Annotation of imach/src/imach.c, revision 1.304
1.304 ! brouard 1: /* $Id: imach.c,v 1.303 2021/02/11 19:50:15 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.304 ! brouard 4: Revision 1.303 2021/02/11 19:50:15 brouard
! 5: * (Module): imach.c Someone entered 'results:' instead of 'result:'. Now it is an error which is printed.
! 6:
1.303 brouard 7: Revision 1.302 2020/02/22 21:00:05 brouard
8: * (Module): imach.c Update mle=-3 (for computing Life expectancy
9: and life table from the data without any state)
10:
1.302 brouard 11: Revision 1.301 2019/06/04 13:51:20 brouard
12: Summary: Error in 'r'parameter file backcast yearsbproj instead of yearsfproj
13:
1.301 brouard 14: Revision 1.300 2019/05/22 19:09:45 brouard
15: Summary: version 0.99r19 of May 2019
16:
1.300 brouard 17: Revision 1.299 2019/05/22 18:37:08 brouard
18: Summary: Cleaned 0.99r19
19:
1.299 brouard 20: Revision 1.298 2019/05/22 18:19:56 brouard
21: *** empty log message ***
22:
1.298 brouard 23: Revision 1.297 2019/05/22 17:56:10 brouard
24: Summary: Fix bug by moving date2dmy and nhstepm which gaefin=-1
25:
1.297 brouard 26: Revision 1.296 2019/05/20 13:03:18 brouard
27: Summary: Projection syntax simplified
28:
29:
30: We can now start projections, forward or backward, from the mean date
31: of inteviews up to or down to a number of years of projection:
32: prevforecast=1 yearsfproj=15.3 mobil_average=0
33: or
34: prevforecast=1 starting-proj-date=1/1/2007 final-proj-date=12/31/2017 mobil_average=0
35: or
36: prevbackcast=1 yearsbproj=12.3 mobil_average=1
37: or
38: prevbackcast=1 starting-back-date=1/10/1999 final-back-date=1/1/1985 mobil_average=1
39:
1.296 brouard 40: Revision 1.295 2019/05/18 09:52:50 brouard
41: Summary: doxygen tex bug
42:
1.295 brouard 43: Revision 1.294 2019/05/16 14:54:33 brouard
44: Summary: There was some wrong lines added
45:
1.294 brouard 46: Revision 1.293 2019/05/09 15:17:34 brouard
47: *** empty log message ***
48:
1.293 brouard 49: Revision 1.292 2019/05/09 14:17:20 brouard
50: Summary: Some updates
51:
1.292 brouard 52: Revision 1.291 2019/05/09 13:44:18 brouard
53: Summary: Before ncovmax
54:
1.291 brouard 55: Revision 1.290 2019/05/09 13:39:37 brouard
56: Summary: 0.99r18 unlimited number of individuals
57:
58: The number n which was limited to 20,000 cases is now unlimited, from firstobs to lastobs. If the number is too for the virtual memory, probably an error will occur.
59:
1.290 brouard 60: Revision 1.289 2018/12/13 09:16:26 brouard
61: Summary: Bug for young ages (<-30) will be in r17
62:
1.289 brouard 63: Revision 1.288 2018/05/02 20:58:27 brouard
64: Summary: Some bugs fixed
65:
1.288 brouard 66: Revision 1.287 2018/05/01 17:57:25 brouard
67: Summary: Bug fixed by providing frequencies only for non missing covariates
68:
1.287 brouard 69: Revision 1.286 2018/04/27 14:27:04 brouard
70: Summary: some minor bugs
71:
1.286 brouard 72: Revision 1.285 2018/04/21 21:02:16 brouard
73: Summary: Some bugs fixed, valgrind tested
74:
1.285 brouard 75: Revision 1.284 2018/04/20 05:22:13 brouard
76: Summary: Computing mean and stdeviation of fixed quantitative variables
77:
1.284 brouard 78: Revision 1.283 2018/04/19 14:49:16 brouard
79: Summary: Some minor bugs fixed
80:
1.283 brouard 81: Revision 1.282 2018/02/27 22:50:02 brouard
82: *** empty log message ***
83:
1.282 brouard 84: Revision 1.281 2018/02/27 19:25:23 brouard
85: Summary: Adding second argument for quitting
86:
1.281 brouard 87: Revision 1.280 2018/02/21 07:58:13 brouard
88: Summary: 0.99r15
89:
90: New Makefile with recent VirtualBox 5.26. Bug in sqrt negatve in imach.c
91:
1.280 brouard 92: Revision 1.279 2017/07/20 13:35:01 brouard
93: Summary: temporary working
94:
1.279 brouard 95: Revision 1.278 2017/07/19 14:09:02 brouard
96: Summary: Bug for mobil_average=0 and prevforecast fixed(?)
