2 .
3455: * For stepm=1 the results are the same as for previous versions of Imach.
3456: * For stepm > 1 the results are less biased than in previous versions.
3457: */
1.234 brouard 3458: s1=s[mw[mi][i]][i];
3459: s2=s[mw[mi+1][i]][i];
3460: bbh=(double)bh[mi][i]/(double)stepm;
3461: /* bias bh is positive if real duration
3462: * is higher than the multiple of stepm and negative otherwise.
3463: */
3464: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
3465: if( s2 > nlstate){
3466: /* i.e. if s2 is a death state and if the date of death is known
3467: then the contribution to the likelihood is the probability to
3468: die between last step unit time and current step unit time,
3469: which is also equal to probability to die before dh
3470: minus probability to die before dh-stepm .
3471: In version up to 0.92 likelihood was computed
3472: as if date of death was unknown. Death was treated as any other
3473: health state: the date of the interview describes the actual state
3474: and not the date of a change in health state. The former idea was
3475: to consider that at each interview the state was recorded
3476: (healthy, disable or death) and IMaCh was corrected; but when we
3477: introduced the exact date of death then we should have modified
3478: the contribution of an exact death to the likelihood. This new
3479: contribution is smaller and very dependent of the step unit
3480: stepm. It is no more the probability to die between last interview
3481: and month of death but the probability to survive from last
3482: interview up to one month before death multiplied by the
3483: probability to die within a month. Thanks to Chris
3484: Jackson for correcting this bug. Former versions increased
3485: mortality artificially. The bad side is that we add another loop
3486: which slows down the processing. The difference can be up to 10%
3487: lower mortality.
3488: */
3489: /* If, at the beginning of the maximization mostly, the
3490: cumulative probability or probability to be dead is
3491: constant (ie = 1) over time d, the difference is equal to
3492: 0. out[s1][3] = savm[s1][3]: probability, being at state
3493: s1 at precedent wave, to be dead a month before current
3494: wave is equal to probability, being at state s1 at
3495: precedent wave, to be dead at mont of the current
3496: wave. Then the observed probability (that this person died)
3497: is null according to current estimated parameter. In fact,
3498: it should be very low but not zero otherwise the log go to
3499: infinity.
3500: */
1.183 brouard 3501: /* #ifdef INFINITYORIGINAL */
3502: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3503: /* #else */
3504: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
3505: /* lli=log(mytinydouble); */
3506: /* else */
3507: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3508: /* #endif */
1.226 brouard 3509: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3510:
1.226 brouard 3511: } else if ( s2==-1 ) { /* alive */
3512: for (j=1,survp=0. ; j<=nlstate; j++)
3513: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3514: /*survp += out[s1][j]; */
3515: lli= log(survp);
3516: }
3517: else if (s2==-4) {
3518: for (j=3,survp=0. ; j<=nlstate; j++)
3519: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3520: lli= log(survp);
3521: }
3522: else if (s2==-5) {
3523: for (j=1,survp=0. ; j<=2; j++)
3524: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3525: lli= log(survp);
3526: }
3527: else{
3528: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3529: /* 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 */
3530: }
3531: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
3532: /*if(lli ==000.0)*/
3533: /*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); */
3534: ipmx +=1;
3535: sw += weight[i];
3536: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3537: /* if (lli < log(mytinydouble)){ */
3538: /* 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); */
3539: /* 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]); */
3540: /* } */
3541: } /* end of wave */
3542: } /* end of individual */
3543: } else if(mle==2){
3544: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3545: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3546: for(mi=1; mi<= wav[i]-1; mi++){
3547: for (ii=1;ii<=nlstate+ndeath;ii++)
3548: for (j=1;j<=nlstate+ndeath;j++){
3549: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3550: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3551: }
3552: for(d=0; d<=dh[mi][i]; d++){
3553: newm=savm;
3554: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3555: cov[2]=agexact;
3556: if(nagesqr==1)
3557: cov[3]= agexact*agexact;
3558: for (kk=1; kk<=cptcovage;kk++) {
3559: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3560: }
3561: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3562: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3563: savm=oldm;
3564: oldm=newm;
3565: } /* end mult */
3566:
3567: s1=s[mw[mi][i]][i];
3568: s2=s[mw[mi+1][i]][i];
3569: bbh=(double)bh[mi][i]/(double)stepm;
3570: 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 */
3571: ipmx +=1;
3572: sw += weight[i];
3573: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3574: } /* end of wave */
3575: } /* end of individual */
3576: } else if(mle==3){ /* exponential inter-extrapolation */
3577: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3578: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3579: for(mi=1; mi<= wav[i]-1; mi++){
3580: for (ii=1;ii<=nlstate+ndeath;ii++)
3581: for (j=1;j<=nlstate+ndeath;j++){
3582: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3583: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3584: }
3585: for(d=0; d<dh[mi][i]; d++){
3586: newm=savm;
3587: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3588: cov[2]=agexact;
3589: if(nagesqr==1)
3590: cov[3]= agexact*agexact;
3591: for (kk=1; kk<=cptcovage;kk++) {
3592: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3593: }
3594: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3595: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3596: savm=oldm;
3597: oldm=newm;
3598: } /* end mult */
3599:
3600: s1=s[mw[mi][i]][i];
3601: s2=s[mw[mi+1][i]][i];
3602: bbh=(double)bh[mi][i]/(double)stepm;
3603: 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 */
3604: ipmx +=1;
3605: sw += weight[i];
3606: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3607: } /* end of wave */
3608: } /* end of individual */
3609: }else if (mle==4){ /* ml=4 no inter-extrapolation */
3610: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3611: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3612: for(mi=1; mi<= wav[i]-1; mi++){
3613: for (ii=1;ii<=nlstate+ndeath;ii++)
3614: for (j=1;j<=nlstate+ndeath;j++){
3615: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3616: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3617: }
3618: for(d=0; d<dh[mi][i]; d++){
3619: newm=savm;
3620: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3621: cov[2]=agexact;
3622: if(nagesqr==1)
3623: cov[3]= agexact*agexact;
3624: for (kk=1; kk<=cptcovage;kk++) {
3625: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3626: }
1.126 brouard 3627:
1.226 brouard 3628: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3629: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3630: savm=oldm;
3631: oldm=newm;
3632: } /* end mult */
3633:
3634: s1=s[mw[mi][i]][i];
3635: s2=s[mw[mi+1][i]][i];
3636: if( s2 > nlstate){
3637: lli=log(out[s1][s2] - savm[s1][s2]);
3638: } else if ( s2==-1 ) { /* alive */
3639: for (j=1,survp=0. ; j<=nlstate; j++)
3640: survp += out[s1][j];
3641: lli= log(survp);
3642: }else{
3643: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3644: }
3645: ipmx +=1;
3646: sw += weight[i];
3647: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.126 brouard 3648: /* 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 3649: } /* end of wave */
3650: } /* end of individual */
3651: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
3652: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3653: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3654: for(mi=1; mi<= wav[i]-1; mi++){
3655: for (ii=1;ii<=nlstate+ndeath;ii++)
3656: for (j=1;j<=nlstate+ndeath;j++){
3657: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3658: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3659: }
3660: for(d=0; d<dh[mi][i]; d++){
3661: newm=savm;
3662: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3663: cov[2]=agexact;
3664: if(nagesqr==1)
3665: cov[3]= agexact*agexact;
3666: for (kk=1; kk<=cptcovage;kk++) {
3667: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3668: }
1.126 brouard 3669:
1.226 brouard 3670: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3671: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3672: savm=oldm;
3673: oldm=newm;
3674: } /* end mult */
3675:
3676: s1=s[mw[mi][i]][i];
3677: s2=s[mw[mi+1][i]][i];
3678: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3679: ipmx +=1;
3680: sw += weight[i];
3681: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3682: /*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]);*/
3683: } /* end of wave */
3684: } /* end of individual */
3685: } /* End of if */
3686: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3687: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3688: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3689: return -l;
1.126 brouard 3690: }
3691:
3692: /*************** log-likelihood *************/
3693: double funcone( double *x)
3694: {
1.228 brouard 3695: /* Same as func but slower because of a lot of printf and if */
1.126 brouard 3696: int i, ii, j, k, mi, d, kk;
1.228 brouard 3697: int ioffset=0;
1.131 brouard 3698: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 3699: double **out;
3700: double lli; /* Individual log likelihood */
3701: double llt;
3702: int s1, s2;
1.228 brouard 3703: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
3704:
1.126 brouard 3705: double bbh, survp;
1.187 brouard 3706: double agexact;
1.214 brouard 3707: double agebegin, ageend;
1.126 brouard 3708: /*extern weight */
3709: /* We are differentiating ll according to initial status */
3710: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3711: /*for(i=1;i<imx;i++)
3712: printf(" %d\n",s[4][i]);
3713: */
3714: cov[1]=1.;
3715:
3716: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3717: ioffset=0;
3718: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.243 brouard 3719: /* ioffset=2+nagesqr+cptcovage; */
3720: ioffset=2+nagesqr;
1.232 brouard 3721: /* Fixed */
1.224 brouard 3722: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 3723: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
3724: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */
3725: 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)*/
3726: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
3727: /* cov[2+6]=covar[Tvar[6]][i]; */
3728: /* cov[2+6]=covar[2][i]; V2 */
3729: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
3730: /* cov[2+7]=covar[Tvar[7]][i]; */
3731: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
3732: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
3733: /* cov[2+9]=covar[Tvar[9]][i]; */
3734: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 3735: }
1.232 brouard 3736: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
3737: /* 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?)*\/ */
3738: /* } */
1.231 brouard 3739: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
3740: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
3741: /* } */
1.225 brouard 3742:
1.233 brouard 3743:
3744: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.232 brouard 3745: /* Wave varying (but not age varying) */
3746: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 3747: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
3748: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
3749: }
1.232 brouard 3750: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates (single??)*\/ */
1.242 brouard 3751: /* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3752: /* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; */
3753: /* k=ioffset-2-nagesqr-cptcovage+itv; /\* position in simple model *\/ */
3754: /* cov[ioffset+itv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; */
3755: /* 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 3756: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 3757: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3758: /* /\* 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]); *\/ */
3759: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 3760: /* } */
1.126 brouard 3761: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 3762: for (j=1;j<=nlstate+ndeath;j++){
3763: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3764: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3765: }
1.214 brouard 3766:
3767: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
3768: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
3769: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 3770: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 3771: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
3772: and mw[mi+1][i]. dh depends on stepm.*/
3773: newm=savm;
1.247 brouard 3774: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 3775: cov[2]=agexact;
3776: if(nagesqr==1)
3777: cov[3]= agexact*agexact;
3778: for (kk=1; kk<=cptcovage;kk++) {
3779: if(!FixedV[Tvar[Tage[kk]]])
3780: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3781: else
3782: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
3783: }
3784: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
3785: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3786: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3787: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3788: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
3789: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
3790: savm=oldm;
3791: oldm=newm;
1.126 brouard 3792: } /* end mult */
3793:
3794: s1=s[mw[mi][i]][i];
3795: s2=s[mw[mi+1][i]][i];
1.217 brouard 3796: /* if(s2==-1){ */
1.268 brouard 3797: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 3798: /* /\* exit(1); *\/ */
3799: /* } */
1.126 brouard 3800: bbh=(double)bh[mi][i]/(double)stepm;
3801: /* bias is positive if real duration
3802: * is higher than the multiple of stepm and negative otherwise.
3803: */
3804: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 3805: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3806: } else if ( s2==-1 ) { /* alive */
1.242 brouard 3807: for (j=1,survp=0. ; j<=nlstate; j++)
3808: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3809: lli= log(survp);
1.126 brouard 3810: }else if (mle==1){
1.242 brouard 3811: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 3812: } else if(mle==2){
1.242 brouard 3813: 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 3814: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 3815: 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 3816: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 3817: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 3818: } else{ /* mle=0 back to 1 */
1.242 brouard 3819: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3820: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 3821: } /* End of if */
3822: ipmx +=1;
3823: sw += weight[i];
3824: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.132 brouard 3825: /*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 3826: if(globpr){
1.246 brouard 3827: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 3828: %11.6f %11.6f %11.6f ", \
1.242 brouard 3829: 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 3830: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.242 brouard 3831: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
3832: llt +=ll[k]*gipmx/gsw;
3833: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
3834: }
3835: fprintf(ficresilk," %10.6f\n", -llt);
1.126 brouard 3836: }
1.232 brouard 3837: } /* end of wave */
3838: } /* end of individual */
3839: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3840: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3841: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3842: if(globpr==0){ /* First time we count the contributions and weights */
3843: gipmx=ipmx;
3844: gsw=sw;
3845: }
3846: return -l;
1.126 brouard 3847: }
3848:
3849:
3850: /*************** function likelione ***********/
3851: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*funcone)(double []))
3852: {
3853: /* This routine should help understanding what is done with
3854: the selection of individuals/waves and
3855: to check the exact contribution to the likelihood.
3856: Plotting could be done.
3857: */
3858: int k;
3859:
3860: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 3861: strcpy(fileresilk,"ILK_");
1.202 brouard 3862: strcat(fileresilk,fileresu);
1.126 brouard 3863: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
3864: printf("Problem with resultfile: %s\n", fileresilk);
3865: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
3866: }
1.214 brouard 3867: 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");
3868: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 3869: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
3870: for(k=1; k<=nlstate; k++)
3871: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
3872: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total)\n");
3873: }
3874:
3875: *fretone=(*funcone)(p);
3876: if(*globpri !=0){
3877: fclose(ficresilk);
1.205 brouard 3878: if (mle ==0)
3879: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
3880: else if(mle >=1)
3881: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
3882: 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 3883: fprintf(fichtm,"\n<br>Equation of the model: <b>model=1+age+%s</b><br>\n",model);
1.208 brouard 3884:
3885: for (k=1; k<= nlstate ; k++) {
1.211 brouard 3886: 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 3887: <img src=\"%s-p%dj.png\">",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
3888: }
1.207 brouard 3889: 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 3890: <img src=\"%s-ori.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 3891: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.204 brouard 3892: <img src=\"%s-dest.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 3893: fflush(fichtm);
1.205 brouard 3894: }
1.126 brouard 3895: return;
3896: }
3897:
3898:
3899: /*********** Maximum Likelihood Estimation ***************/
3900:
3901: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
3902: {
1.165 brouard 3903: int i,j, iter=0;
1.126 brouard 3904: double **xi;
3905: double fret;
3906: double fretone; /* Only one call to likelihood */
3907: /* char filerespow[FILENAMELENGTH];*/
1.162 brouard 3908:
3909: #ifdef NLOPT
3910: int creturn;
3911: nlopt_opt opt;
3912: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
3913: double *lb;
3914: double minf; /* the minimum objective value, upon return */
3915: double * p1; /* Shifted parameters from 0 instead of 1 */
3916: myfunc_data dinst, *d = &dinst;
3917: #endif
3918:
3919:
1.126 brouard 3920: xi=matrix(1,npar,1,npar);
3921: for (i=1;i<=npar;i++)
3922: for (j=1;j<=npar;j++)
3923: xi[i][j]=(i==j ? 1.0 : 0.0);
3924: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 3925: strcpy(filerespow,"POW_");
1.126 brouard 3926: strcat(filerespow,fileres);
3927: if((ficrespow=fopen(filerespow,"w"))==NULL) {
3928: printf("Problem with resultfile: %s\n", filerespow);
3929: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
3930: }
3931: fprintf(ficrespow,"# Powell\n# iter -2*LL");
3932: for (i=1;i<=nlstate;i++)
3933: for(j=1;j<=nlstate+ndeath;j++)
3934: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
3935: fprintf(ficrespow,"\n");
1.162 brouard 3936: #ifdef POWELL
1.126 brouard 3937: powell(p,xi,npar,ftol,&iter,&fret,func);
1.162 brouard 3938: #endif
1.126 brouard 3939:
1.162 brouard 3940: #ifdef NLOPT
3941: #ifdef NEWUOA
3942: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
3943: #else
3944: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
3945: #endif
3946: lb=vector(0,npar-1);
3947: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
3948: nlopt_set_lower_bounds(opt, lb);
3949: nlopt_set_initial_step1(opt, 0.1);
3950:
3951: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
3952: d->function = func;
3953: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
3954: nlopt_set_min_objective(opt, myfunc, d);
3955: nlopt_set_xtol_rel(opt, ftol);
3956: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
3957: printf("nlopt failed! %d\n",creturn);
3958: }
3959: else {
3960: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
3961: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
3962: iter=1; /* not equal */
3963: }
3964: nlopt_destroy(opt);
3965: #endif
1.126 brouard 3966: free_matrix(xi,1,npar,1,npar);
3967: fclose(ficrespow);
1.203 brouard 3968: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
3969: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 3970: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 3971:
3972: }
3973:
3974: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 3975: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 3976: {
3977: double **a,**y,*x,pd;
1.203 brouard 3978: /* double **hess; */
1.164 brouard 3979: int i, j;
1.126 brouard 3980: int *indx;
3981:
3982: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 3983: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 3984: void lubksb(double **a, int npar, int *indx, double b[]) ;
3985: void ludcmp(double **a, int npar, int *indx, double *d) ;
3986: double gompertz(double p[]);
1.203 brouard 3987: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 3988:
3989: printf("\nCalculation of the hessian matrix. Wait...\n");
3990: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
3991: for (i=1;i<=npar;i++){
1.203 brouard 3992: printf("%d-",i);fflush(stdout);
3993: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 3994:
3995: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
3996:
3997: /* printf(" %f ",p[i]);
3998: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
3999: }
4000:
4001: for (i=1;i<=npar;i++) {
4002: for (j=1;j<=npar;j++) {
4003: if (j>i) {
1.203 brouard 4004: printf(".%d-%d",i,j);fflush(stdout);
4005: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
4006: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 4007:
4008: hess[j][i]=hess[i][j];
4009: /*printf(" %lf ",hess[i][j]);*/
4010: }
4011: }
4012: }
4013: printf("\n");
4014: fprintf(ficlog,"\n");
4015:
4016: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
4017: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
4018:
4019: a=matrix(1,npar,1,npar);
4020: y=matrix(1,npar,1,npar);
4021: x=vector(1,npar);
4022: indx=ivector(1,npar);
4023: for (i=1;i<=npar;i++)
4024: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
4025: ludcmp(a,npar,indx,&pd);
4026:
4027: for (j=1;j<=npar;j++) {
4028: for (i=1;i<=npar;i++) x[i]=0;
4029: x[j]=1;
4030: lubksb(a,npar,indx,x);
4031: for (i=1;i<=npar;i++){
4032: matcov[i][j]=x[i];
4033: }
4034: }
4035:
4036: printf("\n#Hessian matrix#\n");
4037: fprintf(ficlog,"\n#Hessian matrix#\n");
4038: for (i=1;i<=npar;i++) {
4039: for (j=1;j<=npar;j++) {
1.203 brouard 4040: printf("%.6e ",hess[i][j]);
4041: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 4042: }
4043: printf("\n");
4044: fprintf(ficlog,"\n");
4045: }
4046:
1.203 brouard 4047: /* printf("\n#Covariance matrix#\n"); */
4048: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
4049: /* for (i=1;i<=npar;i++) { */
4050: /* for (j=1;j<=npar;j++) { */
4051: /* printf("%.6e ",matcov[i][j]); */
4052: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
4053: /* } */
4054: /* printf("\n"); */
4055: /* fprintf(ficlog,"\n"); */
4056: /* } */
4057:
1.126 brouard 4058: /* Recompute Inverse */
1.203 brouard 4059: /* for (i=1;i<=npar;i++) */
4060: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
4061: /* ludcmp(a,npar,indx,&pd); */
4062:
4063: /* printf("\n#Hessian matrix recomputed#\n"); */
4064:
4065: /* for (j=1;j<=npar;j++) { */
4066: /* for (i=1;i<=npar;i++) x[i]=0; */
4067: /* x[j]=1; */
4068: /* lubksb(a,npar,indx,x); */
4069: /* for (i=1;i<=npar;i++){ */
4070: /* y[i][j]=x[i]; */
4071: /* printf("%.3e ",y[i][j]); */
4072: /* fprintf(ficlog,"%.3e ",y[i][j]); */
4073: /* } */
4074: /* printf("\n"); */
4075: /* fprintf(ficlog,"\n"); */
4076: /* } */
4077:
4078: /* Verifying the inverse matrix */
4079: #ifdef DEBUGHESS
4080: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 4081:
1.203 brouard 4082: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
4083: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 4084:
4085: for (j=1;j<=npar;j++) {
4086: for (i=1;i<=npar;i++){
1.203 brouard 4087: printf("%.2f ",y[i][j]);
4088: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 4089: }
4090: printf("\n");
4091: fprintf(ficlog,"\n");
4092: }
1.203 brouard 4093: #endif
1.126 brouard 4094:
4095: free_matrix(a,1,npar,1,npar);
4096: free_matrix(y,1,npar,1,npar);
4097: free_vector(x,1,npar);
4098: free_ivector(indx,1,npar);
1.203 brouard 4099: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 4100:
4101:
4102: }
4103:
4104: /*************** hessian matrix ****************/
4105: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 4106: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 4107: int i;
4108: int l=1, lmax=20;
1.203 brouard 4109: double k1,k2, res, fx;
1.132 brouard 4110: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 4111: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
4112: int k=0,kmax=10;
4113: double l1;
4114:
4115: fx=func(x);
4116: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 4117: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 4118: l1=pow(10,l);
4119: delts=delt;
4120: for(k=1 ; k <kmax; k=k+1){
4121: delt = delta*(l1*k);
4122: p2[theta]=x[theta] +delt;
1.145 brouard 4123: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 4124: p2[theta]=x[theta]-delt;
4125: k2=func(p2)-fx;
4126: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 4127: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 4128:
1.203 brouard 4129: #ifdef DEBUGHESSII
1.126 brouard 4130: 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);
4131: 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);
4132: #endif
4133: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
4134: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
4135: k=kmax;
4136: }
4137: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 4138: k=kmax; l=lmax*10;
1.126 brouard 4139: }
4140: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
4141: delts=delt;
4142: }
1.203 brouard 4143: } /* End loop k */
1.126 brouard 4144: }
4145: delti[theta]=delts;
4146: return res;
4147:
4148: }
4149:
1.203 brouard 4150: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 4151: {
4152: int i;
1.164 brouard 4153: int l=1, lmax=20;
1.126 brouard 4154: double k1,k2,k3,k4,res,fx;
1.132 brouard 4155: double p2[MAXPARM+1];
1.203 brouard 4156: int k, kmax=1;
4157: double v1, v2, cv12, lc1, lc2;
1.208 brouard 4158:
4159: int firstime=0;
1.203 brouard 4160:
1.126 brouard 4161: fx=func(x);
1.203 brouard 4162: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 4163: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 4164: p2[thetai]=x[thetai]+delti[thetai]*k;
4165: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4166: k1=func(p2)-fx;
4167:
1.203 brouard 4168: p2[thetai]=x[thetai]+delti[thetai]*k;
4169: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4170: k2=func(p2)-fx;
4171:
1.203 brouard 4172: p2[thetai]=x[thetai]-delti[thetai]*k;
4173: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4174: k3=func(p2)-fx;
4175:
1.203 brouard 4176: p2[thetai]=x[thetai]-delti[thetai]*k;
4177: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4178: k4=func(p2)-fx;
1.203 brouard 4179: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
4180: if(k1*k2*k3*k4 <0.){
1.208 brouard 4181: firstime=1;
1.203 brouard 4182: kmax=kmax+10;
1.208 brouard 4183: }
4184: if(kmax >=10 || firstime ==1){
1.246 brouard 4185: 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);
4186: 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 4187: 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);
4188: 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);
4189: }
4190: #ifdef DEBUGHESSIJ
4191: v1=hess[thetai][thetai];
4192: v2=hess[thetaj][thetaj];
4193: cv12=res;
4194: /* Computing eigen value of Hessian matrix */
4195: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4196: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4197: if ((lc2 <0) || (lc1 <0) ){
4198: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4199: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4200: 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);
4201: 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);
4202: }
1.126 brouard 4203: #endif
4204: }
4205: return res;
4206: }
4207:
1.203 brouard 4208: /* Not done yet: Was supposed to fix if not exactly at the maximum */
4209: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
4210: /* { */
4211: /* int i; */
4212: /* int l=1, lmax=20; */
4213: /* double k1,k2,k3,k4,res,fx; */
4214: /* double p2[MAXPARM+1]; */
4215: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
4216: /* int k=0,kmax=10; */
4217: /* double l1; */
4218:
4219: /* fx=func(x); */
4220: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
4221: /* l1=pow(10,l); */
4222: /* delts=delt; */
4223: /* for(k=1 ; k <kmax; k=k+1){ */
4224: /* delt = delti*(l1*k); */
4225: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
4226: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4227: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4228: /* k1=func(p2)-fx; */
4229:
4230: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4231: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4232: /* k2=func(p2)-fx; */
4233:
4234: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4235: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4236: /* k3=func(p2)-fx; */
4237:
4238: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4239: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4240: /* k4=func(p2)-fx; */
4241: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
4242: /* #ifdef DEBUGHESSIJ */
4243: /* printf("%d %d k=%d, k1=%.12e k2=%.12e k3=%.12e k4=%.12e delti/k=%.12e deltj/k=%.12e, xi-de/k=%.12e xj-de/k=%.12e res=%.12e k1234=%.12e,k1-2=%.12e,k3-4=%.12e\n",thetai,thetaj,k,k1,k2,k3,k4,delti[thetai]/k,delti[thetaj]/k,x[thetai]-delti[thetai]/k,x[thetaj]-delti[thetaj]/k, res,k1-k2-k3+k4,k1-k2,k3-k4); */
4244: /* fprintf(ficlog,"%d %d k=%d, k1=%.12e k2=%.12e k3=%.12e k4=%.12e delti/k=%.12e deltj/k=%.12e, xi-de/k=%.12e xj-de/k=%.12e res=%.12e k1234=%.12e,k1-2=%.12e,k3-4=%.12e\n",thetai,thetaj,k,k1,k2,k3,k4,delti[thetai]/k,delti[thetaj]/k,x[thetai]-delti[thetai]/k,x[thetaj]-delti[thetaj]/k, res,k1-k2-k3+k4,k1-k2,k3-k4); */
4245: /* #endif */
4246: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
4247: /* k=kmax; */
4248: /* } */
4249: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
4250: /* k=kmax; l=lmax*10; */
4251: /* } */
4252: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
4253: /* delts=delt; */
4254: /* } */
4255: /* } /\* End loop k *\/ */
4256: /* } */
4257: /* delti[theta]=delts; */
4258: /* return res; */
4259: /* } */
4260:
4261:
1.126 brouard 4262: /************** Inverse of matrix **************/
4263: void ludcmp(double **a, int n, int *indx, double *d)
4264: {
4265: int i,imax,j,k;
4266: double big,dum,sum,temp;
4267: double *vv;
4268:
4269: vv=vector(1,n);
4270: *d=1.0;
4271: for (i=1;i<=n;i++) {
4272: big=0.0;
4273: for (j=1;j<=n;j++)
4274: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 4275: if (big == 0.0){
4276: printf(" Singular Hessian matrix at row %d:\n",i);
4277: for (j=1;j<=n;j++) {
4278: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
4279: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
4280: }
4281: fflush(ficlog);
4282: fclose(ficlog);
4283: nrerror("Singular matrix in routine ludcmp");
4284: }
1.126 brouard 4285: vv[i]=1.0/big;
4286: }
4287: for (j=1;j<=n;j++) {
4288: for (i=1;i<j;i++) {
4289: sum=a[i][j];
4290: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
4291: a[i][j]=sum;
4292: }
4293: big=0.0;
4294: for (i=j;i<=n;i++) {
4295: sum=a[i][j];
4296: for (k=1;k<j;k++)
4297: sum -= a[i][k]*a[k][j];
4298: a[i][j]=sum;
4299: if ( (dum=vv[i]*fabs(sum)) >= big) {
4300: big=dum;
4301: imax=i;
4302: }
4303: }
4304: if (j != imax) {
4305: for (k=1;k<=n;k++) {
4306: dum=a[imax][k];
4307: a[imax][k]=a[j][k];
4308: a[j][k]=dum;
4309: }
4310: *d = -(*d);
4311: vv[imax]=vv[j];
4312: }
4313: indx[j]=imax;
4314: if (a[j][j] == 0.0) a[j][j]=TINY;
4315: if (j != n) {
4316: dum=1.0/(a[j][j]);
4317: for (i=j+1;i<=n;i++) a[i][j] *= dum;
4318: }
4319: }
4320: free_vector(vv,1,n); /* Doesn't work */
4321: ;
4322: }
4323:
4324: void lubksb(double **a, int n, int *indx, double b[])
4325: {
4326: int i,ii=0,ip,j;
4327: double sum;
4328:
4329: for (i=1;i<=n;i++) {
4330: ip=indx[i];
4331: sum=b[ip];
4332: b[ip]=b[i];
4333: if (ii)
4334: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
4335: else if (sum) ii=i;
4336: b[i]=sum;
4337: }
4338: for (i=n;i>=1;i--) {
4339: sum=b[i];
4340: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
4341: b[i]=sum/a[i][i];
4342: }
4343: }
4344:
4345: void pstamp(FILE *fichier)
4346: {
1.196 brouard 4347: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 4348: }
4349:
1.253 brouard 4350:
4351:
1.126 brouard 4352: /************ Frequencies ********************/
1.251 brouard 4353: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 4354: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
4355: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 4356: { /* Some frequencies as well as proposing some starting values */
1.226 brouard 4357:
1.265 brouard 4358: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 4359: int iind=0, iage=0;
4360: int mi; /* Effective wave */
4361: int first;
4362: double ***freq; /* Frequencies */
1.268 brouard 4363: 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 */
4364: 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);
1.226 brouard 4365: double *meanq;
4366: double **meanqt;
4367: double *pp, **prop, *posprop, *pospropt;
4368: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
4369: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
4370: double agebegin, ageend;
4371:
4372: pp=vector(1,nlstate);
1.251 brouard 4373: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4374: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
4375: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
4376: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
4377: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
4378: meanqt=matrix(1,lastpass,1,nqtveff);
4379: strcpy(fileresp,"P_");
4380: strcat(fileresp,fileresu);
4381: /*strcat(fileresphtm,fileresu);*/
4382: if((ficresp=fopen(fileresp,"w"))==NULL) {
4383: printf("Problem with prevalence resultfile: %s\n", fileresp);
4384: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
4385: exit(0);
4386: }
1.240 brouard 4387:
1.226 brouard 4388: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
4389: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
4390: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4391: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4392: fflush(ficlog);
4393: exit(70);
4394: }
4395: else{
4396: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 4397: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4398: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4399: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4400: }
1.237 brouard 4401: 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 4402:
1.226 brouard 4403: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
4404: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
4405: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4406: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4407: fflush(ficlog);
4408: exit(70);
1.240 brouard 4409: } else{
1.226 brouard 4410: 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 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: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4414: }
1.240 brouard 4415: 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);
4416:
1.253 brouard 4417: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
4418: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 4419: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4420: j1=0;
1.126 brouard 4421:
1.227 brouard 4422: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
4423: j=cptcoveff; /* Only dummy covariates of the model */
1.226 brouard 4424: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 4425:
4426:
1.226 brouard 4427: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
4428: reference=low_education V1=0,V2=0
4429: med_educ V1=1 V2=0,
4430: high_educ V1=0 V2=1
4431: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcoveff
4432: */
1.249 brouard 4433: dateintsum=0;
4434: k2cpt=0;
4435:
1.253 brouard 4436: if(cptcoveff == 0 )
1.265 brouard 4437: nl=1; /* Constant and age model only */
1.253 brouard 4438: else
4439: nl=2;
1.265 brouard 4440:
4441: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
4442: /* Loop on nj=1 or 2 if dummy covariates j!=0
4443: * Loop on j1(1 to 2**cptcoveff) covariate combination
4444: * freq[s1][s2][iage] =0.