97:
1.278 brouard 98: Revision 1.277 2017/07/17 08:53:49 brouard
99: Summary: BOM files can be read now
100:
1.277 brouard 101: Revision 1.276 2017/06/30 15:48:31 brouard
102: Summary: Graphs improvements
103:
1.276 brouard 104: Revision 1.275 2017/06/30 13:39:33 brouard
105: Summary: Saito's color
106:
1.275 brouard 107: Revision 1.274 2017/06/29 09:47:08 brouard
108: Summary: Version 0.99r14
109:
1.274 brouard 110: Revision 1.273 2017/06/27 11:06:02 brouard
111: Summary: More documentation on projections
112:
1.273 brouard 113: Revision 1.272 2017/06/27 10:22:40 brouard
114: Summary: Color of backprojection changed from 6 to 5(yellow)
115:
1.272 brouard 116: Revision 1.271 2017/06/27 10:17:50 brouard
117: Summary: Some bug with rint
118:
1.271 brouard 119: Revision 1.270 2017/05/24 05:45:29 brouard
120: *** empty log message ***
121:
1.270 brouard 122: Revision 1.269 2017/05/23 08:39:25 brouard
123: Summary: Code into subroutine, cleanings
124:
1.269 brouard 125: Revision 1.268 2017/05/18 20:09:32 brouard
126: Summary: backprojection and confidence intervals of backprevalence
127:
1.268 brouard 128: Revision 1.267 2017/05/13 10:25:05 brouard
129: Summary: temporary save for backprojection
130:
1.267 brouard 131: Revision 1.266 2017/05/13 07:26:12 brouard
132: Summary: Version 0.99r13 (improvements and bugs fixed)
133:
1.266 brouard 134: Revision 1.265 2017/04/26 16:22:11 brouard
135: Summary: imach 0.99r13 Some bugs fixed
136:
1.265 brouard 137: Revision 1.264 2017/04/26 06:01:29 brouard
138: Summary: Labels in graphs
139:
1.264 brouard 140: Revision 1.263 2017/04/24 15:23:15 brouard
141: Summary: to save
142:
1.263 brouard 143: Revision 1.262 2017/04/18 16:48:12 brouard
144: *** empty log message ***
145:
1.262 brouard 146: Revision 1.261 2017/04/05 10:14:09 brouard
147: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
148:
1.261 brouard 149: Revision 1.260 2017/04/04 17:46:59 brouard
150: Summary: Gnuplot indexations fixed (humm)
151:
1.260 brouard 152: Revision 1.259 2017/04/04 13:01:16 brouard
153: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
154:
1.259 brouard 155: Revision 1.258 2017/04/03 10:17:47 brouard
156: Summary: Version 0.99r12
157:
158: Some cleanings, conformed with updated documentation.
159:
1.258 brouard 160: Revision 1.257 2017/03/29 16:53:30 brouard
161: Summary: Temp
162:
1.257 brouard 163: Revision 1.256 2017/03/27 05:50:23 brouard
164: Summary: Temporary
165:
1.256 brouard 166: Revision 1.255 2017/03/08 16:02:28 brouard
167: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
168:
1.255 brouard 169: Revision 1.254 2017/03/08 07:13:00 brouard
170: Summary: Fixing data parameter line
171:
1.254 brouard 172: Revision 1.253 2016/12/15 11:59:41 brouard
173: Summary: 0.99 in progress
174:
1.253 brouard 175: Revision 1.252 2016/09/15 21:15:37 brouard
176: *** empty log message ***
177:
1.252 brouard 178: Revision 1.251 2016/09/15 15:01:13 brouard
179: Summary: not working
180:
1.251 brouard 181: Revision 1.250 2016/09/08 16:07:27 brouard
182: Summary: continue
183:
1.250 brouard 184: Revision 1.249 2016/09/07 17:14:18 brouard
185: Summary: Starting values from frequencies
186:
1.249 brouard 187: Revision 1.248 2016/09/07 14:10:18 brouard
188: *** empty log message ***
189:
1.248 brouard 190: Revision 1.247 2016/09/02 11:11:21 brouard
191: *** empty log message ***
192:
1.247 brouard 193: Revision 1.246 2016/09/02 08:49:22 brouard
194: *** empty log message ***
195:
1.246 brouard 196: Revision 1.245 2016/09/02 07:25:01 brouard
197: *** empty log message ***
198:
1.245 brouard 199: Revision 1.244 2016/09/02 07:17:34 brouard
200: *** empty log message ***
201:
1.244 brouard 202: Revision 1.243 2016/09/02 06:45:35 brouard
203: *** empty log message ***
204:
1.243 brouard 205: Revision 1.242 2016/08/30 15:01:20 brouard
206: Summary: Fixing a lots
207:
1.242 brouard 208: Revision 1.241 2016/08/29 17:17:25 brouard
209: Summary: gnuplot problem in Back projection to fix
210:
1.241 brouard 211: Revision 1.240 2016/08/29 07:53:18 brouard
212: Summary: Better
213:
1.240 brouard 214: Revision 1.239 2016/08/26 15:51:03 brouard
215: Summary: Improvement in Powell output in order to copy and paste
216:
217: Author:
218:
1.239 brouard 219: Revision 1.238 2016/08/26 14:23:35 brouard
220: Summary: Starting tests of 0.99
221:
1.238 brouard 222: Revision 1.237 2016/08/26 09:20:19 brouard
223: Summary: to valgrind
224:
1.237 brouard 225: Revision 1.236 2016/08/25 10:50:18 brouard
226: *** empty log message ***
227:
1.236 brouard 228: Revision 1.235 2016/08/25 06:59:23 brouard
229: *** empty log message ***
230:
1.235 brouard 231: Revision 1.234 2016/08/23 16:51:20 brouard
232: *** empty log message ***
233:
1.234 brouard 234: Revision 1.233 2016/08/23 07:40:50 brouard
235: Summary: not working
236:
1.233 brouard 237: Revision 1.232 2016/08/22 14:20:21 brouard
238: Summary: not working
239:
1.232 brouard 240: Revision 1.231 2016/08/22 07:17:15 brouard
241: Summary: not working
242:
1.231 brouard 243: Revision 1.230 2016/08/22 06:55:53 brouard
244: Summary: Not working
245:
1.230 brouard 246: Revision 1.229 2016/07/23 09:45:53 brouard
247: Summary: Completing for func too
248:
1.229 brouard 249: Revision 1.228 2016/07/22 17:45:30 brouard
250: Summary: Fixing some arrays, still debugging
251:
1.227 brouard 252: Revision 1.226 2016/07/12 18:42:34 brouard
253: Summary: temp
254:
1.226 brouard 255: Revision 1.225 2016/07/12 08:40:03 brouard
256: Summary: saving but not running
257:
1.225 brouard 258: Revision 1.224 2016/07/01 13:16:01 brouard
259: Summary: Fixes
260:
1.224 brouard 261: Revision 1.223 2016/02/19 09:23:35 brouard
262: Summary: temporary
263:
1.223 brouard 264: Revision 1.222 2016/02/17 08:14:50 brouard
265: Summary: Probably last 0.98 stable version 0.98r6
266:
1.222 brouard 267: Revision 1.221 2016/02/15 23:35:36 brouard
268: Summary: minor bug
269:
1.220 brouard 270: Revision 1.219 2016/02/15 00:48:12 brouard
271: *** empty log message ***
272:
1.219 brouard 273: Revision 1.218 2016/02/12 11:29:23 brouard
274: Summary: 0.99 Back projections
275:
1.218 brouard 276: Revision 1.217 2015/12/23 17:18:31 brouard
277: Summary: Experimental backcast
278:
1.217 brouard 279: Revision 1.216 2015/12/18 17:32:11 brouard
280: Summary: 0.98r4 Warning and status=-2
281:
282: Version 0.98r4 is now:
283: - displaying an error when status is -1, date of interview unknown and date of death known;
284: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
285: Older changes concerning s=-2, dating from 2005 have been supersed.
286:
1.216 brouard 287: Revision 1.215 2015/12/16 08:52:24 brouard
288: Summary: 0.98r4 working
289:
1.215 brouard 290: Revision 1.214 2015/12/16 06:57:54 brouard
291: Summary: temporary not working
292:
1.214 brouard 293: Revision 1.213 2015/12/11 18:22:17 brouard
294: Summary: 0.98r4
295:
1.213 brouard 296: Revision 1.212 2015/11/21 12:47:24 brouard
297: Summary: minor typo
298:
1.212 brouard 299: Revision 1.211 2015/11/21 12:41:11 brouard
300: Summary: 0.98r3 with some graph of projected cross-sectional
301:
302: Author: Nicolas Brouard
303:
1.211 brouard 304: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 305: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 306: Summary: Adding ftolpl parameter
307: Author: N Brouard
308:
309: We had difficulties to get smoothed confidence intervals. It was due
310: to the period prevalence which wasn't computed accurately. The inner
311: parameter ftolpl is now an outer parameter of the .imach parameter
312: file after estepm. If ftolpl is small 1.e-4 and estepm too,
313: computation are long.