4445: * Loop on iind
4446: * ++freq[s1][s2][iage] weighted
4447: * end iind
4448: * if covariate and j!0
4449: * headers Variable on one line
4450: * endif cov j!=0
4451: * header of frequency table by age
4452: * Loop on age
4453: * pp[s1]+=freq[s1][s2][iage] weighted
4454: * pos+=freq[s1][s2][iage] weighted
4455: * Loop on s1 initial state
4456: * fprintf(ficresp
4457: * end s1
4458: * end age
4459: * if j!=0 computes starting values
4460: * end compute starting values
4461: * end j1
4462: * end nl
4463: */
1.253 brouard 4464: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
4465: if(nj==1)
4466: j=0; /* First pass for the constant */
1.265 brouard 4467: else{
1.253 brouard 4468: j=cptcoveff; /* Other passes for the covariate values */
1.265 brouard 4469: }
1.251 brouard 4470: first=1;
1.265 brouard 4471: 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 4472: posproptt=0.;
4473: /*printf("cptcoveff=%d Tvaraff=%d", cptcoveff,Tvaraff[1]);
4474: scanf("%d", i);*/
4475: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 4476: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 4477: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 4478: freq[i][s2][m]=0;
1.251 brouard 4479:
4480: for (i=1; i<=nlstate; i++) {
1.240 brouard 4481: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 4482: prop[i][m]=0;
4483: posprop[i]=0;
4484: pospropt[i]=0;
4485: }
4486: /* for (z1=1; z1<= nqfveff; z1++) { */
4487: /* meanq[z1]+=0.; */
4488: /* for(m=1;m<=lastpass;m++){ */
4489: /* meanqt[m][z1]=0.; */
4490: /* } */
4491: /* } */
4492:
4493: /* dateintsum=0; */
4494: /* k2cpt=0; */
4495:
1.265 brouard 4496: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 4497: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
4498: bool=1;
4499: if(j !=0){
4500: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
4501: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
4502: /* for (z1=1; z1<= nqfveff; z1++) { */
4503: /* meanq[z1]+=coqvar[Tvar[z1]][iind]; /\* Computes mean of quantitative with selected filter *\/ */
4504: /* } */
4505: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
4506: /* if(Tvaraff[z1] ==-20){ */
4507: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
4508: /* }else if(Tvaraff[z1] ==-10){ */
4509: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
4510: /* }else */
4511: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]){ /* for combination j1 of covariates */
1.265 brouard 4512: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 4513: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
4514: /* 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",
4515: bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),
4516: j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
4517: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
4518: } /* Onlyf fixed */
4519: } /* end z1 */
4520: } /* cptcovn > 0 */
4521: } /* end any */
4522: }/* end j==0 */
1.265 brouard 4523: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 4524: /* for(m=firstpass; m<=lastpass; m++){ */
4525: for(mi=1; mi<wav[iind];mi++){ /* For that wave */
4526: m=mw[mi][iind];
4527: if(j!=0){
4528: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
4529: for (z1=1; z1<=cptcoveff; z1++) {
4530: if( Fixed[Tmodelind[z1]]==1){
4531: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
4532: if (cotvar[m][iv][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality. If covariate's
4533: value is -1, we don't select. It differs from the
4534: constant and age model which counts them. */
4535: bool=0; /* not selected */
4536: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
4537: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
4538: bool=0;
4539: }
4540: }
4541: }
4542: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
4543: } /* end j==0 */
4544: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
4545: if(bool==1){
4546: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
4547: and mw[mi+1][iind]. dh depends on stepm. */
4548: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
4549: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
4550: if(m >=firstpass && m <=lastpass){
4551: k2=anint[m][iind]+(mint[m][iind]/12.);
4552: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
4553: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
4554: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
4555: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
4556: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
4557: if (m<lastpass) {
4558: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
4559: /* 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]); */
4560: if(s[m][iind]==-1)
4561: 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.));
4562: freq[s[m][iind]][s[m+1][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
4563: /* if((int)agev[m][iind] == 55) */
4564: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
4565: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
4566: 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 4567: }
1.251 brouard 4568: } /* end if between passes */
4569: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
4570: dateintsum=dateintsum+k2; /* on all covariates ?*/
4571: k2cpt++;
4572: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 4573: }
1.251 brouard 4574: }else{
4575: bool=1;
4576: }/* end bool 2 */
4577: } /* end m */
4578: } /* end bool */
4579: } /* end iind = 1 to imx */
4580: /* prop[s][age] is feeded for any initial and valid live state as well as
4581: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
4582:
4583:
4584: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.265 brouard 4585: if(cptcoveff==0 && nj==1) /* no covariate and first pass */
4586: pstamp(ficresp);
1.251 brouard 4587: if (cptcoveff>0 && j!=0){
1.265 brouard 4588: pstamp(ficresp);
1.251 brouard 4589: printf( "\n#********** Variable ");
4590: fprintf(ficresp, "\n#********** Variable ");
4591: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
4592: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
4593: fprintf(ficlog, "\n#********** Variable ");
4594: for (z1=1; z1<=cptcoveff; z1++){
4595: if(!FixedV[Tvaraff[z1]]){
4596: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4597: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4598: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4599: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4600: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.250 brouard 4601: }else{
1.251 brouard 4602: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4603: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4604: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4605: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4606: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4607: }
4608: }
4609: printf( "**********\n#");
4610: fprintf(ficresp, "**********\n#");
4611: fprintf(ficresphtm, "**********</h3>\n");
4612: fprintf(ficresphtmfr, "**********</h3>\n");
4613: fprintf(ficlog, "**********\n");
4614: }
4615: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.265 brouard 4616: if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
4617: fprintf(ficresp, " Age");
4618: 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 4619: for(i=1; i<=nlstate;i++) {
1.265 brouard 4620: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 4621: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
4622: }
1.265 brouard 4623: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 4624: fprintf(ficresphtm, "\n");
4625:
4626: /* Header of frequency table by age */
4627: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
4628: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 4629: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 4630: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 4631: if(s2!=0 && m!=0)
4632: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 4633: }
1.226 brouard 4634: }
1.251 brouard 4635: fprintf(ficresphtmfr, "\n");
4636:
4637: /* For each age */
4638: for(iage=iagemin; iage <= iagemax+3; iage++){
4639: fprintf(ficresphtm,"<tr>");
4640: if(iage==iagemax+1){
4641: fprintf(ficlog,"1");
4642: fprintf(ficresphtmfr,"<tr><th>0</th> ");
4643: }else if(iage==iagemax+2){
4644: fprintf(ficlog,"0");
4645: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
4646: }else if(iage==iagemax+3){
4647: fprintf(ficlog,"Total");
4648: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
4649: }else{
1.240 brouard 4650: if(first==1){
1.251 brouard 4651: first=0;
4652: printf("See log file for details...\n");
4653: }
4654: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
4655: fprintf(ficlog,"Age %d", iage);
4656: }
1.265 brouard 4657: for(s1=1; s1 <=nlstate ; s1++){
4658: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
4659: pp[s1] += freq[s1][m][iage];
1.251 brouard 4660: }
1.265 brouard 4661: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 4662: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 4663: pos += freq[s1][m][iage];
4664: if(pp[s1]>=1.e-10){
1.251 brouard 4665: if(first==1){
1.265 brouard 4666: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 4667: }
1.265 brouard 4668: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 4669: }else{
4670: if(first==1)
1.265 brouard 4671: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
4672: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 4673: }
4674: }
4675:
1.265 brouard 4676: for(s1=1; s1 <=nlstate ; s1++){
4677: /* posprop[s1]=0; */
4678: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
4679: pp[s1] += freq[s1][m][iage];
4680: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
4681:
4682: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
4683: pos += pp[s1]; /* pos is the total number of transitions until this age */
4684: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
4685: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
4686: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
4687: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
4688: }
4689:
4690: /* Writing ficresp */
4691: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
4692: if( iage <= iagemax){
4693: fprintf(ficresp," %d",iage);
4694: }
4695: }else if( nj==2){
4696: if( iage <= iagemax){
4697: fprintf(ficresp," %d",iage);
4698: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4699: }
1.240 brouard 4700: }
1.265 brouard 4701: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 4702: if(pos>=1.e-5){
1.251 brouard 4703: if(first==1)
1.265 brouard 4704: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
4705: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 4706: }else{
4707: if(first==1)
1.265 brouard 4708: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
4709: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 4710: }
4711: if( iage <= iagemax){
4712: if(pos>=1.e-5){
1.265 brouard 4713: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
4714: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4715: }else if( nj==2){
4716: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4717: }
4718: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4719: /*probs[iage][s1][j1]= pp[s1]/pos;*/
4720: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
4721: } else{
4722: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
4723: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 4724: }
1.240 brouard 4725: }
1.265 brouard 4726: pospropt[s1] +=posprop[s1];
4727: } /* end loop s1 */
1.251 brouard 4728: /* pospropt=0.; */
1.265 brouard 4729: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 4730: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 4731: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 4732: if(first==1){
1.265 brouard 4733: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 4734: }
1.265 brouard 4735: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
4736: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 4737: }
1.265 brouard 4738: if(s1!=0 && m!=0)
4739: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 4740: }
1.265 brouard 4741: } /* end loop s1 */
1.251 brouard 4742: posproptt=0.;
1.265 brouard 4743: for(s1=1; s1 <=nlstate; s1++){
4744: posproptt += pospropt[s1];
1.251 brouard 4745: }
4746: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 4747: fprintf(ficresphtm,"</tr>\n");
4748: if((cptcoveff==0 && nj==1)|| nj==2 ) {
4749: if(iage <= iagemax)
4750: fprintf(ficresp,"\n");
1.240 brouard 4751: }
1.251 brouard 4752: if(first==1)
4753: printf("Others in log...\n");
4754: fprintf(ficlog,"\n");
4755: } /* end loop age iage */
1.265 brouard 4756:
1.251 brouard 4757: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 4758: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 4759: if(posproptt < 1.e-5){
1.265 brouard 4760: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 4761: }else{
1.265 brouard 4762: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 4763: }
1.226 brouard 4764: }
1.251 brouard 4765: fprintf(ficresphtm,"</tr>\n");
4766: fprintf(ficresphtm,"</table>\n");
4767: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 4768: if(posproptt < 1.e-5){
1.251 brouard 4769: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
4770: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 4771: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
4772: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 4773: invalidvarcomb[j1]=1;
1.226 brouard 4774: }else{
1.251 brouard 4775: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced.</p>",j1);
4776: invalidvarcomb[j1]=0;
1.226 brouard 4777: }
1.251 brouard 4778: fprintf(ficresphtmfr,"</table>\n");
4779: fprintf(ficlog,"\n");
4780: if(j!=0){
4781: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 4782: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 4783: for(k=1; k <=(nlstate+ndeath); k++){
4784: if (k != i) {
1.265 brouard 4785: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 4786: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 4787: if(j1==1){ /* All dummy covariates to zero */
4788: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
4789: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 4790: printf("%d%d ",i,k);
4791: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 4792: 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]));
4793: 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]));
4794: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 4795: }
1.253 brouard 4796: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
4797: for(iage=iagemin; iage <= iagemax+3; iage++){
4798: x[iage]= (double)iage;
4799: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 4800: /* 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 4801: }
1.268 brouard 4802: /* Some are not finite, but linreg will ignore these ages */
4803: no=0;
1.253 brouard 4804: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 4805: pstart[s1]=b;
4806: pstart[s1-1]=a;
1.252 brouard 4807: }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 */
4808: 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]);
4809: 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 4810: 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 4811: printf("%d%d ",i,k);
4812: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 4813: 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 4814: }else{ /* Other cases, like quantitative fixed or varying covariates */
4815: ;
4816: }
4817: /* printf("%12.7f )", param[i][jj][k]); */
4818: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 4819: s1++;
1.251 brouard 4820: } /* end jj */
4821: } /* end k!= i */
4822: } /* end k */
1.265 brouard 4823: } /* end i, s1 */
1.251 brouard 4824: } /* end j !=0 */
4825: } /* end selected combination of covariate j1 */
4826: if(j==0){ /* We can estimate starting values from the occurences in each case */
4827: printf("#Freqsummary: Starting values for the constants:\n");
4828: fprintf(ficlog,"\n");
1.265 brouard 4829: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 4830: for(k=1; k <=(nlstate+ndeath); k++){
4831: if (k != i) {
4832: printf("%d%d ",i,k);
4833: fprintf(ficlog,"%d%d ",i,k);
4834: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 4835: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 4836: if(jj==1){ /* Age has to be done */
1.265 brouard 4837: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
4838: 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]));
4839: 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 4840: }
4841: /* printf("%12.7f )", param[i][jj][k]); */
4842: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 4843: s1++;
1.250 brouard 4844: }
1.251 brouard 4845: printf("\n");
4846: fprintf(ficlog,"\n");
1.250 brouard 4847: }
4848: }
4849: }
1.251 brouard 4850: printf("#Freqsummary\n");
4851: fprintf(ficlog,"\n");
1.265 brouard 4852: for(s1=-1; s1 <=nlstate+ndeath; s1++){
4853: for(s2=-1; s2 <=nlstate+ndeath; s2++){
4854: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
4855: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
4856: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
4857: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
4858: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
4859: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 4860: /* } */
4861: }
1.265 brouard 4862: } /* end loop s1 */
1.251 brouard 4863:
4864: printf("\n");
4865: fprintf(ficlog,"\n");
4866: } /* end j=0 */
1.249 brouard 4867: } /* end j */
1.252 brouard 4868:
1.253 brouard 4869: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 4870: for(i=1, jk=1; i <=nlstate; i++){
4871: for(j=1; j <=nlstate+ndeath; j++){
4872: if(j!=i){
4873: /*ca[0]= k+'a'-1;ca[1]='\0';*/
4874: printf("%1d%1d",i,j);
4875: fprintf(ficparo,"%1d%1d",i,j);
4876: for(k=1; k<=ncovmodel;k++){
4877: /* printf(" %lf",param[i][j][k]); */
4878: /* fprintf(ficparo," %lf",param[i][j][k]); */
4879: p[jk]=pstart[jk];
4880: printf(" %f ",pstart[jk]);
4881: fprintf(ficparo," %f ",pstart[jk]);
4882: jk++;
4883: }
4884: printf("\n");
4885: fprintf(ficparo,"\n");
4886: }
4887: }
4888: }
4889: } /* end mle=-2 */
1.226 brouard 4890: dateintmean=dateintsum/k2cpt;
1.240 brouard 4891:
1.226 brouard 4892: fclose(ficresp);
4893: fclose(ficresphtm);
4894: fclose(ficresphtmfr);
4895: free_vector(meanq,1,nqfveff);
4896: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 4897: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
4898: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 4899: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 4900: free_vector(pospropt,1,nlstate);
4901: free_vector(posprop,1,nlstate);
1.251 brouard 4902: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 4903: free_vector(pp,1,nlstate);
4904: /* End of freqsummary */
4905: }
1.126 brouard 4906:
1.268 brouard 4907: /* Simple linear regression */
4908: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
4909:
4910: /* y=a+bx regression */
4911: double sumx = 0.0; /* sum of x */
4912: double sumx2 = 0.0; /* sum of x**2 */
4913: double sumxy = 0.0; /* sum of x * y */
4914: double sumy = 0.0; /* sum of y */
4915: double sumy2 = 0.0; /* sum of y**2 */
4916: double sume2 = 0.0; /* sum of square or residuals */
4917: double yhat;
4918:
4919: double denom=0;
4920: int i;
4921: int ne=*no;
4922:
4923: for ( i=ifi, ne=0;i<=ila;i++) {
4924: if(!isfinite(x[i]) || !isfinite(y[i])){
4925: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
4926: continue;
4927: }
4928: ne=ne+1;
4929: sumx += x[i];
4930: sumx2 += x[i]*x[i];
4931: sumxy += x[i] * y[i];
4932: sumy += y[i];
4933: sumy2 += y[i]*y[i];
4934: denom = (ne * sumx2 - sumx*sumx);
4935: /* 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); */
4936: }
4937:
4938: denom = (ne * sumx2 - sumx*sumx);
4939: if (denom == 0) {
4940: // vertical, slope m is infinity
4941: *b = INFINITY;
4942: *a = 0;
4943: if (r) *r = 0;
4944: return 1;
4945: }
4946:
4947: *b = (ne * sumxy - sumx * sumy) / denom;
4948: *a = (sumy * sumx2 - sumx * sumxy) / denom;
4949: if (r!=NULL) {
4950: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
4951: sqrt((sumx2 - sumx*sumx/ne) *
4952: (sumy2 - sumy*sumy/ne));
4953: }
4954: *no=ne;
4955: for ( i=ifi, ne=0;i<=ila;i++) {
4956: if(!isfinite(x[i]) || !isfinite(y[i])){
4957: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
4958: continue;
4959: }
4960: ne=ne+1;
4961: yhat = y[i] - *a -*b* x[i];
4962: sume2 += yhat * yhat ;
4963:
4964: denom = (ne * sumx2 - sumx*sumx);
4965: /* 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); */
4966: }
4967: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
4968: *sa= *sb * sqrt(sumx2/ne);
4969:
4970: return 0;
4971: }
4972:
1.126 brouard 4973: /************ Prevalence ********************/
1.227 brouard 4974: 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)
4975: {
4976: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
4977: in each health status at the date of interview (if between dateprev1 and dateprev2).
4978: We still use firstpass and lastpass as another selection.
4979: */
1.126 brouard 4980:
1.227 brouard 4981: int i, m, jk, j1, bool, z1,j, iv;
4982: int mi; /* Effective wave */
4983: int iage;
4984: double agebegin, ageend;
4985:
4986: double **prop;
4987: double posprop;
4988: double y2; /* in fractional years */
4989: int iagemin, iagemax;
4990: int first; /** to stop verbosity which is redirected to log file */
4991:
4992: iagemin= (int) agemin;
4993: iagemax= (int) agemax;
4994: /*pp=vector(1,nlstate);*/
1.251 brouard 4995: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 4996: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
4997: j1=0;
1.222 brouard 4998:
1.227 brouard 4999: /*j=cptcoveff;*/
5000: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 5001:
1.227 brouard 5002: first=1;
5003: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of covariate */
5004: for (i=1; i<=nlstate; i++)
1.251 brouard 5005: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 5006: prop[i][iage]=0.0;
5007: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
5008: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
5009: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
5010:
5011: for (i=1; i<=imx; i++) { /* Each individual */
5012: bool=1;
5013: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
5014: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
5015: m=mw[mi][i];
5016: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
5017: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
5018: for (z1=1; z1<=cptcoveff; z1++){
5019: if( Fixed[Tmodelind[z1]]==1){
5020: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
5021: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality */
5022: bool=0;
5023: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
5024: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
5025: bool=0;
5026: }
5027: }
5028: if(bool==1){ /* Otherwise we skip that wave/person */
5029: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
5030: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
5031: if(m >=firstpass && m <=lastpass){
5032: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
5033: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
5034: if(agev[m][i]==0) agev[m][i]=iagemax+1;
5035: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 5036: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 5037: 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);
5038: exit(1);
5039: }
5040: if (s[m][i]>0 && s[m][i]<=nlstate) {
5041: /*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]]);*/
5042: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
5043: prop[s[m][i]][iagemax+3] += weight[i];
5044: } /* end valid statuses */
5045: } /* end selection of dates */
5046: } /* end selection of waves */
5047: } /* end bool */
5048: } /* end wave */
5049: } /* end individual */
5050: for(i=iagemin; i <= iagemax+3; i++){
5051: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
5052: posprop += prop[jk][i];
5053: }
5054:
5055: for(jk=1; jk <=nlstate ; jk++){
5056: if( i <= iagemax){
5057: if(posprop>=1.e-5){
5058: probs[i][jk][j1]= prop[jk][i]/posprop;
5059: } else{
5060: if(first==1){
5061: first=0;
1.266 brouard 5062: 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]);
5063: 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]);
5064: }else{
5065: 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 5066: }
5067: }
5068: }
5069: }/* end jk */
5070: }/* end i */
1.222 brouard 5071: /*} *//* end i1 */
1.227 brouard 5072: } /* end j1 */
1.222 brouard 5073:
1.227 brouard 5074: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
5075: /*free_vector(pp,1,nlstate);*/
1.251 brouard 5076: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5077: } /* End of prevalence */
1.126 brouard 5078:
5079: /************* Waves Concatenation ***************/
5080:
5081: 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)
5082: {
5083: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
5084: Death is a valid wave (if date is known).
5085: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
5086: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
5087: and mw[mi+1][i]. dh depends on stepm.
1.227 brouard 5088: */
1.126 brouard 5089:
1.224 brouard 5090: int i=0, mi=0, m=0, mli=0;
1.126 brouard 5091: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
5092: double sum=0., jmean=0.;*/
1.224 brouard 5093: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 5094: int j, k=0,jk, ju, jl;
5095: double sum=0.;
5096: first=0;
1.214 brouard 5097: firstwo=0;
1.217 brouard 5098: firsthree=0;
1.218 brouard 5099: firstfour=0;
1.164 brouard 5100: jmin=100000;
1.126 brouard 5101: jmax=-1;
5102: jmean=0.;
1.224 brouard 5103:
5104: /* Treating live states */
1.214 brouard 5105: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 5106: mi=0; /* First valid wave */
1.227 brouard 5107: mli=0; /* Last valid wave */
1.126 brouard 5108: m=firstpass;
1.214 brouard 5109: while(s[m][i] <= nlstate){ /* a live state */
1.227 brouard 5110: 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 */
5111: mli=m-1;/* mw[++mi][i]=m-1; */
5112: }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 */
5113: mw[++mi][i]=m;
5114: mli=m;
1.224 brouard 5115: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
5116: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 5117: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 5118: }
1.227 brouard 5119: else{ /* m >= lastpass, eventual special issue with warning */
1.224 brouard 5120: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 5121: break;
1.224 brouard 5122: #else
1.227 brouard 5123: if(s[m][i]==-1 && (int) andc[i] == 9999 && (int)anint[m][i] != 9999){
5124: if(firsthree == 0){
1.262 brouard 5125: 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 5126: firsthree=1;
5127: }
1.262 brouard 5128: 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 5129: mw[++mi][i]=m;
5130: mli=m;
5131: }
5132: if(s[m][i]==-2){ /* Vital status is really unknown */
5133: nbwarn++;
5134: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified? */
5135: 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);
5136: 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);
5137: }
5138: break;
5139: }
5140: break;
1.224 brouard 5141: #endif
1.227 brouard 5142: }/* End m >= lastpass */
1.126 brouard 5143: }/* end while */
1.224 brouard 5144:
1.227 brouard 5145: /* 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 5146: /* After last pass */
1.224 brouard 5147: /* Treating death states */
1.214 brouard 5148: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 5149: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
5150: /* } */
1.126 brouard 5151: mi++; /* Death is another wave */
5152: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 5153: /* Only death is a correct wave */
1.126 brouard 5154: mw[mi][i]=m;
1.257 brouard 5155: } /* else not in a death state */
1.224 brouard 5156: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 5157: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 5158: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.227 brouard 5159: 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 */
5160: nbwarn++;
5161: if(firstfiv==0){
5162: 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 );
5163: firstfiv=1;
5164: }else{
5165: 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 );
5166: }
5167: }else{ /* Death occured afer last wave potential bias */
5168: nberr++;
5169: if(firstwo==0){
1.257 brouard 5170: 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 5171: firstwo=1;
5172: }
1.257 brouard 5173: 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 5174: }
1.257 brouard 5175: }else{ /* if date of interview is unknown */
1.227 brouard 5176: /* death is known but not confirmed by death status at any wave */
5177: if(firstfour==0){
5178: 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 );
5179: firstfour=1;
5180: }
5181: 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 5182: }
1.224 brouard 5183: } /* end if date of death is known */
5184: #endif
5185: wav[i]=mi; /* mi should be the last effective wave (or mli) */
5186: /* wav[i]=mw[mi][i]; */
1.126 brouard 5187: if(mi==0){
5188: nbwarn++;
5189: if(first==0){
1.227 brouard 5190: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
5191: first=1;
1.126 brouard 5192: }
5193: if(first==1){
1.227 brouard 5194: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 5195: }
5196: } /* end mi==0 */
5197: } /* End individuals */
1.214 brouard 5198: /* wav and mw are no more changed */
1.223 brouard 5199:
1.214 brouard 5200:
1.126 brouard 5201: for(i=1; i<=imx; i++){
5202: for(mi=1; mi<wav[i];mi++){
5203: if (stepm <=0)
1.227 brouard 5204: dh[mi][i]=1;
1.126 brouard 5205: else{
1.260 brouard 5206: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 5207: if (agedc[i] < 2*AGESUP) {
5208: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
5209: if(j==0) j=1; /* Survives at least one month after exam */
5210: else if(j<0){
5211: nberr++;
5212: 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]);
5213: j=1; /* Temporary Dangerous patch */
5214: 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);
5215: 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]);
5216: 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);
5217: }
5218: k=k+1;
5219: if (j >= jmax){
5220: jmax=j;
5221: ijmax=i;
5222: }
5223: if (j <= jmin){
5224: jmin=j;
5225: ijmin=i;
5226: }
5227: sum=sum+j;
5228: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
5229: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
5230: }
5231: }
5232: else{
5233: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 5234: /* 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 5235:
1.227 brouard 5236: k=k+1;
5237: if (j >= jmax) {
5238: jmax=j;
5239: ijmax=i;
5240: }
5241: else if (j <= jmin){
5242: jmin=j;
5243: ijmin=i;
5244: }
5245: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
5246: /*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]);*/
5247: if(j<0){
5248: nberr++;
5249: 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]);
5250: 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]);
5251: }
5252: sum=sum+j;
5253: }
5254: jk= j/stepm;
5255: jl= j -jk*stepm;
5256: ju= j -(jk+1)*stepm;
5257: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
5258: if(jl==0){
5259: dh[mi][i]=jk;
5260: bh[mi][i]=0;
5261: }else{ /* We want a negative bias in order to only have interpolation ie
5262: * to avoid the price of an extra matrix product in likelihood */
5263: dh[mi][i]=jk+1;
5264: bh[mi][i]=ju;
5265: }
5266: }else{
5267: if(jl <= -ju){
5268: dh[mi][i]=jk;
5269: bh[mi][i]=jl; /* bias is positive if real duration
5270: * is higher than the multiple of stepm and negative otherwise.
5271: */
5272: }
5273: else{
5274: dh[mi][i]=jk+1;
5275: bh[mi][i]=ju;
5276: }
5277: if(dh[mi][i]==0){
5278: dh[mi][i]=1; /* At least one step */
5279: bh[mi][i]=ju; /* At least one step */
5280: /* 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);*/
5281: }
5282: } /* end if mle */
1.126 brouard 5283: }
5284: } /* end wave */
5285: }
5286: jmean=sum/k;
5287: 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 5288: 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 5289: }
1.126 brouard 5290:
5291: /*********** Tricode ****************************/
1.220 brouard 5292: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 5293: {
5294: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
5295: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
5296: * Boring subroutine which should only output nbcode[Tvar[j]][k]
5297: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
5298: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
5299: */
1.130 brouard 5300:
1.242 brouard 5301: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
5302: int modmaxcovj=0; /* Modality max of covariates j */
5303: int cptcode=0; /* Modality max of covariates j */
5304: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 5305:
5306:
1.242 brouard 5307: /* cptcoveff=0; */
5308: /* *cptcov=0; */
1.126 brouard 5309:
1.242 brouard 5310: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.126 brouard 5311:
1.242 brouard 5312: /* Loop on covariates without age and products and no quantitative variable */
5313: /* for (j=1; j<=(cptcovs); j++) { /\* From model V1 + V2*age+ V3 + V3*V4 keeps V1 + V3 = 2 only *\/ */
5314: for (k=1; k<=cptcovt; k++) { /* From model V1 + V2*age + V3 + V3*V4 keeps V1 + V3 = 2 only */
5315: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
5316: if(Dummy[k]==0 && Typevar[k] !=1){ /* Dummy covariate and not age product */
5317: switch(Fixed[k]) {
5318: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
5319: 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*/
5320: ij=(int)(covar[Tvar[k]][i]);
5321: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
5322: * If product of Vn*Vm, still boolean *:
5323: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
5324: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
5325: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
5326: modality of the nth covariate of individual i. */
5327: if (ij > modmaxcovj)
5328: modmaxcovj=ij;
5329: else if (ij < modmincovj)
5330: modmincovj=ij;
5331: if ((ij < -1) && (ij > NCOVMAX)){
5332: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
5333: exit(1);
5334: }else
5335: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
5336: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
5337: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
5338: /* getting the maximum value of the modality of the covariate
5339: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
5340: female ies 1, then modmaxcovj=1.
5341: */
5342: } /* end for loop on individuals i */
5343: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5344: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5345: cptcode=modmaxcovj;
5346: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
5347: /*for (i=0; i<=cptcode; i++) {*/
5348: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
5349: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5350: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5351: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
5352: if( j != -1){
5353: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
5354: covariate for which somebody answered excluding
5355: undefined. Usually 2: 0 and 1. */
5356: }
5357: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
5358: covariate for which somebody answered including
5359: undefined. Usually 3: -1, 0 and 1. */
5360: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
5361: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
5362: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 5363:
1.242 brouard 5364: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
5365: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
5366: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
5367: /* modmincovj=3; modmaxcovj = 7; */
5368: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
5369: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
5370: /* defining two dummy variables: variables V1_1 and V1_2.*/
5371: /* nbcode[Tvar[j]][ij]=k; */
5372: /* nbcode[Tvar[j]][1]=0; */
5373: /* nbcode[Tvar[j]][2]=1; */
5374: /* nbcode[Tvar[j]][3]=2; */
5375: /* To be continued (not working yet). */
5376: ij=0; /* ij is similar to i but can jump over null modalities */
5377: 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*/
5378: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
5379: break;
5380: }
5381: ij++;
5382: 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*/
5383: cptcode = ij; /* New max modality for covar j */
5384: } /* end of loop on modality i=-1 to 1 or more */
5385: break;
5386: case 1: /* Testing on varying covariate, could be simple and
5387: * should look at waves or product of fixed *
5388: * varying. No time to test -1, assuming 0 and 1 only */
5389: ij=0;
5390: for(i=0; i<=1;i++){
5391: nbcode[Tvar[k]][++ij]=i;
5392: }
5393: break;
5394: default:
5395: break;
5396: } /* end switch */
5397: } /* end dummy test */
5398:
5399: /* for (k=0; k<= cptcode; k++) { /\* k=-1 ? k=0 to 1 *\//\* Could be 1 to 4 *\//\* cptcode=modmaxcovj *\/ */
5400: /* /\*recode from 0 *\/ */
5401: /* k is a modality. If we have model=V1+V1*sex */
5402: /* then: nbcode[1][1]=0 ; nbcode[1][2]=1; nbcode[2][1]=0 ; nbcode[2][2]=1; */
5403: /* But if some modality were not used, it is recoded from 0 to a newer modmaxcovj=cptcode *\/ */
5404: /* } */
5405: /* /\* cptcode = ij; *\/ /\* New max modality for covar j *\/ */
5406: /* if (ij > ncodemax[j]) { */
5407: /* printf( " Error ij=%d > ncodemax[%d]=%d\n", ij, j, ncodemax[j]); */
5408: /* fprintf(ficlog, " Error ij=%d > ncodemax[%d]=%d\n", ij, j, ncodemax[j]); */
5409: /* break; */
5410: /* } */
5411: /* } /\* end of loop on modality k *\/ */
5412: } /* end of loop on model-covariate j. nbcode[Tvarj][1]=0 and nbcode[Tvarj][2]=1 sets the value of covariate j*/
5413:
5414: for (k=-1; k< maxncov; k++) Ndum[k]=0;
5415: /* Look at fixed dummy (single or product) covariates to check empty modalities */
5416: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
5417: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
5418: 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 */
5419: 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 */
5420: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
5421: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
5422:
5423: ij=0;
5424: /* for (i=0; i<= maxncov-1; i++) { /\* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) *\/ */
5425: for (k=1; k<= cptcovt; k++) { /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
5426: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
5427: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
5428: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy and non empty in the model */
5429: /* If product not in single variable we don't print results */
5430: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
5431: ++ij;/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, */
5432: 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*/
5433: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
5434: 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 */
5435: if(Fixed[k]!=0)
5436: anyvaryingduminmodel=1;
5437: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
5438: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
5439: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
5440: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
5441: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
5442: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
5443: }
5444: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
5445: /* ij--; */
5446: /* cptcoveff=ij; /\*Number of total covariates*\/ */
5447: *cptcov=ij; /*Number of total real effective covariates: effective
5448: * because they can be excluded from the model and real
5449: * if in the model but excluded because missing values, but how to get k from ij?*/
5450: for(j=ij+1; j<= cptcovt; j++){
5451: Tvaraff[j]=0;
5452: Tmodelind[j]=0;
5453: }
5454: for(j=ntveff+1; j<= cptcovt; j++){
5455: TmodelInvind[j]=0;
5456: }
5457: /* To be sorted */
5458: ;
5459: }
1.126 brouard 5460:
1.145 brouard 5461:
1.126 brouard 5462: /*********** Health Expectancies ****************/
5463:
1.235 brouard 5464: 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 5465:
5466: {
5467: /* Health expectancies, no variances */
1.164 brouard 5468: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 5469: int nhstepma, nstepma; /* Decreasing with age */
5470: double age, agelim, hf;
5471: double ***p3mat;
5472: double eip;
5473:
1.238 brouard 5474: /* pstamp(ficreseij); */
1.126 brouard 5475: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
5476: fprintf(ficreseij,"# Age");
5477: for(i=1; i<=nlstate;i++){
5478: for(j=1; j<=nlstate;j++){
5479: fprintf(ficreseij," e%1d%1d ",i,j);
5480: }
5481: fprintf(ficreseij," e%1d. ",i);
5482: }
5483: fprintf(ficreseij,"\n");
5484:
5485:
5486: if(estepm < stepm){
5487: printf ("Problem %d lower than %d\n",estepm, stepm);
5488: }
5489: else hstepm=estepm;
5490: /* We compute the life expectancy from trapezoids spaced every estepm months
5491: * This is mainly to measure the difference between two models: for example
5492: * if stepm=24 months pijx are given only every 2 years and by summing them
5493: * we are calculating an estimate of the Life Expectancy assuming a linear
5494: * progression in between and thus overestimating or underestimating according
5495: * to the curvature of the survival function. If, for the same date, we
5496: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5497: * to compare the new estimate of Life expectancy with the same linear
5498: * hypothesis. A more precise result, taking into account a more precise
5499: * curvature will be obtained if estepm is as small as stepm. */
5500:
5501: /* For example we decided to compute the life expectancy with the smallest unit */
5502: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5503: nhstepm is the number of hstepm from age to agelim
5504: nstepm is the number of stepm from age to agelin.
1.270 brouard 5505: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 5506: and note for a fixed period like estepm months */
5507: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5508: survival function given by stepm (the optimization length). Unfortunately it
5509: means that if the survival funtion is printed only each two years of age and if
5510: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5511: results. So we changed our mind and took the option of the best precision.
5512: */
5513: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5514:
5515: agelim=AGESUP;
5516: /* If stepm=6 months */
5517: /* Computed by stepm unit matrices, product of hstepm matrices, stored
5518: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
5519:
5520: /* nhstepm age range expressed in number of stepm */
5521: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5522: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5523: /* if (stepm >= YEARM) hstepm=1;*/
5524: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5525: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5526:
5527: for (age=bage; age<=fage; age ++){
5528: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5529: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5530: /* if (stepm >= YEARM) hstepm=1;*/
5531: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
5532:
5533: /* If stepm=6 months */
5534: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5535: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5536:
1.235 brouard 5537: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 5538:
5539: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
5540:
5541: printf("%d|",(int)age);fflush(stdout);
5542: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5543:
5544: /* Computing expectancies */
5545: for(i=1; i<=nlstate;i++)
5546: for(j=1; j<=nlstate;j++)
5547: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5548: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
5549:
5550: /* 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]);*/
5551:
5552: }
5553:
5554: fprintf(ficreseij,"%3.0f",age );
5555: for(i=1; i<=nlstate;i++){
5556: eip=0;
5557: for(j=1; j<=nlstate;j++){
5558: eip +=eij[i][j][(int)age];
5559: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
5560: }
5561: fprintf(ficreseij,"%9.4f", eip );
5562: }
5563: fprintf(ficreseij,"\n");
5564:
5565: }
5566: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5567: printf("\n");
5568: fprintf(ficlog,"\n");
5569:
5570: }
5571:
1.235 brouard 5572: 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 5573:
5574: {
5575: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 5576: to initial status i, ei. .
1.126 brouard 5577: */
5578: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
5579: int nhstepma, nstepma; /* Decreasing with age */
5580: double age, agelim, hf;
5581: double ***p3matp, ***p3matm, ***varhe;
5582: double **dnewm,**doldm;
5583: double *xp, *xm;
5584: double **gp, **gm;
5585: double ***gradg, ***trgradg;
5586: int theta;
5587:
5588: double eip, vip;
5589:
5590: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
5591: xp=vector(1,npar);
5592: xm=vector(1,npar);
5593: dnewm=matrix(1,nlstate*nlstate,1,npar);
5594: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
5595:
5596: pstamp(ficresstdeij);
5597: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
5598: fprintf(ficresstdeij,"# Age");
5599: for(i=1; i<=nlstate;i++){
5600: for(j=1; j<=nlstate;j++)
5601: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
5602: fprintf(ficresstdeij," e%1d. ",i);
5603: }
5604: fprintf(ficresstdeij,"\n");
5605:
5606: pstamp(ficrescveij);
5607: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
5608: fprintf(ficrescveij,"# Age");
5609: for(i=1; i<=nlstate;i++)
5610: for(j=1; j<=nlstate;j++){
5611: cptj= (j-1)*nlstate+i;
5612: for(i2=1; i2<=nlstate;i2++)
5613: for(j2=1; j2<=nlstate;j2++){
5614: cptj2= (j2-1)*nlstate+i2;
5615: if(cptj2 <= cptj)
5616: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
5617: }
5618: }
5619: fprintf(ficrescveij,"\n");
5620:
5621: if(estepm < stepm){
5622: printf ("Problem %d lower than %d\n",estepm, stepm);
5623: }
5624: else hstepm=estepm;
5625: /* We compute the life expectancy from trapezoids spaced every estepm months
5626: * This is mainly to measure the difference between two models: for example
5627: * if stepm=24 months pijx are given only every 2 years and by summing them
5628: * we are calculating an estimate of the Life Expectancy assuming a linear
5629: * progression in between and thus overestimating or underestimating according
5630: * to the curvature of the survival function. If, for the same date, we
5631: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5632: * to compare the new estimate of Life expectancy with the same linear
5633: * hypothesis. A more precise result, taking into account a more precise
5634: * curvature will be obtained if estepm is as small as stepm. */
5635:
5636: /* For example we decided to compute the life expectancy with the smallest unit */
5637: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5638: nhstepm is the number of hstepm from age to agelim
5639: nstepm is the number of stepm from age to agelin.
5640: Look at hpijx to understand the reason of that which relies in memory size
5641: and note for a fixed period like estepm months */
5642: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5643: survival function given by stepm (the optimization length). Unfortunately it
5644: means that if the survival funtion is printed only each two years of age and if
5645: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5646: results. So we changed our mind and took the option of the best precision.
5647: */
5648: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5649:
5650: /* If stepm=6 months */
5651: /* nhstepm age range expressed in number of stepm */
5652: agelim=AGESUP;
5653: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
5654: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5655: /* if (stepm >= YEARM) hstepm=1;*/
5656: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5657:
5658: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5659: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5660: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
5661: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
5662: gp=matrix(0,nhstepm,1,nlstate*nlstate);
5663: gm=matrix(0,nhstepm,1,nlstate*nlstate);
5664:
5665: for (age=bage; age<=fage; age ++){
5666: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5667: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5668: /* if (stepm >= YEARM) hstepm=1;*/
5669: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 5670:
1.126 brouard 5671: /* If stepm=6 months */
5672: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5673: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5674:
5675: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 5676:
1.126 brouard 5677: /* Computing Variances of health expectancies */
5678: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
5679: decrease memory allocation */
5680: for(theta=1; theta <=npar; theta++){
5681: for(i=1; i<=npar; i++){
1.222 brouard 5682: xp[i] = x[i] + (i==theta ?delti[theta]:0);
5683: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 5684: }
1.235 brouard 5685: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
5686: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 5687:
1.126 brouard 5688: for(j=1; j<= nlstate; j++){
1.222 brouard 5689: for(i=1; i<=nlstate; i++){
5690: for(h=0; h<=nhstepm-1; h++){
5691: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
5692: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
5693: }
5694: }
1.126 brouard 5695: }
1.218 brouard 5696:
1.126 brouard 5697: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 5698: for(h=0; h<=nhstepm-1; h++){
5699: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
5700: }
1.126 brouard 5701: }/* End theta */
5702:
5703:
5704: for(h=0; h<=nhstepm-1; h++)
5705: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 5706: for(theta=1; theta <=npar; theta++)
5707: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 5708:
1.218 brouard 5709:
1.222 brouard 5710: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 5711: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 5712: varhe[ij][ji][(int)age] =0.;
1.218 brouard 5713:
1.222 brouard 5714: printf("%d|",(int)age);fflush(stdout);
5715: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5716: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 5717: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 5718: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
5719: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
5720: for(ij=1;ij<=nlstate*nlstate;ij++)
5721: for(ji=1;ji<=nlstate*nlstate;ji++)
5722: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 5723: }
5724: }
1.218 brouard 5725:
1.126 brouard 5726: /* Computing expectancies */
1.235 brouard 5727: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 5728: for(i=1; i<=nlstate;i++)
5729: for(j=1; j<=nlstate;j++)
1.222 brouard 5730: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5731: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 5732:
1.222 brouard 5733: /* 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 5734:
1.222 brouard 5735: }
1.269 brouard 5736:
5737: /* Standard deviation of expectancies ij */
1.126 brouard 5738: fprintf(ficresstdeij,"%3.0f",age );
5739: for(i=1; i<=nlstate;i++){
5740: eip=0.;
5741: vip=0.;
5742: for(j=1; j<=nlstate;j++){
1.222 brouard 5743: eip += eij[i][j][(int)age];
5744: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
5745: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
5746: 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 5747: }
5748: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
5749: }
5750: fprintf(ficresstdeij,"\n");
1.218 brouard 5751:
1.269 brouard 5752: /* Variance of expectancies ij */
1.126 brouard 5753: fprintf(ficrescveij,"%3.0f",age );
5754: for(i=1; i<=nlstate;i++)
5755: for(j=1; j<=nlstate;j++){
1.222 brouard 5756: cptj= (j-1)*nlstate+i;
5757: for(i2=1; i2<=nlstate;i2++)
5758: for(j2=1; j2<=nlstate;j2++){
5759: cptj2= (j2-1)*nlstate+i2;
5760: if(cptj2 <= cptj)
5761: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
5762: }
1.126 brouard 5763: }
5764: fprintf(ficrescveij,"\n");
1.218 brouard 5765:
1.126 brouard 5766: }
5767: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
5768: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
5769: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
5770: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
5771: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5772: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5773: printf("\n");
5774: fprintf(ficlog,"\n");
1.218 brouard 5775:
1.126 brouard 5776: free_vector(xm,1,npar);
5777: free_vector(xp,1,npar);
5778: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
5779: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
5780: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
5781: }
1.218 brouard 5782:
1.126 brouard 5783: /************ Variance ******************/
1.235 brouard 5784: 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 5785: {
1.279 brouard 5786: /** Variance of health expectancies
5787: * double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);
5788: * double **newm;
5789: * int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)
5790: */
1.218 brouard 5791:
5792: /* int movingaverage(); */
5793: double **dnewm,**doldm;
5794: double **dnewmp,**doldmp;
5795: int i, j, nhstepm, hstepm, h, nstepm ;
5796: int k;
5797: double *xp;
1.279 brouard 5798: double **gp, **gm; /**< for var eij */
5799: double ***gradg, ***trgradg; /**< for var eij */
5800: double **gradgp, **trgradgp; /**< for var p point j */
5801: double *gpp, *gmp; /**< for var p point j */
5802: double **varppt; /**< for var p point j nlstate to nlstate+ndeath */
1.218 brouard 5803: double ***p3mat;
5804: double age,agelim, hf;
5805: /* double ***mobaverage; */
5806: int theta;
5807: char digit[4];
5808: char digitp[25];
5809:
5810: char fileresprobmorprev[FILENAMELENGTH];
5811:
5812: if(popbased==1){
5813: if(mobilav!=0)
5814: strcpy(digitp,"-POPULBASED-MOBILAV_");
5815: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
5816: }
5817: else
5818: strcpy(digitp,"-STABLBASED_");
1.126 brouard 5819:
1.218 brouard 5820: /* if (mobilav!=0) { */
5821: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
5822: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
5823: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
5824: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
5825: /* } */
5826: /* } */
5827:
5828: strcpy(fileresprobmorprev,"PRMORPREV-");
5829: sprintf(digit,"%-d",ij);
5830: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
5831: strcat(fileresprobmorprev,digit); /* Tvar to be done */
5832: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
5833: strcat(fileresprobmorprev,fileresu);
5834: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
5835: printf("Problem with resultfile: %s\n", fileresprobmorprev);
5836: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
5837: }
5838: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
5839: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
5840: pstamp(ficresprobmorprev);
5841: 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 5842: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
5843: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
5844: fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
5845: }
5846: for(j=1;j<=cptcoveff;j++)
5847: fprintf(ficresprobmorprev,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,j)]);
5848: fprintf(ficresprobmorprev,"\n");
5849:
1.218 brouard 5850: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
5851: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
5852: fprintf(ficresprobmorprev," p.%-d SE",j);
5853: for(i=1; i<=nlstate;i++)
5854: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
5855: }
5856: fprintf(ficresprobmorprev,"\n");
5857:
5858: fprintf(ficgp,"\n# Routine varevsij");
5859: fprintf(ficgp,"\nunset title \n");
5860: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
5861: 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");
5862: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
1.279 brouard 5863:
1.218 brouard 5864: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
5865: pstamp(ficresvij);
5866: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
5867: if(popbased==1)
5868: 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);
5869: else
5870: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
5871: fprintf(ficresvij,"# Age");
5872: for(i=1; i<=nlstate;i++)
5873: for(j=1; j<=nlstate;j++)
5874: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
5875: fprintf(ficresvij,"\n");
5876:
5877: xp=vector(1,npar);
5878: dnewm=matrix(1,nlstate,1,npar);
5879: doldm=matrix(1,nlstate,1,nlstate);
5880: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
5881: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
5882:
5883: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
5884: gpp=vector(nlstate+1,nlstate+ndeath);
5885: gmp=vector(nlstate+1,nlstate+ndeath);
5886: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 5887:
1.218 brouard 5888: if(estepm < stepm){
5889: printf ("Problem %d lower than %d\n",estepm, stepm);
5890: }
5891: else hstepm=estepm;
5892: /* For example we decided to compute the life expectancy with the smallest unit */
5893: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5894: nhstepm is the number of hstepm from age to agelim
5895: nstepm is the number of stepm from age to agelim.