314:
1.209 brouard 315: Revision 1.208 2015/11/17 14:31:57 brouard
316: Summary: temporary
317:
1.208 brouard 318: Revision 1.207 2015/10/27 17:36:57 brouard
319: *** empty log message ***
320:
1.207 brouard 321: Revision 1.206 2015/10/24 07:14:11 brouard
322: *** empty log message ***
323:
1.206 brouard 324: Revision 1.205 2015/10/23 15:50:53 brouard
325: Summary: 0.98r3 some clarification for graphs on likelihood contributions
326:
1.205 brouard 327: Revision 1.204 2015/10/01 16:20:26 brouard
328: Summary: Some new graphs of contribution to likelihood
329:
1.204 brouard 330: Revision 1.203 2015/09/30 17:45:14 brouard
331: Summary: looking at better estimation of the hessian
332:
333: Also a better criteria for convergence to the period prevalence And
334: therefore adding the number of years needed to converge. (The
335: prevalence in any alive state shold sum to one
336:
1.203 brouard 337: Revision 1.202 2015/09/22 19:45:16 brouard
338: Summary: Adding some overall graph on contribution to likelihood. Might change
339:
1.202 brouard 340: Revision 1.201 2015/09/15 17:34:58 brouard
341: Summary: 0.98r0
342:
343: - Some new graphs like suvival functions
344: - Some bugs fixed like model=1+age+V2.
345:
1.201 brouard 346: Revision 1.200 2015/09/09 16:53:55 brouard
347: Summary: Big bug thanks to Flavia
348:
349: Even model=1+age+V2. did not work anymore
350:
1.200 brouard 351: Revision 1.199 2015/09/07 14:09:23 brouard
352: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
353:
1.199 brouard 354: Revision 1.198 2015/09/03 07:14:39 brouard
355: Summary: 0.98q5 Flavia
356:
1.198 brouard 357: Revision 1.197 2015/09/01 18:24:39 brouard
358: *** empty log message ***
359:
1.197 brouard 360: Revision 1.196 2015/08/18 23:17:52 brouard
361: Summary: 0.98q5
362:
1.196 brouard 363: Revision 1.195 2015/08/18 16:28:39 brouard
364: Summary: Adding a hack for testing purpose
365:
366: After reading the title, ftol and model lines, if the comment line has
367: a q, starting with #q, the answer at the end of the run is quit. It
368: permits to run test files in batch with ctest. The former workaround was
369: $ echo q | imach foo.imach
370:
1.195 brouard 371: Revision 1.194 2015/08/18 13:32:00 brouard
372: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
373:
1.194 brouard 374: Revision 1.193 2015/08/04 07:17:42 brouard
375: Summary: 0.98q4
376:
1.193 brouard 377: Revision 1.192 2015/07/16 16:49:02 brouard
378: Summary: Fixing some outputs
379:
1.192 brouard 380: Revision 1.191 2015/07/14 10:00:33 brouard
381: Summary: Some fixes
382:
1.191 brouard 383: Revision 1.190 2015/05/05 08:51:13 brouard
384: Summary: Adding digits in output parameters (7 digits instead of 6)
385:
386: Fix 1+age+.
387:
1.190 brouard 388: Revision 1.189 2015/04/30 14:45:16 brouard
389: Summary: 0.98q2
390:
1.189 brouard 391: Revision 1.188 2015/04/30 08:27:53 brouard
392: *** empty log message ***
393:
1.188 brouard 394: Revision 1.187 2015/04/29 09:11:15 brouard
395: *** empty log message ***
396:
1.187 brouard 397: Revision 1.186 2015/04/23 12:01:52 brouard
398: Summary: V1*age is working now, version 0.98q1
399:
400: Some codes had been disabled in order to simplify and Vn*age was
401: working in the optimization phase, ie, giving correct MLE parameters,
402: but, as usual, outputs were not correct and program core dumped.
403:
1.186 brouard 404: Revision 1.185 2015/03/11 13:26:42 brouard
405: Summary: Inclusion of compile and links command line for Intel Compiler
406:
1.185 brouard 407: Revision 1.184 2015/03/11 11:52:39 brouard
408: Summary: Back from Windows 8. Intel Compiler
409:
1.184 brouard 410: Revision 1.183 2015/03/10 20:34:32 brouard
411: Summary: 0.98q0, trying with directest, mnbrak fixed
412:
413: We use directest instead of original Powell test; probably no
414: incidence on the results, but better justifications;
415: We fixed Numerical Recipes mnbrak routine which was wrong and gave
416: wrong results.
417:
1.183 brouard 418: Revision 1.182 2015/02/12 08:19:57 brouard
419: Summary: Trying to keep directest which seems simpler and more general
420: Author: Nicolas Brouard
421:
1.182 brouard 422: Revision 1.181 2015/02/11 23:22:24 brouard
423: Summary: Comments on Powell added
424:
425: Author:
426:
1.181 brouard 427: Revision 1.180 2015/02/11 17:33:45 brouard
428: Summary: Finishing move from main to function (hpijx and prevalence_limit)
429:
1.180 brouard 430: Revision 1.179 2015/01/04 09:57:06 brouard
431: Summary: back to OS/X
432:
1.179 brouard 433: Revision 1.178 2015/01/04 09:35:48 brouard
434: *** empty log message ***
435:
1.178 brouard 436: Revision 1.177 2015/01/03 18:40:56 brouard
437: Summary: Still testing ilc32 on OSX
438:
1.177 brouard 439: Revision 1.176 2015/01/03 16:45:04 brouard
440: *** empty log message ***
441:
1.176 brouard 442: Revision 1.175 2015/01/03 16:33:42 brouard
443: *** empty log message ***
444:
1.175 brouard 445: Revision 1.174 2015/01/03 16:15:49 brouard
446: Summary: Still in cross-compilation
447:
1.174 brouard 448: Revision 1.173 2015/01/03 12:06:26 brouard
449: Summary: trying to detect cross-compilation
450:
1.173 brouard 451: Revision 1.172 2014/12/27 12:07:47 brouard
452: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
453:
1.172 brouard 454: Revision 1.171 2014/12/23 13:26:59 brouard
455: Summary: Back from Visual C
456:
457: Still problem with utsname.h on Windows
458:
1.171 brouard 459: Revision 1.170 2014/12/23 11:17:12 brouard
460: Summary: Cleaning some \%% back to %%
461:
462: The escape was mandatory for a specific compiler (which one?), but too many warnings.
463:
1.170 brouard 464: Revision 1.169 2014/12/22 23:08:31 brouard
465: Summary: 0.98p
466:
467: Outputs some informations on compiler used, OS etc. Testing on different platforms.
468:
1.169 brouard 469: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 470: Summary: update
1.169 brouard 471:
1.168 brouard 472: Revision 1.167 2014/12/22 13:50:56 brouard
473: Summary: Testing uname and compiler version and if compiled 32 or 64
474:
475: Testing on Linux 64
476:
1.167 brouard 477: Revision 1.166 2014/12/22 11:40:47 brouard
478: *** empty log message ***
479:
1.166 brouard 480: Revision 1.165 2014/12/16 11:20:36 brouard
481: Summary: After compiling on Visual C
482:
483: * imach.c (Module): Merging 1.61 to 1.162
484:
1.165 brouard 485: Revision 1.164 2014/12/16 10:52:11 brouard
486: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
487:
488: * imach.c (Module): Merging 1.61 to 1.162
489:
1.164 brouard 490: Revision 1.163 2014/12/16 10:30:11 brouard
491: * imach.c (Module): Merging 1.61 to 1.162
492:
1.163 brouard 493: Revision 1.162 2014/09/25 11:43:39 brouard
494: Summary: temporary backup 0.99!
495:
1.162 brouard 496: Revision 1.1 2014/09/16 11:06:58 brouard
497: Summary: With some code (wrong) for nlopt
498:
499: Author:
500:
501: Revision 1.161 2014/09/15 20:41:41 brouard
502: Summary: Problem with macro SQR on Intel compiler
503:
1.161 brouard 504: Revision 1.160 2014/09/02 09:24:05 brouard
505: *** empty log message ***
506:
1.160 brouard 507: Revision 1.159 2014/09/01 10:34:10 brouard
508: Summary: WIN32
509: Author: Brouard
510:
1.159 brouard 511: Revision 1.158 2014/08/27 17:11:51 brouard
512: *** empty log message ***
513:
1.158 brouard 514: Revision 1.157 2014/08/27 16:26:55 brouard
515: Summary: Preparing windows Visual studio version
516: Author: Brouard
517:
518: In order to compile on Visual studio, time.h is now correct and time_t
519: and tm struct should be used. difftime should be used but sometimes I
520: just make the differences in raw time format (time(&now).
521: Trying to suppress #ifdef LINUX
522: Add xdg-open for __linux in order to open default browser.
523:
1.157 brouard 524: Revision 1.156 2014/08/25 20:10:10 brouard
525: *** empty log message ***
526:
1.156 brouard 527: Revision 1.155 2014/08/25 18:32:34 brouard
528: Summary: New compile, minor changes
529: Author: Brouard
530:
1.155 brouard 531: Revision 1.154 2014/06/20 17:32:08 brouard
532: Summary: Outputs now all graphs of convergence to period prevalence
533:
1.154 brouard 534: Revision 1.153 2014/06/20 16:45:46 brouard
535: Summary: If 3 live state, convergence to period prevalence on same graph
536: Author: Brouard
537:
1.153 brouard 538: Revision 1.152 2014/06/18 17:54:09 brouard
539: Summary: open browser, use gnuplot on same dir than imach if not found in the path
540:
1.152 brouard 541: Revision 1.151 2014/06/18 16:43:30 brouard
542: *** empty log message ***
543:
1.151 brouard 544: Revision 1.150 2014/06/18 16:42:35 brouard
545: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
546: Author: brouard
547:
1.150 brouard 548: Revision 1.149 2014/06/18 15:51:14 brouard
549: Summary: Some fixes in parameter files errors
550: Author: Nicolas Brouard
551:
1.149 brouard 552: Revision 1.148 2014/06/17 17:38:48 brouard
553: Summary: Nothing new
554: Author: Brouard
555:
556: Just a new packaging for OS/X version 0.98nS
557:
1.148 brouard 558: Revision 1.147 2014/06/16 10:33:11 brouard
559: *** empty log message ***
560:
1.147 brouard 561: Revision 1.146 2014/06/16 10:20:28 brouard
562: Summary: Merge
563: Author: Brouard
564:
565: Merge, before building revised version.