5896: Look at function hpijx to understand why because of memory size limitations,
5897: we decided (b) to get a life expectancy respecting the most precise curvature of the
5898: survival function given by stepm (the optimization length). Unfortunately it
5899: means that if the survival funtion is printed every two years of age and if
5900: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5901: results. So we changed our mind and took the option of the best precision.
5902: */
5903: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5904: agelim = AGESUP;
5905: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
5906: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
5907: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5908: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5909: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
5910: gp=matrix(0,nhstepm,1,nlstate);
5911: gm=matrix(0,nhstepm,1,nlstate);
5912:
5913:
5914: for(theta=1; theta <=npar; theta++){
5915: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
5916: xp[i] = x[i] + (i==theta ?delti[theta]:0);
5917: }
1.279 brouard 5918: /**< Computes the prevalence limit with parameter theta shifted of delta up to ftolpl precision and
5919: * returns into prlim .
5920: */
1.242 brouard 5921: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.279 brouard 5922:
5923: /* If popbased = 1 we use crossection prevalences. Previous step is useless but prlim is created */
1.218 brouard 5924: if (popbased==1) {
5925: if(mobilav ==0){
5926: for(i=1; i<=nlstate;i++)
5927: prlim[i][i]=probs[(int)age][i][ij];
5928: }else{ /* mobilav */
5929: for(i=1; i<=nlstate;i++)
5930: prlim[i][i]=mobaverage[(int)age][i][ij];
5931: }
5932: }
1.279 brouard 5933: /**< Computes the shifted transition matrix \f$ {}{h}_p^{ij}_x\f$ at horizon h.
5934: */
5935: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres); /* Returns p3mat[i][j][h] for h=0 to nhstepm */
5936: /**< And for each alive state j, sums over i \f$ w^i_x {}{h}_p^{ij}_x\f$, which are the probability
5937: * at horizon h in state j including mortality.
5938: */
1.218 brouard 5939: for(j=1; j<= nlstate; j++){
5940: for(h=0; h<=nhstepm; h++){
5941: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
5942: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
5943: }
5944: }
1.279 brouard 5945: /* Next for computing shifted+ probability of death (h=1 means
1.218 brouard 5946: computed over hstepm matrices product = hstepm*stepm months)
1.279 brouard 5947: as a weighted average of prlim(i) * p(i,j) p.3=w1*p13 + w2*p23 .
1.218 brouard 5948: */
5949: for(j=nlstate+1;j<=nlstate+ndeath;j++){
5950: for(i=1,gpp[j]=0.; i<= nlstate; i++)
5951: gpp[j] += prlim[i][i]*p3mat[i][j][1];
1.279 brouard 5952: }
5953:
5954: /* Again with minus shift */
1.218 brouard 5955:
5956: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
5957: xp[i] = x[i] - (i==theta ?delti[theta]:0);
5958:
1.242 brouard 5959: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 5960:
5961: if (popbased==1) {
5962: if(mobilav ==0){
5963: for(i=1; i<=nlstate;i++)
5964: prlim[i][i]=probs[(int)age][i][ij];
5965: }else{ /* mobilav */
5966: for(i=1; i<=nlstate;i++)
5967: prlim[i][i]=mobaverage[(int)age][i][ij];
5968: }
5969: }
5970:
1.235 brouard 5971: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 5972:
5973: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
5974: for(h=0; h<=nhstepm; h++){
5975: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
5976: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
5977: }
5978: }
5979: /* This for computing probability of death (h=1 means
5980: computed over hstepm matrices product = hstepm*stepm months)
5981: as a weighted average of prlim.
5982: */
5983: for(j=nlstate+1;j<=nlstate+ndeath;j++){
5984: for(i=1,gmp[j]=0.; i<= nlstate; i++)
5985: gmp[j] += prlim[i][i]*p3mat[i][j][1];
5986: }
1.279 brouard 5987: /* end shifting computations */
5988:
5989: /**< Computing gradient matrix at horizon h
5990: */
1.218 brouard 5991: for(j=1; j<= nlstate; j++) /* vareij */
5992: for(h=0; h<=nhstepm; h++){
5993: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
5994: }
1.279 brouard 5995: /**< Gradient of overall mortality p.3 (or p.j)
5996: */
5997: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu mortality from j */
1.218 brouard 5998: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
5999: }
6000:
6001: } /* End theta */
1.279 brouard 6002:
6003: /* We got the gradient matrix for each theta and state j */
1.218 brouard 6004: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
6005:
6006: for(h=0; h<=nhstepm; h++) /* veij */
6007: for(j=1; j<=nlstate;j++)
6008: for(theta=1; theta <=npar; theta++)
6009: trgradg[h][j][theta]=gradg[h][theta][j];
6010:
6011: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
6012: for(theta=1; theta <=npar; theta++)
6013: trgradgp[j][theta]=gradgp[theta][j];
1.279 brouard 6014: /**< as well as its transposed matrix
6015: */
1.218 brouard 6016:
6017: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6018: for(i=1;i<=nlstate;i++)
6019: for(j=1;j<=nlstate;j++)
6020: vareij[i][j][(int)age] =0.;
1.279 brouard 6021:
6022: /* Computing trgradg by matcov by gradg at age and summing over h
6023: * and k (nhstepm) formula 15 of article
6024: * Lievre-Brouard-Heathcote
6025: */
6026:
1.218 brouard 6027: for(h=0;h<=nhstepm;h++){
6028: for(k=0;k<=nhstepm;k++){
6029: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
6030: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
6031: for(i=1;i<=nlstate;i++)
6032: for(j=1;j<=nlstate;j++)
6033: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
6034: }
6035: }
6036:
1.279 brouard 6037: /* pptj is p.3 or p.j = trgradgp by cov by gradgp, variance of
6038: * p.j overall mortality formula 49 but computed directly because
6039: * we compute the grad (wix pijx) instead of grad (pijx),even if
6040: * wix is independent of theta.
6041: */
1.218 brouard 6042: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
6043: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
6044: for(j=nlstate+1;j<=nlstate+ndeath;j++)
6045: for(i=nlstate+1;i<=nlstate+ndeath;i++)
6046: varppt[j][i]=doldmp[j][i];
6047: /* end ppptj */
6048: /* x centered again */
6049:
1.242 brouard 6050: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 6051:
6052: if (popbased==1) {
6053: if(mobilav ==0){
6054: for(i=1; i<=nlstate;i++)
6055: prlim[i][i]=probs[(int)age][i][ij];
6056: }else{ /* mobilav */
6057: for(i=1; i<=nlstate;i++)
6058: prlim[i][i]=mobaverage[(int)age][i][ij];
6059: }
6060: }
6061:
6062: /* This for computing probability of death (h=1 means
6063: computed over hstepm (estepm) matrices product = hstepm*stepm months)
6064: as a weighted average of prlim.
6065: */
1.235 brouard 6066: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 6067: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6068: for(i=1,gmp[j]=0.;i<= nlstate; i++)
6069: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6070: }
6071: /* end probability of death */
6072:
6073: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
6074: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6075: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
6076: for(i=1; i<=nlstate;i++){
6077: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
6078: }
6079: }
6080: fprintf(ficresprobmorprev,"\n");
6081:
6082: fprintf(ficresvij,"%.0f ",age );
6083: for(i=1; i<=nlstate;i++)
6084: for(j=1; j<=nlstate;j++){
6085: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
6086: }
6087: fprintf(ficresvij,"\n");
6088: free_matrix(gp,0,nhstepm,1,nlstate);
6089: free_matrix(gm,0,nhstepm,1,nlstate);
6090: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
6091: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
6092: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6093: } /* End age */
6094: free_vector(gpp,nlstate+1,nlstate+ndeath);
6095: free_vector(gmp,nlstate+1,nlstate+ndeath);
6096: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
6097: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
6098: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
6099: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
6100: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
6101: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
6102: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
6103: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
6104: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
6105: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
6106: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
6107: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
6108: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
6109: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
6110: 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);
6111: /* 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 6112: */
1.218 brouard 6113: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
6114: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 6115:
1.218 brouard 6116: free_vector(xp,1,npar);
6117: free_matrix(doldm,1,nlstate,1,nlstate);
6118: free_matrix(dnewm,1,nlstate,1,npar);
6119: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6120: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
6121: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6122: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6123: fclose(ficresprobmorprev);
6124: fflush(ficgp);
6125: fflush(fichtm);
6126: } /* end varevsij */
1.126 brouard 6127:
6128: /************ Variance of prevlim ******************/
1.269 brouard 6129: 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 6130: {
1.205 brouard 6131: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 6132: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 6133:
1.268 brouard 6134: double **dnewmpar,**doldm;
1.126 brouard 6135: int i, j, nhstepm, hstepm;
6136: double *xp;
6137: double *gp, *gm;
6138: double **gradg, **trgradg;
1.208 brouard 6139: double **mgm, **mgp;
1.126 brouard 6140: double age,agelim;
6141: int theta;
6142:
6143: pstamp(ficresvpl);
6144: fprintf(ficresvpl,"# Standard deviation of period (stable) prevalences \n");
1.241 brouard 6145: fprintf(ficresvpl,"# Age ");
6146: if(nresult >=1)
6147: fprintf(ficresvpl," Result# ");
1.126 brouard 6148: for(i=1; i<=nlstate;i++)
6149: fprintf(ficresvpl," %1d-%1d",i,i);
6150: fprintf(ficresvpl,"\n");
6151:
6152: xp=vector(1,npar);
1.268 brouard 6153: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 6154: doldm=matrix(1,nlstate,1,nlstate);
6155:
6156: hstepm=1*YEARM; /* Every year of age */
6157: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6158: agelim = AGESUP;
6159: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6160: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6161: if (stepm >= YEARM) hstepm=1;
6162: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6163: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 6164: mgp=matrix(1,npar,1,nlstate);
6165: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 6166: gp=vector(1,nlstate);
6167: gm=vector(1,nlstate);
6168:
6169: for(theta=1; theta <=npar; theta++){
6170: for(i=1; i<=npar; i++){ /* Computes gradient */
6171: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6172: }
1.209 brouard 6173: if((int)age==79 ||(int)age== 80 ||(int)age== 81 )
1.235 brouard 6174: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.209 brouard 6175: else
1.235 brouard 6176: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6177: for(i=1;i<=nlstate;i++){
1.126 brouard 6178: gp[i] = prlim[i][i];
1.208 brouard 6179: mgp[theta][i] = prlim[i][i];
6180: }
1.126 brouard 6181: for(i=1; i<=npar; i++) /* Computes gradient */
6182: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.209 brouard 6183: if((int)age==79 ||(int)age== 80 ||(int)age== 81 )
1.235 brouard 6184: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.209 brouard 6185: else
1.235 brouard 6186: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6187: for(i=1;i<=nlstate;i++){
1.126 brouard 6188: gm[i] = prlim[i][i];
1.208 brouard 6189: mgm[theta][i] = prlim[i][i];
6190: }
1.126 brouard 6191: for(i=1;i<=nlstate;i++)
6192: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 6193: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 6194: } /* End theta */
6195:
6196: trgradg =matrix(1,nlstate,1,npar);
6197:
6198: for(j=1; j<=nlstate;j++)
6199: for(theta=1; theta <=npar; theta++)
6200: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 6201: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6202: /* printf("\nmgm mgp %d ",(int)age); */
6203: /* for(j=1; j<=nlstate;j++){ */
6204: /* printf(" %d ",j); */
6205: /* for(theta=1; theta <=npar; theta++) */
6206: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6207: /* printf("\n "); */
6208: /* } */
6209: /* } */
6210: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6211: /* printf("\n gradg %d ",(int)age); */
6212: /* for(j=1; j<=nlstate;j++){ */
6213: /* printf("%d ",j); */
6214: /* for(theta=1; theta <=npar; theta++) */
6215: /* printf("%d %lf ",theta,gradg[theta][j]); */
6216: /* printf("\n "); */
6217: /* } */
6218: /* } */
1.126 brouard 6219:
6220: for(i=1;i<=nlstate;i++)
6221: varpl[i][(int)age] =0.;
1.209 brouard 6222: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 brouard 6223: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6224: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6225: }else{
1.268 brouard 6226: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6227: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6228: }
1.126 brouard 6229: for(i=1;i<=nlstate;i++)
6230: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6231:
6232: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 6233: if(nresult >=1)
6234: fprintf(ficresvpl,"%d ",nres );
1.126 brouard 6235: for(i=1; i<=nlstate;i++)
6236: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
6237: fprintf(ficresvpl,"\n");
6238: free_vector(gp,1,nlstate);
6239: free_vector(gm,1,nlstate);
1.208 brouard 6240: free_matrix(mgm,1,npar,1,nlstate);
6241: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 6242: free_matrix(gradg,1,npar,1,nlstate);
6243: free_matrix(trgradg,1,nlstate,1,npar);
6244: } /* End age */
6245:
6246: free_vector(xp,1,npar);
6247: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 6248: free_matrix(dnewmpar,1,nlstate,1,nlstate);
6249:
6250: }
6251:
6252:
6253: /************ Variance of backprevalence limit ******************/
1.269 brouard 6254: 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 6255: {
6256: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
6257: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
6258:
6259: double **dnewmpar,**doldm;
6260: int i, j, nhstepm, hstepm;
6261: double *xp;
6262: double *gp, *gm;
6263: double **gradg, **trgradg;
6264: double **mgm, **mgp;
6265: double age,agelim;
6266: int theta;
6267:
6268: pstamp(ficresvbl);
6269: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
6270: fprintf(ficresvbl,"# Age ");
6271: if(nresult >=1)
6272: fprintf(ficresvbl," Result# ");
6273: for(i=1; i<=nlstate;i++)
6274: fprintf(ficresvbl," %1d-%1d",i,i);
6275: fprintf(ficresvbl,"\n");
6276:
6277: xp=vector(1,npar);
6278: dnewmpar=matrix(1,nlstate,1,npar);
6279: doldm=matrix(1,nlstate,1,nlstate);
6280:
6281: hstepm=1*YEARM; /* Every year of age */
6282: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6283: agelim = AGEINF;
6284: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
6285: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6286: if (stepm >= YEARM) hstepm=1;
6287: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6288: gradg=matrix(1,npar,1,nlstate);
6289: mgp=matrix(1,npar,1,nlstate);
6290: mgm=matrix(1,npar,1,nlstate);
6291: gp=vector(1,nlstate);
6292: gm=vector(1,nlstate);
6293:
6294: for(theta=1; theta <=npar; theta++){
6295: for(i=1; i<=npar; i++){ /* Computes gradient */
6296: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6297: }
6298: if(mobilavproj > 0 )
6299: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6300: else
6301: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6302: for(i=1;i<=nlstate;i++){
6303: gp[i] = bprlim[i][i];
6304: mgp[theta][i] = bprlim[i][i];
6305: }
6306: for(i=1; i<=npar; i++) /* Computes gradient */
6307: xp[i] = x[i] - (i==theta ?delti[theta]:0);
6308: if(mobilavproj > 0 )
6309: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6310: else
6311: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6312: for(i=1;i<=nlstate;i++){
6313: gm[i] = bprlim[i][i];
6314: mgm[theta][i] = bprlim[i][i];
6315: }
6316: for(i=1;i<=nlstate;i++)
6317: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
6318: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
6319: } /* End theta */
6320:
6321: trgradg =matrix(1,nlstate,1,npar);
6322:
6323: for(j=1; j<=nlstate;j++)
6324: for(theta=1; theta <=npar; theta++)
6325: trgradg[j][theta]=gradg[theta][j];
6326: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6327: /* printf("\nmgm mgp %d ",(int)age); */
6328: /* for(j=1; j<=nlstate;j++){ */
6329: /* printf(" %d ",j); */
6330: /* for(theta=1; theta <=npar; theta++) */
6331: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6332: /* printf("\n "); */
6333: /* } */
6334: /* } */
6335: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6336: /* printf("\n gradg %d ",(int)age); */
6337: /* for(j=1; j<=nlstate;j++){ */
6338: /* printf("%d ",j); */
6339: /* for(theta=1; theta <=npar; theta++) */
6340: /* printf("%d %lf ",theta,gradg[theta][j]); */
6341: /* printf("\n "); */
6342: /* } */
6343: /* } */
6344:
6345: for(i=1;i<=nlstate;i++)
6346: varbpl[i][(int)age] =0.;
6347: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
6348: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6349: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6350: }else{
6351: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6352: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6353: }
6354: for(i=1;i<=nlstate;i++)
6355: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6356:
6357: fprintf(ficresvbl,"%.0f ",age );
6358: if(nresult >=1)
6359: fprintf(ficresvbl,"%d ",nres );
6360: for(i=1; i<=nlstate;i++)
6361: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
6362: fprintf(ficresvbl,"\n");
6363: free_vector(gp,1,nlstate);
6364: free_vector(gm,1,nlstate);
6365: free_matrix(mgm,1,npar,1,nlstate);
6366: free_matrix(mgp,1,npar,1,nlstate);
6367: free_matrix(gradg,1,npar,1,nlstate);
6368: free_matrix(trgradg,1,nlstate,1,npar);
6369: } /* End age */
6370:
6371: free_vector(xp,1,npar);
6372: free_matrix(doldm,1,nlstate,1,npar);
6373: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 6374:
6375: }
6376:
6377: /************ Variance of one-step probabilities ******************/
6378: 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 6379: {
6380: int i, j=0, k1, l1, tj;
6381: int k2, l2, j1, z1;
6382: int k=0, l;
6383: int first=1, first1, first2;
6384: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
6385: double **dnewm,**doldm;
6386: double *xp;
6387: double *gp, *gm;
6388: double **gradg, **trgradg;
6389: double **mu;
6390: double age, cov[NCOVMAX+1];
6391: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
6392: int theta;
6393: char fileresprob[FILENAMELENGTH];
6394: char fileresprobcov[FILENAMELENGTH];
6395: char fileresprobcor[FILENAMELENGTH];
6396: double ***varpij;
6397:
6398: strcpy(fileresprob,"PROB_");
6399: strcat(fileresprob,fileres);
6400: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
6401: printf("Problem with resultfile: %s\n", fileresprob);
6402: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
6403: }
6404: strcpy(fileresprobcov,"PROBCOV_");
6405: strcat(fileresprobcov,fileresu);
6406: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
6407: printf("Problem with resultfile: %s\n", fileresprobcov);
6408: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
6409: }
6410: strcpy(fileresprobcor,"PROBCOR_");
6411: strcat(fileresprobcor,fileresu);
6412: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
6413: printf("Problem with resultfile: %s\n", fileresprobcor);
6414: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
6415: }
6416: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6417: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6418: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6419: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6420: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6421: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6422: pstamp(ficresprob);
6423: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
6424: fprintf(ficresprob,"# Age");
6425: pstamp(ficresprobcov);
6426: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
6427: fprintf(ficresprobcov,"# Age");
6428: pstamp(ficresprobcor);
6429: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
6430: fprintf(ficresprobcor,"# Age");
1.126 brouard 6431:
6432:
1.222 brouard 6433: for(i=1; i<=nlstate;i++)
6434: for(j=1; j<=(nlstate+ndeath);j++){
6435: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
6436: fprintf(ficresprobcov," p%1d-%1d ",i,j);
6437: fprintf(ficresprobcor," p%1d-%1d ",i,j);
6438: }
6439: /* fprintf(ficresprob,"\n");
6440: fprintf(ficresprobcov,"\n");
6441: fprintf(ficresprobcor,"\n");
6442: */
6443: xp=vector(1,npar);
6444: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6445: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6446: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
6447: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
6448: first=1;
6449: fprintf(ficgp,"\n# Routine varprob");
6450: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
6451: fprintf(fichtm,"\n");
6452:
1.266 brouard 6453: 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 6454: 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);
6455: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 6456: and drawn. It helps understanding how is the covariance between two incidences.\
6457: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 6458: 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 6459: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
6460: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
6461: standard deviations wide on each axis. <br>\
6462: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
6463: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
6464: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
6465:
1.222 brouard 6466: cov[1]=1;
6467: /* tj=cptcoveff; */
1.225 brouard 6468: tj = (int) pow(2,cptcoveff);
1.222 brouard 6469: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
6470: j1=0;
1.224 brouard 6471: for(j1=1; j1<=tj;j1++){ /* For each valid combination of covariates or only once*/
1.222 brouard 6472: if (cptcovn>0) {
6473: fprintf(ficresprob, "\n#********** Variable ");
1.225 brouard 6474: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6475: fprintf(ficresprob, "**********\n#\n");
6476: fprintf(ficresprobcov, "\n#********** Variable ");
1.225 brouard 6477: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcov, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6478: fprintf(ficresprobcov, "**********\n#\n");
1.220 brouard 6479:
1.222 brouard 6480: fprintf(ficgp, "\n#********** Variable ");
1.225 brouard 6481: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficgp, " V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6482: fprintf(ficgp, "**********\n#\n");
1.220 brouard 6483:
6484:
1.222 brouard 6485: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
1.225 brouard 6486: for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtm, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6487: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 6488:
1.222 brouard 6489: fprintf(ficresprobcor, "\n#********** Variable ");
1.225 brouard 6490: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcor, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6491: fprintf(ficresprobcor, "**********\n#");
6492: if(invalidvarcomb[j1]){
6493: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
6494: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
6495: continue;
6496: }
6497: }
6498: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
6499: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6500: gp=vector(1,(nlstate)*(nlstate+ndeath));
6501: gm=vector(1,(nlstate)*(nlstate+ndeath));
6502: for (age=bage; age<=fage; age ++){
6503: cov[2]=age;
6504: if(nagesqr==1)
6505: cov[3]= age*age;
6506: for (k=1; k<=cptcovn;k++) {
6507: cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)];
6508: /*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*//* j1 1 2 3 4
6509: * 1 1 1 1 1
6510: * 2 2 1 1 1
6511: * 3 1 2 1 1
6512: */
6513: /* nbcode[1][1]=0 nbcode[1][2]=1;*/
6514: }
6515: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; */
6516: for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
6517: for (k=1; k<=cptcovprod;k++)
6518: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.220 brouard 6519:
6520:
1.222 brouard 6521: for(theta=1; theta <=npar; theta++){
6522: for(i=1; i<=npar; i++)
6523: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 6524:
1.222 brouard 6525: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 6526:
1.222 brouard 6527: k=0;
6528: for(i=1; i<= (nlstate); i++){
6529: for(j=1; j<=(nlstate+ndeath);j++){
6530: k=k+1;
6531: gp[k]=pmmij[i][j];
6532: }
6533: }
1.220 brouard 6534:
1.222 brouard 6535: for(i=1; i<=npar; i++)
6536: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 6537:
1.222 brouard 6538: pmij(pmmij,cov,ncovmodel,xp,nlstate);
6539: k=0;
6540: for(i=1; i<=(nlstate); i++){
6541: for(j=1; j<=(nlstate+ndeath);j++){
6542: k=k+1;
6543: gm[k]=pmmij[i][j];
6544: }
6545: }
1.220 brouard 6546:
1.222 brouard 6547: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
6548: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
6549: }
1.126 brouard 6550:
1.222 brouard 6551: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
6552: for(theta=1; theta <=npar; theta++)
6553: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 6554:
1.222 brouard 6555: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
6556: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 6557:
1.222 brouard 6558: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 6559:
1.222 brouard 6560: k=0;
6561: for(i=1; i<=(nlstate); i++){
6562: for(j=1; j<=(nlstate+ndeath);j++){
6563: k=k+1;
6564: mu[k][(int) age]=pmmij[i][j];
6565: }
6566: }
6567: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
6568: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
6569: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 6570:
1.222 brouard 6571: /*printf("\n%d ",(int)age);
6572: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6573: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6574: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6575: }*/
1.220 brouard 6576:
1.222 brouard 6577: fprintf(ficresprob,"\n%d ",(int)age);
6578: fprintf(ficresprobcov,"\n%d ",(int)age);
6579: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 6580:
1.222 brouard 6581: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
6582: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
6583: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6584: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
6585: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
6586: }
6587: i=0;
6588: for (k=1; k<=(nlstate);k++){
6589: for (l=1; l<=(nlstate+ndeath);l++){
6590: i++;
6591: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
6592: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
6593: for (j=1; j<=i;j++){
6594: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
6595: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
6596: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
6597: }
6598: }
6599: }/* end of loop for state */
6600: } /* end of loop for age */
6601: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
6602: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
6603: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
6604: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
6605:
6606: /* Confidence intervalle of pij */
6607: /*
6608: fprintf(ficgp,"\nunset parametric;unset label");
6609: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
6610: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
6611: 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);
6612: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
6613: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
6614: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
6615: */
6616:
6617: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
6618: first1=1;first2=2;
6619: for (k2=1; k2<=(nlstate);k2++){
6620: for (l2=1; l2<=(nlstate+ndeath);l2++){
6621: if(l2==k2) continue;
6622: j=(k2-1)*(nlstate+ndeath)+l2;
6623: for (k1=1; k1<=(nlstate);k1++){
6624: for (l1=1; l1<=(nlstate+ndeath);l1++){
6625: if(l1==k1) continue;
6626: i=(k1-1)*(nlstate+ndeath)+l1;
6627: if(i<=j) continue;
6628: for (age=bage; age<=fage; age ++){
6629: if ((int)age %5==0){
6630: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
6631: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
6632: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
6633: mu1=mu[i][(int) age]/stepm*YEARM ;
6634: mu2=mu[j][(int) age]/stepm*YEARM;
6635: c12=cv12/sqrt(v1*v2);
6636: /* Computing eigen value of matrix of covariance */
6637: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6638: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6639: if ((lc2 <0) || (lc1 <0) ){
6640: if(first2==1){
6641: first1=0;
6642: 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);
6643: }
6644: 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);
6645: /* lc1=fabs(lc1); */ /* If we want to have them positive */
6646: /* lc2=fabs(lc2); */
6647: }
1.220 brouard 6648:
1.222 brouard 6649: /* Eigen vectors */
1.280 brouard 6650: if(1+(v1-lc1)*(v1-lc1)/cv12/cv12 <1.e-5){
6651: printf(" Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
6652: fprintf(ficlog," Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
6653: v11=(1./sqrt(fabs(1+(v1-lc1)*(v1-lc1)/cv12/cv12)));
6654: }else
6655: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
1.222 brouard 6656: /*v21=sqrt(1.-v11*v11); *//* error */
6657: v21=(lc1-v1)/cv12*v11;
6658: v12=-v21;
6659: v22=v11;
6660: tnalp=v21/v11;
6661: if(first1==1){
6662: first1=0;
6663: 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);
6664: }
6665: 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);
6666: /*printf(fignu*/
6667: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
6668: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
6669: if(first==1){
6670: first=0;
6671: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
6672: fprintf(ficgp,"\nset parametric;unset label");
6673: 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);
6674: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 6675: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 6676: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 6677: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 6678: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
6679: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6680: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6681: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
6682: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6683: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
6684: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
6685: 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 6686: mu1,std,v11,sqrt(fabs(lc1)),v12,sqrt(fabs(lc2)), \
6687: mu2,std,v21,sqrt(fabs(lc1)),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 6688: }else{
6689: first=0;
6690: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
6691: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
6692: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
6693: 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 6694: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
6695: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 6696: }/* if first */
6697: } /* age mod 5 */
6698: } /* end loop age */
6699: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6700: first=1;
6701: } /*l12 */
6702: } /* k12 */
6703: } /*l1 */
6704: }/* k1 */
6705: } /* loop on combination of covariates j1 */
6706: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
6707: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
6708: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6709: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
6710: free_vector(xp,1,npar);
6711: fclose(ficresprob);
6712: fclose(ficresprobcov);
6713: fclose(ficresprobcor);
6714: fflush(ficgp);
6715: fflush(fichtmcov);
6716: }
1.126 brouard 6717:
6718:
6719: /******************* Printing html file ***********/
1.201 brouard 6720: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 6721: int lastpass, int stepm, int weightopt, char model[],\
6722: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.258 brouard 6723: int popforecast, int mobilav, int prevfcast, int mobilavproj, int backcast, int estepm , \
1.273 brouard 6724: double jprev1, double mprev1,double anprev1, double dateprev1, double dateproj1, double dateback1, \
6725: double jprev2, double mprev2,double anprev2, double dateprev2, double dateproj2, double dateback2){
1.237 brouard 6726: int jj1, k1, i1, cpt, k4, nres;
1.126 brouard 6727:
6728: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
6729: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
6730: </ul>");
1.237 brouard 6731: fprintf(fichtm,"<ul><li> model=1+age+%s\n \
6732: </ul>", model);
1.214 brouard 6733: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
6734: 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",
6735: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
6736: 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 6737: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
6738: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 6739: fprintf(fichtm,"\
6740: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 6741: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 6742: fprintf(fichtm,"\
1.217 brouard 6743: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
6744: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
6745: fprintf(fichtm,"\
1.126 brouard 6746: - Period (stable) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 6747: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 6748: fprintf(fichtm,"\
1.217 brouard 6749: - Period (stable) back prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
6750: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
6751: fprintf(fichtm,"\
1.211 brouard 6752: - (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 6753: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 6754: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 6755: if(prevfcast==1){
6756: fprintf(fichtm,"\
6757: - Prevalence projections by age and states: \
1.201 brouard 6758: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 6759: }
1.126 brouard 6760:
6761:
1.225 brouard 6762: m=pow(2,cptcoveff);
1.222 brouard 6763: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 6764:
1.264 brouard 6765: fprintf(fichtm," \n<ul><li><b>Graphs</b></li><p>");
6766:
6767: jj1=0;
6768:
6769: fprintf(fichtm," \n<ul>");
6770: for(nres=1; nres <= nresult; nres++) /* For each resultline */
6771: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
6772: if(m != 1 && TKresult[nres]!= k1)
6773: continue;
6774: jj1++;
6775: if (cptcovn > 0) {
6776: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
6777: for (cpt=1; cpt<=cptcoveff;cpt++){
6778: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6779: }
6780: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6781: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
6782: }
6783: fprintf(fichtm,"\">");
6784:
6785: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
6786: fprintf(fichtm,"************ Results for covariates");
6787: for (cpt=1; cpt<=cptcoveff;cpt++){
6788: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6789: }
6790: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6791: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6792: }
6793: if(invalidvarcomb[k1]){
6794: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
6795: continue;
6796: }
6797: fprintf(fichtm,"</a></li>");
6798: } /* cptcovn >0 */
6799: }
6800: fprintf(fichtm," \n</ul>");
6801:
1.222 brouard 6802: jj1=0;
1.237 brouard 6803:
6804: for(nres=1; nres <= nresult; nres++) /* For each resultline */
1.241 brouard 6805: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
1.253 brouard 6806: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 6807: continue;
1.220 brouard 6808:
1.222 brouard 6809: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
6810: jj1++;
6811: if (cptcovn > 0) {
1.264 brouard 6812: fprintf(fichtm,"\n<p><a name=\"rescov");
6813: for (cpt=1; cpt<=cptcoveff;cpt++){
6814: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6815: }
6816: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6817: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
6818: }
6819: fprintf(fichtm,"\"</a>");
6820:
1.222 brouard 6821: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 6822: for (cpt=1; cpt<=cptcoveff;cpt++){
1.237 brouard 6823: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6824: printf(" V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);fflush(stdout);
6825: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
6826: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 6827: }
1.237 brouard 6828: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6829: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6830: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);fflush(stdout);
6831: }
6832:
1.230 brouard 6833: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.222 brouard 6834: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
6835: if(invalidvarcomb[k1]){
6836: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
6837: printf("\nCombination (%d) ignored because no cases \n",k1);
6838: continue;
6839: }
6840: }
6841: /* aij, bij */
1.259 brouard 6842: 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 6843: <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 6844: /* Pij */
1.241 brouard 6845: 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> \
6846: <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 6847: /* Quasi-incidences */
6848: 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 6849: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 6850: 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 6851: 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> \
6852: <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 6853: /* Survival functions (period) in state j */
6854: for(cpt=1; cpt<=nlstate;cpt++){
1.241 brouard 6855: 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> \
6856: <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 6857: }
6858: /* State specific survival functions (period) */
6859: for(cpt=1; cpt<=nlstate;cpt++){
6860: fprintf(fichtm,"<br>\n- Survival functions from state %d in each live state and total.\
1.220 brouard 6861: Or probability to survive in various states (1 to %d) being in state %d at different ages. \
1.241 brouard 6862: <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 6863: }
6864: /* Period (stable) prevalence in each health state */
6865: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 6866: 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> \
6867: <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 6868: }
6869: if(backcast==1){
6870: /* Period (stable) back prevalence in each health state */
6871: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 6872: 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 6873: <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 6874: }
1.217 brouard 6875: }
1.222 brouard 6876: if(prevfcast==1){
6877: /* Projection of prevalence up to period (stable) prevalence in each health state */
6878: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 6879: 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> \
6880: <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 6881: }
6882: }
1.268 brouard 6883: if(backcast==1){
6884: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
6885: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 6886: fprintf(fichtm,"<br>\n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), \
6887: 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 \
6888: 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) \
6889: with weights corresponding to observed prevalence at different ages. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br> \
6890: <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 6891: }
6892: }
1.220 brouard 6893:
1.222 brouard 6894: for(cpt=1; cpt<=nlstate;cpt++) {
1.241 brouard 6895: 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> \
6896: <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 6897: }
6898: /* } /\* end i1 *\/ */
6899: }/* End k1 */
6900: fprintf(fichtm,"</ul>");
1.126 brouard 6901:
1.222 brouard 6902: fprintf(fichtm,"\
1.126 brouard 6903: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 6904: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 6905: - 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 6906: But because parameters are usually highly correlated (a higher incidence of disability \
6907: and a higher incidence of recovery can give very close observed transition) it might \
6908: be very useful to look not only at linear confidence intervals estimated from the \
6909: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
6910: (parameters) of the logistic regression, it might be more meaningful to visualize the \
6911: covariance matrix of the one-step probabilities. \
6912: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 6913:
1.222 brouard 6914: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
6915: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
6916: fprintf(fichtm,"\
1.126 brouard 6917: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 6918: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 6919:
1.222 brouard 6920: fprintf(fichtm,"\
1.126 brouard 6921: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 6922: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
6923: fprintf(fichtm,"\
1.126 brouard 6924: - 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): \
6925: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 6926: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 6927: fprintf(fichtm,"\
1.126 brouard 6928: - (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): \
6929: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 6930: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 6931: fprintf(fichtm,"\
1.128 brouard 6932: - 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 6933: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
6934: fprintf(fichtm,"\
1.128 brouard 6935: - 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 6936: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
6937: fprintf(fichtm,"\
1.126 brouard 6938: - Standard deviation of period (stable) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 6939: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 6940:
6941: /* if(popforecast==1) fprintf(fichtm,"\n */
6942: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
6943: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
6944: /* <br>",fileres,fileres,fileres,fileres); */
6945: /* else */
6946: /* 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 6947: fflush(fichtm);
6948: fprintf(fichtm," <ul><li><b>Graphs</b></li><p>");
1.126 brouard 6949:
1.225 brouard 6950: m=pow(2,cptcoveff);
1.222 brouard 6951: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 6952:
1.222 brouard 6953: jj1=0;
1.237 brouard 6954:
1.241 brouard 6955: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.222 brouard 6956: for(k1=1; k1<=m;k1++){
1.253 brouard 6957: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 6958: continue;
1.222 brouard 6959: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
6960: jj1++;
1.126 brouard 6961: if (cptcovn > 0) {
6962: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 6963: for (cpt=1; cpt<=cptcoveff;cpt++) /**< cptcoveff number of variables */
1.237 brouard 6964: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);
6965: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
6966: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6967: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6968: }
6969:
1.126 brouard 6970: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 6971:
1.222 brouard 6972: if(invalidvarcomb[k1]){
6973: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
6974: continue;
6975: }
1.126 brouard 6976: }
6977: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 6978: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.241 brouard 6979: 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 6980: <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 6981: }
6982: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.128 brouard 6983: health expectancies in states (1) and (2). If popbased=1 the smooth (due to the model) \
6984: true period expectancies (those weighted with period prevalences are also\
6985: drawn in addition to the population based expectancies computed using\
1.241 brouard 6986: observed and cahotic prevalences: <a href=\"%s_%d-%d.svg\">%s_%d-%d.svg</a>\n<br>\
6987: <img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 6988: /* } /\* end i1 *\/ */
6989: }/* End k1 */
1.241 brouard 6990: }/* End nres */
1.222 brouard 6991: fprintf(fichtm,"</ul>");
6992: fflush(fichtm);
1.126 brouard 6993: }
6994:
6995: /******************* Gnuplot file **************/
1.270 brouard 6996: 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 6997:
6998: char dirfileres[132],optfileres[132];
1.264 brouard 6999: char gplotcondition[132], gplotlabel[132];
1.237 brouard 7000: 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 7001: int lv=0, vlv=0, kl=0;
1.130 brouard 7002: int ng=0;
1.201 brouard 7003: int vpopbased;
1.223 brouard 7004: int ioffset; /* variable offset for columns */
1.270 brouard 7005: int iyearc=1; /* variable column for year of projection */
7006: int iagec=1; /* variable column for age of projection */
1.235 brouard 7007: int nres=0; /* Index of resultline */
1.266 brouard 7008: int istart=1; /* For starting graphs in projections */
1.219 brouard 7009:
1.126 brouard 7010: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
7011: /* printf("Problem with file %s",optionfilegnuplot); */
7012: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
7013: /* } */
7014:
7015: /*#ifdef windows */
7016: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 7017: /*#endif */
1.225 brouard 7018: m=pow(2,cptcoveff);
1.126 brouard 7019:
1.274 brouard 7020: /* diagram of the model */
7021: fprintf(ficgp,"\n#Diagram of the model \n");
7022: fprintf(ficgp,"\ndelta=0.03;delta2=0.07;unset arrow;\n");
7023: fprintf(ficgp,"yoff=(%d > 2? 0:1);\n",nlstate);
7024: 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);
7025:
7026: 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);
7027: fprintf(ficgp,"\n#show arrow\nunset label\n");
7028: 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);
7029: fprintf(ficgp,"\nset label %d+1 sprintf(\"State %%d\",%d+1) center at 0.,0. font \"helvetica, 16\" tc rgbcolor \"red\"\n",nlstate,nlstate);
7030: fprintf(ficgp,"\n#show label\nunset border;unset xtics; unset ytics;\n");
7031: fprintf(ficgp,"\n\nset ter svg size 640, 480;set out \"%s_.svg\" \n",subdirf2(optionfilefiname,"D_"));
7032: fprintf(ficgp,"unset log y; plot [-1.2:1.2][yoff-1.2:1.2] 1/0 not; set out;reset;\n");
7033:
1.202 brouard 7034: /* Contribution to likelihood */
7035: /* Plot the probability implied in the likelihood */
1.223 brouard 7036: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
7037: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
7038: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
7039: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 7040: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 7041: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
7042: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 7043: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
7044: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
7045: 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));
7046: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
7047: 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));
7048: for (i=1; i<= nlstate ; i ++) {
7049: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
7050: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
7051: 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);
7052: for (j=2; j<= nlstate+ndeath ; j ++) {
7053: 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);
7054: }
7055: fprintf(ficgp,";\nset out; unset ylabel;\n");
7056: }
7057: /* 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 */
7058: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
7059: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
7060: fprintf(ficgp,"\nset out;unset log\n");
7061: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 7062:
1.126 brouard 7063: strcpy(dirfileres,optionfilefiname);
7064: strcpy(optfileres,"vpl");
1.223 brouard 7065: /* 1eme*/
1.238 brouard 7066: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
7067: for (k1=1; k1<= m ; k1 ++){ /* For each valid combination of covariate */
1.236 brouard 7068: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.238 brouard 7069: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.253 brouard 7070: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7071: continue;
7072: /* We are interested in selected combination by the resultline */
1.246 brouard 7073: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.238 brouard 7074: fprintf(ficgp,"\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 7075: strcpy(gplotlabel,"(");
1.238 brouard 7076: for (k=1; k<=cptcoveff; k++){ /* For each covariate k get corresponding value lv for combination k1 */