566:
1.146 brouard 567: Revision 1.145 2014/06/10 21:23:15 brouard
568: Summary: Debugging with valgrind
569: Author: Nicolas Brouard
570:
571: Lot of changes in order to output the results with some covariates
572: After the Edimburgh REVES conference 2014, it seems mandatory to
573: improve the code.
574: No more memory valgrind error but a lot has to be done in order to
575: continue the work of splitting the code into subroutines.
576: Also, decodemodel has been improved. Tricode is still not
577: optimal. nbcode should be improved. Documentation has been added in
578: the source code.
579:
1.144 brouard 580: Revision 1.143 2014/01/26 09:45:38 brouard
581: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
582:
583: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
584: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
585:
1.143 brouard 586: Revision 1.142 2014/01/26 03:57:36 brouard
587: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
588:
589: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
590:
1.142 brouard 591: Revision 1.141 2014/01/26 02:42:01 brouard
592: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
593:
1.141 brouard 594: Revision 1.140 2011/09/02 10:37:54 brouard
595: Summary: times.h is ok with mingw32 now.
596:
1.140 brouard 597: Revision 1.139 2010/06/14 07:50:17 brouard
598: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
599: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
600:
1.139 brouard 601: Revision 1.138 2010/04/30 18:19:40 brouard
602: *** empty log message ***
603:
1.138 brouard 604: Revision 1.137 2010/04/29 18:11:38 brouard
605: (Module): Checking covariates for more complex models
606: than V1+V2. A lot of change to be done. Unstable.
607:
1.137 brouard 608: Revision 1.136 2010/04/26 20:30:53 brouard
609: (Module): merging some libgsl code. Fixing computation
610: of likelione (using inter/intrapolation if mle = 0) in order to
611: get same likelihood as if mle=1.
612: Some cleaning of code and comments added.
613:
1.136 brouard 614: Revision 1.135 2009/10/29 15:33:14 brouard
615: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
616:
1.135 brouard 617: Revision 1.134 2009/10/29 13:18:53 brouard
618: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
619:
1.134 brouard 620: Revision 1.133 2009/07/06 10:21:25 brouard
621: just nforces
622:
1.133 brouard 623: Revision 1.132 2009/07/06 08:22:05 brouard
624: Many tings
625:
1.132 brouard 626: Revision 1.131 2009/06/20 16:22:47 brouard
627: Some dimensions resccaled
628:
1.131 brouard 629: Revision 1.130 2009/05/26 06:44:34 brouard
630: (Module): Max Covariate is now set to 20 instead of 8. A
631: lot of cleaning with variables initialized to 0. Trying to make
632: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
633:
1.130 brouard 634: Revision 1.129 2007/08/31 13:49:27 lievre
635: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
636:
1.129 lievre 637: Revision 1.128 2006/06/30 13:02:05 brouard
638: (Module): Clarifications on computing e.j
639:
1.128 brouard 640: Revision 1.127 2006/04/28 18:11:50 brouard
641: (Module): Yes the sum of survivors was wrong since
642: imach-114 because nhstepm was no more computed in the age
643: loop. Now we define nhstepma in the age loop.
644: (Module): In order to speed up (in case of numerous covariates) we
645: compute health expectancies (without variances) in a first step
646: and then all the health expectancies with variances or standard
647: deviation (needs data from the Hessian matrices) which slows the
648: computation.
649: In the future we should be able to stop the program is only health
650: expectancies and graph are needed without standard deviations.
651:
1.127 brouard 652: Revision 1.126 2006/04/28 17:23:28 brouard
653: (Module): Yes the sum of survivors was wrong since
654: imach-114 because nhstepm was no more computed in the age
655: loop. Now we define nhstepma in the age loop.
656: Version 0.98h
657:
1.126 brouard 658: Revision 1.125 2006/04/04 15:20:31 lievre
659: Errors in calculation of health expectancies. Age was not initialized.
660: Forecasting file added.
661:
662: Revision 1.124 2006/03/22 17:13:53 lievre
663: Parameters are printed with %lf instead of %f (more numbers after the comma).
664: The log-likelihood is printed in the log file
665:
666: Revision 1.123 2006/03/20 10:52:43 brouard
667: * imach.c (Module): <title> changed, corresponds to .htm file
668: name. <head> headers where missing.