7077: lv= decodtabm(k1,k,cptcoveff); /* Should be the value of the covariate corresponding to k1 combination */
7078: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7079: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7080: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7081: vlv= nbcode[Tvaraff[k]][lv]; /* vlv is the value of the covariate lv, 0 or 1 */
7082: /* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv */
1.246 brouard 7083: /* printf(" V%d=%d ",Tvaraff[k],vlv); */
1.238 brouard 7084: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7085: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7086: }
7087: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.246 brouard 7088: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 7089: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7090: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7091: }
7092: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 7093: /* printf("\n#\n"); */
1.238 brouard 7094: fprintf(ficgp,"\n#\n");
7095: if(invalidvarcomb[k1]){
1.260 brouard 7096: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 7097: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7098: continue;
7099: }
1.235 brouard 7100:
1.241 brouard 7101: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
7102: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.276 brouard 7103: /* fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel); */
7104: fprintf(ficgp,"set title \"Alive state %d %s\" font \"Helvetica,12\"\n",cpt,gplotlabel);
1.260 brouard 7105: 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);
7106: /* 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); */
7107: /* k1-1 error should be nres-1*/
1.238 brouard 7108: for (i=1; i<= nlstate ; i ++) {
7109: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7110: else fprintf(ficgp," %%*lf (%%*lf)");
7111: }
1.260 brouard 7112: 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 7113: for (i=1; i<= nlstate ; i ++) {
7114: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7115: else fprintf(ficgp," %%*lf (%%*lf)");
7116: }
1.260 brouard 7117: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 7118: for (i=1; i<= nlstate ; i ++) {
7119: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7120: else fprintf(ficgp," %%*lf (%%*lf)");
7121: }
1.265 brouard 7122: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
7123:
7124: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
7125: if(cptcoveff ==0){
1.271 brouard 7126: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+3*(cpt-1), cpt );
1.265 brouard 7127: }else{
7128: kl=0;
7129: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7130: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7131: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7132: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7133: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7134: vlv= nbcode[Tvaraff[k]][lv];
7135: kl++;
7136: /* 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 *\/ */
7137: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7138: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7139: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7140: if(k==cptcoveff){
7141: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
7142: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
7143: }else{
7144: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7145: kl++;
7146: }
7147: } /* end covariate */
7148: } /* end if no covariate */
7149:
1.238 brouard 7150: if(backcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
7151: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 7152: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 7153: if(cptcoveff ==0){
1.245 brouard 7154: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 7155: }else{
7156: kl=0;
7157: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7158: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7159: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7160: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7161: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7162: vlv= nbcode[Tvaraff[k]][lv];
1.223 brouard 7163: kl++;
1.238 brouard 7164: /* 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 *\/ */
7165: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7166: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7167: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7168: if(k==cptcoveff){
1.245 brouard 7169: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 7170: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 7171: }else{
7172: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7173: kl++;
7174: }
7175: } /* end covariate */
7176: } /* end if no covariate */
1.268 brouard 7177: if(backcast == 1){
7178: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
7179: /* k1-1 error should be nres-1*/
7180: for (i=1; i<= nlstate ; i ++) {
7181: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7182: else fprintf(ficgp," %%*lf (%%*lf)");
7183: }
1.271 brouard 7184: 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 7185: for (i=1; i<= nlstate ; i ++) {
7186: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7187: else fprintf(ficgp," %%*lf (%%*lf)");
7188: }
1.276 brouard 7189: 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 7190: for (i=1; i<= nlstate ; i ++) {
7191: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7192: else fprintf(ficgp," %%*lf (%%*lf)");
7193: }
1.274 brouard 7194: fprintf(ficgp,"\" t\"\" w l lt 4");
1.268 brouard 7195: } /* end if backprojcast */
1.238 brouard 7196: } /* end if backcast */
1.276 brouard 7197: /* fprintf(ficgp,"\nset out ;unset label;\n"); */
7198: fprintf(ficgp,"\nset out ;unset title;\n");
1.238 brouard 7199: } /* nres */
1.201 brouard 7200: } /* k1 */
7201: } /* cpt */
1.235 brouard 7202:
7203:
1.126 brouard 7204: /*2 eme*/
1.238 brouard 7205: for (k1=1; k1<= m ; k1 ++){
7206: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7207: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7208: continue;
7209: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 7210: strcpy(gplotlabel,"(");
1.238 brouard 7211: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.225 brouard 7212: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
1.223 brouard 7213: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7214: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7215: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7216: vlv= nbcode[Tvaraff[k]][lv];
7217: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7218: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7219: }
1.237 brouard 7220: /* for(k=1; k <= ncovds; k++){ */
1.236 brouard 7221: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 7222: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.236 brouard 7223: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7224: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7225: }
1.264 brouard 7226: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7227: fprintf(ficgp,"\n#\n");
1.223 brouard 7228: if(invalidvarcomb[k1]){
7229: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7230: continue;
7231: }
1.219 brouard 7232:
1.241 brouard 7233: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 7234: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 7235: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
7236: if(vpopbased==0){
1.238 brouard 7237: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 7238: }else
1.238 brouard 7239: fprintf(ficgp,"\nreplot ");
7240: for (i=1; i<= nlstate+1 ; i ++) {
7241: k=2*i;
1.261 brouard 7242: 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 7243: for (j=1; j<= nlstate+1 ; j ++) {
7244: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7245: else fprintf(ficgp," %%*lf (%%*lf)");
7246: }
7247: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
7248: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
1.261 brouard 7249: 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 7250: for (j=1; j<= nlstate+1 ; j ++) {
7251: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7252: else fprintf(ficgp," %%*lf (%%*lf)");
7253: }
7254: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 7255: 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 7256: for (j=1; j<= nlstate+1 ; j ++) {
7257: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7258: else fprintf(ficgp," %%*lf (%%*lf)");
7259: }
7260: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
7261: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
7262: } /* state */
7263: } /* vpopbased */
1.264 brouard 7264: 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 7265: } /* end nres */
7266: } /* k1 end 2 eme*/
7267:
7268:
7269: /*3eme*/
7270: for (k1=1; k1<= m ; k1 ++){
7271: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7272: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7273: continue;
7274:
7275: for (cpt=1; cpt<= nlstate ; cpt ++) {
1.261 brouard 7276: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 7277: strcpy(gplotlabel,"(");
1.238 brouard 7278: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7279: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7280: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7281: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7282: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7283: vlv= nbcode[Tvaraff[k]][lv];
7284: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7285: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7286: }
7287: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7288: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7289: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7290: }
1.264 brouard 7291: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7292: fprintf(ficgp,"\n#\n");
7293: if(invalidvarcomb[k1]){
7294: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7295: continue;
7296: }
7297:
7298: /* k=2+nlstate*(2*cpt-2); */
7299: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 7300: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 7301: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 7302: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 7303: 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 7304: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7305: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7306: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
7307: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7308: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7309: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 7310:
1.238 brouard 7311: */
7312: for (i=1; i< nlstate ; i ++) {
1.261 brouard 7313: 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 7314: /* 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 7315:
1.238 brouard 7316: }
1.261 brouard 7317: 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 7318: }
1.264 brouard 7319: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 7320: } /* end nres */
7321: } /* end kl 3eme */
1.126 brouard 7322:
1.223 brouard 7323: /* 4eme */
1.201 brouard 7324: /* Survival functions (period) from state i in state j by initial state i */
1.238 brouard 7325: for (k1=1; k1<=m; k1++){ /* For each covariate and each value */
7326: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7327: if(m != 1 && TKresult[nres]!= k1)
1.223 brouard 7328: continue;
1.238 brouard 7329: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 7330: strcpy(gplotlabel,"(");
1.238 brouard 7331: fprintf(ficgp,"\n#\n#\n# Survival functions in state j : 'LIJ_' files, cov=%d state=%d",k1, cpt);
7332: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7333: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7334: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7335: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7336: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7337: vlv= nbcode[Tvaraff[k]][lv];
7338: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7339: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7340: }
7341: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7342: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7343: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7344: }
1.264 brouard 7345: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7346: fprintf(ficgp,"\n#\n");
7347: if(invalidvarcomb[k1]){
7348: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7349: continue;
1.223 brouard 7350: }
1.238 brouard 7351:
1.241 brouard 7352: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 7353: 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 7354: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7355: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7356: k=3;
7357: for (i=1; i<= nlstate ; i ++){
7358: if(i==1){
7359: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7360: }else{
7361: fprintf(ficgp,", '' ");
7362: }
7363: l=(nlstate+ndeath)*(i-1)+1;
7364: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7365: for (j=2; j<= nlstate+ndeath ; j ++)
7366: fprintf(ficgp,"+$%d",k+l+j-1);
7367: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
7368: } /* nlstate */
1.264 brouard 7369: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7370: } /* end cpt state*/
7371: } /* end nres */
7372: } /* end covariate k1 */
7373:
1.220 brouard 7374: /* 5eme */
1.201 brouard 7375: /* Survival functions (period) from state i in state j by final state j */
1.238 brouard 7376: for (k1=1; k1<= m ; k1++){ /* For each covariate combination if any */
7377: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7378: if(m != 1 && TKresult[nres]!= k1)
1.227 brouard 7379: continue;
1.238 brouard 7380: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 7381: strcpy(gplotlabel,"(");
1.238 brouard 7382: 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);
7383: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7384: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7385: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7386: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7387: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7388: vlv= nbcode[Tvaraff[k]][lv];
7389: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7390: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7391: }
7392: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7393: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7394: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7395: }
1.264 brouard 7396: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7397: fprintf(ficgp,"\n#\n");
7398: if(invalidvarcomb[k1]){
7399: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7400: continue;
7401: }
1.227 brouard 7402:
1.241 brouard 7403: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 7404: 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 7405: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7406: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7407: k=3;
7408: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7409: if(j==1)
7410: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7411: else
7412: fprintf(ficgp,", '' ");
7413: l=(nlstate+ndeath)*(cpt-1) +j;
7414: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
7415: /* for (i=2; i<= nlstate+ndeath ; i ++) */
7416: /* fprintf(ficgp,"+$%d",k+l+i-1); */
7417: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
7418: } /* nlstate */
7419: fprintf(ficgp,", '' ");
7420: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
7421: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7422: l=(nlstate+ndeath)*(cpt-1) +j;
7423: if(j < nlstate)
7424: fprintf(ficgp,"$%d +",k+l);
7425: else
7426: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
7427: }
1.264 brouard 7428: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7429: } /* end cpt state*/
7430: } /* end covariate */
7431: } /* end nres */
1.227 brouard 7432:
1.220 brouard 7433: /* 6eme */
1.202 brouard 7434: /* CV preval stable (period) for each covariate */
1.237 brouard 7435: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7436: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7437: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7438: continue;
1.255 brouard 7439: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 7440: strcpy(gplotlabel,"(");
1.211 brouard 7441: fprintf(ficgp,"\n#\n#\n#CV preval stable (period): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.225 brouard 7442: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.227 brouard 7443: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7444: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7445: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7446: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7447: vlv= nbcode[Tvaraff[k]][lv];
7448: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7449: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7450: }
1.237 brouard 7451: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7452: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7453: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7454: }
1.264 brouard 7455: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7456: fprintf(ficgp,"\n#\n");
1.223 brouard 7457: if(invalidvarcomb[k1]){
1.227 brouard 7458: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7459: continue;
1.223 brouard 7460: }
1.227 brouard 7461:
1.241 brouard 7462: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 7463: 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 7464: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7465: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 7466: k=3; /* Offset */
1.255 brouard 7467: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 7468: if(i==1)
7469: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7470: else
7471: fprintf(ficgp,", '' ");
1.255 brouard 7472: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7473: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7474: for (j=2; j<= nlstate ; j ++)
7475: fprintf(ficgp,"+$%d",k+l+j-1);
7476: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 7477: } /* nlstate */
1.264 brouard 7478: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 7479: } /* end cpt state*/
7480: } /* end covariate */
1.227 brouard 7481:
7482:
1.220 brouard 7483: /* 7eme */
1.218 brouard 7484: if(backcast == 1){
1.217 brouard 7485: /* CV back preval stable (period) for each covariate */
1.237 brouard 7486: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7487: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7488: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7489: continue;
1.268 brouard 7490: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 7491: strcpy(gplotlabel,"(");
7492: fprintf(ficgp,"\n#\n#\n#CV Back preval stable (period): 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 7493: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7494: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7495: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7496: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
1.223 brouard 7497: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.227 brouard 7498: vlv= nbcode[Tvaraff[k]][lv];
7499: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7500: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 7501: }
1.237 brouard 7502: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7503: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7504: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7505: }
1.264 brouard 7506: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 7507: fprintf(ficgp,"\n#\n");
7508: if(invalidvarcomb[k1]){
7509: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7510: continue;
7511: }
7512:
1.241 brouard 7513: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 7514: 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 7515: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7516: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 7517: k=3; /* Offset */
1.268 brouard 7518: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 7519: if(i==1)
7520: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
7521: else
7522: fprintf(ficgp,", '' ");
7523: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 7524: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7525: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
7526: /* 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 7527: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 7528: /* for (j=2; j<= nlstate ; j ++) */
7529: /* fprintf(ficgp,"+$%d",k+l+j-1); */
7530: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 7531: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 7532: } /* nlstate */
1.264 brouard 7533: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 7534: } /* end cpt state*/
7535: } /* end covariate */
7536: } /* End if backcast */
7537:
1.223 brouard 7538: /* 8eme */
1.218 brouard 7539: if(prevfcast==1){
7540: /* Projection from cross-sectional to stable (period) for each covariate */
7541:
1.237 brouard 7542: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7543: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7544: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7545: continue;
1.211 brouard 7546: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 7547: strcpy(gplotlabel,"(");
1.227 brouard 7548: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to stable (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
7549: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7550: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7551: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7552: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7553: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7554: vlv= nbcode[Tvaraff[k]][lv];
7555: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7556: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 7557: }
1.237 brouard 7558: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7559: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7560: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7561: }
1.264 brouard 7562: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 7563: fprintf(ficgp,"\n#\n");
7564: if(invalidvarcomb[k1]){
7565: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7566: continue;
7567: }
7568:
7569: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 7570: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 7571: 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 7572: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 7573: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 7574:
7575: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
7576: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
7577: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
7578: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 7579: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7580: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7581: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7582: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 7583: if(i==istart){
1.227 brouard 7584: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
7585: }else{
7586: fprintf(ficgp,",\\\n '' ");
7587: }
7588: if(cptcoveff ==0){ /* No covariate */
7589: ioffset=2; /* Age is in 2 */
7590: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7591: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7592: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7593: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7594: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 7595: if(i==nlstate+1){
1.270 brouard 7596: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 7597: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
7598: fprintf(ficgp,",\\\n '' ");
7599: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 7600: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 7601: offyear, \
1.268 brouard 7602: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 7603: }else
1.227 brouard 7604: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
7605: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
7606: }else{ /* more than 2 covariates */
1.270 brouard 7607: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
7608: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7609: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7610: iyearc=ioffset-1;
7611: iagec=ioffset;
1.227 brouard 7612: fprintf(ficgp," u %d:(",ioffset);
7613: kl=0;
7614: strcpy(gplotcondition,"(");
7615: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
7616: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
7617: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7618: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7619: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7620: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
7621: kl++;
7622: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
7623: kl++;
7624: if(k <cptcoveff && cptcoveff>1)
7625: sprintf(gplotcondition+strlen(gplotcondition)," && ");
7626: }
7627: strcpy(gplotcondition+strlen(gplotcondition),")");
7628: /* 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 *\/ */
7629: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7630: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7631: /* '' 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*/
7632: if(i==nlstate+1){
1.270 brouard 7633: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
7634: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 7635: fprintf(ficgp,",\\\n '' ");
1.270 brouard 7636: fprintf(ficgp," u %d:(",iagec);
7637: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
7638: iyearc, iagec, offyear, \
7639: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 7640: /* '' 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 7641: }else{
7642: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
7643: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
7644: }
7645: } /* end if covariate */
7646: } /* nlstate */
1.264 brouard 7647: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 7648: } /* end cpt state*/
7649: } /* end covariate */
7650: } /* End if prevfcast */
1.227 brouard 7651:
1.268 brouard 7652: if(backcast==1){
7653: /* Back projection from cross-sectional to stable (mixed) for each covariate */
7654:
7655: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7656: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
7657: if(m != 1 && TKresult[nres]!= k1)
7658: continue;
7659: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
7660: strcpy(gplotlabel,"(");
7661: fprintf(ficgp,"\n#\n#\n#Back projection of prevalence to stable (mixed) back prevalence: 'BPROJ_' files, covariatecombination#=%d originstate=%d",k1, cpt);
7662: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7663: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7664: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7665: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7666: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7667: vlv= nbcode[Tvaraff[k]][lv];
7668: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
7669: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
7670: }
7671: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7672: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7673: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7674: }
7675: strcpy(gplotlabel+strlen(gplotlabel),")");
7676: fprintf(ficgp,"\n#\n");
7677: if(invalidvarcomb[k1]){
7678: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7679: continue;
7680: }
7681:
7682: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
7683: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
7684: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
7685: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
7686: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7687:
7688: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
7689: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
7690: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
7691: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
7692: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7693: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7694: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7695: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7696: if(i==istart){
7697: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
7698: }else{
7699: fprintf(ficgp,",\\\n '' ");
7700: }
7701: if(cptcoveff ==0){ /* No covariate */
7702: ioffset=2; /* Age is in 2 */
7703: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7704: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7705: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7706: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7707: fprintf(ficgp," u %d:(", ioffset);
7708: if(i==nlstate+1){
1.270 brouard 7709: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 7710: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
7711: fprintf(ficgp,",\\\n '' ");
7712: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 7713: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 7714: offbyear, \
7715: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
7716: }else
7717: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
7718: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
7719: }else{ /* more than 2 covariates */
1.270 brouard 7720: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
7721: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7722: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7723: iyearc=ioffset-1;
7724: iagec=ioffset;
1.268 brouard 7725: fprintf(ficgp," u %d:(",ioffset);
7726: kl=0;
7727: strcpy(gplotcondition,"(");
7728: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
7729: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
7730: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7731: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7732: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7733: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
7734: kl++;
7735: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
7736: kl++;
7737: if(k <cptcoveff && cptcoveff>1)
7738: sprintf(gplotcondition+strlen(gplotcondition)," && ");
7739: }
7740: strcpy(gplotcondition+strlen(gplotcondition),")");
7741: /* 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 *\/ */
7742: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7743: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7744: /* '' 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*/
7745: if(i==nlstate+1){
1.270 brouard 7746: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
7747: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 7748: fprintf(ficgp,",\\\n '' ");
1.270 brouard 7749: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 7750: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 brouard 7751: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
7752: iyearc,iagec,offbyear, \
7753: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 7754: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
7755: }else{
7756: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
7757: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
7758: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
7759: }
7760: } /* end if covariate */
7761: } /* nlstate */
7762: fprintf(ficgp,"\nset out; unset label;\n");
7763: } /* end cpt state*/
7764: } /* end covariate */
7765: } /* End if backcast */
7766:
1.227 brouard 7767:
1.238 brouard 7768: /* 9eme writing MLE parameters */
7769: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 7770: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 7771: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 7772: for(k=1; k <=(nlstate+ndeath); k++){
7773: if (k != i) {
1.227 brouard 7774: fprintf(ficgp,"# current state %d\n",k);
7775: for(j=1; j <=ncovmodel; j++){
7776: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
7777: jk++;
7778: }
7779: fprintf(ficgp,"\n");
1.126 brouard 7780: }
7781: }
1.223 brouard 7782: }
1.187 brouard 7783: fprintf(ficgp,"##############\n#\n");
1.227 brouard 7784:
1.145 brouard 7785: /*goto avoid;*/
1.238 brouard 7786: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
7787: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 7788: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
7789: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
7790: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
7791: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
7792: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7793: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
7794: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7795: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
7796: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
7797: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7798: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
7799: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
7800: fprintf(ficgp,"#\n");
1.223 brouard 7801: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 7802: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.237 brouard 7803: fprintf(ficgp,"#model=%s \n",model);
1.238 brouard 7804: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.264 brouard 7805: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/* to be checked */
7806: for(k1=1; k1 <=m; k1++) /* For each combination of covariate */
1.237 brouard 7807: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.264 brouard 7808: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7809: continue;
1.264 brouard 7810: fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1);
7811: strcpy(gplotlabel,"(");
1.276 brouard 7812: /*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*/
1.264 brouard 7813: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7814: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7815: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7816: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7817: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7818: vlv= nbcode[Tvaraff[k]][lv];
7819: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
7820: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
7821: }
1.237 brouard 7822: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7823: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7824: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7825: }
1.264 brouard 7826: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 7827: fprintf(ficgp,"\n#\n");
1.264 brouard 7828: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
1.276 brouard 7829: fprintf(ficgp,"\nset key outside ");
7830: /* fprintf(ficgp,"\nset label \"%s\" at graph 1.2,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel); */
7831: fprintf(ficgp,"\nset title \"%s\" font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 7832: fprintf(ficgp,"\nset ter svg size 640, 480 ");
7833: if (ng==1){
7834: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
7835: fprintf(ficgp,"\nunset log y");
7836: }else if (ng==2){
7837: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
7838: fprintf(ficgp,"\nset log y");
7839: }else if (ng==3){
7840: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
7841: fprintf(ficgp,"\nset log y");
7842: }else
7843: fprintf(ficgp,"\nunset title ");
7844: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
7845: i=1;
7846: for(k2=1; k2<=nlstate; k2++) {
7847: k3=i;
7848: for(k=1; k<=(nlstate+ndeath); k++) {
7849: if (k != k2){
7850: switch( ng) {
7851: case 1:
7852: if(nagesqr==0)
7853: fprintf(ficgp," p%d+p%d*x",i,i+1);
7854: else /* nagesqr =1 */
7855: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
7856: break;
7857: case 2: /* ng=2 */
7858: if(nagesqr==0)
7859: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
7860: else /* nagesqr =1 */
7861: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
7862: break;
7863: case 3:
7864: if(nagesqr==0)
7865: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
7866: else /* nagesqr =1 */
7867: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
7868: break;
7869: }
7870: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 7871: ijp=1; /* product no age */
7872: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
7873: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 7874: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.268 brouard 7875: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
7876: if(j==Tage[ij]) { /* Product by age To be looked at!!*/
7877: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
7878: if(DummyV[j]==0){
7879: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
7880: }else{ /* quantitative */
7881: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
7882: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
7883: }
7884: ij++;
1.237 brouard 7885: }
1.268 brouard 7886: }
7887: }else if(cptcovprod >0){
7888: if(j==Tprod[ijp]) { /* */
7889: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
7890: if(ijp <=cptcovprod) { /* Product */
7891: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
7892: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
7893: /* 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)]); */
7894: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
7895: }else{ /* Vn is dummy and Vm is quanti */
7896: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
7897: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
7898: }
7899: }else{ /* Vn*Vm Vn is quanti */
7900: if(DummyV[Tvard[ijp][2]]==0){
7901: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
7902: }else{ /* Both quanti */
7903: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
7904: }
1.237 brouard 7905: }
1.268 brouard 7906: ijp++;
1.237 brouard 7907: }
1.268 brouard 7908: } /* end Tprod */
1.237 brouard 7909: } else{ /* simple covariate */
1.264 brouard 7910: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 7911: if(Dummy[j]==0){
7912: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
7913: }else{ /* quantitative */
7914: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 7915: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 7916: }
1.237 brouard 7917: } /* end simple */
7918: } /* end j */
1.223 brouard 7919: }else{
7920: i=i-ncovmodel;
7921: if(ng !=1 ) /* For logit formula of log p11 is more difficult to get */
7922: fprintf(ficgp," (1.");
7923: }
1.227 brouard 7924:
1.223 brouard 7925: if(ng != 1){
7926: fprintf(ficgp,")/(1");
1.227 brouard 7927:
1.264 brouard 7928: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 7929: if(nagesqr==0)
1.264 brouard 7930: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 7931: else /* nagesqr =1 */
1.264 brouard 7932: 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 7933:
1.223 brouard 7934: ij=1;
7935: for(j=3; j <=ncovmodel-nagesqr; j++){
1.268 brouard 7936: if(cptcovage >0){
7937: if((j-2)==Tage[ij]) { /* Bug valgrind */
7938: if(ij <=cptcovage) { /* Bug valgrind */
7939: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);
7940: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
7941: ij++;
7942: }
7943: }
7944: }else
7945: 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 7946: }
7947: fprintf(ficgp,")");
7948: }
7949: fprintf(ficgp,")");
7950: if(ng ==2)
1.276 brouard 7951: 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 7952: else /* ng= 3 */
1.276 brouard 7953: 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 7954: }else{ /* end ng <> 1 */
7955: if( k !=k2) /* logit p11 is hard to draw */
1.276 brouard 7956: 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 7957: }
7958: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
7959: fprintf(ficgp,",");
7960: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
7961: fprintf(ficgp,",");
7962: i=i+ncovmodel;
7963: } /* end k */
7964: } /* end k2 */
1.276 brouard 7965: /* fprintf(ficgp,"\n set out; unset label;set key default;\n"); */
7966: fprintf(ficgp,"\n set out; unset title;set key default;\n");
1.264 brouard 7967: } /* end k1 */
1.223 brouard 7968: } /* end ng */
7969: /* avoid: */
7970: fflush(ficgp);
1.126 brouard 7971: } /* end gnuplot */
7972:
7973:
7974: /*************** Moving average **************/
1.219 brouard 7975: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 7976: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 7977:
1.222 brouard 7978: int i, cpt, cptcod;
7979: int modcovmax =1;
7980: int mobilavrange, mob;
7981: int iage=0;
7982:
1.266 brouard 7983: double sum=0., sumr=0.;
1.222 brouard 7984: double age;
1.266 brouard 7985: double *sumnewp, *sumnewm, *sumnewmr;
7986: double *agemingood, *agemaxgood;
7987: double *agemingoodr, *agemaxgoodr;
1.222 brouard 7988:
7989:
1.278 brouard 7990: /* modcovmax=2*cptcoveff; Max number of modalities. We suppose */
7991: /* a covariate has 2 modalities, should be equal to ncovcombmax */
1.222 brouard 7992:
7993: sumnewp = vector(1,ncovcombmax);
7994: sumnewm = vector(1,ncovcombmax);
1.266 brouard 7995: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 7996: agemingood = vector(1,ncovcombmax);
1.266 brouard 7997: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 7998: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 7999: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 8000:
8001: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 8002: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 8003: sumnewp[cptcod]=0.;
1.266 brouard 8004: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
8005: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 8006: }
8007: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
8008:
1.266 brouard 8009: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
8010: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 8011: else mobilavrange=mobilav;
8012: for (age=bage; age<=fage; age++)
8013: for (i=1; i<=nlstate;i++)
8014: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
8015: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8016: /* We keep the original values on the extreme ages bage, fage and for
8017: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
8018: we use a 5 terms etc. until the borders are no more concerned.
8019: */
8020: for (mob=3;mob <=mobilavrange;mob=mob+2){
8021: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 8022: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
8023: sumnewm[cptcod]=0.;
8024: for (i=1; i<=nlstate;i++){
1.222 brouard 8025: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
8026: for (cpt=1;cpt<=(mob-1)/2;cpt++){
8027: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
8028: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
8029: }
8030: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 8031: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8032: } /* end i */
8033: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
8034: } /* end cptcod */
1.222 brouard 8035: }/* end age */
8036: }/* end mob */
1.266 brouard 8037: }else{
8038: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 8039: return -1;
1.266 brouard 8040: }
8041:
8042: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 8043: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
8044: if(invalidvarcomb[cptcod]){
8045: printf("\nCombination (%d) ignored because no cases \n",cptcod);
8046: continue;
8047: }
1.219 brouard 8048:
1.266 brouard 8049: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
8050: sumnewm[cptcod]=0.;
8051: sumnewmr[cptcod]=0.;
8052: for (i=1; i<=nlstate;i++){
8053: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8054: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8055: }
8056: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8057: agemingoodr[cptcod]=age;
8058: }
8059: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8060: agemingood[cptcod]=age;
8061: }
8062: } /* age */
8063: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 8064: sumnewm[cptcod]=0.;
1.266 brouard 8065: sumnewmr[cptcod]=0.;
1.222 brouard 8066: for (i=1; i<=nlstate;i++){
8067: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8068: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8069: }
8070: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8071: agemaxgoodr[cptcod]=age;
1.222 brouard 8072: }
8073: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 8074: agemaxgood[cptcod]=age;
8075: }
8076: } /* age */
8077: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
8078: /* but they will change */
8079: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
8080: sumnewm[cptcod]=0.;
8081: sumnewmr[cptcod]=0.;
8082: for (i=1; i<=nlstate;i++){
8083: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8084: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8085: }
8086: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8087: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8088: agemaxgoodr[cptcod]=age; /* age min */
8089: for (i=1; i<=nlstate;i++)
8090: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8091: }else{ /* bad we change the value with the values of good ages */
8092: for (i=1; i<=nlstate;i++){
8093: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
8094: } /* i */
8095: } /* end bad */
8096: }else{
8097: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8098: agemaxgood[cptcod]=age;
8099: }else{ /* bad we change the value with the values of good ages */
8100: for (i=1; i<=nlstate;i++){
8101: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
8102: } /* i */
8103: } /* end bad */
8104: }/* end else */
8105: sum=0.;sumr=0.;
8106: for (i=1; i<=nlstate;i++){
8107: sum+=mobaverage[(int)age][i][cptcod];
8108: sumr+=probs[(int)age][i][cptcod];
8109: }
8110: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 8111: 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 8112: } /* end bad */
8113: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8114: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 8115: 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 8116: } /* end bad */
8117: }/* age */
1.266 brouard 8118:
8119: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 8120: sumnewm[cptcod]=0.;
1.266 brouard 8121: sumnewmr[cptcod]=0.;
1.222 brouard 8122: for (i=1; i<=nlstate;i++){
8123: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8124: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8125: }
8126: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8127: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
8128: agemingoodr[cptcod]=age;
8129: for (i=1; i<=nlstate;i++)
8130: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8131: }else{ /* bad we change the value with the values of good ages */
8132: for (i=1; i<=nlstate;i++){
8133: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
8134: } /* i */
8135: } /* end bad */
8136: }else{
8137: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8138: agemingood[cptcod]=age;
8139: }else{ /* bad */
8140: for (i=1; i<=nlstate;i++){
8141: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
8142: } /* i */
8143: } /* end bad */
8144: }/* end else */
8145: sum=0.;sumr=0.;
8146: for (i=1; i<=nlstate;i++){
8147: sum+=mobaverage[(int)age][i][cptcod];
8148: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 8149: }
1.266 brouard 8150: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 8151: 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 8152: } /* end bad */
8153: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8154: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 8155: 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 8156: } /* end bad */
8157: }/* age */
1.266 brouard 8158:
1.222 brouard 8159:
8160: for (age=bage; age<=fage; age++){
1.235 brouard 8161: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 8162: sumnewp[cptcod]=0.;
8163: sumnewm[cptcod]=0.;
8164: for (i=1; i<=nlstate;i++){
8165: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
8166: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8167: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
8168: }
8169: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
8170: }
8171: /* printf("\n"); */
8172: /* } */
1.266 brouard 8173:
1.222 brouard 8174: /* brutal averaging */
1.266 brouard 8175: /* for (i=1; i<=nlstate;i++){ */
8176: /* for (age=1; age<=bage; age++){ */
8177: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
8178: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8179: /* } */
8180: /* for (age=fage; age<=AGESUP; age++){ */
8181: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
8182: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8183: /* } */
8184: /* } /\* end i status *\/ */
8185: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
8186: /* for (age=1; age<=AGESUP; age++){ */
8187: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
8188: /* mobaverage[(int)age][i][cptcod]=0.; */
8189: /* } */
8190: /* } */
1.222 brouard 8191: }/* end cptcod */
1.266 brouard 8192: free_vector(agemaxgoodr,1, ncovcombmax);
8193: free_vector(agemaxgood,1, ncovcombmax);
8194: free_vector(agemingood,1, ncovcombmax);
8195: free_vector(agemingoodr,1, ncovcombmax);
8196: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 8197: free_vector(sumnewm,1, ncovcombmax);
8198: free_vector(sumnewp,1, ncovcombmax);
8199: return 0;
8200: }/* End movingaverage */
1.218 brouard 8201:
1.126 brouard 8202:
8203: /************** Forecasting ******************/
1.269 brouard 8204: 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 8205: /* proj1, year, month, day of starting projection
8206: agemin, agemax range of age
8207: dateprev1 dateprev2 range of dates during which prevalence is computed
8208: anproj2 year of en of projection (same day and month as proj1).
8209: */
1.267 brouard 8210: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 8211: double agec; /* generic age */
8212: double agelim, ppij, yp,yp1,yp2,jprojmean,mprojmean,anprojmean;
8213: double *popeffectif,*popcount;
8214: double ***p3mat;
1.218 brouard 8215: /* double ***mobaverage; */
1.126 brouard 8216: char fileresf[FILENAMELENGTH];
8217:
8218: agelim=AGESUP;
1.211 brouard 8219: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8220: in each health status at the date of interview (if between dateprev1 and dateprev2).
8221: We still use firstpass and lastpass as another selection.
8222: */
1.214 brouard 8223: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8224: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 8225:
1.201 brouard 8226: strcpy(fileresf,"F_");
8227: strcat(fileresf,fileresu);
1.126 brouard 8228: if((ficresf=fopen(fileresf,"w"))==NULL) {
8229: printf("Problem with forecast resultfile: %s\n", fileresf);
8230: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
8231: }
1.235 brouard 8232: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
8233: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 8234:
1.225 brouard 8235: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 8236:
8237:
8238: stepsize=(int) (stepm+YEARM-1)/YEARM;
8239: if (stepm<=12) stepsize=1;
8240: if(estepm < stepm){
8241: printf ("Problem %d lower than %d\n",estepm, stepm);
8242: }
1.270 brouard 8243: else{
8244: hstepm=estepm;
8245: }
8246: if(estepm > stepm){ /* Yes every two year */
8247: stepsize=2;
8248: }
1.126 brouard 8249:
8250: hstepm=hstepm/stepm;
8251: yp1=modf(dateintmean,&yp);/* extracts integral of datemean in yp and
8252: fractional in yp1 */
8253: anprojmean=yp;
8254: yp2=modf((yp1*12),&yp);
8255: mprojmean=yp;
8256: yp1=modf((yp2*30.5),&yp);
8257: jprojmean=yp;
8258: if(jprojmean==0) jprojmean=1;
8259: if(mprojmean==0) jprojmean=1;
8260:
1.227 brouard 8261: i1=pow(2,cptcoveff);
1.126 brouard 8262: if (cptcovn < 1){i1=1;}
8263:
8264: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
8265:
8266: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 8267:
1.126 brouard 8268: /* if (h==(int)(YEARM*yearp)){ */
1.235 brouard 8269: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8270: for(k=1; k<=i1;k++){
1.253 brouard 8271: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 8272: continue;
1.227 brouard 8273: if(invalidvarcomb[k]){
8274: printf("\nCombination (%d) projection ignored because no cases \n",k);
8275: continue;
8276: }
8277: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
8278: for(j=1;j<=cptcoveff;j++) {
8279: fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8280: }
1.235 brouard 8281: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 8282: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.235 brouard 8283: }
1.227 brouard 8284: fprintf(ficresf," yearproj age");
8285: for(j=1; j<=nlstate+ndeath;j++){
8286: for(i=1; i<=nlstate;i++)
8287: fprintf(ficresf," p%d%d",i,j);
8288: fprintf(ficresf," wp.%d",j);
8289: }
8290: for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) {
8291: fprintf(ficresf,"\n");
8292: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jproj1,mproj1,anproj1+yearp);
1.270 brouard 8293: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
8294: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 8295: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
8296: nhstepm = nhstepm/hstepm;
8297: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8298: oldm=oldms;savm=savms;
1.268 brouard 8299: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 8300: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 8301: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 8302: for (h=0; h<=nhstepm; h++){
8303: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 8304: break;
8305: }
8306: }
8307: fprintf(ficresf,"\n");
8308: for(j=1;j<=cptcoveff;j++)
8309: fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8310: fprintf(ficresf,"%.f %.f ",anproj1+yearp,agec+h*hstepm/YEARM*stepm);
8311:
8312: for(j=1; j<=nlstate+ndeath;j++) {
8313: ppij=0.;
8314: for(i=1; i<=nlstate;i++) {
1.278 brouard 8315: if (mobilav>=1)
8316: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
8317: else { /* even if mobilav==-1 we use mobaverage, probs may not sums to 1 */
8318: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
8319: }
1.268 brouard 8320: fprintf(ficresf," %.3f", p3mat[i][j][h]);
8321: } /* end i */
8322: fprintf(ficresf," %.3f", ppij);
8323: }/* end j */
1.227 brouard 8324: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8325: } /* end agec */
1.266 brouard 8326: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
8327: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 8328: } /* end yearp */
8329: } /* end k */
1.219 brouard 8330:
1.126 brouard 8331: fclose(ficresf);
1.215 brouard 8332: printf("End of Computing forecasting \n");
8333: fprintf(ficlog,"End of Computing forecasting\n");
8334:
1.126 brouard 8335: }
8336:
1.269 brouard 8337: /************** Back Forecasting ******************/
8338: 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 8339: /* back1, year, month, day of starting backection
8340: agemin, agemax range of age
8341: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 8342: anback2 year of end of backprojection (same day and month as back1).
8343: prevacurrent and prev are prevalences.
1.267 brouard 8344: */
8345: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
8346: double agec; /* generic age */
1.268 brouard 8347: double agelim, ppij, ppi, yp,yp1,yp2,jprojmean,mprojmean,anprojmean;
1.267 brouard 8348: double *popeffectif,*popcount;
8349: double ***p3mat;
8350: /* double ***mobaverage; */
8351: char fileresfb[FILENAMELENGTH];
8352:
1.268 brouard 8353: agelim=AGEINF;
1.267 brouard 8354: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8355: in each health status at the date of interview (if between dateprev1 and dateprev2).
8356: We still use firstpass and lastpass as another selection.
8357: */
8358: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8359: /* firstpass, lastpass, stepm, weightopt, model); */
8360:
8361: /*Do we need to compute prevalence again?*/
8362:
8363: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
8364:
8365: strcpy(fileresfb,"FB_");
8366: strcat(fileresfb,fileresu);
8367: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
8368: printf("Problem with back forecast resultfile: %s\n", fileresfb);
8369: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
8370: }
8371: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8372: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8373:
8374: if (cptcoveff==0) ncodemax[cptcoveff]=1;
8375:
8376:
8377: stepsize=(int) (stepm+YEARM-1)/YEARM;
8378: if (stepm<=12) stepsize=1;
8379: if(estepm < stepm){
8380: printf ("Problem %d lower than %d\n",estepm, stepm);
8381: }
1.270 brouard 8382: else{
8383: hstepm=estepm;
8384: }
8385: if(estepm >= stepm){ /* Yes every two year */
8386: stepsize=2;
8387: }
1.267 brouard 8388:
8389: hstepm=hstepm/stepm;
8390: yp1=modf(dateintmean,&yp);/* extracts integral of datemean in yp and
8391: fractional in yp1 */
8392: anprojmean=yp;
8393: yp2=modf((yp1*12),&yp);
8394: mprojmean=yp;
8395: yp1=modf((yp2*30.5),&yp);
8396: jprojmean=yp;
8397: if(jprojmean==0) jprojmean=1;
8398: if(mprojmean==0) jprojmean=1;
8399:
8400: i1=pow(2,cptcoveff);
8401: if (cptcovn < 1){i1=1;}
8402:
8403: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
1.268 brouard 8404: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 8405:
8406: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
8407:
8408: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8409: for(k=1; k<=i1;k++){
8410: if(i1 != 1 && TKresult[nres]!= k)
8411: continue;
8412: if(invalidvarcomb[k]){
8413: printf("\nCombination (%d) projection ignored because no cases \n",k);
8414: continue;
8415: }
1.268 brouard 8416: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.267 brouard 8417: for(j=1;j<=cptcoveff;j++) {
8418: fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8419: }
8420: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8421: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
8422: }
8423: fprintf(ficresfb," yearbproj age");
8424: for(j=1; j<=nlstate+ndeath;j++){
8425: for(i=1; i<=nlstate;i++)
1.268 brouard 8426: fprintf(ficresfb," b%d%d",i,j);
8427: fprintf(ficresfb," b.%d",j);
1.267 brouard 8428: }
8429: for (yearp=0; yearp>=(anback2-anback1);yearp -=stepsize) {
8430: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
8431: fprintf(ficresfb,"\n");
8432: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp);
1.273 brouard 8433: /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
1.270 brouard 8434: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
8435: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 8436: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
1.271 brouard 8437: nhstepm=(int) (agec-agelim) *YEARM/stepm;/* nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
1.267 brouard 8438: nhstepm = nhstepm/hstepm;
8439: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8440: oldm=oldms;savm=savms;
1.268 brouard 8441: /* computes hbxij at age agec over 1 to nhstepm */
1.271 brouard 8442: /* printf("####prevbackforecast debug agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
1.267 brouard 8443: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 8444: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
8445: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
8446: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 8447: for (h=0; h<=nhstepm; h++){
1.268 brouard 8448: if (h*hstepm/YEARM*stepm ==-yearp) {
8449: break;
8450: }
8451: }
8452: fprintf(ficresfb,"\n");
8453: for(j=1;j<=cptcoveff;j++)
8454: fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8455: fprintf(ficresfb,"%.f %.f ",anback1+yearp,agec-h*hstepm/YEARM*stepm);
8456: for(i=1; i<=nlstate+ndeath;i++) {
8457: ppij=0.;ppi=0.;
8458: for(j=1; j<=nlstate;j++) {
8459: /* if (mobilav==1) */
1.269 brouard 8460: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
8461: ppi=ppi+prevacurrent[(int)agec][j][k];
8462: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
8463: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 8464: /* else { */
8465: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
8466: /* } */
1.268 brouard 8467: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
8468: } /* end j */
8469: if(ppi <0.99){
8470: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
8471: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
8472: }
8473: fprintf(ficresfb," %.3f", ppij);
8474: }/* end j */
1.267 brouard 8475: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8476: } /* end agec */
8477: } /* end yearp */
8478: } /* end k */
1.217 brouard 8479:
1.267 brouard 8480: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 8481:
1.267 brouard 8482: fclose(ficresfb);
8483: printf("End of Computing Back forecasting \n");
8484: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 8485:
1.267 brouard 8486: }
1.217 brouard 8487:
1.269 brouard 8488: /* Variance of prevalence limit: varprlim */
8489: 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){
8490: /*------- Variance of period (stable) prevalence------*/
8491:
8492: char fileresvpl[FILENAMELENGTH];
8493: FILE *ficresvpl;
8494: double **oldm, **savm;
8495: double **varpl; /* Variances of prevalence limits by age */
8496: int i1, k, nres, j ;
8497:
8498: strcpy(fileresvpl,"VPL_");
8499: strcat(fileresvpl,fileresu);
8500: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
8501: printf("Problem with variance of period (stable) prevalence resultfile: %s\n", fileresvpl);
8502: exit(0);
8503: }
8504: printf("Computing Variance-covariance of period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
8505: fprintf(ficlog, "Computing Variance-covariance of period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
8506:
8507: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
8508: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
8509:
8510: i1=pow(2,cptcoveff);
8511: if (cptcovn < 1){i1=1;}
8512:
8513: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8514: for(k=1; k<=i1;k++){
8515: if(i1 != 1 && TKresult[nres]!= k)
8516: continue;
8517: fprintf(ficresvpl,"\n#****** ");
8518: printf("\n#****** ");
8519: fprintf(ficlog,"\n#****** ");
8520: for(j=1;j<=cptcoveff;j++) {
8521: fprintf(ficresvpl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8522: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8523: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8524: }
8525: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
8526: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8527: fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8528: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8529: }
8530: fprintf(ficresvpl,"******\n");
8531: printf("******\n");
8532: fprintf(ficlog,"******\n");
8533:
8534: varpl=matrix(1,nlstate,(int) bage, (int) fage);
8535: oldm=oldms;savm=savms;
8536: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
8537: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
8538: /*}*/
8539: }
8540:
8541: fclose(ficresvpl);
8542: printf("done variance-covariance of period prevalence\n");fflush(stdout);
8543: fprintf(ficlog,"done variance-covariance of period prevalence\n");fflush(ficlog);
8544:
8545: }
8546: /* Variance of back prevalence: varbprlim */
8547: 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){
8548: /*------- Variance of back (stable) prevalence------*/
8549:
8550: char fileresvbl[FILENAMELENGTH];
8551: FILE *ficresvbl;
8552:
8553: double **oldm, **savm;
8554: double **varbpl; /* Variances of back prevalence limits by age */
8555: int i1, k, nres, j ;
8556:
8557: strcpy(fileresvbl,"VBL_");
8558: strcat(fileresvbl,fileresu);
8559: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
8560: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
8561: exit(0);
8562: }
8563: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
8564: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
8565:
8566:
8567: i1=pow(2,cptcoveff);
8568: if (cptcovn < 1){i1=1;}
8569:
8570: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8571: for(k=1; k<=i1;k++){
8572: if(i1 != 1 && TKresult[nres]!= k)
8573: continue;
8574: fprintf(ficresvbl,"\n#****** ");
8575: printf("\n#****** ");
8576: fprintf(ficlog,"\n#****** ");
8577: for(j=1;j<=cptcoveff;j++) {
8578: fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8579: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8580: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8581: }
8582: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
8583: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8584: fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8585: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8586: }
8587: fprintf(ficresvbl,"******\n");
8588: printf("******\n");
8589: fprintf(ficlog,"******\n");
8590:
8591: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
8592: oldm=oldms;savm=savms;
8593:
8594: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
8595: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
8596: /*}*/
8597: }
8598:
8599: fclose(ficresvbl);
8600: printf("done variance-covariance of back prevalence\n");fflush(stdout);
8601: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
8602:
8603: } /* End of varbprlim */
8604:
1.126 brouard 8605: /************** Forecasting *****not tested NB*************/
1.227 brouard 8606: /* 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 8607:
1.227 brouard 8608: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
8609: /* int *popage; */
8610: /* double calagedatem, agelim, kk1, kk2; */
8611: /* double *popeffectif,*popcount; */
8612: /* double ***p3mat,***tabpop,***tabpopprev; */
8613: /* /\* double ***mobaverage; *\/ */
8614: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 8615:
1.227 brouard 8616: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8617: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8618: /* agelim=AGESUP; */
8619: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 8620:
1.227 brouard 8621: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 8622:
8623:
1.227 brouard 8624: /* strcpy(filerespop,"POP_"); */
8625: /* strcat(filerespop,fileresu); */
8626: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
8627: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
8628: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
8629: /* } */
8630: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
8631: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 8632:
1.227 brouard 8633: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 8634:
1.227 brouard 8635: /* /\* if (mobilav!=0) { *\/ */
8636: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
8637: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
8638: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
8639: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
8640: /* /\* } *\/ */
8641: /* /\* } *\/ */
1.126 brouard 8642:
1.227 brouard 8643: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
8644: /* if (stepm<=12) stepsize=1; */
1.126 brouard 8645:
1.227 brouard 8646: /* agelim=AGESUP; */
1.126 brouard 8647:
1.227 brouard 8648: /* hstepm=1; */
8649: /* hstepm=hstepm/stepm; */
1.218 brouard 8650:
1.227 brouard 8651: /* if (popforecast==1) { */
8652: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
8653: /* printf("Problem with population file : %s\n",popfile);exit(0); */
8654: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
8655: /* } */
8656: /* popage=ivector(0,AGESUP); */
8657: /* popeffectif=vector(0,AGESUP); */
8658: /* popcount=vector(0,AGESUP); */
1.126 brouard 8659:
1.227 brouard 8660: /* i=1; */
8661: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 8662:
1.227 brouard 8663: /* imx=i; */
8664: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
8665: /* } */
1.218 brouard 8666:
1.227 brouard 8667: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
8668: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
8669: /* k=k+1; */
8670: /* fprintf(ficrespop,"\n#******"); */
8671: /* for(j=1;j<=cptcoveff;j++) { */
8672: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
8673: /* } */
8674: /* fprintf(ficrespop,"******\n"); */
8675: /* fprintf(ficrespop,"# Age"); */
8676: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
8677: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 8678:
1.227 brouard 8679: /* for (cpt=0; cpt<=0;cpt++) { */
8680: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 8681:
1.227 brouard 8682: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
8683: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
8684: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 8685:
1.227 brouard 8686: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8687: /* oldm=oldms;savm=savms; */
8688: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 8689:
1.227 brouard 8690: /* for (h=0; h<=nhstepm; h++){ */
8691: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
8692: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
8693: /* } */
8694: /* for(j=1; j<=nlstate+ndeath;j++) { */
8695: /* kk1=0.;kk2=0; */
8696: /* for(i=1; i<=nlstate;i++) { */
8697: /* if (mobilav==1) */
8698: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
8699: /* else { */
8700: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
8701: /* } */
8702: /* } */
8703: /* if (h==(int)(calagedatem+12*cpt)){ */
8704: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
8705: /* /\*fprintf(ficrespop," %.3f", kk1); */
8706: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
8707: /* } */
8708: /* } */
8709: /* for(i=1; i<=nlstate;i++){ */
8710: /* kk1=0.; */
8711: /* for(j=1; j<=nlstate;j++){ */
8712: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
8713: /* } */
8714: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
8715: /* } */
1.218 brouard 8716:
1.227 brouard 8717: /* if (h==(int)(calagedatem+12*cpt)) */
8718: /* for(j=1; j<=nlstate;j++) */
8719: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
8720: /* } */
8721: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8722: /* } */
8723: /* } */
1.218 brouard 8724:
1.227 brouard 8725: /* /\******\/ */
1.218 brouard 8726:
1.227 brouard 8727: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
8728: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
8729: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
8730: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
8731: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 8732:
1.227 brouard 8733: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8734: /* oldm=oldms;savm=savms; */
8735: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
8736: /* for (h=0; h<=nhstepm; h++){ */
8737: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
8738: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
8739: /* } */
8740: /* for(j=1; j<=nlstate+ndeath;j++) { */
8741: /* kk1=0.;kk2=0; */
8742: /* for(i=1; i<=nlstate;i++) { */
8743: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
8744: /* } */
8745: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
8746: /* } */
8747: /* } */
8748: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8749: /* } */
8750: /* } */
8751: /* } */
8752: /* } */
1.218 brouard 8753:
1.227 brouard 8754: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 8755:
1.227 brouard 8756: /* if (popforecast==1) { */
8757: /* free_ivector(popage,0,AGESUP); */
8758: /* free_vector(popeffectif,0,AGESUP); */
8759: /* free_vector(popcount,0,AGESUP); */
8760: /* } */
8761: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8762: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8763: /* fclose(ficrespop); */
8764: /* } /\* End of popforecast *\/ */
1.218 brouard 8765:
1.126 brouard 8766: int fileappend(FILE *fichier, char *optionfich)
8767: {
8768: if((fichier=fopen(optionfich,"a"))==NULL) {
8769: printf("Problem with file: %s\n", optionfich);
8770: fprintf(ficlog,"Problem with file: %s\n", optionfich);
8771: return (0);
8772: }
8773: fflush(fichier);
8774: return (1);
8775: }
8776:
8777:
8778: /**************** function prwizard **********************/
8779: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
8780: {
8781:
8782: /* Wizard to print covariance matrix template */
8783:
1.164 brouard 8784: char ca[32], cb[32];
8785: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 8786: int numlinepar;
8787:
8788: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
8789: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
8790: for(i=1; i <=nlstate; i++){
8791: jj=0;
8792: for(j=1; j <=nlstate+ndeath; j++){
8793: if(j==i) continue;
8794: jj++;
8795: /*ca[0]= k+'a'-1;ca[1]='\0';*/
8796: printf("%1d%1d",i,j);
8797: fprintf(ficparo,"%1d%1d",i,j);
8798: for(k=1; k<=ncovmodel;k++){
8799: /* printf(" %lf",param[i][j][k]); */
8800: /* fprintf(ficparo," %lf",param[i][j][k]); */
8801: printf(" 0.");
8802: fprintf(ficparo," 0.");
8803: }
8804: printf("\n");
8805: fprintf(ficparo,"\n");
8806: }
8807: }
8808: printf("# Scales (for hessian or gradient estimation)\n");
8809: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
8810: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
8811: for(i=1; i <=nlstate; i++){
8812: jj=0;
8813: for(j=1; j <=nlstate+ndeath; j++){
8814: if(j==i) continue;
8815: jj++;
8816: fprintf(ficparo,"%1d%1d",i,j);
8817: printf("%1d%1d",i,j);
8818: fflush(stdout);
8819: for(k=1; k<=ncovmodel;k++){
8820: /* printf(" %le",delti3[i][j][k]); */
8821: /* fprintf(ficparo," %le",delti3[i][j][k]); */
8822: printf(" 0.");
8823: fprintf(ficparo," 0.");
8824: }
8825: numlinepar++;
8826: printf("\n");
8827: fprintf(ficparo,"\n");
8828: }
8829: }
8830: printf("# Covariance matrix\n");
8831: /* # 121 Var(a12)\n\ */
8832: /* # 122 Cov(b12,a12) Var(b12)\n\ */
8833: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
8834: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
8835: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
8836: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
8837: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
8838: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
8839: fflush(stdout);
8840: fprintf(ficparo,"# Covariance matrix\n");
8841: /* # 121 Var(a12)\n\ */
8842: /* # 122 Cov(b12,a12) Var(b12)\n\ */
8843: /* # ...\n\ */
8844: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
8845:
8846: for(itimes=1;itimes<=2;itimes++){
8847: jj=0;
8848: for(i=1; i <=nlstate; i++){
8849: for(j=1; j <=nlstate+ndeath; j++){
8850: if(j==i) continue;
8851: for(k=1; k<=ncovmodel;k++){
8852: jj++;
8853: ca[0]= k+'a'-1;ca[1]='\0';
8854: if(itimes==1){
8855: printf("#%1d%1d%d",i,j,k);
8856: fprintf(ficparo,"#%1d%1d%d",i,j,k);
8857: }else{
8858: printf("%1d%1d%d",i,j,k);
8859: fprintf(ficparo,"%1d%1d%d",i,j,k);
8860: /* printf(" %.5le",matcov[i][j]); */
8861: }
8862: ll=0;
8863: for(li=1;li <=nlstate; li++){
8864: for(lj=1;lj <=nlstate+ndeath; lj++){
8865: if(lj==li) continue;
8866: for(lk=1;lk<=ncovmodel;lk++){
8867: ll++;
8868: if(ll<=jj){
8869: cb[0]= lk +'a'-1;cb[1]='\0';
8870: if(ll<jj){
8871: if(itimes==1){
8872: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
8873: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
8874: }else{
8875: printf(" 0.");
8876: fprintf(ficparo," 0.");
8877: }
8878: }else{
8879: if(itimes==1){
8880: printf(" Var(%s%1d%1d)",ca,i,j);
8881: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
8882: }else{
8883: printf(" 0.");
8884: fprintf(ficparo," 0.");
8885: }
8886: }
8887: }
8888: } /* end lk */
8889: } /* end lj */
8890: } /* end li */
8891: printf("\n");
8892: fprintf(ficparo,"\n");
8893: numlinepar++;
8894: } /* end k*/
8895: } /*end j */
8896: } /* end i */
8897: } /* end itimes */
8898:
8899: } /* end of prwizard */
8900: /******************* Gompertz Likelihood ******************************/
8901: double gompertz(double x[])
8902: {
8903: double A,B,L=0.0,sump=0.,num=0.;
8904: int i,n=0; /* n is the size of the sample */
8905:
1.220 brouard 8906: for (i=1;i<=imx ; i++) {
1.126 brouard 8907: sump=sump+weight[i];
8908: /* sump=sump+1;*/
8909: num=num+1;
8910: }
8911:
8912:
8913: /* for (i=0; i<=imx; i++)
8914: 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]);*/
8915:
8916: for (i=1;i<=imx ; i++)
8917: {
8918: if (cens[i] == 1 && wav[i]>1)
8919: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
8920:
8921: if (cens[i] == 0 && wav[i]>1)
8922: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
8923: +log(x[1]/YEARM)+x[2]*(agedc[i]-agegomp)+log(YEARM);
8924:
8925: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
8926: if (wav[i] > 1 ) { /* ??? */
8927: L=L+A*weight[i];
8928: /* 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]);*/
8929: }
8930: }
8931:
8932: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
8933:
8934: return -2*L*num/sump;
8935: }
8936:
1.136 brouard 8937: #ifdef GSL
8938: /******************* Gompertz_f Likelihood ******************************/
8939: double gompertz_f(const gsl_vector *v, void *params)
8940: {
8941: double A,B,LL=0.0,sump=0.,num=0.;
8942: double *x= (double *) v->data;
8943: int i,n=0; /* n is the size of the sample */
8944:
8945: for (i=0;i<=imx-1 ; i++) {
8946: sump=sump+weight[i];
8947: /* sump=sump+1;*/
8948: num=num+1;
8949: }
8950:
8951:
8952: /* for (i=0; i<=imx; i++)
8953: 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]);*/
8954: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
8955: for (i=1;i<=imx ; i++)
8956: {
8957: if (cens[i] == 1 && wav[i]>1)
8958: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
8959:
8960: if (cens[i] == 0 && wav[i]>1)
8961: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
8962: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
8963:
8964: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
8965: if (wav[i] > 1 ) { /* ??? */
8966: LL=LL+A*weight[i];
8967: /* 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]);*/
8968: }
8969: }
8970:
8971: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
8972: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
8973:
8974: return -2*LL*num/sump;
8975: }
8976: #endif
8977:
1.126 brouard 8978: /******************* Printing html file ***********/
1.201 brouard 8979: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 8980: int lastpass, int stepm, int weightopt, char model[],\
8981: int imx, double p[],double **matcov,double agemortsup){
8982: int i,k;
8983:
8984: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
8985: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
8986: for (i=1;i<=2;i++)
8987: 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 8988: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 8989: fprintf(fichtm,"</ul>");
8990:
8991: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
8992:
8993: 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>");
8994:
8995: for (k=agegomp;k<(agemortsup-2);k++)
8996: 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]);
8997:
8998:
8999: fflush(fichtm);
9000: }
9001:
9002: /******************* Gnuplot file **************/
1.201 brouard 9003: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 9004:
9005: char dirfileres[132],optfileres[132];
1.164 brouard 9006:
1.126 brouard 9007: int ng;
9008:
9009:
9010: /*#ifdef windows */
9011: fprintf(ficgp,"cd \"%s\" \n",pathc);
9012: /*#endif */
9013:
9014:
9015: strcpy(dirfileres,optionfilefiname);
9016: strcpy(optfileres,"vpl");
1.199 brouard 9017: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 9018: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 9019: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 9020: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 9021: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
9022:
9023: }
9024:
1.136 brouard 9025: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
9026: {
1.126 brouard 9027:
1.136 brouard 9028: /*-------- data file ----------*/
9029: FILE *fic;
9030: char dummy[]=" ";
1.240 brouard 9031: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 9032: int lstra;
1.136 brouard 9033: int linei, month, year,iout;
9034: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 9035: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 9036: char *stratrunc;
1.223 brouard 9037:
1.240 brouard 9038: DummyV=ivector(1,NCOVMAX); /* 1 to 3 */
9039: FixedV=ivector(1,NCOVMAX); /* 1 to 3 */
1.126 brouard 9040:
1.240 brouard 9041: for(v=1; v <=ncovcol;v++){
9042: DummyV[v]=0;
9043: FixedV[v]=0;
9044: }
9045: for(v=ncovcol+1; v <=ncovcol+nqv;v++){
9046: DummyV[v]=1;
9047: FixedV[v]=0;
9048: }
9049: for(v=ncovcol+nqv+1; v <=ncovcol+nqv+ntv;v++){
9050: DummyV[v]=0;
9051: FixedV[v]=1;
9052: }
9053: for(v=ncovcol+nqv+ntv+1; v <=ncovcol+nqv+ntv+nqtv;v++){
9054: DummyV[v]=1;
9055: FixedV[v]=1;
9056: }
9057: for(v=1; v <=ncovcol+nqv+ntv+nqtv;v++){
9058: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",v,v,DummyV[v],v,FixedV[v]);
9059: 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]);
9060: }
1.126 brouard 9061:
1.136 brouard 9062: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 9063: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
9064: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 9065: }
1.126 brouard 9066:
1.136 brouard 9067: i=1;
9068: linei=0;
9069: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
9070: linei=linei+1;
9071: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
9072: if(line[j] == '\t')
9073: line[j] = ' ';
9074: }
9075: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
9076: ;
9077: };
9078: line[j+1]=0; /* Trims blanks at end of line */
9079: if(line[0]=='#'){
9080: fprintf(ficlog,"Comment line\n%s\n",line);
9081: printf("Comment line\n%s\n",line);
9082: continue;
9083: }
9084: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 9085: strcpy(line, linetmp);
1.223 brouard 9086:
9087: /* Loops on waves */
9088: for (j=maxwav;j>=1;j--){
9089: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 9090: cutv(stra, strb, line, ' ');
9091: if(strb[0]=='.') { /* Missing value */
9092: lval=-1;
9093: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
9094: cotvar[j][ntv+iv][i]=-1; /* For performance reasons */
9095: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
9096: 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);
9097: 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);
9098: return 1;
9099: }
9100: }else{
9101: errno=0;
9102: /* what_kind_of_number(strb); */
9103: dval=strtod(strb,&endptr);
9104: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
9105: /* if(strb != endptr && *endptr == '\0') */
9106: /* dval=dlval; */
9107: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9108: if( strb[0]=='\0' || (*endptr != '\0')){
9109: 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);
9110: 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);
9111: return 1;
9112: }
9113: cotqvar[j][iv][i]=dval;
9114: cotvar[j][ntv+iv][i]=dval;
9115: }
9116: strcpy(line,stra);
1.223 brouard 9117: }/* end loop ntqv */
1.225 brouard 9118:
1.223 brouard 9119: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 9120: cutv(stra, strb, line, ' ');
9121: if(strb[0]=='.') { /* Missing value */
9122: lval=-1;
9123: }else{
9124: errno=0;
9125: lval=strtol(strb,&endptr,10);
9126: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9127: if( strb[0]=='\0' || (*endptr != '\0')){
9128: 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);
9129: 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);
9130: return 1;
9131: }
9132: }
9133: if(lval <-1 || lval >1){
9134: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.223 brouard 9135: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9136: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9137: For example, for multinomial values like 1, 2 and 3,\n \
9138: build V1=0 V2=0 for the reference value (1),\n \
9139: V1=1 V2=0 for (2) \n \
1.223 brouard 9140: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9141: output of IMaCh is often meaningless.\n \
1.223 brouard 9142: Exiting.\n",lval,linei, i,line,j);
1.238 brouard 9143: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.223 brouard 9144: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9145: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9146: For example, for multinomial values like 1, 2 and 3,\n \
9147: build V1=0 V2=0 for the reference value (1),\n \
9148: V1=1 V2=0 for (2) \n \
1.223 brouard 9149: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9150: output of IMaCh is often meaningless.\n \
1.223 brouard 9151: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.238 brouard 9152: return 1;
9153: }
9154: cotvar[j][iv][i]=(double)(lval);
9155: strcpy(line,stra);
1.223 brouard 9156: }/* end loop ntv */
1.225 brouard 9157:
1.223 brouard 9158: /* Statuses at wave */
1.137 brouard 9159: cutv(stra, strb, line, ' ');
1.223 brouard 9160: if(strb[0]=='.') { /* Missing value */
1.238 brouard 9161: lval=-1;
1.136 brouard 9162: }else{
1.238 brouard 9163: errno=0;
9164: lval=strtol(strb,&endptr,10);
9165: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9166: if( strb[0]=='\0' || (*endptr != '\0')){
9167: 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);
9168: 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);
9169: return 1;
9170: }
1.136 brouard 9171: }
1.225 brouard 9172:
1.136 brouard 9173: s[j][i]=lval;
1.225 brouard 9174:
1.223 brouard 9175: /* Date of Interview */
1.136 brouard 9176: strcpy(line,stra);
9177: cutv(stra, strb,line,' ');
1.169 brouard 9178: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9179: }
1.169 brouard 9180: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 9181: month=99;
9182: year=9999;
1.136 brouard 9183: }else{
1.225 brouard 9184: 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);
9185: 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);
9186: return 1;
1.136 brouard 9187: }
9188: anint[j][i]= (double) year;
9189: mint[j][i]= (double)month;
9190: strcpy(line,stra);
1.223 brouard 9191: } /* End loop on waves */
1.225 brouard 9192:
1.223 brouard 9193: /* Date of death */
1.136 brouard 9194: cutv(stra, strb,line,' ');
1.169 brouard 9195: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9196: }
1.169 brouard 9197: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 9198: month=99;
9199: year=9999;
9200: }else{
1.141 brouard 9201: 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 9202: 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);
9203: return 1;
1.136 brouard 9204: }
9205: andc[i]=(double) year;
9206: moisdc[i]=(double) month;
9207: strcpy(line,stra);
9208:
1.223 brouard 9209: /* Date of birth */
1.136 brouard 9210: cutv(stra, strb,line,' ');
1.169 brouard 9211: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9212: }
1.169 brouard 9213: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 9214: month=99;
9215: year=9999;
9216: }else{
1.141 brouard 9217: 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);
9218: 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 9219: return 1;
1.136 brouard 9220: }
9221: if (year==9999) {
1.141 brouard 9222: 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);
9223: 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 9224: return 1;
9225:
1.136 brouard 9226: }
9227: annais[i]=(double)(year);
9228: moisnais[i]=(double)(month);
9229: strcpy(line,stra);
1.225 brouard 9230:
1.223 brouard 9231: /* Sample weight */
1.136 brouard 9232: cutv(stra, strb,line,' ');
9233: errno=0;
9234: dval=strtod(strb,&endptr);
9235: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 9236: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
9237: 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 9238: fflush(ficlog);
9239: return 1;
9240: }
9241: weight[i]=dval;
9242: strcpy(line,stra);
1.225 brouard 9243:
1.223 brouard 9244: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
9245: cutv(stra, strb, line, ' ');
9246: if(strb[0]=='.') { /* Missing value */
1.225 brouard 9247: lval=-1;
1.223 brouard 9248: }else{
1.225 brouard 9249: errno=0;
9250: /* what_kind_of_number(strb); */
9251: dval=strtod(strb,&endptr);
9252: /* if(strb != endptr && *endptr == '\0') */
9253: /* dval=dlval; */
9254: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9255: if( strb[0]=='\0' || (*endptr != '\0')){
9256: printf("Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be 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);
9257: 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);
9258: return 1;
9259: }
9260: coqvar[iv][i]=dval;
1.226 brouard 9261: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 9262: }
9263: strcpy(line,stra);
9264: }/* end loop nqv */
1.136 brouard 9265:
1.223 brouard 9266: /* Covariate values */
1.136 brouard 9267: for (j=ncovcol;j>=1;j--){
9268: cutv(stra, strb,line,' ');
1.223 brouard 9269: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 9270: lval=-1;
1.136 brouard 9271: }else{
1.225 brouard 9272: errno=0;
9273: lval=strtol(strb,&endptr,10);
9274: if( strb[0]=='\0' || (*endptr != '\0')){
9275: 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);
9276: 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);
9277: return 1;
9278: }
1.136 brouard 9279: }
9280: if(lval <-1 || lval >1){
1.225 brouard 9281: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9282: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9283: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9284: For example, for multinomial values like 1, 2 and 3,\n \
9285: build V1=0 V2=0 for the reference value (1),\n \
9286: V1=1 V2=0 for (2) \n \
1.136 brouard 9287: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9288: output of IMaCh is often meaningless.\n \
1.136 brouard 9289: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 9290: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9291: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9292: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9293: For example, for multinomial values like 1, 2 and 3,\n \
9294: build V1=0 V2=0 for the reference value (1),\n \
9295: V1=1 V2=0 for (2) \n \
1.136 brouard 9296: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9297: output of IMaCh is often meaningless.\n \
1.136 brouard 9298: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 9299: return 1;
1.136 brouard 9300: }
9301: covar[j][i]=(double)(lval);
9302: strcpy(line,stra);
9303: }
9304: lstra=strlen(stra);
1.225 brouard 9305:
1.136 brouard 9306: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
9307: stratrunc = &(stra[lstra-9]);
9308: num[i]=atol(stratrunc);
9309: }
9310: else
9311: num[i]=atol(stra);
9312: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
9313: 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;}*/
9314:
9315: i=i+1;
9316: } /* End loop reading data */
1.225 brouard 9317:
1.136 brouard 9318: *imax=i-1; /* Number of individuals */
9319: fclose(fic);
1.225 brouard 9320:
1.136 brouard 9321: return (0);
1.164 brouard 9322: /* endread: */
1.225 brouard 9323: printf("Exiting readdata: ");
9324: fclose(fic);
9325: return (1);
1.223 brouard 9326: }
1.126 brouard 9327:
1.234 brouard 9328: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 9329: char *p1 = *stri, *p2 = *stri;
1.235 brouard 9330: while (*p2 == ' ')
1.234 brouard 9331: p2++;
9332: /* while ((*p1++ = *p2++) !=0) */
9333: /* ; */
9334: /* do */
9335: /* while (*p2 == ' ') */
9336: /* p2++; */
9337: /* while (*p1++ == *p2++); */
9338: *stri=p2;
1.145 brouard 9339: }
9340:
1.235 brouard 9341: int decoderesult ( char resultline[], int nres)
1.230 brouard 9342: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
9343: {
1.235 brouard 9344: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 9345: char resultsav[MAXLINE];
1.234 brouard 9346: int resultmodel[MAXLINE];
9347: int modelresult[MAXLINE];
1.230 brouard 9348: char stra[80], strb[80], strc[80], strd[80],stre[80];
9349:
1.234 brouard 9350: removefirstspace(&resultline);
1.233 brouard 9351: printf("decoderesult:%s\n",resultline);
1.230 brouard 9352:
9353: if (strstr(resultline,"v") !=0){
9354: printf("Error. 'v' must be in upper case 'V' result: %s ",resultline);
9355: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultline);fflush(ficlog);
9356: return 1;
9357: }
9358: trimbb(resultsav, resultline);
9359: if (strlen(resultsav) >1){
9360: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' */
9361: }
1.253 brouard 9362: if(j == 0){ /* Resultline but no = */
9363: TKresult[nres]=0; /* Combination for the nresult and the model */
9364: return (0);
9365: }
9366:
1.234 brouard 9367: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
9368: 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);
9369: 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);
9370: }
9371: for(k=1; k<=j;k++){ /* Loop on any covariate of the result line */
9372: if(nbocc(resultsav,'=') >1){
9373: cutl(stra,strb,resultsav,' '); /* keeps in strb after the first ' '
9374: resultsav= V4=1 V5=25.1 V3=0 strb=V3=0 stra= V4=1 V5=25.1 */
9375: cutl(strc,strd,strb,'='); /* strb:V4=1 strc=1 strd=V4 */
9376: }else
9377: cutl(strc,strd,resultsav,'=');
1.230 brouard 9378: Tvalsel[k]=atof(strc); /* 1 */
1.234 brouard 9379:
1.230 brouard 9380: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
9381: Tvarsel[k]=atoi(strc);
9382: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
9383: /* cptcovsel++; */
9384: if (nbocc(stra,'=') >0)
9385: strcpy(resultsav,stra); /* and analyzes it */
9386: }
1.235 brouard 9387: /* Checking for missing or useless values in comparison of current model needs */
1.236 brouard 9388: for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9389: if(Typevar[k1]==0){ /* Single covariate in model */
1.234 brouard 9390: match=0;
1.236 brouard 9391: for(k2=1; k2 <=j;k2++){/* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.237 brouard 9392: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar[1]=5 == Tvarsel[2]=5 */
1.236 brouard 9393: modelresult[k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.234 brouard 9394: match=1;
9395: break;
9396: }
9397: }
9398: if(match == 0){
9399: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
9400: }
9401: }
9402: }
1.235 brouard 9403: /* Checking for missing or useless values in comparison of current model needs */
9404: for(k2=1; k2 <=j;k2++){ /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 9405: match=0;
1.235 brouard 9406: for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9407: if(Typevar[k1]==0){ /* Single */
1.237 brouard 9408: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 */
1.235 brouard 9409: resultmodel[k1]=k2; /* resultmodel[2]=1 resultmodel[1]=2 resultmodel[3]=3 resultmodel[6]=4 resultmodel[9]=5 */
1.234 brouard 9410: ++match;
9411: }
9412: }
9413: }
9414: if(match == 0){
9415: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
9416: }else if(match > 1){
9417: printf("Error in result line: %d doubled; result: %s, model=%s\n",k2, resultline, model);
9418: }
9419: }
1.235 brouard 9420:
1.234 brouard 9421: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 9422: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9423: /* result line V4=1 V5=25.1 V3=0 V2=8 V1=1 */
9424: /* should give a combination of dummy V4=1, V3=0, V1=1 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 5 + (1offset) = 6*/
9425: /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
9426: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
9427: /* 1 0 0 0 */
9428: /* 2 1 0 0 */
9429: /* 3 0 1 0 */
9430: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 */
9431: /* 5 0 0 1 */
9432: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 */
9433: /* 7 0 1 1 */
9434: /* 8 1 1 1 */
1.237 brouard 9435: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
9436: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
9437: /* V5*age V5 known which value for nres? */
9438: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.235 brouard 9439: for(k1=1, k=0, k4=0, k4q=0; k1 <=cptcovt;k1++){ /* model line */
9440: if( Dummy[k1]==0 && Typevar[k1]==0 ){ /* Single dummy */
1.237 brouard 9441: k3= resultmodel[k1]; /* resultmodel[2(V4)] = 1=k3 */
1.235 brouard 9442: k2=(int)Tvarsel[k3]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
9443: k+=Tvalsel[k3]*pow(2,k4); /* Tvalsel[1]=1 */
1.237 brouard 9444: Tresult[nres][k4+1]=Tvalsel[k3];/* Tresult[nres][1]=1(V4=1) Tresult[nres][2]=0(V3=0) */
9445: Tvresult[nres][k4+1]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
9446: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.235 brouard 9447: printf("Decoderesult Dummy k=%d, V(k2=V%d)= Tvalsel[%d]=%d, 2**(%d)\n",k, k2, k3, (int)Tvalsel[k3], k4);
9448: k4++;;
9449: } else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Single quantitative */
9450: k3q= resultmodel[k1]; /* resultmodel[2] = 1=k3 */
9451: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
1.237 brouard 9452: Tqresult[nres][k4q+1]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
9453: Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
9454: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.235 brouard 9455: printf("Decoderesult Quantitative nres=%d, V(k2q=V%d)= Tvalsel[%d]=%d, Tvarsel[%d]=%f\n",nres, k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]);
9456: k4q++;;
9457: }
9458: }
1.234 brouard 9459:
1.235 brouard 9460: TKresult[nres]=++k; /* Combination for the nresult and the model */
1.230 brouard 9461: return (0);
9462: }
1.235 brouard 9463:
1.230 brouard 9464: int decodemodel( char model[], int lastobs)
9465: /**< This routine decodes the model and returns:
1.224 brouard 9466: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
9467: * - nagesqr = 1 if age*age in the model, otherwise 0.