669:
670: * imach.c (Module): Weights can have a decimal point as for
671: English (a comma might work with a correct LC_NUMERIC environment,
672: otherwise the weight is truncated).
673: Modification of warning when the covariates values are not 0 or
674: 1.
675: Version 0.98g
676:
677: Revision 1.122 2006/03/20 09:45:41 brouard
678: (Module): Weights can have a decimal point as for
679: English (a comma might work with a correct LC_NUMERIC environment,
680: otherwise the weight is truncated).
681: Modification of warning when the covariates values are not 0 or
682: 1.
683: Version 0.98g
684:
685: Revision 1.121 2006/03/16 17:45:01 lievre
686: * imach.c (Module): Comments concerning covariates added
687:
688: * imach.c (Module): refinements in the computation of lli if
689: status=-2 in order to have more reliable computation if stepm is
690: not 1 month. Version 0.98f
691:
692: Revision 1.120 2006/03/16 15:10:38 lievre
693: (Module): refinements in the computation of lli if
694: status=-2 in order to have more reliable computation if stepm is
695: not 1 month. Version 0.98f
696:
697: Revision 1.119 2006/03/15 17:42:26 brouard
698: (Module): Bug if status = -2, the loglikelihood was
699: computed as likelihood omitting the logarithm. Version O.98e
700:
701: Revision 1.118 2006/03/14 18:20:07 brouard
702: (Module): varevsij Comments added explaining the second
703: table of variances if popbased=1 .
704: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
705: (Module): Function pstamp added
706: (Module): Version 0.98d
707:
708: Revision 1.117 2006/03/14 17:16:22 brouard
709: (Module): varevsij Comments added explaining the second
710: table of variances if popbased=1 .
711: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
712: (Module): Function pstamp added
713: (Module): Version 0.98d
714:
715: Revision 1.116 2006/03/06 10:29:27 brouard
716: (Module): Variance-covariance wrong links and
717: varian-covariance of ej. is needed (Saito).
718:
719: Revision 1.115 2006/02/27 12:17:45 brouard
720: (Module): One freematrix added in mlikeli! 0.98c
721:
722: Revision 1.114 2006/02/26 12:57:58 brouard
723: (Module): Some improvements in processing parameter
724: filename with strsep.
725:
726: Revision 1.113 2006/02/24 14:20:24 brouard
727: (Module): Memory leaks checks with valgrind and:
728: datafile was not closed, some imatrix were not freed and on matrix
729: allocation too.
730:
731: Revision 1.112 2006/01/30 09:55:26 brouard
732: (Module): Back to gnuplot.exe instead of wgnuplot.exe
733:
734: Revision 1.111 2006/01/25 20:38:18 brouard
735: (Module): Lots of cleaning and bugs added (Gompertz)
736: (Module): Comments can be added in data file. Missing date values
737: can be a simple dot '.'.
738:
739: Revision 1.110 2006/01/25 00:51:50 brouard
740: (Module): Lots of cleaning and bugs added (Gompertz)
741:
742: Revision 1.109 2006/01/24 19:37:15 brouard
743: (Module): Comments (lines starting with a #) are allowed in data.
744:
745: Revision 1.108 2006/01/19 18:05:42 lievre
746: Gnuplot problem appeared...
747: To be fixed
748:
749: Revision 1.107 2006/01/19 16:20:37 brouard
750: Test existence of gnuplot in imach path
751:
752: Revision 1.106 2006/01/19 13:24:36 brouard
753: Some cleaning and links added in html output
754:
755: Revision 1.105 2006/01/05 20:23:19 lievre
756: *** empty log message ***
757:
758: Revision 1.104 2005/09/30 16:11:43 lievre
759: (Module): sump fixed, loop imx fixed, and simplifications.
760: (Module): If the status is missing at the last wave but we know
761: that the person is alive, then we can code his/her status as -2
762: (instead of missing=-1 in earlier versions) and his/her
763: contributions to the likelihood is 1 - Prob of dying from last
764: health status (= 1-p13= p11+p12 in the easiest case of somebody in
765: the healthy state at last known wave). Version is 0.98
766:
767: Revision 1.103 2005/09/30 15:54:49 lievre
768: (Module): sump fixed, loop imx fixed, and simplifications.
769:
770: Revision 1.102 2004/09/15 17:31:30 brouard
771: Add the possibility to read data file including tab characters.
772:
773: Revision 1.101 2004/09/15 10:38:38 brouard
774: Fix on curr_time
775:
776: Revision 1.100 2004/07/12 18:29:06 brouard
777: Add version for Mac OS X. Just define UNIX in Makefile
778:
779: Revision 1.99 2004/06/05 08:57:40 brouard
780: *** empty log message ***
781:
782: Revision 1.98 2004/05/16 15:05:56 brouard
783: New version 0.97 . First attempt to estimate force of mortality
784: directly from the data i.e. without the need of knowing the health
785: state at each age, but using a Gompertz model: log u =a + b*age .