9468: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
9469: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
9470: * - cptcovage number of covariates with age*products =2
9471: * - cptcovs number of simple covariates
9472: * - 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
9473: * which is a new column after the 9 (ncovcol) variables.
9474: * - if k is a product Vn*Vm covar[k][i] is filled with correct values for each individual
9475: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
9476: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
9477: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
9478: */
1.136 brouard 9479: {
1.238 brouard 9480: int i, j, k, ks, v;
1.227 brouard 9481: int j1, k1, k2, k3, k4;
1.136 brouard 9482: char modelsav[80];
1.145 brouard 9483: char stra[80], strb[80], strc[80], strd[80],stre[80];
1.187 brouard 9484: char *strpt;
1.136 brouard 9485:
1.145 brouard 9486: /*removespace(model);*/
1.136 brouard 9487: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.145 brouard 9488: j=0, j1=0, k1=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 9489: if (strstr(model,"AGE") !=0){
1.192 brouard 9490: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
9491: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 9492: return 1;
9493: }
1.141 brouard 9494: if (strstr(model,"v") !=0){
9495: printf("Error. 'v' must be in upper case 'V' model=%s ",model);
9496: fprintf(ficlog,"Error. 'v' must be in upper case model=%s ",model);fflush(ficlog);
9497: return 1;
9498: }
1.187 brouard 9499: strcpy(modelsav,model);
9500: if ((strpt=strstr(model,"age*age")) !=0){
9501: printf(" strpt=%s, model=%s\n",strpt, model);
9502: if(strpt != model){
1.234 brouard 9503: printf("Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 9504: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 9505: corresponding column of parameters.\n",model);
1.234 brouard 9506: fprintf(ficlog,"Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 9507: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 9508: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 9509: return 1;
1.225 brouard 9510: }
1.187 brouard 9511: nagesqr=1;
9512: if (strstr(model,"+age*age") !=0)
1.234 brouard 9513: substrchaine(modelsav, model, "+age*age");
1.187 brouard 9514: else if (strstr(model,"age*age+") !=0)
1.234 brouard 9515: substrchaine(modelsav, model, "age*age+");
1.187 brouard 9516: else
1.234 brouard 9517: substrchaine(modelsav, model, "age*age");
1.187 brouard 9518: }else
9519: nagesqr=0;
9520: if (strlen(modelsav) >1){
9521: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
9522: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.224 brouard 9523: cptcovs=j+1-j1; /**< Number of simple covariates V1+V1*age+V3 +V3*V4+age*age=> V1 + V3 =5-3=2 */
1.187 brouard 9524: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 9525: * cst, age and age*age
9526: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
9527: /* including age products which are counted in cptcovage.
9528: * but the covariates which are products must be treated
9529: * separately: ncovn=4- 2=2 (V1+V3). */
1.187 brouard 9530: cptcovprod=j1; /**< Number of products V1*V2 +v3*age = 2 */
9531: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.225 brouard 9532:
9533:
1.187 brouard 9534: /* Design
9535: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
9536: * < ncovcol=8 >
9537: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
9538: * k= 1 2 3 4 5 6 7 8
9539: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
9540: * covar[k,i], value of kth covariate if not including age for individual i:
1.224 brouard 9541: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
9542: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 9543: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
9544: * Tage[++cptcovage]=k
9545: * if products, new covar are created after ncovcol with k1
9546: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
9547: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
9548: * 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
9549: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
9550: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
9551: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
9552: * < ncovcol=8 >
9553: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
9554: * k= 1 2 3 4 5 6 7 8 9 10 11 12
9555: * Tvar[k]= 2 1 3 3 10 11 8 8 5 6 7 8
9556: * p Tvar[1]@12={2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
9557: * p Tprod[1]@2={ 6, 5}
9558: *p Tvard[1][1]@4= {7, 8, 5, 6}
9559: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
9560: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
9561: *How to reorganize?
9562: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
9563: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
9564: * {2, 1, 4, 8, 5, 6, 3, 7}
9565: * Struct []
9566: */
1.225 brouard 9567:
1.187 brouard 9568: /* This loop fills the array Tvar from the string 'model'.*/
9569: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
9570: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
9571: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
9572: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
9573: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
9574: /* k=1 Tvar[1]=2 (from V2) */
9575: /* k=5 Tvar[5] */
9576: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 9577: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 9578: /* } */
1.198 brouard 9579: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 9580: /*
9581: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 9582: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
9583: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
9584: }
1.187 brouard 9585: cptcovage=0;
9586: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model */
1.234 brouard 9587: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+'
1.225 brouard 9588: modelsav==V2+V1+V4+V3*age strb=V3*age stra=V2+V1+V4 */
1.234 brouard 9589: if (nbocc(modelsav,'+')==0) strcpy(strb,modelsav); /* and analyzes it */
9590: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
9591: /*scanf("%d",i);*/
9592: if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V4+V3*age strb=V3*age */
9593: cutl(strc,strd,strb,'*'); /**< strd*strc Vm*Vn: strb=V3*age(input) strc=age strd=V3 ; V3*V2 strc=V2, strd=V3 */
9594: if (strcmp(strc,"age")==0) { /**< Model includes age: Vn*age */
9595: /* covar is not filled and then is empty */
9596: cptcovprod--;
9597: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
9598: Tvar[k]=atoi(stre); /* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1 */
9599: Typevar[k]=1; /* 1 for age product */
9600: cptcovage++; /* Sums the number of covariates which include age as a product */
9601: Tage[cptcovage]=k; /* Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */
9602: /*printf("stre=%s ", stre);*/
9603: } else if (strcmp(strd,"age")==0) { /* or age*Vn */
9604: cptcovprod--;
9605: cutl(stre,strb,strc,'V');
9606: Tvar[k]=atoi(stre);
9607: Typevar[k]=1; /* 1 for age product */
9608: cptcovage++;
9609: Tage[cptcovage]=k;
9610: } else { /* Age is not in the model product V2+V1+V1*V4+V3*age+V3*V2 strb=V3*V2*/
9611: /* loops on k1=1 (V3*V2) and k1=2 V4*V3 */
9612: cptcovn++;
9613: cptcovprodnoage++;k1++;
9614: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
9615: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* For model-covariate k tells which data-covariate to use but
9616: because this model-covariate is a construction we invent a new column
9617: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
9618: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2
9619: Tvar[3=V1*V4]=4+1 Tvar[5=V3*V2]=4 + 2= 6, etc */
9620: Typevar[k]=2; /* 2 for double fixed dummy covariates */
9621: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
9622: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 */
9623: Tposprod[k]=k1; /* Tpsprod[3]=1, Tposprod[2]=5 */
9624: Tvard[k1][1] =atoi(strc); /* m 1 for V1*/
9625: Tvard[k1][2] =atoi(stre); /* n 4 for V4*/
9626: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
9627: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
9628: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
1.225 brouard 9629: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
1.234 brouard 9630: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
9631: for (i=1; i<=lastobs;i++){
9632: /* Computes the new covariate which is a product of
9633: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
9634: covar[ncovcol+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
9635: }
9636: } /* End age is not in the model */
9637: } /* End if model includes a product */
9638: else { /* no more sum */
9639: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
9640: /* scanf("%d",i);*/
9641: cutl(strd,strc,strb,'V');
9642: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
9643: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
9644: Tvar[k]=atoi(strd);
9645: Typevar[k]=0; /* 0 for simple covariates */
9646: }
9647: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 9648: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 9649: scanf("%d",i);*/
1.187 brouard 9650: } /* end of loop + on total covariates */
9651: } /* end if strlen(modelsave == 0) age*age might exist */
9652: } /* end if strlen(model == 0) */
1.136 brouard 9653:
9654: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
9655: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 9656:
1.136 brouard 9657: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 9658: printf("cptcovprod=%d ", cptcovprod);
9659: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
9660: scanf("%d ",i);*/
9661:
9662:
1.230 brouard 9663: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
9664: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 9665: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
9666: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
9667: k = 1 2 3 4 5 6 7 8 9
9668: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
9669: Typevar[k]= 0 0 0 2 1 0 2 1 1
1.227 brouard 9670: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
9671: Dummy[k] 1 0 0 0 3 1 1 2 3
9672: Tmodelind[combination of covar]=k;
1.225 brouard 9673: */
9674: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 9675: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 9676: /* 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 9677: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.227 brouard 9678: printf("Model=%s\n\
9679: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
9680: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
9681: 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);
9682: fprintf(ficlog,"Model=%s\n\
9683: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
9684: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
9685: 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);
1.240 brouard 9686: for(k=1;k<=cptcovt; k++){ Fixed[k]=0; Dummy[k]=0;}
1.234 brouard 9687: 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 */
9688: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 9689: Fixed[k]= 0;
9690: Dummy[k]= 0;
1.225 brouard 9691: ncoveff++;
1.232 brouard 9692: ncovf++;
1.234 brouard 9693: nsd++;
9694: modell[k].maintype= FTYPE;
9695: TvarsD[nsd]=Tvar[k];
9696: TvarsDind[nsd]=k;
9697: TvarF[ncovf]=Tvar[k];
9698: TvarFind[ncovf]=k;
9699: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9700: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9701: }else if( Tvar[k] <=ncovcol && Typevar[k]==2){ /* Product of fixed dummy (<=ncovcol) covariates */
9702: Fixed[k]= 0;
9703: Dummy[k]= 0;
9704: ncoveff++;
9705: ncovf++;
9706: modell[k].maintype= FTYPE;
9707: TvarF[ncovf]=Tvar[k];
9708: TvarFind[ncovf]=k;
1.230 brouard 9709: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.231 brouard 9710: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.240 brouard 9711: }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 9712: Fixed[k]= 0;
9713: Dummy[k]= 1;
1.230 brouard 9714: nqfveff++;
1.234 brouard 9715: modell[k].maintype= FTYPE;
9716: modell[k].subtype= FQ;
9717: nsq++;
9718: TvarsQ[nsq]=Tvar[k];
9719: TvarsQind[nsq]=k;
1.232 brouard 9720: ncovf++;
1.234 brouard 9721: TvarF[ncovf]=Tvar[k];
9722: TvarFind[ncovf]=k;
1.231 brouard 9723: 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 9724: 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 9725: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.227 brouard 9726: Fixed[k]= 1;
9727: Dummy[k]= 0;
1.225 brouard 9728: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 9729: modell[k].maintype= VTYPE;
9730: modell[k].subtype= VD;
9731: nsd++;
9732: TvarsD[nsd]=Tvar[k];
9733: TvarsDind[nsd]=k;
9734: ncovv++; /* Only simple time varying variables */
9735: TvarV[ncovv]=Tvar[k];
1.242 brouard 9736: 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 9737: 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 */
9738: 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 9739: 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);
9740: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 9741: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.234 brouard 9742: Fixed[k]= 1;
9743: Dummy[k]= 1;
9744: nqtveff++;
9745: modell[k].maintype= VTYPE;
9746: modell[k].subtype= VQ;
9747: ncovv++; /* Only simple time varying variables */
9748: nsq++;
9749: TvarsQ[nsq]=Tvar[k];
9750: TvarsQind[nsq]=k;
9751: TvarV[ncovv]=Tvar[k];
1.242 brouard 9752: 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 9753: 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 */
9754: 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 9755: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
9756: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
9757: 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 9758: printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv);
1.227 brouard 9759: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 9760: ncova++;
9761: TvarA[ncova]=Tvar[k];
9762: TvarAind[ncova]=k;
1.231 brouard 9763: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 9764: Fixed[k]= 2;
9765: Dummy[k]= 2;
9766: modell[k].maintype= ATYPE;
9767: modell[k].subtype= APFD;
9768: /* ncoveff++; */
1.227 brouard 9769: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 9770: Fixed[k]= 2;
9771: Dummy[k]= 3;
9772: modell[k].maintype= ATYPE;
9773: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
9774: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 9775: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 9776: Fixed[k]= 3;
9777: Dummy[k]= 2;
9778: modell[k].maintype= ATYPE;
9779: modell[k].subtype= APVD; /* Product age * varying dummy */
9780: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 9781: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 9782: Fixed[k]= 3;
9783: Dummy[k]= 3;
9784: modell[k].maintype= ATYPE;
9785: modell[k].subtype= APVQ; /* Product age * varying quantitative */
9786: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 9787: }
9788: }else if (Typevar[k] == 2) { /* product without age */
9789: k1=Tposprod[k];
9790: if(Tvard[k1][1] <=ncovcol){
1.240 brouard 9791: if(Tvard[k1][2] <=ncovcol){
9792: Fixed[k]= 1;
9793: Dummy[k]= 0;
9794: modell[k].maintype= FTYPE;
9795: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
9796: ncovf++; /* Fixed variables without age */
9797: TvarF[ncovf]=Tvar[k];
9798: TvarFind[ncovf]=k;
9799: }else if(Tvard[k1][2] <=ncovcol+nqv){
9800: Fixed[k]= 0; /* or 2 ?*/
9801: Dummy[k]= 1;
9802: modell[k].maintype= FTYPE;
9803: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
9804: ncovf++; /* Varying variables without age */
9805: TvarF[ncovf]=Tvar[k];
9806: TvarFind[ncovf]=k;
9807: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9808: Fixed[k]= 1;
9809: Dummy[k]= 0;
9810: modell[k].maintype= VTYPE;
9811: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
9812: ncovv++; /* Varying variables without age */
9813: TvarV[ncovv]=Tvar[k];
9814: TvarVind[ncovv]=k;
9815: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9816: Fixed[k]= 1;
9817: Dummy[k]= 1;
9818: modell[k].maintype= VTYPE;
9819: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
9820: ncovv++; /* Varying variables without age */
9821: TvarV[ncovv]=Tvar[k];
9822: TvarVind[ncovv]=k;
9823: }
1.227 brouard 9824: }else if(Tvard[k1][1] <=ncovcol+nqv){
1.240 brouard 9825: if(Tvard[k1][2] <=ncovcol){
9826: Fixed[k]= 0; /* or 2 ?*/
9827: Dummy[k]= 1;
9828: modell[k].maintype= FTYPE;
9829: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
9830: ncovf++; /* Fixed variables without age */
9831: TvarF[ncovf]=Tvar[k];
9832: TvarFind[ncovf]=k;
9833: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9834: Fixed[k]= 1;
9835: Dummy[k]= 1;
9836: modell[k].maintype= VTYPE;
9837: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
9838: ncovv++; /* Varying variables without age */
9839: TvarV[ncovv]=Tvar[k];
9840: TvarVind[ncovv]=k;
9841: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9842: Fixed[k]= 1;
9843: Dummy[k]= 1;
9844: modell[k].maintype= VTYPE;
9845: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
9846: ncovv++; /* Varying variables without age */
9847: TvarV[ncovv]=Tvar[k];
9848: TvarVind[ncovv]=k;
9849: ncovv++; /* Varying variables without age */
9850: TvarV[ncovv]=Tvar[k];
9851: TvarVind[ncovv]=k;
9852: }
1.227 brouard 9853: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){
1.240 brouard 9854: if(Tvard[k1][2] <=ncovcol){
9855: Fixed[k]= 1;
9856: Dummy[k]= 1;
9857: modell[k].maintype= VTYPE;
9858: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
9859: ncovv++; /* Varying variables without age */
9860: TvarV[ncovv]=Tvar[k];
9861: TvarVind[ncovv]=k;
9862: }else if(Tvard[k1][2] <=ncovcol+nqv){
9863: Fixed[k]= 1;
9864: Dummy[k]= 1;
9865: modell[k].maintype= VTYPE;
9866: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
9867: ncovv++; /* Varying variables without age */
9868: TvarV[ncovv]=Tvar[k];
9869: TvarVind[ncovv]=k;
9870: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9871: Fixed[k]= 1;
9872: Dummy[k]= 0;
9873: modell[k].maintype= VTYPE;
9874: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
9875: ncovv++; /* Varying variables without age */
9876: TvarV[ncovv]=Tvar[k];
9877: TvarVind[ncovv]=k;
9878: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9879: Fixed[k]= 1;
9880: Dummy[k]= 1;
9881: modell[k].maintype= VTYPE;
9882: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
9883: ncovv++; /* Varying variables without age */
9884: TvarV[ncovv]=Tvar[k];
9885: TvarVind[ncovv]=k;
9886: }
1.227 brouard 9887: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 9888: if(Tvard[k1][2] <=ncovcol){
9889: Fixed[k]= 1;
9890: Dummy[k]= 1;
9891: modell[k].maintype= VTYPE;
9892: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
9893: ncovv++; /* Varying variables without age */
9894: TvarV[ncovv]=Tvar[k];
9895: TvarVind[ncovv]=k;
9896: }else if(Tvard[k1][2] <=ncovcol+nqv){
9897: Fixed[k]= 1;
9898: Dummy[k]= 1;
9899: modell[k].maintype= VTYPE;
9900: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
9901: ncovv++; /* Varying variables without age */
9902: TvarV[ncovv]=Tvar[k];
9903: TvarVind[ncovv]=k;
9904: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9905: Fixed[k]= 1;
9906: Dummy[k]= 1;
9907: modell[k].maintype= VTYPE;
9908: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
9909: ncovv++; /* Varying variables without age */
9910: TvarV[ncovv]=Tvar[k];
9911: TvarVind[ncovv]=k;
9912: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9913: Fixed[k]= 1;
9914: Dummy[k]= 1;
9915: modell[k].maintype= VTYPE;
9916: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
9917: ncovv++; /* Varying variables without age */
9918: TvarV[ncovv]=Tvar[k];
9919: TvarVind[ncovv]=k;
9920: }
1.227 brouard 9921: }else{
1.240 brouard 9922: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
9923: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
9924: } /*end k1*/
1.225 brouard 9925: }else{
1.226 brouard 9926: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
9927: 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 9928: }
1.227 brouard 9929: 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 9930: printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype);
1.227 brouard 9931: 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]);
9932: }
9933: /* Searching for doublons in the model */
9934: for(k1=1; k1<= cptcovt;k1++){
9935: for(k2=1; k2 <k1;k2++){
9936: if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){
1.234 brouard 9937: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
9938: if(Tvar[k1]==Tvar[k2]){
9939: 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[Tvar[k1]],Dummy[Tvar[k1]]);
9940: 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[Tvar[k1]],Dummy[Tvar[k1]]); fflush(ficlog);
9941: return(1);
9942: }
9943: }else if (Typevar[k1] ==2){
9944: k3=Tposprod[k1];
9945: k4=Tposprod[k2];
9946: 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])) ){
9947: 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]]);
9948: 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);
9949: return(1);
9950: }
9951: }
1.227 brouard 9952: }
9953: }
1.225 brouard 9954: }
9955: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
9956: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 9957: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
9958: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.137 brouard 9959: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 9960: /*endread:*/
1.225 brouard 9961: printf("Exiting decodemodel: ");
9962: return (1);
1.136 brouard 9963: }
9964:
1.169 brouard 9965: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 9966: {/* Check ages at death */
1.136 brouard 9967: int i, m;
1.218 brouard 9968: int firstone=0;
9969:
1.136 brouard 9970: for (i=1; i<=imx; i++) {
9971: for(m=2; (m<= maxwav); m++) {
9972: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
9973: anint[m][i]=9999;
1.216 brouard 9974: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
9975: s[m][i]=-1;
1.136 brouard 9976: }
9977: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 9978: *nberr = *nberr + 1;
1.218 brouard 9979: if(firstone == 0){
9980: firstone=1;
1.260 brouard 9981: 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 9982: }
1.262 brouard 9983: 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 9984: s[m][i]=-1; /* Droping the death status */
1.136 brouard 9985: }
9986: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 9987: (*nberr)++;
1.259 brouard 9988: 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 9989: 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 9990: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 9991: }
9992: }
9993: }
9994:
9995: for (i=1; i<=imx; i++) {
9996: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
9997: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 9998: 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 9999: if (s[m][i] >= nlstate+1) {
1.169 brouard 10000: if(agedc[i]>0){
10001: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 10002: agev[m][i]=agedc[i];
1.214 brouard 10003: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 10004: }else {
1.136 brouard 10005: if ((int)andc[i]!=9999){
10006: nbwarn++;
10007: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
10008: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
10009: agev[m][i]=-1;
10010: }
10011: }
1.169 brouard 10012: } /* agedc > 0 */
1.214 brouard 10013: } /* end if */
1.136 brouard 10014: else if(s[m][i] !=9){ /* Standard case, age in fractional
10015: years but with the precision of a month */
10016: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
10017: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
10018: agev[m][i]=1;
10019: else if(agev[m][i] < *agemin){
10020: *agemin=agev[m][i];
10021: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
10022: }
10023: else if(agev[m][i] >*agemax){
10024: *agemax=agev[m][i];
1.156 brouard 10025: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 10026: }
10027: /*agev[m][i]=anint[m][i]-annais[i];*/
10028: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 10029: } /* en if 9*/
1.136 brouard 10030: else { /* =9 */
1.214 brouard 10031: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 10032: agev[m][i]=1;
10033: s[m][i]=-1;
10034: }
10035: }
1.214 brouard 10036: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 10037: agev[m][i]=1;
1.214 brouard 10038: else{
10039: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
10040: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
10041: agev[m][i]=0;
10042: }
10043: } /* End for lastpass */
10044: }
1.136 brouard 10045:
10046: for (i=1; i<=imx; i++) {
10047: for(m=firstpass; (m<=lastpass); m++){
10048: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 10049: (*nberr)++;
1.136 brouard 10050: 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);
10051: 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);
10052: return 1;
10053: }
10054: }
10055: }
10056:
10057: /*for (i=1; i<=imx; i++){
10058: for (m=firstpass; (m<lastpass); m++){
10059: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
10060: }
10061:
10062: }*/
10063:
10064:
1.139 brouard 10065: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
10066: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 10067:
10068: return (0);
1.164 brouard 10069: /* endread:*/
1.136 brouard 10070: printf("Exiting calandcheckages: ");
10071: return (1);
10072: }
10073:
1.172 brouard 10074: #if defined(_MSC_VER)
10075: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
10076: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
10077: //#include "stdafx.h"
10078: //#include <stdio.h>
10079: //#include <tchar.h>
10080: //#include <windows.h>
10081: //#include <iostream>
10082: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
10083:
10084: LPFN_ISWOW64PROCESS fnIsWow64Process;
10085:
10086: BOOL IsWow64()
10087: {
10088: BOOL bIsWow64 = FALSE;
10089:
10090: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
10091: // (HANDLE, PBOOL);
10092:
10093: //LPFN_ISWOW64PROCESS fnIsWow64Process;
10094:
10095: HMODULE module = GetModuleHandle(_T("kernel32"));
10096: const char funcName[] = "IsWow64Process";
10097: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
10098: GetProcAddress(module, funcName);
10099:
10100: if (NULL != fnIsWow64Process)
10101: {
10102: if (!fnIsWow64Process(GetCurrentProcess(),
10103: &bIsWow64))
10104: //throw std::exception("Unknown error");
10105: printf("Unknown error\n");
10106: }
10107: return bIsWow64 != FALSE;
10108: }
10109: #endif
1.177 brouard 10110:
1.191 brouard 10111: void syscompilerinfo(int logged)
1.167 brouard 10112: {
10113: /* #include "syscompilerinfo.h"*/
1.185 brouard 10114: /* command line Intel compiler 32bit windows, XP compatible:*/
10115: /* /GS /W3 /Gy
10116: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
10117: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
10118: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 10119: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
10120: */
10121: /* 64 bits */
1.185 brouard 10122: /*
10123: /GS /W3 /Gy
10124: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
10125: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
10126: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
10127: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
10128: /* Optimization are useless and O3 is slower than O2 */
10129: /*
10130: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
10131: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
10132: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
10133: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
10134: */
1.186 brouard 10135: /* Link is */ /* /OUT:"visual studio
1.185 brouard 10136: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
10137: /PDB:"visual studio
10138: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
10139: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
10140: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
10141: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
10142: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
10143: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
10144: uiAccess='false'"
10145: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
10146: /NOLOGO /TLBID:1
10147: */
1.177 brouard 10148: #if defined __INTEL_COMPILER
1.178 brouard 10149: #if defined(__GNUC__)
10150: struct utsname sysInfo; /* For Intel on Linux and OS/X */
10151: #endif
1.177 brouard 10152: #elif defined(__GNUC__)
1.179 brouard 10153: #ifndef __APPLE__
1.174 brouard 10154: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 10155: #endif
1.177 brouard 10156: struct utsname sysInfo;
1.178 brouard 10157: int cross = CROSS;
10158: if (cross){
10159: printf("Cross-");
1.191 brouard 10160: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 10161: }
1.174 brouard 10162: #endif
10163:
1.171 brouard 10164: #include <stdint.h>
1.178 brouard 10165:
1.191 brouard 10166: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 10167: #if defined(__clang__)
1.191 brouard 10168: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 10169: #endif
10170: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 10171: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 10172: #endif
10173: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 10174: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 10175: #endif
10176: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 10177: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 10178: #endif
10179: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 10180: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 10181: #endif
10182: #if defined(_MSC_VER)
1.191 brouard 10183: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 10184: #endif
10185: #if defined(__PGI)
1.191 brouard 10186: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 10187: #endif
10188: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 10189: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 10190: #endif
1.191 brouard 10191: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 10192:
1.167 brouard 10193: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
10194: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
10195: // Windows (x64 and x86)
1.191 brouard 10196: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 10197: #elif __unix__ // all unices, not all compilers
10198: // Unix
1.191 brouard 10199: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 10200: #elif __linux__
10201: // linux
1.191 brouard 10202: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 10203: #elif __APPLE__
1.174 brouard 10204: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 10205: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 10206: #endif
10207:
10208: /* __MINGW32__ */
10209: /* __CYGWIN__ */
10210: /* __MINGW64__ */
10211: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
10212: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
10213: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
10214: /* _WIN64 // Defined for applications for Win64. */
10215: /* _M_X64 // Defined for compilations that target x64 processors. */
10216: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 10217:
1.167 brouard 10218: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 10219: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 10220: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 10221: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 10222: #else
1.191 brouard 10223: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 10224: #endif
10225:
1.169 brouard 10226: #if defined(__GNUC__)
10227: # if defined(__GNUC_PATCHLEVEL__)
10228: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10229: + __GNUC_MINOR__ * 100 \
10230: + __GNUC_PATCHLEVEL__)
10231: # else
10232: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10233: + __GNUC_MINOR__ * 100)
10234: # endif
1.174 brouard 10235: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 10236: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 10237:
10238: if (uname(&sysInfo) != -1) {
10239: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 10240: 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 10241: }
10242: else
10243: perror("uname() error");
1.179 brouard 10244: //#ifndef __INTEL_COMPILER
10245: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 10246: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 10247: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 10248: #endif
1.169 brouard 10249: #endif
1.172 brouard 10250:
10251: // void main()
10252: // {
1.169 brouard 10253: #if defined(_MSC_VER)
1.174 brouard 10254: if (IsWow64()){
1.191 brouard 10255: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
10256: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 10257: }
10258: else{
1.191 brouard 10259: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
10260: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 10261: }
1.172 brouard 10262: // printf("\nPress Enter to continue...");
10263: // getchar();
10264: // }
10265:
1.169 brouard 10266: #endif
10267:
1.167 brouard 10268:
1.219 brouard 10269: }
1.136 brouard 10270:
1.219 brouard 10271: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.180 brouard 10272: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.235 brouard 10273: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 10274: /* double ftolpl = 1.e-10; */
1.180 brouard 10275: double age, agebase, agelim;
1.203 brouard 10276: double tot;
1.180 brouard 10277:
1.202 brouard 10278: strcpy(filerespl,"PL_");
10279: strcat(filerespl,fileresu);
10280: if((ficrespl=fopen(filerespl,"w"))==NULL) {
10281: printf("Problem with period (stable) prevalence resultfile: %s\n", filerespl);return 1;
10282: fprintf(ficlog,"Problem with period (stable) prevalence resultfile: %s\n", filerespl);return 1;
10283: }
1.227 brouard 10284: printf("\nComputing period (stable) prevalence: result on file '%s' \n", filerespl);
10285: fprintf(ficlog,"\nComputing period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 10286: pstamp(ficrespl);
1.203 brouard 10287: fprintf(ficrespl,"# Period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 10288: fprintf(ficrespl,"#Age ");
10289: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
10290: fprintf(ficrespl,"\n");
1.180 brouard 10291:
1.219 brouard 10292: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 10293:
1.219 brouard 10294: agebase=ageminpar;
10295: agelim=agemaxpar;
1.180 brouard 10296:
1.227 brouard 10297: /* i1=pow(2,ncoveff); */
1.234 brouard 10298: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 10299: if (cptcovn < 1){i1=1;}
1.180 brouard 10300:
1.238 brouard 10301: for(k=1; k<=i1;k++){ /* For each combination k of dummy covariates in the model */
10302: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 10303: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10304: continue;
1.235 brouard 10305:
1.238 brouard 10306: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10307: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
10308: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
10309: /* k=k+1; */
10310: /* to clean */
10311: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10312: fprintf(ficrespl,"#******");
10313: printf("#******");
10314: fprintf(ficlog,"#******");
10315: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10316: fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); /* Here problem for varying dummy*/
10317: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10318: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10319: }
10320: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
10321: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10322: fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10323: fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10324: }
10325: fprintf(ficrespl,"******\n");
10326: printf("******\n");
10327: fprintf(ficlog,"******\n");
10328: if(invalidvarcomb[k]){
10329: printf("\nCombination (%d) ignored because no case \n",k);
10330: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
10331: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
10332: continue;
10333: }
1.219 brouard 10334:
1.238 brouard 10335: fprintf(ficrespl,"#Age ");
10336: for(j=1;j<=cptcoveff;j++) {
10337: fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10338: }
10339: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
10340: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 10341:
1.238 brouard 10342: for (age=agebase; age<=agelim; age++){
10343: /* for (age=agebase; age<=agebase; age++){ */
10344: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres);
10345: fprintf(ficrespl,"%.0f ",age );
10346: for(j=1;j<=cptcoveff;j++)
10347: fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10348: tot=0.;
10349: for(i=1; i<=nlstate;i++){
10350: tot += prlim[i][i];
10351: fprintf(ficrespl," %.5f", prlim[i][i]);
10352: }
10353: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
10354: } /* Age */
10355: /* was end of cptcod */
10356: } /* cptcov */
10357: } /* nres */
1.219 brouard 10358: return 0;
1.180 brouard 10359: }
10360:
1.218 brouard 10361: 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){
10362: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
10363:
10364: /* Computes the back prevalence limit for any combination of covariate values
10365: * at any age between ageminpar and agemaxpar
10366: */
1.235 brouard 10367: int i, j, k, i1, nres=0 ;
1.217 brouard 10368: /* double ftolpl = 1.e-10; */
10369: double age, agebase, agelim;
10370: double tot;
1.218 brouard 10371: /* double ***mobaverage; */
10372: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 10373:
10374: strcpy(fileresplb,"PLB_");
10375: strcat(fileresplb,fileresu);
10376: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
10377: printf("Problem with period (stable) back prevalence resultfile: %s\n", fileresplb);return 1;
10378: fprintf(ficlog,"Problem with period (stable) back prevalence resultfile: %s\n", fileresplb);return 1;
10379: }
10380: printf("Computing period (stable) back prevalence: result on file '%s' \n", fileresplb);
10381: fprintf(ficlog,"Computing period (stable) back prevalence: result on file '%s' \n", fileresplb);
10382: pstamp(ficresplb);
10383: fprintf(ficresplb,"# Period (stable) back prevalence. Precision given by ftolpl=%g \n", ftolpl);
10384: fprintf(ficresplb,"#Age ");
10385: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
10386: fprintf(ficresplb,"\n");
10387:
1.218 brouard 10388:
10389: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
10390:
10391: agebase=ageminpar;
10392: agelim=agemaxpar;
10393:
10394:
1.227 brouard 10395: i1=pow(2,cptcoveff);
1.218 brouard 10396: if (cptcovn < 1){i1=1;}
1.227 brouard 10397:
1.238 brouard 10398: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10399: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 10400: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10401: continue;
10402: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10403: fprintf(ficresplb,"#******");
10404: printf("#******");
10405: fprintf(ficlog,"#******");
10406: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10407: fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10408: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10409: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10410: }
10411: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
10412: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10413: fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10414: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10415: }
10416: fprintf(ficresplb,"******\n");
10417: printf("******\n");
10418: fprintf(ficlog,"******\n");
10419: if(invalidvarcomb[k]){
10420: printf("\nCombination (%d) ignored because no cases \n",k);
10421: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
10422: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
10423: continue;
10424: }
1.218 brouard 10425:
1.238 brouard 10426: fprintf(ficresplb,"#Age ");
10427: for(j=1;j<=cptcoveff;j++) {
10428: fprintf(ficresplb,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10429: }
10430: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
10431: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 10432:
10433:
1.238 brouard 10434: for (age=agebase; age<=agelim; age++){
10435: /* for (age=agebase; age<=agebase; age++){ */
10436: if(mobilavproj > 0){
10437: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
10438: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 10439: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 10440: }else if (mobilavproj == 0){
10441: 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);
10442: 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);
10443: exit(1);
10444: }else{
10445: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 10446: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 10447: /* printf("TOTOT\n"); */
10448: /* exit(1); */
1.238 brouard 10449: }
10450: fprintf(ficresplb,"%.0f ",age );
10451: for(j=1;j<=cptcoveff;j++)
10452: fprintf(ficresplb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10453: tot=0.;
10454: for(i=1; i<=nlstate;i++){
10455: tot += bprlim[i][i];
10456: fprintf(ficresplb," %.5f", bprlim[i][i]);
10457: }
10458: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
10459: } /* Age */
10460: /* was end of cptcod */
1.255 brouard 10461: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.238 brouard 10462: } /* end of any combination */
10463: } /* end of nres */
1.218 brouard 10464: /* hBijx(p, bage, fage); */
10465: /* fclose(ficrespijb); */
10466:
10467: return 0;
1.217 brouard 10468: }
1.218 brouard 10469:
1.180 brouard 10470: int hPijx(double *p, int bage, int fage){
10471: /*------------- h Pij x at various ages ------------*/
10472:
10473: int stepsize;
10474: int agelim;
10475: int hstepm;
10476: int nhstepm;
1.235 brouard 10477: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 10478:
10479: double agedeb;
10480: double ***p3mat;
10481:
1.201 brouard 10482: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
1.180 brouard 10483: if((ficrespij=fopen(filerespij,"w"))==NULL) {
10484: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
10485: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
10486: }
10487: printf("Computing pij: result on file '%s' \n", filerespij);
10488: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
10489:
10490: stepsize=(int) (stepm+YEARM-1)/YEARM;
10491: /*if (stepm<=24) stepsize=2;*/
10492:
10493: agelim=AGESUP;
10494: hstepm=stepsize*YEARM; /* Every year of age */
10495: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
1.218 brouard 10496:
1.180 brouard 10497: /* hstepm=1; aff par mois*/
10498: pstamp(ficrespij);
10499: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
1.227 brouard 10500: i1= pow(2,cptcoveff);
1.218 brouard 10501: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10502: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
10503: /* k=k+1; */
1.235 brouard 10504: for(nres=1; nres <= nresult; nres++) /* For each resultline */
10505: for(k=1; k<=i1;k++){
1.253 brouard 10506: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 10507: continue;
1.183 brouard 10508: fprintf(ficrespij,"\n#****** ");
1.227 brouard 10509: for(j=1;j<=cptcoveff;j++)
1.198 brouard 10510: fprintf(ficrespij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 10511: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
10512: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10513: fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10514: }
1.183 brouard 10515: fprintf(ficrespij,"******\n");
10516:
10517: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
10518: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
10519: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
10520:
10521: /* nhstepm=nhstepm*YEARM; aff par mois*/
1.180 brouard 10522:
1.183 brouard 10523: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10524: oldm=oldms;savm=savms;
1.235 brouard 10525: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.183 brouard 10526: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
10527: for(i=1; i<=nlstate;i++)
10528: for(j=1; j<=nlstate+ndeath;j++)
10529: fprintf(ficrespij," %1d-%1d",i,j);
10530: fprintf(ficrespij,"\n");
10531: for (h=0; h<=nhstepm; h++){
10532: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
10533: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.180 brouard 10534: for(i=1; i<=nlstate;i++)
10535: for(j=1; j<=nlstate+ndeath;j++)
1.183 brouard 10536: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.180 brouard 10537: fprintf(ficrespij,"\n");
10538: }
1.183 brouard 10539: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10540: fprintf(ficrespij,"\n");
10541: }
1.180 brouard 10542: /*}*/
10543: }
1.218 brouard 10544: return 0;
1.180 brouard 10545: }
1.218 brouard 10546:
10547: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 10548: /*------------- h Bij x at various ages ------------*/
10549:
10550: int stepsize;
1.218 brouard 10551: /* int agelim; */
10552: int ageminl;
1.217 brouard 10553: int hstepm;
10554: int nhstepm;
1.238 brouard 10555: int h, i, i1, j, k, nres;
1.218 brouard 10556:
1.217 brouard 10557: double agedeb;
10558: double ***p3mat;
1.218 brouard 10559:
10560: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
10561: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
10562: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
10563: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
10564: }
10565: printf("Computing pij back: result on file '%s' \n", filerespijb);
10566: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
10567:
10568: stepsize=(int) (stepm+YEARM-1)/YEARM;
10569: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 10570:
1.218 brouard 10571: /* agelim=AGESUP; */
10572: ageminl=30;
10573: hstepm=stepsize*YEARM; /* Every year of age */
10574: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
10575:
10576: /* hstepm=1; aff par mois*/
10577: pstamp(ficrespijb);
1.255 brouard 10578: 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 10579: i1= pow(2,cptcoveff);
1.218 brouard 10580: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10581: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
10582: /* k=k+1; */
1.238 brouard 10583: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10584: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 10585: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10586: continue;
10587: fprintf(ficrespijb,"\n#****** ");
10588: for(j=1;j<=cptcoveff;j++)
10589: fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10590: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
10591: fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10592: }
10593: fprintf(ficrespijb,"******\n");
1.264 brouard 10594: if(invalidvarcomb[k]){ /* Is it necessary here? */
1.238 brouard 10595: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
10596: continue;
10597: }
10598:
10599: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
10600: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
10601: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
10602: nhstepm=(int) rint((agedeb-ageminl)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
10603: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 */
10604:
10605: /* nhstepm=nhstepm*YEARM; aff par mois*/
10606:
1.266 brouard 10607: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
10608: /* and memory limitations if stepm is small */
10609:
1.238 brouard 10610: /* oldm=oldms;savm=savms; */
10611: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.267 brouard 10612: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.238 brouard 10613: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
1.255 brouard 10614: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
1.217 brouard 10615: for(i=1; i<=nlstate;i++)
10616: for(j=1; j<=nlstate+ndeath;j++)
1.238 brouard 10617: fprintf(ficrespijb," %1d-%1d",i,j);
1.217 brouard 10618: fprintf(ficrespijb,"\n");
1.238 brouard 10619: for (h=0; h<=nhstepm; h++){
10620: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
10621: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
10622: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
10623: for(i=1; i<=nlstate;i++)
10624: for(j=1; j<=nlstate+ndeath;j++)
10625: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);
10626: fprintf(ficrespijb,"\n");
10627: }
10628: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10629: fprintf(ficrespijb,"\n");
10630: } /* end age deb */
10631: } /* end combination */
10632: } /* end nres */
1.218 brouard 10633: return 0;
10634: } /* hBijx */
1.217 brouard 10635:
1.180 brouard 10636:
1.136 brouard 10637: /***********************************************/
10638: /**************** Main Program *****************/
10639: /***********************************************/
10640:
10641: int main(int argc, char *argv[])
10642: {
10643: #ifdef GSL
10644: const gsl_multimin_fminimizer_type *T;
10645: size_t iteri = 0, it;
10646: int rval = GSL_CONTINUE;
10647: int status = GSL_SUCCESS;
10648: double ssval;
10649: #endif
10650: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.164 brouard 10651: int i,j, k, n=MAXN,iter=0,m,size=100, cptcod;
1.209 brouard 10652: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 10653: int jj, ll, li, lj, lk;
1.136 brouard 10654: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 10655: int num_filled;
1.136 brouard 10656: int itimes;
10657: int NDIM=2;
10658: int vpopbased=0;
1.235 brouard 10659: int nres=0;
1.258 brouard 10660: int endishere=0;
1.277 brouard 10661: int noffset=0;
1.274 brouard 10662: int ncurrv=0; /* Temporary variable */
10663:
1.164 brouard 10664: char ca[32], cb[32];
1.136 brouard 10665: /* FILE *fichtm; *//* Html File */
10666: /* FILE *ficgp;*/ /*Gnuplot File */
10667: struct stat info;
1.191 brouard 10668: double agedeb=0.;
1.194 brouard 10669:
10670: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 10671: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 10672:
1.165 brouard 10673: double fret;
1.191 brouard 10674: double dum=0.; /* Dummy variable */
1.136 brouard 10675: double ***p3mat;
1.218 brouard 10676: /* double ***mobaverage; */
1.164 brouard 10677:
10678: char line[MAXLINE];
1.197 brouard 10679: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
10680:
1.234 brouard 10681: char modeltemp[MAXLINE];
1.230 brouard 10682: char resultline[MAXLINE];
10683:
1.136 brouard 10684: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 10685: char *tok, *val; /* pathtot */
1.136 brouard 10686: int firstobs=1, lastobs=10;
1.195 brouard 10687: int c, h , cpt, c2;
1.191 brouard 10688: int jl=0;
10689: int i1, j1, jk, stepsize=0;
1.194 brouard 10690: int count=0;
10691:
1.164 brouard 10692: int *tab;
1.136 brouard 10693: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.217 brouard 10694: int backcast=0;
1.136 brouard 10695: int mobilav=0,popforecast=0;
1.191 brouard 10696: int hstepm=0, nhstepm=0;
1.136 brouard 10697: int agemortsup;
10698: float sumlpop=0.;
10699: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
10700: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
10701:
1.191 brouard 10702: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 10703: double ftolpl=FTOL;
10704: double **prlim;
1.217 brouard 10705: double **bprlim;
1.136 brouard 10706: double ***param; /* Matrix of parameters */
1.251 brouard 10707: double ***paramstart; /* Matrix of starting parameter values */
10708: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 10709: double **matcov; /* Matrix of covariance */
1.203 brouard 10710: double **hess; /* Hessian matrix */
1.136 brouard 10711: double ***delti3; /* Scale */
10712: double *delti; /* Scale */
10713: double ***eij, ***vareij;
10714: double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 10715:
1.136 brouard 10716: double *epj, vepp;
1.164 brouard 10717:
1.273 brouard 10718: double dateprev1, dateprev2;
10719: double jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000, dateproj1=0, dateproj2=0;
10720: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000, dateback1=0, dateback2=0;
1.217 brouard 10721:
1.136 brouard 10722: double **ximort;
1.145 brouard 10723: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 10724: int *dcwave;
10725:
1.164 brouard 10726: char z[1]="c";
1.136 brouard 10727:
10728: /*char *strt;*/
10729: char strtend[80];
1.126 brouard 10730:
1.164 brouard 10731:
1.126 brouard 10732: /* setlocale (LC_ALL, ""); */
10733: /* bindtextdomain (PACKAGE, LOCALEDIR); */
10734: /* textdomain (PACKAGE); */
10735: /* setlocale (LC_CTYPE, ""); */
10736: /* setlocale (LC_MESSAGES, ""); */
10737:
10738: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 10739: rstart_time = time(NULL);
10740: /* (void) gettimeofday(&start_time,&tzp);*/
10741: start_time = *localtime(&rstart_time);
1.126 brouard 10742: curr_time=start_time;
1.157 brouard 10743: /*tml = *localtime(&start_time.tm_sec);*/
10744: /* strcpy(strstart,asctime(&tml)); */
10745: strcpy(strstart,asctime(&start_time));
1.126 brouard 10746:
10747: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 10748: /* tp.tm_sec = tp.tm_sec +86400; */
10749: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 10750: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
10751: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
10752: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 10753: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 10754: /* strt=asctime(&tmg); */
10755: /* printf("Time(after) =%s",strstart); */
10756: /* (void) time (&time_value);
10757: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
10758: * tm = *localtime(&time_value);
10759: * strstart=asctime(&tm);
10760: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
10761: */
10762:
10763: nberr=0; /* Number of errors and warnings */
10764: nbwarn=0;
1.184 brouard 10765: #ifdef WIN32
10766: _getcwd(pathcd, size);
10767: #else
1.126 brouard 10768: getcwd(pathcd, size);
1.184 brouard 10769: #endif
1.191 brouard 10770: syscompilerinfo(0);
1.196 brouard 10771: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 10772: if(argc <=1){
10773: printf("\nEnter the parameter file name: ");
1.205 brouard 10774: if(!fgets(pathr,FILENAMELENGTH,stdin)){
10775: printf("ERROR Empty parameter file name\n");
10776: goto end;
10777: }
1.126 brouard 10778: i=strlen(pathr);
10779: if(pathr[i-1]=='\n')
10780: pathr[i-1]='\0';
1.156 brouard 10781: i=strlen(pathr);
1.205 brouard 10782: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 10783: pathr[i-1]='\0';
1.205 brouard 10784: }
10785: i=strlen(pathr);
10786: if( i==0 ){
10787: printf("ERROR Empty parameter file name\n");
10788: goto end;
10789: }
10790: for (tok = pathr; tok != NULL; ){
1.126 brouard 10791: printf("Pathr |%s|\n",pathr);
10792: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
10793: printf("val= |%s| pathr=%s\n",val,pathr);
10794: strcpy (pathtot, val);
10795: if(pathr[0] == '\0') break; /* Dirty */
10796: }
10797: }
1.281 ! brouard 10798: else if (argc<=2){
! 10799: strcpy(pathtot,argv[1]);
! 10800: }
1.126 brouard 10801: else{
10802: strcpy(pathtot,argv[1]);
1.281 ! brouard 10803: strcpy(z,argv[2]);
! 10804: printf("\nargv[2]=%s z=%c\n",argv[2],z[0]);
1.126 brouard 10805: }
10806: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
10807: /*cygwin_split_path(pathtot,path,optionfile);
10808: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
10809: /* cutv(path,optionfile,pathtot,'\\');*/
10810:
10811: /* Split argv[0], imach program to get pathimach */
10812: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
10813: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
10814: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
10815: /* strcpy(pathimach,argv[0]); */
10816: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
10817: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
10818: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 10819: #ifdef WIN32
10820: _chdir(path); /* Can be a relative path */
10821: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
10822: #else
1.126 brouard 10823: chdir(path); /* Can be a relative path */
1.184 brouard 10824: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
10825: #endif
10826: printf("Current directory %s!\n",pathcd);
1.126 brouard 10827: strcpy(command,"mkdir ");
10828: strcat(command,optionfilefiname);
10829: if((outcmd=system(command)) != 0){
1.169 brouard 10830: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 10831: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
10832: /* fclose(ficlog); */
10833: /* exit(1); */
10834: }
10835: /* if((imk=mkdir(optionfilefiname))<0){ */
10836: /* perror("mkdir"); */
10837: /* } */
10838:
10839: /*-------- arguments in the command line --------*/
10840:
1.186 brouard 10841: /* Main Log file */
1.126 brouard 10842: strcat(filelog, optionfilefiname);
10843: strcat(filelog,".log"); /* */
10844: if((ficlog=fopen(filelog,"w"))==NULL) {
10845: printf("Problem with logfile %s\n",filelog);
10846: goto end;
10847: }
10848: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 10849: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 10850: fprintf(ficlog,"\nEnter the parameter file name: \n");
10851: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
10852: path=%s \n\
10853: optionfile=%s\n\
10854: optionfilext=%s\n\
1.156 brouard 10855: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 10856:
1.197 brouard 10857: syscompilerinfo(1);
1.167 brouard 10858:
1.126 brouard 10859: printf("Local time (at start):%s",strstart);
10860: fprintf(ficlog,"Local time (at start): %s",strstart);
10861: fflush(ficlog);
10862: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 10863: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 10864:
10865: /* */
10866: strcpy(fileres,"r");
10867: strcat(fileres, optionfilefiname);
1.201 brouard 10868: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 10869: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 10870: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 10871:
1.186 brouard 10872: /* Main ---------arguments file --------*/
1.126 brouard 10873:
10874: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 10875: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
10876: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 10877: fflush(ficlog);
1.149 brouard 10878: /* goto end; */
10879: exit(70);
1.126 brouard 10880: }
10881:
10882: strcpy(filereso,"o");
1.201 brouard 10883: strcat(filereso,fileresu);
1.126 brouard 10884: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
10885: printf("Problem with Output resultfile: %s\n", filereso);
10886: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
10887: fflush(ficlog);
10888: goto end;
10889: }
1.278 brouard 10890: /*-------- Rewriting parameter file ----------*/
10891: strcpy(rfileres,"r"); /* "Rparameterfile */
10892: strcat(rfileres,optionfilefiname); /* Parameter file first name */
10893: strcat(rfileres,"."); /* */
10894: strcat(rfileres,optionfilext); /* Other files have txt extension */
10895: if((ficres =fopen(rfileres,"w"))==NULL) {
10896: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
10897: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
10898: fflush(ficlog);
10899: goto end;
10900: }
10901: fprintf(ficres,"#IMaCh %s\n",version);
1.126 brouard 10902:
1.278 brouard 10903:
1.126 brouard 10904: /* Reads comments: lines beginning with '#' */
10905: numlinepar=0;
1.277 brouard 10906: /* Is it a BOM UTF-8 Windows file? */
10907: /* First parameter line */
1.197 brouard 10908: while(fgets(line, MAXLINE, ficpar)) {
1.277 brouard 10909: noffset=0;
10910: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
10911: {
10912: noffset=noffset+3;
10913: printf("# File is an UTF8 Bom.\n"); // 0xBF
10914: }
10915: else if( line[0] == (char)0xFE && line[1] == (char)0xFF)
10916: {
10917: noffset=noffset+2;
10918: printf("# File is an UTF16BE BOM file\n");
10919: }
10920: else if( line[0] == 0 && line[1] == 0)
10921: {
10922: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
10923: noffset=noffset+4;
10924: printf("# File is an UTF16BE BOM file\n");
10925: }
10926: } else{
10927: ;/*printf(" Not a BOM file\n");*/
10928: }
10929:
1.197 brouard 10930: /* If line starts with a # it is a comment */
1.277 brouard 10931: if (line[noffset] == '#') {
1.197 brouard 10932: numlinepar++;
10933: fputs(line,stdout);
10934: fputs(line,ficparo);
1.278 brouard 10935: fputs(line,ficres);
1.197 brouard 10936: fputs(line,ficlog);
10937: continue;
10938: }else
10939: break;
10940: }
10941: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
10942: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
10943: if (num_filled != 5) {
10944: printf("Should be 5 parameters\n");
10945: }
1.126 brouard 10946: numlinepar++;
1.197 brouard 10947: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
10948: }
10949: /* Second parameter line */
10950: while(fgets(line, MAXLINE, ficpar)) {
10951: /* If line starts with a # it is a comment */
10952: if (line[0] == '#') {
10953: numlinepar++;
10954: fputs(line,stdout);
10955: fputs(line,ficparo);
1.278 brouard 10956: fputs(line,ficres);
1.197 brouard 10957: fputs(line,ficlog);
10958: continue;
10959: }else
10960: break;
10961: }
1.223 brouard 10962: 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", \
10963: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
10964: if (num_filled != 11) {
10965: 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 10966: printf("but line=%s\n",line);
1.197 brouard 10967: }
1.223 brouard 10968: 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);
1.126 brouard 10969: }
1.203 brouard 10970: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 10971: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 10972: /* Third parameter line */
10973: while(fgets(line, MAXLINE, ficpar)) {
10974: /* If line starts with a # it is a comment */
10975: if (line[0] == '#') {
10976: numlinepar++;
10977: fputs(line,stdout);
10978: fputs(line,ficparo);
1.278 brouard 10979: fputs(line,ficres);
1.197 brouard 10980: fputs(line,ficlog);
10981: continue;
10982: }else
10983: break;
10984: }
1.201 brouard 10985: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){
1.279 brouard 10986: if (num_filled != 1){
10987: printf("ERROR %d: Model should be at minimum 'model=1+age' %s\n",num_filled, line);
10988: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age' %s\n",num_filled, line);
1.197 brouard 10989: model[0]='\0';
10990: goto end;
10991: }
10992: else{
10993: if (model[0]=='+'){
10994: for(i=1; i<=strlen(model);i++)
10995: modeltemp[i-1]=model[i];
1.201 brouard 10996: strcpy(model,modeltemp);
1.197 brouard 10997: }
10998: }
1.199 brouard 10999: /* printf(" model=1+age%s modeltemp= %s, model=%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 11000: printf("model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 11001: }
11002: /* 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); */
11003: /* numlinepar=numlinepar+3; /\* In general *\/ */
11004: /* 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); */
1.223 brouard 11005: 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);
11006: 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 11007: fflush(ficlog);
1.190 brouard 11008: /* if(model[0]=='#'|| model[0]== '\0'){ */
11009: if(model[0]=='#'){
1.279 brouard 11010: printf("Error in 'model' line: model should start with 'model=1+age+' and end without space \n \
11011: 'model=1+age+' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age' or \n \
11012: 'model=1+age+V1+V2' or 'model=1+age+V1+V2+V1*V2' etc. \n"); \
1.187 brouard 11013: if(mle != -1){
1.279 brouard 11014: 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 11015: exit(1);
11016: }
11017: }
1.126 brouard 11018: while((c=getc(ficpar))=='#' && c!= EOF){
11019: ungetc(c,ficpar);
11020: fgets(line, MAXLINE, ficpar);
11021: numlinepar++;
1.195 brouard 11022: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
11023: z[0]=line[1];
11024: }
11025: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 11026: fputs(line, stdout);
11027: //puts(line);
1.126 brouard 11028: fputs(line,ficparo);
11029: fputs(line,ficlog);
11030: }
11031: ungetc(c,ficpar);
11032:
11033:
1.145 brouard 11034: covar=matrix(0,NCOVMAX,1,n); /**< used in readdata */
1.268 brouard 11035: if(nqv>=1)coqvar=matrix(1,nqv,1,n); /**< Fixed quantitative covariate */
11036: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,1,n); /**< Time varying quantitative covariate */
11037: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,1,n); /**< Time varying covariate (dummy and quantitative)*/
1.136 brouard 11038: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
11039: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
11040: v1+v2*age+v2*v3 makes cptcovn = 3
11041: */
11042: if (strlen(model)>1)
1.187 brouard 11043: 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 11044: else
1.187 brouard 11045: ncovmodel=2; /* Constant and age */
1.133 brouard 11046: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
11047: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 11048: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
11049: 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);
11050: 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);
11051: fflush(stdout);
11052: fclose (ficlog);
11053: goto end;
11054: }
1.126 brouard 11055: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
11056: delti=delti3[1][1];
11057: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
11058: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 11059: /* We could also provide initial parameters values giving by simple logistic regression
11060: * only one way, that is without matrix product. We will have nlstate maximizations */
11061: /* for(i=1;i<nlstate;i++){ */
11062: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
11063: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
11064: /* } */
1.126 brouard 11065: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 11066: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
11067: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 11068: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
11069: fclose (ficparo);
11070: fclose (ficlog);
11071: goto end;
11072: exit(0);
1.220 brouard 11073: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 11074: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 11075: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
11076: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 11077: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
11078: matcov=matrix(1,npar,1,npar);
1.203 brouard 11079: hess=matrix(1,npar,1,npar);
1.220 brouard 11080: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 11081: /* Read guessed parameters */
1.126 brouard 11082: /* Reads comments: lines beginning with '#' */
11083: while((c=getc(ficpar))=='#' && c!= EOF){
11084: ungetc(c,ficpar);
11085: fgets(line, MAXLINE, ficpar);
11086: numlinepar++;
1.141 brouard 11087: fputs(line,stdout);
1.126 brouard 11088: fputs(line,ficparo);
11089: fputs(line,ficlog);
11090: }
11091: ungetc(c,ficpar);
11092:
11093: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 11094: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 11095: for(i=1; i <=nlstate; i++){
1.234 brouard 11096: j=0;
1.126 brouard 11097: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 11098: if(jj==i) continue;
11099: j++;
11100: fscanf(ficpar,"%1d%1d",&i1,&j1);
11101: if ((i1 != i) || (j1 != jj)){
11102: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 11103: It might be a problem of design; if ncovcol and the model are correct\n \
11104: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 11105: exit(1);
11106: }
11107: fprintf(ficparo,"%1d%1d",i1,j1);
11108: if(mle==1)
11109: printf("%1d%1d",i,jj);
11110: fprintf(ficlog,"%1d%1d",i,jj);
11111: for(k=1; k<=ncovmodel;k++){
11112: fscanf(ficpar," %lf",¶m[i][j][k]);
11113: if(mle==1){
11114: printf(" %lf",param[i][j][k]);
11115: fprintf(ficlog," %lf",param[i][j][k]);
11116: }
11117: else
11118: fprintf(ficlog," %lf",param[i][j][k]);
11119: fprintf(ficparo," %lf",param[i][j][k]);
11120: }
11121: fscanf(ficpar,"\n");
11122: numlinepar++;
11123: if(mle==1)
11124: printf("\n");
11125: fprintf(ficlog,"\n");
11126: fprintf(ficparo,"\n");
1.126 brouard 11127: }
11128: }
11129: fflush(ficlog);
1.234 brouard 11130:
1.251 brouard 11131: /* Reads parameters values */
1.126 brouard 11132: p=param[1][1];
1.251 brouard 11133: pstart=paramstart[1][1];
1.126 brouard 11134:
11135: /* Reads comments: lines beginning with '#' */
11136: while((c=getc(ficpar))=='#' && c!= EOF){
11137: ungetc(c,ficpar);
11138: fgets(line, MAXLINE, ficpar);
11139: numlinepar++;
1.141 brouard 11140: fputs(line,stdout);
1.126 brouard 11141: fputs(line,ficparo);
11142: fputs(line,ficlog);
11143: }
11144: ungetc(c,ficpar);
11145:
11146: for(i=1; i <=nlstate; i++){
11147: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 11148: fscanf(ficpar,"%1d%1d",&i1,&j1);
11149: if ( (i1-i) * (j1-j) != 0){
11150: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
11151: exit(1);
11152: }
11153: printf("%1d%1d",i,j);
11154: fprintf(ficparo,"%1d%1d",i1,j1);
11155: fprintf(ficlog,"%1d%1d",i1,j1);
11156: for(k=1; k<=ncovmodel;k++){
11157: fscanf(ficpar,"%le",&delti3[i][j][k]);
11158: printf(" %le",delti3[i][j][k]);
11159: fprintf(ficparo," %le",delti3[i][j][k]);
11160: fprintf(ficlog," %le",delti3[i][j][k]);
11161: }
11162: fscanf(ficpar,"\n");
11163: numlinepar++;
11164: printf("\n");
11165: fprintf(ficparo,"\n");
11166: fprintf(ficlog,"\n");
1.126 brouard 11167: }
11168: }
11169: fflush(ficlog);
1.234 brouard 11170:
1.145 brouard 11171: /* Reads covariance matrix */
1.126 brouard 11172: delti=delti3[1][1];
1.220 brouard 11173:
11174:
1.126 brouard 11175: /* 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 11176:
1.126 brouard 11177: /* Reads comments: lines beginning with '#' */
11178: while((c=getc(ficpar))=='#' && c!= EOF){
11179: ungetc(c,ficpar);
11180: fgets(line, MAXLINE, ficpar);
11181: numlinepar++;
1.141 brouard 11182: fputs(line,stdout);
1.126 brouard 11183: fputs(line,ficparo);
11184: fputs(line,ficlog);
11185: }
11186: ungetc(c,ficpar);
1.220 brouard 11187:
1.126 brouard 11188: matcov=matrix(1,npar,1,npar);
1.203 brouard 11189: hess=matrix(1,npar,1,npar);
1.131 brouard 11190: for(i=1; i <=npar; i++)
11191: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 11192:
1.194 brouard 11193: /* Scans npar lines */
1.126 brouard 11194: for(i=1; i <=npar; i++){
1.226 brouard 11195: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 11196: if(count != 3){
1.226 brouard 11197: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11198: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11199: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11200: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11201: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11202: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11203: exit(1);
1.220 brouard 11204: }else{
1.226 brouard 11205: if(mle==1)
11206: printf("%1d%1d%d",i1,j1,jk);
11207: }
11208: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
11209: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 11210: for(j=1; j <=i; j++){
1.226 brouard 11211: fscanf(ficpar," %le",&matcov[i][j]);
11212: if(mle==1){
11213: printf(" %.5le",matcov[i][j]);
11214: }
11215: fprintf(ficlog," %.5le",matcov[i][j]);
11216: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 11217: }
11218: fscanf(ficpar,"\n");
11219: numlinepar++;
11220: if(mle==1)
1.220 brouard 11221: printf("\n");
1.126 brouard 11222: fprintf(ficlog,"\n");
11223: fprintf(ficparo,"\n");
11224: }
1.194 brouard 11225: /* End of read covariance matrix npar lines */
1.126 brouard 11226: for(i=1; i <=npar; i++)
11227: for(j=i+1;j<=npar;j++)
1.226 brouard 11228: matcov[i][j]=matcov[j][i];
1.126 brouard 11229:
11230: if(mle==1)
11231: printf("\n");
11232: fprintf(ficlog,"\n");
11233:
11234: fflush(ficlog);
11235:
11236: } /* End of mle != -3 */
1.218 brouard 11237:
1.186 brouard 11238: /* Main data
11239: */
1.126 brouard 11240: n= lastobs;
11241: num=lvector(1,n);
11242: moisnais=vector(1,n);
11243: annais=vector(1,n);
11244: moisdc=vector(1,n);
11245: andc=vector(1,n);
1.220 brouard 11246: weight=vector(1,n);
1.126 brouard 11247: agedc=vector(1,n);
11248: cod=ivector(1,n);
1.220 brouard 11249: for(i=1;i<=n;i++){
1.234 brouard 11250: num[i]=0;
11251: moisnais[i]=0;
11252: annais[i]=0;
11253: moisdc[i]=0;
11254: andc[i]=0;
11255: agedc[i]=0;
11256: cod[i]=0;
11257: weight[i]=1.0; /* Equal weights, 1 by default */
11258: }
1.126 brouard 11259: mint=matrix(1,maxwav,1,n);
11260: anint=matrix(1,maxwav,1,n);
1.131 brouard 11261: s=imatrix(1,maxwav+1,1,n); /* s[i][j] health state for wave i and individual j */
1.126 brouard 11262: tab=ivector(1,NCOVMAX);
1.144 brouard 11263: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 11264: 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 11265:
1.136 brouard 11266: /* Reads data from file datafile */
11267: if (readdata(datafile, firstobs, lastobs, &imx)==1)
11268: goto end;
11269:
11270: /* Calculation of the number of parameters from char model */
1.234 brouard 11271: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 11272: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
11273: k=3 V4 Tvar[k=3]= 4 (from V4)
11274: k=2 V1 Tvar[k=2]= 1 (from V1)
11275: k=1 Tvar[1]=2 (from V2)
1.234 brouard 11276: */
11277:
11278: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
11279: TvarsDind=ivector(1,NCOVMAX); /* */
11280: TvarsD=ivector(1,NCOVMAX); /* */
11281: TvarsQind=ivector(1,NCOVMAX); /* */
11282: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 11283: TvarF=ivector(1,NCOVMAX); /* */
11284: TvarFind=ivector(1,NCOVMAX); /* */
11285: TvarV=ivector(1,NCOVMAX); /* */
11286: TvarVind=ivector(1,NCOVMAX); /* */
11287: TvarA=ivector(1,NCOVMAX); /* */
11288: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 11289: TvarFD=ivector(1,NCOVMAX); /* */
11290: TvarFDind=ivector(1,NCOVMAX); /* */
11291: TvarFQ=ivector(1,NCOVMAX); /* */
11292: TvarFQind=ivector(1,NCOVMAX); /* */
11293: TvarVD=ivector(1,NCOVMAX); /* */
11294: TvarVDind=ivector(1,NCOVMAX); /* */
11295: TvarVQ=ivector(1,NCOVMAX); /* */
11296: TvarVQind=ivector(1,NCOVMAX); /* */
11297:
1.230 brouard 11298: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 11299: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 11300: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
11301: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
11302: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.137 brouard 11303: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
11304: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
11305: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
11306: */
11307: /* For model-covariate k tells which data-covariate to use but
11308: because this model-covariate is a construction we invent a new column
11309: ncovcol + k1
11310: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
11311: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 11312: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
11313: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 11314: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
11315: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 11316: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 11317: */
1.145 brouard 11318: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
11319: 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 11320: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
11321: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.145 brouard 11322: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 11323: 4 covariates (3 plus signs)
11324: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
11325: */
1.230 brouard 11326: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 11327: * individual dummy, fixed or varying:
11328: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
11329: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 11330: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
11331: * V1 df, V2 qf, V3 & V4 dv, V5 qv
11332: * Tmodelind[1]@9={9,0,3,2,}*/
11333: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
11334: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 11335: * individual quantitative, fixed or varying:
11336: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
11337: * 3, 1, 0, 0, 0, 0, 0, 0},
11338: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.186 brouard 11339: /* Main decodemodel */
11340:
1.187 brouard 11341:
1.223 brouard 11342: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 11343: goto end;
11344:
1.137 brouard 11345: if((double)(lastobs-imx)/(double)imx > 1.10){
11346: nbwarn++;
11347: 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);
11348: 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);
11349: }
1.136 brouard 11350: /* if(mle==1){*/
1.137 brouard 11351: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
11352: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 11353: }
11354:
11355: /*-calculation of age at interview from date of interview and age at death -*/
11356: agev=matrix(1,maxwav,1,imx);
11357:
11358: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
11359: goto end;
11360:
1.126 brouard 11361:
1.136 brouard 11362: agegomp=(int)agemin;
11363: free_vector(moisnais,1,n);
11364: free_vector(annais,1,n);
1.126 brouard 11365: /* free_matrix(mint,1,maxwav,1,n);
11366: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 11367: /* free_vector(moisdc,1,n); */
11368: /* free_vector(andc,1,n); */
1.145 brouard 11369: /* */
11370:
1.126 brouard 11371: wav=ivector(1,imx);
1.214 brouard 11372: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
11373: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
11374: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
11375: 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.*/
11376: bh=imatrix(1,lastpass-firstpass+2,1,imx);
11377: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 11378:
11379: /* Concatenates waves */
1.214 brouard 11380: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
11381: Death is a valid wave (if date is known).
11382: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
11383: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
11384: and mw[mi+1][i]. dh depends on stepm.
11385: */
11386:
1.126 brouard 11387: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 11388: /* Concatenates waves */
1.145 brouard 11389:
1.215 brouard 11390: free_vector(moisdc,1,n);
11391: free_vector(andc,1,n);
11392:
1.126 brouard 11393: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
11394: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
11395: ncodemax[1]=1;
1.145 brouard 11396: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 11397: cptcoveff=0;
1.220 brouard 11398: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
11399: tricode(&cptcoveff,Tvar,nbcode,imx, Ndum); /**< Fills nbcode[Tvar[j]][l]; */
1.227 brouard 11400: }
11401:
11402: ncovcombmax=pow(2,cptcoveff);
11403: invalidvarcomb=ivector(1, ncovcombmax);
11404: for(i=1;i<ncovcombmax;i++)
11405: invalidvarcomb[i]=0;
11406:
1.211 brouard 11407: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 11408: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 11409: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 11410:
1.200 brouard 11411: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 11412: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 11413: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 11414: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
11415: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
11416: * (currently 0 or 1) in the data.
11417: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
11418: * corresponding modality (h,j).
11419: */
11420:
1.145 brouard 11421: h=0;
11422: /*if (cptcovn > 0) */
1.126 brouard 11423: m=pow(2,cptcoveff);
11424:
1.144 brouard 11425: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 11426: * For k=4 covariates, h goes from 1 to m=2**k
11427: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
11428: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.186 brouard 11429: * h\k 1 2 3 4
1.143 brouard 11430: *______________________________
11431: * 1 i=1 1 i=1 1 i=1 1 i=1 1
11432: * 2 2 1 1 1
11433: * 3 i=2 1 2 1 1
11434: * 4 2 2 1 1
11435: * 5 i=3 1 i=2 1 2 1
11436: * 6 2 1 2 1
11437: * 7 i=4 1 2 2 1
11438: * 8 2 2 2 1
1.197 brouard 11439: * 9 i=5 1 i=3 1 i=2 1 2
11440: * 10 2 1 1 2
11441: * 11 i=6 1 2 1 2
11442: * 12 2 2 1 2
11443: * 13 i=7 1 i=4 1 2 2
11444: * 14 2 1 2 2
11445: * 15 i=8 1 2 2 2
11446: * 16 2 2 2 2
1.143 brouard 11447: */
1.212 brouard 11448: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 11449: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
11450: * and the value of each covariate?
11451: * V1=1, V2=1, V3=2, V4=1 ?
11452: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
11453: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
11454: * In order to get the real value in the data, we use nbcode
11455: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
11456: * We are keeping this crazy system in order to be able (in the future?)
11457: * to have more than 2 values (0 or 1) for a covariate.
11458: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
11459: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
11460: * bbbbbbbb
11461: * 76543210
11462: * h-1 00000101 (6-1=5)
1.219 brouard 11463: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 11464: * &
11465: * 1 00000001 (1)
1.219 brouard 11466: * 00000000 = 1 & ((h-1) >> (k-1))
11467: * +1= 00000001 =1
1.211 brouard 11468: *
11469: * h=14, k=3 => h'=h-1=13, k'=k-1=2
11470: * h' 1101 =2^3+2^2+0x2^1+2^0
11471: * >>k' 11
11472: * & 00000001
11473: * = 00000001
11474: * +1 = 00000010=2 = codtabm(14,3)
11475: * Reverse h=6 and m=16?
11476: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
11477: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
11478: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
11479: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
11480: * V3=decodtabm(14,3,2**4)=2
11481: * h'=13 1101 =2^3+2^2+0x2^1+2^0
11482: *(h-1) >> (j-1) 0011 =13 >> 2
11483: * &1 000000001
11484: * = 000000001
11485: * +1= 000000010 =2
11486: * 2211
11487: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
11488: * V3=2
1.220 brouard 11489: * codtabm and decodtabm are identical
1.211 brouard 11490: */
11491:
1.145 brouard 11492:
11493: free_ivector(Ndum,-1,NCOVMAX);
11494:
11495:
1.126 brouard 11496:
1.186 brouard 11497: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 11498: strcpy(optionfilegnuplot,optionfilefiname);
11499: if(mle==-3)
1.201 brouard 11500: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 11501: strcat(optionfilegnuplot,".gp");
11502:
11503: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
11504: printf("Problem with file %s",optionfilegnuplot);
11505: }
11506: else{
1.204 brouard 11507: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 11508: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 11509: //fprintf(ficgp,"set missing 'NaNq'\n");
11510: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 11511: }
11512: /* fclose(ficgp);*/
1.186 brouard 11513:
11514:
11515: /* Initialisation of --------- index.htm --------*/
1.126 brouard 11516:
11517: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
11518: if(mle==-3)
1.201 brouard 11519: strcat(optionfilehtm,"-MORT_");
1.126 brouard 11520: strcat(optionfilehtm,".htm");
11521: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 11522: printf("Problem with %s \n",optionfilehtm);
11523: exit(0);
1.126 brouard 11524: }
11525:
11526: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
11527: strcat(optionfilehtmcov,"-cov.htm");
11528: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
11529: printf("Problem with %s \n",optionfilehtmcov), exit(0);
11530: }
11531: else{
11532: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
11533: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 11534: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 11535: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
11536: }
11537:
1.213 brouard 11538: 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 11539: <hr size=\"2\" color=\"#EC5E5E\"> \n\
11540: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 11541: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 11542: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n\
1.126 brouard 11543: \n\
11544: <hr size=\"2\" color=\"#EC5E5E\">\
11545: <ul><li><h4>Parameter files</h4>\n\
11546: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
11547: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
11548: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
11549: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
11550: - Date and time at start: %s</ul>\n",\
11551: optionfilehtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model,\
11552: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
11553: fileres,fileres,\
11554: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
11555: fflush(fichtm);
11556:
11557: strcpy(pathr,path);
11558: strcat(pathr,optionfilefiname);
1.184 brouard 11559: #ifdef WIN32
11560: _chdir(optionfilefiname); /* Move to directory named optionfile */
11561: #else
1.126 brouard 11562: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 11563: #endif
11564:
1.126 brouard 11565:
1.220 brouard 11566: /* Calculates basic frequencies. Computes observed prevalence at single age
11567: and for any valid combination of covariates
1.126 brouard 11568: and prints on file fileres'p'. */
1.251 brouard 11569: freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 11570: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 11571:
11572: fprintf(fichtm,"\n");
1.274 brouard 11573: 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",\
11574: ftol, stepm);
11575: fprintf(fichtm,"\n<li>Number of fixed dummy covariates: ncovcol=%d ", ncovcol);
11576: ncurrv=1;
11577: for(i=ncurrv; i <=ncovcol; i++) fprintf(fichtm,"V%d ", i);
11578: fprintf(fichtm,"\n<li> Number of fixed quantitative variables: nqv=%d ", nqv);
11579: ncurrv=i;
11580: for(i=ncurrv; i <=ncurrv-1+nqv; i++) fprintf(fichtm,"V%d ", i);
11581: fprintf(fichtm,"\n<li> Number of time varying (wave varying) covariates: ntv=%d ", ntv);
11582: ncurrv=i;
11583: for(i=ncurrv; i <=ncurrv-1+ntv; i++) fprintf(fichtm,"V%d ", i);
11584: fprintf(fichtm,"\n<li>Number of quantitative time varying covariates: nqtv=%d ", nqtv);
11585: ncurrv=i;
11586: for(i=ncurrv; i <=ncurrv-1+nqtv; i++) fprintf(fichtm,"V%d ", i);
11587: 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", \
11588: nlstate, ndeath, maxwav, mle, weightopt);
11589:
11590: fprintf(fichtm,"<h4> Diagram of states <a href=\"%s_.svg\">%s_.svg</a></h4> \n\
11591: <img src=\"%s_.svg\">", subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"));
11592:
11593:
11594: fprintf(fichtm,"\n<h4>Some descriptive statistics </h4>\n<br>Total number of observations=%d <br>\n\
1.126 brouard 11595: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
11596: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
1.274 brouard 11597: imx,agemin,agemax,jmin,jmax,jmean);
1.126 brouard 11598: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 11599: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11600: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11601: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11602: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 11603:
1.126 brouard 11604: /* For Powell, parameters are in a vector p[] starting at p[1]
11605: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
11606: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
11607:
11608: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 11609: /* For mortality only */
1.126 brouard 11610: if (mle==-3){
1.136 brouard 11611: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 11612: for(i=1;i<=NDIM;i++)
11613: for(j=1;j<=NDIM;j++)
11614: ximort[i][j]=0.;
1.186 brouard 11615: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.126 brouard 11616: cens=ivector(1,n);
11617: ageexmed=vector(1,n);
11618: agecens=vector(1,n);
11619: dcwave=ivector(1,n);
1.223 brouard 11620:
1.126 brouard 11621: for (i=1; i<=imx; i++){
11622: dcwave[i]=-1;
11623: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 11624: if (s[m][i]>nlstate) {
11625: dcwave[i]=m;
11626: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
11627: break;
11628: }
1.126 brouard 11629: }
1.226 brouard 11630:
1.126 brouard 11631: for (i=1; i<=imx; i++) {
11632: if (wav[i]>0){
1.226 brouard 11633: ageexmed[i]=agev[mw[1][i]][i];
11634: j=wav[i];
11635: agecens[i]=1.;
11636:
11637: if (ageexmed[i]> 1 && wav[i] > 0){
11638: agecens[i]=agev[mw[j][i]][i];
11639: cens[i]= 1;
11640: }else if (ageexmed[i]< 1)
11641: cens[i]= -1;
11642: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
11643: cens[i]=0 ;
1.126 brouard 11644: }
11645: else cens[i]=-1;
11646: }
11647:
11648: for (i=1;i<=NDIM;i++) {
11649: for (j=1;j<=NDIM;j++)
1.226 brouard 11650: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 11651: }
11652:
1.145 brouard 11653: /*p[1]=0.0268; p[NDIM]=0.083;*/
1.126 brouard 11654: /*printf("%lf %lf", p[1], p[2]);*/
11655:
11656:
1.136 brouard 11657: #ifdef GSL
11658: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 11659: #else
1.126 brouard 11660: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 11661: #endif
1.201 brouard 11662: strcpy(filerespow,"POW-MORT_");
11663: strcat(filerespow,fileresu);
1.126 brouard 11664: if((ficrespow=fopen(filerespow,"w"))==NULL) {
11665: printf("Problem with resultfile: %s\n", filerespow);
11666: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
11667: }
1.136 brouard 11668: #ifdef GSL
11669: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 11670: #else
1.126 brouard 11671: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 11672: #endif
1.126 brouard 11673: /* for (i=1;i<=nlstate;i++)
11674: for(j=1;j<=nlstate+ndeath;j++)
11675: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
11676: */
11677: fprintf(ficrespow,"\n");
1.136 brouard 11678: #ifdef GSL
11679: /* gsl starts here */
11680: T = gsl_multimin_fminimizer_nmsimplex;
11681: gsl_multimin_fminimizer *sfm = NULL;
11682: gsl_vector *ss, *x;
11683: gsl_multimin_function minex_func;
11684:
11685: /* Initial vertex size vector */
11686: ss = gsl_vector_alloc (NDIM);
11687:
11688: if (ss == NULL){
11689: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
11690: }
11691: /* Set all step sizes to 1 */
11692: gsl_vector_set_all (ss, 0.001);
11693:
11694: /* Starting point */
1.126 brouard 11695:
1.136 brouard 11696: x = gsl_vector_alloc (NDIM);
11697:
11698: if (x == NULL){
11699: gsl_vector_free(ss);
11700: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
11701: }
11702:
11703: /* Initialize method and iterate */
11704: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 11705: /* gsl_vector_set(x, 0, 0.0268); */
11706: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 11707: gsl_vector_set(x, 0, p[1]);
11708: gsl_vector_set(x, 1, p[2]);
11709:
11710: minex_func.f = &gompertz_f;
11711: minex_func.n = NDIM;
11712: minex_func.params = (void *)&p; /* ??? */
11713:
11714: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
11715: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
11716:
11717: printf("Iterations beginning .....\n\n");
11718: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
11719:
11720: iteri=0;
11721: while (rval == GSL_CONTINUE){
11722: iteri++;
11723: status = gsl_multimin_fminimizer_iterate(sfm);
11724:
11725: if (status) printf("error: %s\n", gsl_strerror (status));
11726: fflush(0);
11727:
11728: if (status)
11729: break;
11730:
11731: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
11732: ssval = gsl_multimin_fminimizer_size (sfm);
11733:
11734: if (rval == GSL_SUCCESS)
11735: printf ("converged to a local maximum at\n");
11736:
11737: printf("%5d ", iteri);
11738: for (it = 0; it < NDIM; it++){
11739: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
11740: }
11741: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
11742: }
11743:
11744: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
11745:
11746: gsl_vector_free(x); /* initial values */
11747: gsl_vector_free(ss); /* inital step size */
11748: for (it=0; it<NDIM; it++){
11749: p[it+1]=gsl_vector_get(sfm->x,it);
11750: fprintf(ficrespow," %.12lf", p[it]);
11751: }
11752: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
11753: #endif
11754: #ifdef POWELL
11755: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
11756: #endif
1.126 brouard 11757: fclose(ficrespow);
11758:
1.203 brouard 11759: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 11760:
11761: for(i=1; i <=NDIM; i++)
11762: for(j=i+1;j<=NDIM;j++)
1.220 brouard 11763: matcov[i][j]=matcov[j][i];
1.126 brouard 11764:
11765: printf("\nCovariance matrix\n ");
1.203 brouard 11766: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 11767: for(i=1; i <=NDIM; i++) {
11768: for(j=1;j<=NDIM;j++){
1.220 brouard 11769: printf("%f ",matcov[i][j]);
11770: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 11771: }
1.203 brouard 11772: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 11773: }
11774:
11775: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 11776: for (i=1;i<=NDIM;i++) {
1.126 brouard 11777: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 11778: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
11779: }
1.126 brouard 11780: lsurv=vector(1,AGESUP);
11781: lpop=vector(1,AGESUP);
11782: tpop=vector(1,AGESUP);
11783: lsurv[agegomp]=100000;
11784:
11785: for (k=agegomp;k<=AGESUP;k++) {
11786: agemortsup=k;
11787: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
11788: }
11789:
11790: for (k=agegomp;k<agemortsup;k++)
11791: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
11792:
11793: for (k=agegomp;k<agemortsup;k++){
11794: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
11795: sumlpop=sumlpop+lpop[k];
11796: }
11797:
11798: tpop[agegomp]=sumlpop;
11799: for (k=agegomp;k<(agemortsup-3);k++){
11800: /* tpop[k+1]=2;*/
11801: tpop[k+1]=tpop[k]-lpop[k];
11802: }
11803:
11804:
11805: printf("\nAge lx qx dx Lx Tx e(x)\n");
11806: for (k=agegomp;k<(agemortsup-2);k++)
11807: 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]);
11808:
11809:
11810: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 11811: ageminpar=50;
11812: agemaxpar=100;
1.194 brouard 11813: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
11814: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
11815: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
11816: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
11817: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
11818: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
11819: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 11820: }else{
11821: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
11822: 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 11823: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 11824: }
1.201 brouard 11825: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 11826: stepm, weightopt,\
11827: model,imx,p,matcov,agemortsup);
11828:
11829: free_vector(lsurv,1,AGESUP);
11830: free_vector(lpop,1,AGESUP);
11831: free_vector(tpop,1,AGESUP);
1.220 brouard 11832: free_matrix(ximort,1,NDIM,1,NDIM);
1.136 brouard 11833: free_ivector(cens,1,n);
11834: free_vector(agecens,1,n);
11835: free_ivector(dcwave,1,n);
1.220 brouard 11836: #ifdef GSL
1.136 brouard 11837: #endif
1.186 brouard 11838: } /* Endof if mle==-3 mortality only */
1.205 brouard 11839: /* Standard */
11840: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
11841: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
11842: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 11843: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 11844: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
11845: for (k=1; k<=npar;k++)
11846: printf(" %d %8.5f",k,p[k]);
11847: printf("\n");
1.205 brouard 11848: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
11849: /* mlikeli uses func not funcone */
1.247 brouard 11850: /* for(i=1;i<nlstate;i++){ */
11851: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
11852: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
11853: /* } */
1.205 brouard 11854: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
11855: }
11856: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
11857: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
11858: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
11859: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
11860: }
11861: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 11862: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
11863: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
11864: for (k=1; k<=npar;k++)
11865: printf(" %d %8.5f",k,p[k]);
11866: printf("\n");
11867:
11868: /*--------- results files --------------*/
1.224 brouard 11869: 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 11870:
11871:
11872: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
11873: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
11874: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
11875: for(i=1,jk=1; i <=nlstate; i++){
11876: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 11877: if (k != i) {
11878: printf("%d%d ",i,k);
11879: fprintf(ficlog,"%d%d ",i,k);
11880: fprintf(ficres,"%1d%1d ",i,k);
11881: for(j=1; j <=ncovmodel; j++){
11882: printf("%12.7f ",p[jk]);
11883: fprintf(ficlog,"%12.7f ",p[jk]);
11884: fprintf(ficres,"%12.7f ",p[jk]);
11885: jk++;
11886: }
11887: printf("\n");
11888: fprintf(ficlog,"\n");
11889: fprintf(ficres,"\n");
11890: }
1.126 brouard 11891: }
11892: }
1.203 brouard 11893: if(mle != 0){
11894: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 11895: ftolhess=ftol; /* Usually correct */
1.203 brouard 11896: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
11897: 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");
11898: 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");
11899: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 11900: for(k=1; k <=(nlstate+ndeath); k++){
11901: if (k != i) {
11902: printf("%d%d ",i,k);
11903: fprintf(ficlog,"%d%d ",i,k);
11904: for(j=1; j <=ncovmodel; j++){
11905: 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]));
11906: 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]));
11907: jk++;
11908: }
11909: printf("\n");
11910: fprintf(ficlog,"\n");
11911: }
11912: }
1.193 brouard 11913: }
1.203 brouard 11914: } /* end of hesscov and Wald tests */
1.225 brouard 11915:
1.203 brouard 11916: /* */
1.126 brouard 11917: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
11918: printf("# Scales (for hessian or gradient estimation)\n");
11919: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
11920: for(i=1,jk=1; i <=nlstate; i++){
11921: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 11922: if (j!=i) {
11923: fprintf(ficres,"%1d%1d",i,j);
11924: printf("%1d%1d",i,j);
11925: fprintf(ficlog,"%1d%1d",i,j);
11926: for(k=1; k<=ncovmodel;k++){
11927: printf(" %.5e",delti[jk]);
11928: fprintf(ficlog," %.5e",delti[jk]);
11929: fprintf(ficres," %.5e",delti[jk]);
11930: jk++;
11931: }
11932: printf("\n");
11933: fprintf(ficlog,"\n");
11934: fprintf(ficres,"\n");
11935: }
1.126 brouard 11936: }
11937: }
11938:
11939: 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 11940: if(mle >= 1) /* To big for the screen */
1.126 brouard 11941: 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");
11942: 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");
11943: /* # 121 Var(a12)\n\ */
11944: /* # 122 Cov(b12,a12) Var(b12)\n\ */
11945: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
11946: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
11947: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
11948: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
11949: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
11950: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
11951:
11952:
11953: /* Just to have a covariance matrix which will be more understandable
11954: even is we still don't want to manage dictionary of variables
11955: */
11956: for(itimes=1;itimes<=2;itimes++){
11957: jj=0;
11958: for(i=1; i <=nlstate; i++){
1.225 brouard 11959: for(j=1; j <=nlstate+ndeath; j++){
11960: if(j==i) continue;
11961: for(k=1; k<=ncovmodel;k++){
11962: jj++;
11963: ca[0]= k+'a'-1;ca[1]='\0';
11964: if(itimes==1){
11965: if(mle>=1)
11966: printf("#%1d%1d%d",i,j,k);
11967: fprintf(ficlog,"#%1d%1d%d",i,j,k);
11968: fprintf(ficres,"#%1d%1d%d",i,j,k);
11969: }else{
11970: if(mle>=1)
11971: printf("%1d%1d%d",i,j,k);
11972: fprintf(ficlog,"%1d%1d%d",i,j,k);
11973: fprintf(ficres,"%1d%1d%d",i,j,k);
11974: }
11975: ll=0;
11976: for(li=1;li <=nlstate; li++){
11977: for(lj=1;lj <=nlstate+ndeath; lj++){
11978: if(lj==li) continue;
11979: for(lk=1;lk<=ncovmodel;lk++){
11980: ll++;
11981: if(ll<=jj){
11982: cb[0]= lk +'a'-1;cb[1]='\0';
11983: if(ll<jj){
11984: if(itimes==1){
11985: if(mle>=1)
11986: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
11987: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
11988: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
11989: }else{
11990: if(mle>=1)
11991: printf(" %.5e",matcov[jj][ll]);
11992: fprintf(ficlog," %.5e",matcov[jj][ll]);
11993: fprintf(ficres," %.5e",matcov[jj][ll]);
11994: }
11995: }else{
11996: if(itimes==1){
11997: if(mle>=1)
11998: printf(" Var(%s%1d%1d)",ca,i,j);
11999: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
12000: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
12001: }else{
12002: if(mle>=1)
12003: printf(" %.7e",matcov[jj][ll]);
12004: fprintf(ficlog," %.7e",matcov[jj][ll]);
12005: fprintf(ficres," %.7e",matcov[jj][ll]);
12006: }
12007: }
12008: }
12009: } /* end lk */
12010: } /* end lj */
12011: } /* end li */
12012: if(mle>=1)
12013: printf("\n");
12014: fprintf(ficlog,"\n");
12015: fprintf(ficres,"\n");
12016: numlinepar++;
12017: } /* end k*/
12018: } /*end j */
1.126 brouard 12019: } /* end i */
12020: } /* end itimes */
12021:
12022: fflush(ficlog);
12023: fflush(ficres);
1.225 brouard 12024: while(fgets(line, MAXLINE, ficpar)) {
12025: /* If line starts with a # it is a comment */
12026: if (line[0] == '#') {
12027: numlinepar++;
12028: fputs(line,stdout);
12029: fputs(line,ficparo);
12030: fputs(line,ficlog);
12031: continue;
12032: }else
12033: break;
12034: }
12035:
1.209 brouard 12036: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
12037: /* ungetc(c,ficpar); */
12038: /* fgets(line, MAXLINE, ficpar); */
12039: /* fputs(line,stdout); */
12040: /* fputs(line,ficparo); */
12041: /* } */
12042: /* ungetc(c,ficpar); */
1.126 brouard 12043:
12044: estepm=0;
1.209 brouard 12045: 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 12046:
12047: if (num_filled != 6) {
12048: 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);
12049: 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);
12050: goto end;
12051: }
12052: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
12053: }
12054: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
12055: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
12056:
1.209 brouard 12057: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 12058: if (estepm==0 || estepm < stepm) estepm=stepm;
12059: if (fage <= 2) {
12060: bage = ageminpar;
12061: fage = agemaxpar;
12062: }
12063:
12064: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 12065: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
12066: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 12067:
1.186 brouard 12068: /* Other stuffs, more or less useful */
1.254 brouard 12069: while(fgets(line, MAXLINE, ficpar)) {
12070: /* If line starts with a # it is a comment */
12071: if (line[0] == '#') {
12072: numlinepar++;
12073: fputs(line,stdout);
12074: fputs(line,ficparo);
12075: fputs(line,ficlog);
12076: continue;
12077: }else
12078: break;
12079: }
12080:
12081: 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){
12082:
12083: if (num_filled != 7) {
12084: 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);
12085: 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);
12086: goto end;
12087: }
12088: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
12089: 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);
12090: 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);
12091: 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 12092: }
1.254 brouard 12093:
12094: while(fgets(line, MAXLINE, ficpar)) {
12095: /* If line starts with a # it is a comment */
12096: if (line[0] == '#') {
12097: numlinepar++;
12098: fputs(line,stdout);
12099: fputs(line,ficparo);
12100: fputs(line,ficlog);
12101: continue;
12102: }else
12103: break;
1.126 brouard 12104: }
12105:
12106:
12107: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
12108: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
12109:
1.254 brouard 12110: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
12111: if (num_filled != 1) {
12112: 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);
12113: 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);
12114: goto end;
12115: }
12116: printf("pop_based=%d\n",popbased);
12117: fprintf(ficlog,"pop_based=%d\n",popbased);
12118: fprintf(ficparo,"pop_based=%d\n",popbased);
12119: fprintf(ficres,"pop_based=%d\n",popbased);
12120: }
12121:
1.258 brouard 12122: /* Results */
12123: nresult=0;
12124: do{
12125: if(!fgets(line, MAXLINE, ficpar)){
12126: endishere=1;
12127: parameterline=14;
12128: }else if (line[0] == '#') {
12129: /* If line starts with a # it is a comment */
1.254 brouard 12130: numlinepar++;
12131: fputs(line,stdout);
12132: fputs(line,ficparo);
12133: fputs(line,ficlog);
12134: continue;
1.258 brouard 12135: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
12136: parameterline=11;
12137: else if(sscanf(line,"backcast=%[^\n]\n",modeltemp))
12138: parameterline=12;
12139: else if(sscanf(line,"result:%[^\n]\n",modeltemp))
12140: parameterline=13;
12141: else{
12142: parameterline=14;
1.254 brouard 12143: }
1.258 brouard 12144: switch (parameterline){
12145: case 11:
12146: 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){
12147: if (num_filled != 8) {
12148: 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);
12149: 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);
12150: goto end;
12151: }
12152: 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);
12153: 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);
12154: 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);
12155: 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);
12156: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 12157: dateproj1=anproj1+(mproj1-1)/12.+(jproj1-1)/365.;
12158: dateproj2=anproj2+(mproj2-1)/12.+(jproj2-1)/365.;
12159:
1.258 brouard 12160: }
1.254 brouard 12161: break;
1.258 brouard 12162: case 12:
12163: /*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);*/
12164: 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){
12165: if (num_filled != 8) {
1.262 brouard 12166: 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);
12167: 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 12168: goto end;
12169: }
12170: 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);
12171: 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);
12172: 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);
12173: 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);
12174: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 12175: dateback1=anback1+(mback1-1)/12.+(jback1-1)/365.;
12176: dateback2=anback2+(mback2-1)/12.+(jback2-1)/365.;
1.258 brouard 12177: }
1.230 brouard 12178: break;
1.258 brouard 12179: case 13:
12180: if((num_filled=sscanf(line,"result:%[^\n]\n",resultline)) !=EOF){
12181: if (num_filled == 0){
12182: resultline[0]='\0';
12183: printf("Warning %d: no result line! It should be at minimum 'result: V2=0 V1=1 or result:.\n%s\n", num_filled, line);
12184: 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);
12185: break;
12186: } else if (num_filled != 1){
12187: printf("ERROR %d: result line! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",num_filled, line);
12188: fprintf(ficlog,"ERROR %d: result line! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",num_filled, line);
12189: }
12190: nresult++; /* Sum of resultlines */
12191: printf("Result %d: result=%s\n",nresult, resultline);
12192: if(nresult > MAXRESULTLINES){
12193: printf("ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\n",MAXRESULTLINES,nresult);
12194: fprintf(ficlog,"ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\n",MAXRESULTLINES,nresult);
12195: goto end;
12196: }
12197: decoderesult(resultline, nresult); /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
12198: fprintf(ficparo,"result: %s\n",resultline);
12199: fprintf(ficres,"result: %s\n",resultline);
12200: fprintf(ficlog,"result: %s\n",resultline);
1.230 brouard 12201: break;
1.258 brouard 12202: case 14:
1.259 brouard 12203: if(ncovmodel >2 && nresult==0 ){
12204: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 12205: goto end;
12206: }
1.259 brouard 12207: break;
1.258 brouard 12208: default:
12209: nresult=1;
12210: decoderesult(".",nresult ); /* No covariate */
12211: }
12212: } /* End switch parameterline */
12213: }while(endishere==0); /* End do */
1.126 brouard 12214:
1.230 brouard 12215: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 12216: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 12217:
12218: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 12219: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 12220: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 12221: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12222: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 12223: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 12224: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12225: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 12226: }else{
1.270 brouard 12227: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
12228: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, backcast, pathc,p, (int)anproj1-bage, (int)anback1-fage);
1.220 brouard 12229: }
12230: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.258 brouard 12231: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,backcast, estepm, \
1.273 brouard 12232: jprev1,mprev1,anprev1,dateprev1, dateproj1, dateback1,jprev2,mprev2,anprev2,dateprev2,dateproj2, dateback2);
1.220 brouard 12233:
1.225 brouard 12234: /*------------ free_vector -------------*/
12235: /* chdir(path); */
1.220 brouard 12236:
1.215 brouard 12237: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
12238: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
12239: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
12240: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.126 brouard 12241: free_lvector(num,1,n);
12242: free_vector(agedc,1,n);
12243: /*free_matrix(covar,0,NCOVMAX,1,n);*/
12244: /*free_matrix(covar,1,NCOVMAX,1,n);*/
12245: fclose(ficparo);
12246: fclose(ficres);
1.220 brouard 12247:
12248:
1.186 brouard 12249: /* Other results (useful)*/
1.220 brouard 12250:
12251:
1.126 brouard 12252: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 12253: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
12254: prlim=matrix(1,nlstate,1,nlstate);
1.209 brouard 12255: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 12256: fclose(ficrespl);
12257:
12258: /*------------- h Pij x at various ages ------------*/
1.180 brouard 12259: /*#include "hpijx.h"*/
12260: hPijx(p, bage, fage);
1.145 brouard 12261: fclose(ficrespij);
1.227 brouard 12262:
1.220 brouard 12263: /* ncovcombmax= pow(2,cptcoveff); */
1.219 brouard 12264: /*-------------- Variance of one-step probabilities---*/
1.145 brouard 12265: k=1;
1.126 brouard 12266: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 12267:
1.269 brouard 12268: /* Prevalence for each covariate combination in probs[age][status][cov] */
12269: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
12270: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 12271: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 12272: for(k=1;k<=ncovcombmax;k++)
12273: probs[i][j][k]=0.;
1.269 brouard 12274: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
12275: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 12276: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 12277: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
12278: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 12279: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 12280: for(k=1;k<=ncovcombmax;k++)
12281: mobaverages[i][j][k]=0.;
1.219 brouard 12282: mobaverage=mobaverages;
12283: if (mobilav!=0) {
1.235 brouard 12284: printf("Movingaveraging observed prevalence\n");
1.258 brouard 12285: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 12286: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
12287: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
12288: printf(" Error in movingaverage mobilav=%d\n",mobilav);
12289: }
1.269 brouard 12290: } else if (mobilavproj !=0) {
1.235 brouard 12291: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 12292: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 12293: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
12294: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
12295: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
12296: }
1.269 brouard 12297: }else{
12298: printf("Internal error moving average\n");
12299: fflush(stdout);
12300: exit(1);
1.219 brouard 12301: }
12302: }/* end if moving average */
1.227 brouard 12303:
1.126 brouard 12304: /*---------- Forecasting ------------------*/
12305: if(prevfcast==1){
12306: /* if(stepm ==1){*/
1.269 brouard 12307: prevforecast(fileresu, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);
1.126 brouard 12308: }
1.269 brouard 12309:
12310: /* Backcasting */
1.217 brouard 12311: if(backcast==1){
1.219 brouard 12312: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12313: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12314: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12315:
12316: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
12317:
12318: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 12319:
1.219 brouard 12320: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
12321: fclose(ficresplb);
12322:
1.222 brouard 12323: hBijx(p, bage, fage, mobaverage);
12324: fclose(ficrespijb);
1.219 brouard 12325:
1.269 brouard 12326: prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2,
12327: mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff);
12328: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 12329:
12330:
1.269 brouard 12331: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 12332: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
12333: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
12334: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.269 brouard 12335: } /* end Backcasting */
1.268 brouard 12336:
1.186 brouard 12337:
12338: /* ------ Other prevalence ratios------------ */
1.126 brouard 12339:
1.215 brouard 12340: free_ivector(wav,1,imx);
12341: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
12342: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
12343: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 12344:
12345:
1.127 brouard 12346: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 12347:
1.201 brouard 12348: strcpy(filerese,"E_");
12349: strcat(filerese,fileresu);
1.126 brouard 12350: if((ficreseij=fopen(filerese,"w"))==NULL) {
12351: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
12352: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
12353: }
1.208 brouard 12354: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
12355: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 12356:
12357: pstamp(ficreseij);
1.219 brouard 12358:
1.235 brouard 12359: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
12360: if (cptcovn < 1){i1=1;}
12361:
12362: for(nres=1; nres <= nresult; nres++) /* For each resultline */
12363: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 12364: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 12365: continue;
1.219 brouard 12366: fprintf(ficreseij,"\n#****** ");
1.235 brouard 12367: printf("\n#****** ");
1.225 brouard 12368: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 12369: fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 12370: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12371: }
12372: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12373: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12374: fprintf(ficreseij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
1.219 brouard 12375: }
12376: fprintf(ficreseij,"******\n");
1.235 brouard 12377: printf("******\n");
1.219 brouard 12378:
12379: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12380: oldm=oldms;savm=savms;
1.235 brouard 12381: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 12382:
1.219 brouard 12383: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 12384: }
12385: fclose(ficreseij);
1.208 brouard 12386: printf("done evsij\n");fflush(stdout);
12387: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 12388:
1.218 brouard 12389:
1.227 brouard 12390: /*---------- State-specific expectancies and variances ------------*/
1.218 brouard 12391:
1.201 brouard 12392: strcpy(filerest,"T_");
12393: strcat(filerest,fileresu);
1.127 brouard 12394: if((ficrest=fopen(filerest,"w"))==NULL) {
12395: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
12396: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
12397: }
1.208 brouard 12398: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
12399: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 12400: strcpy(fileresstde,"STDE_");
12401: strcat(fileresstde,fileresu);
1.126 brouard 12402: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 12403: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
12404: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 12405: }
1.227 brouard 12406: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
12407: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 12408:
1.201 brouard 12409: strcpy(filerescve,"CVE_");
12410: strcat(filerescve,fileresu);
1.126 brouard 12411: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 12412: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
12413: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 12414: }
1.227 brouard 12415: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
12416: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 12417:
1.201 brouard 12418: strcpy(fileresv,"V_");
12419: strcat(fileresv,fileresu);
1.126 brouard 12420: if((ficresvij=fopen(fileresv,"w"))==NULL) {
12421: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
12422: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
12423: }
1.227 brouard 12424: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
12425: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 12426:
1.235 brouard 12427: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
12428: if (cptcovn < 1){i1=1;}
12429:
12430: for(nres=1; nres <= nresult; nres++) /* For each resultline */
12431: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 12432: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 12433: continue;
1.242 brouard 12434: printf("\n#****** Result for:");
12435: fprintf(ficrest,"\n#****** Result for:");
12436: fprintf(ficlog,"\n#****** Result for:");
1.227 brouard 12437: for(j=1;j<=cptcoveff;j++){
12438: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12439: fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12440: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12441: }
1.235 brouard 12442: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12443: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12444: fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12445: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12446: }
1.208 brouard 12447: fprintf(ficrest,"******\n");
1.227 brouard 12448: fprintf(ficlog,"******\n");
12449: printf("******\n");
1.208 brouard 12450:
12451: fprintf(ficresstdeij,"\n#****** ");
12452: fprintf(ficrescveij,"\n#****** ");
1.225 brouard 12453: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 12454: fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12455: fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.208 brouard 12456: }
1.235 brouard 12457: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12458: fprintf(ficresstdeij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12459: fprintf(ficrescveij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12460: }
1.208 brouard 12461: fprintf(ficresstdeij,"******\n");
12462: fprintf(ficrescveij,"******\n");
12463:
12464: fprintf(ficresvij,"\n#****** ");
1.238 brouard 12465: /* pstamp(ficresvij); */
1.225 brouard 12466: for(j=1;j<=cptcoveff;j++)
1.227 brouard 12467: fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 12468: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12469: fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12470: }
1.208 brouard 12471: fprintf(ficresvij,"******\n");
12472:
12473: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12474: oldm=oldms;savm=savms;
1.235 brouard 12475: printf(" cvevsij ");
12476: fprintf(ficlog, " cvevsij ");
12477: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 12478: printf(" end cvevsij \n ");
12479: fprintf(ficlog, " end cvevsij \n ");
12480:
12481: /*
12482: */
12483: /* goto endfree; */
12484:
12485: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12486: pstamp(ficrest);
12487:
1.269 brouard 12488: epj=vector(1,nlstate+1);
1.208 brouard 12489: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 12490: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
12491: cptcod= 0; /* To be deleted */
12492: printf("varevsij vpopbased=%d \n",vpopbased);
12493: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 12494: 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 12495: 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 ");
12496: if(vpopbased==1)
12497: 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);
12498: else
12499: fprintf(ficrest,"the age specific period (stable) prevalences in each health state \n");
12500: fprintf(ficrest,"# Age popbased mobilav e.. (std) ");
12501: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
12502: fprintf(ficrest,"\n");
12503: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
12504: printf("Computing age specific period (stable) prevalences in each health state \n");
12505: fprintf(ficlog,"Computing age specific period (stable) prevalences in each health state \n");
12506: for(age=bage; age <=fage ;age++){
1.235 brouard 12507: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 12508: if (vpopbased==1) {
12509: if(mobilav ==0){
12510: for(i=1; i<=nlstate;i++)
12511: prlim[i][i]=probs[(int)age][i][k];
12512: }else{ /* mobilav */
12513: for(i=1; i<=nlstate;i++)
12514: prlim[i][i]=mobaverage[(int)age][i][k];
12515: }
12516: }
1.219 brouard 12517:
1.227 brouard 12518: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
12519: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
12520: /* printf(" age %4.0f ",age); */
12521: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
12522: for(i=1, epj[j]=0.;i <=nlstate;i++) {
12523: epj[j] += prlim[i][i]*eij[i][j][(int)age];
12524: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
12525: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
12526: }
12527: epj[nlstate+1] +=epj[j];
12528: }
12529: /* printf(" age %4.0f \n",age); */
1.219 brouard 12530:
1.227 brouard 12531: for(i=1, vepp=0.;i <=nlstate;i++)
12532: for(j=1;j <=nlstate;j++)
12533: vepp += vareij[i][j][(int)age];
12534: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
12535: for(j=1;j <=nlstate;j++){
12536: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
12537: }
12538: fprintf(ficrest,"\n");
12539: }
1.208 brouard 12540: } /* End vpopbased */
1.269 brouard 12541: free_vector(epj,1,nlstate+1);
1.208 brouard 12542: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
12543: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 12544: printf("done selection\n");fflush(stdout);
12545: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 12546:
1.235 brouard 12547: } /* End k selection */
1.227 brouard 12548:
12549: printf("done State-specific expectancies\n");fflush(stdout);
12550: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
12551:
1.269 brouard 12552: /* variance-covariance of period prevalence*/
12553: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 12554:
1.227 brouard 12555:
12556: free_vector(weight,1,n);
12557: free_imatrix(Tvard,1,NCOVMAX,1,2);
12558: free_imatrix(s,1,maxwav+1,1,n);
12559: free_matrix(anint,1,maxwav,1,n);
12560: free_matrix(mint,1,maxwav,1,n);
12561: free_ivector(cod,1,n);
12562: free_ivector(tab,1,NCOVMAX);
12563: fclose(ficresstdeij);
12564: fclose(ficrescveij);
12565: fclose(ficresvij);
12566: fclose(ficrest);
12567: fclose(ficpar);
12568:
12569:
1.126 brouard 12570: /*---------- End : free ----------------*/
1.219 brouard 12571: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 12572: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
12573: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 12574: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
12575: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 12576: } /* mle==-3 arrives here for freeing */
1.227 brouard 12577: /* endfree:*/
12578: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
12579: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
12580: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.268 brouard 12581: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,1,n);
12582: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,1,n);
12583: if(nqv>=1)free_matrix(coqvar,1,nqv,1,n);
1.227 brouard 12584: free_matrix(covar,0,NCOVMAX,1,n);
12585: free_matrix(matcov,1,npar,1,npar);
12586: free_matrix(hess,1,npar,1,npar);
12587: /*free_vector(delti,1,npar);*/
12588: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
12589: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 12590: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 12591: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
12592:
12593: free_ivector(ncodemax,1,NCOVMAX);
12594: free_ivector(ncodemaxwundef,1,NCOVMAX);
12595: free_ivector(Dummy,-1,NCOVMAX);
12596: free_ivector(Fixed,-1,NCOVMAX);
1.238 brouard 12597: free_ivector(DummyV,1,NCOVMAX);
12598: free_ivector(FixedV,1,NCOVMAX);
1.227 brouard 12599: free_ivector(Typevar,-1,NCOVMAX);
12600: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 12601: free_ivector(TvarsQ,1,NCOVMAX);
12602: free_ivector(TvarsQind,1,NCOVMAX);
12603: free_ivector(TvarsD,1,NCOVMAX);
12604: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 12605: free_ivector(TvarFD,1,NCOVMAX);
12606: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 12607: free_ivector(TvarF,1,NCOVMAX);
12608: free_ivector(TvarFind,1,NCOVMAX);
12609: free_ivector(TvarV,1,NCOVMAX);
12610: free_ivector(TvarVind,1,NCOVMAX);
12611: free_ivector(TvarA,1,NCOVMAX);
12612: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 12613: free_ivector(TvarFQ,1,NCOVMAX);
12614: free_ivector(TvarFQind,1,NCOVMAX);
12615: free_ivector(TvarVD,1,NCOVMAX);
12616: free_ivector(TvarVDind,1,NCOVMAX);
12617: free_ivector(TvarVQ,1,NCOVMAX);
12618: free_ivector(TvarVQind,1,NCOVMAX);
1.230 brouard 12619: free_ivector(Tvarsel,1,NCOVMAX);
12620: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 12621: free_ivector(Tposprod,1,NCOVMAX);
12622: free_ivector(Tprod,1,NCOVMAX);
12623: free_ivector(Tvaraff,1,NCOVMAX);
12624: free_ivector(invalidvarcomb,1,ncovcombmax);
12625: free_ivector(Tage,1,NCOVMAX);
12626: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 12627: free_ivector(TmodelInvind,1,NCOVMAX);
12628: free_ivector(TmodelInvQind,1,NCOVMAX);
1.227 brouard 12629:
12630: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
12631: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 12632: fflush(fichtm);
12633: fflush(ficgp);
12634:
1.227 brouard 12635:
1.126 brouard 12636: if((nberr >0) || (nbwarn>0)){
1.216 brouard 12637: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
12638: 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 12639: }else{
12640: printf("End of Imach\n");
12641: fprintf(ficlog,"End of Imach\n");
12642: }
12643: printf("See log file on %s\n",filelog);
12644: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 12645: /*(void) gettimeofday(&end_time,&tzp);*/
12646: rend_time = time(NULL);
12647: end_time = *localtime(&rend_time);
12648: /* tml = *localtime(&end_time.tm_sec); */
12649: strcpy(strtend,asctime(&end_time));
1.126 brouard 12650: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
12651: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 12652: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 12653:
1.157 brouard 12654: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
12655: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
12656: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 12657: /* printf("Total time was %d uSec.\n", total_usecs);*/
12658: /* if(fileappend(fichtm,optionfilehtm)){ */
12659: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
12660: fclose(fichtm);
12661: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
12662: fclose(fichtmcov);
12663: fclose(ficgp);
12664: fclose(ficlog);
12665: /*------ End -----------*/
1.227 brouard 12666:
1.281 ! brouard 12667:
! 12668: /* Executes gnuplot */
1.227 brouard 12669:
12670: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 12671: #ifdef WIN32
1.227 brouard 12672: if (_chdir(pathcd) != 0)
12673: printf("Can't move to directory %s!\n",path);
12674: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 12675: #else
1.227 brouard 12676: if(chdir(pathcd) != 0)
12677: printf("Can't move to directory %s!\n", path);
12678: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 12679: #endif
1.126 brouard 12680: printf("Current directory %s!\n",pathcd);
12681: /*strcat(plotcmd,CHARSEPARATOR);*/
12682: sprintf(plotcmd,"gnuplot");
1.157 brouard 12683: #ifdef _WIN32
1.126 brouard 12684: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
12685: #endif
12686: if(!stat(plotcmd,&info)){
1.158 brouard 12687: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 12688: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 12689: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 12690: }else
12691: strcpy(pplotcmd,plotcmd);
1.157 brouard 12692: #ifdef __unix
1.126 brouard 12693: strcpy(plotcmd,GNUPLOTPROGRAM);
12694: if(!stat(plotcmd,&info)){
1.158 brouard 12695: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 12696: }else
12697: strcpy(pplotcmd,plotcmd);
12698: #endif
12699: }else
12700: strcpy(pplotcmd,plotcmd);
12701:
12702: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 12703: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.227 brouard 12704:
1.126 brouard 12705: if((outcmd=system(plotcmd)) != 0){
1.158 brouard 12706: printf("gnuplot command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 12707: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 12708: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.150 brouard 12709: if((outcmd=system(plotcmd)) != 0)
1.153 brouard 12710: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.126 brouard 12711: }
1.158 brouard 12712: printf(" Successful, please wait...");
1.126 brouard 12713: while (z[0] != 'q') {
12714: /* chdir(path); */
1.154 brouard 12715: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 12716: scanf("%s",z);
12717: /* if (z[0] == 'c') system("./imach"); */
12718: if (z[0] == 'e') {
1.158 brouard 12719: #ifdef __APPLE__
1.152 brouard 12720: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 12721: #elif __linux
12722: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 12723: #else
1.152 brouard 12724: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 12725: #endif
12726: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
12727: system(pplotcmd);
1.126 brouard 12728: }
12729: else if (z[0] == 'g') system(plotcmd);
12730: else if (z[0] == 'q') exit(0);
12731: }
1.227 brouard 12732: end:
1.126 brouard 12733: while (z[0] != 'q') {
1.195 brouard 12734: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 12735: scanf("%s",z);
12736: }
12737: }
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