786: This is the basic analysis of mortality and should be done before any
787: other analysis, in order to test if the mortality estimated from the
788: cross-longitudinal survey is different from the mortality estimated
789: from other sources like vital statistic data.
790:
791: The same imach parameter file can be used but the option for mle should be -3.
792:
1.133 brouard 793: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 794: former routines in order to include the new code within the former code.
795:
796: The output is very simple: only an estimate of the intercept and of
797: the slope with 95% confident intervals.
798:
799: Current limitations:
800: A) Even if you enter covariates, i.e. with the
801: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
802: B) There is no computation of Life Expectancy nor Life Table.
803:
804: Revision 1.97 2004/02/20 13:25:42 lievre
805: Version 0.96d. Population forecasting command line is (temporarily)
806: suppressed.
807:
808: Revision 1.96 2003/07/15 15:38:55 brouard
809: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
810: rewritten within the same printf. Workaround: many printfs.
811:
812: Revision 1.95 2003/07/08 07:54:34 brouard
813: * imach.c (Repository):
814: (Repository): Using imachwizard code to output a more meaningful covariance
815: matrix (cov(a12,c31) instead of numbers.
816:
817: Revision 1.94 2003/06/27 13:00:02 brouard
818: Just cleaning
819:
820: Revision 1.93 2003/06/25 16:33:55 brouard
821: (Module): On windows (cygwin) function asctime_r doesn't
822: exist so I changed back to asctime which exists.
823: (Module): Version 0.96b
824:
825: Revision 1.92 2003/06/25 16:30:45 brouard
826: (Module): On windows (cygwin) function asctime_r doesn't
827: exist so I changed back to asctime which exists.
828:
829: Revision 1.91 2003/06/25 15:30:29 brouard
830: * imach.c (Repository): Duplicated warning errors corrected.
831: (Repository): Elapsed time after each iteration is now output. It
832: helps to forecast when convergence will be reached. Elapsed time
833: is stamped in powell. We created a new html file for the graphs
834: concerning matrix of covariance. It has extension -cov.htm.
835:
836: Revision 1.90 2003/06/24 12:34:15 brouard
837: (Module): Some bugs corrected for windows. Also, when
838: mle=-1 a template is output in file "or"mypar.txt with the design
839: of the covariance matrix to be input.
840:
841: Revision 1.89 2003/06/24 12:30:52 brouard
842: (Module): Some bugs corrected for windows. Also, when
843: mle=-1 a template is output in file "or"mypar.txt with the design
844: of the covariance matrix to be input.
845:
846: Revision 1.88 2003/06/23 17:54:56 brouard
847: * 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.
848:
849: Revision 1.87 2003/06/18 12:26:01 brouard
850: Version 0.96
851:
852: Revision 1.86 2003/06/17 20:04:08 brouard
853: (Module): Change position of html and gnuplot routines and added
854: routine fileappend.
855:
856: Revision 1.85 2003/06/17 13:12:43 brouard
857: * imach.c (Repository): Check when date of death was earlier that
858: current date of interview. It may happen when the death was just
859: prior to the death. In this case, dh was negative and likelihood
860: was wrong (infinity). We still send an "Error" but patch by
861: assuming that the date of death was just one stepm after the
862: interview.
863: (Repository): Because some people have very long ID (first column)
864: we changed int to long in num[] and we added a new lvector for
865: memory allocation. But we also truncated to 8 characters (left
866: truncation)
867: (Repository): No more line truncation errors.
868:
869: Revision 1.84 2003/06/13 21:44:43 brouard
870: * imach.c (Repository): Replace "freqsummary" at a correct
871: place. It differs from routine "prevalence" which may be called
872: many times. Probs is memory consuming and must be used with
873: parcimony.
874: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
875:
876: Revision 1.83 2003/06/10 13:39:11 lievre
877: *** empty log message ***
878:
879: Revision 1.82 2003/06/05 15:57:20 brouard
880: Add log in imach.c and fullversion number is now printed.
881:
882: */
883: /*
884: Interpolated Markov Chain
885:
886: Short summary of the programme:
887:
1.227 brouard 888: This program computes Healthy Life Expectancies or State-specific
889: (if states aren't health statuses) Expectancies from
890: cross-longitudinal data. Cross-longitudinal data consist in:
891:
892: -1- a first survey ("cross") where individuals from different ages
893: are interviewed on their health status or degree of disability (in
894: the case of a health survey which is our main interest)
895:
896: -2- at least a second wave of interviews ("longitudinal") which
897: measure each change (if any) in individual health status. Health
898: expectancies are computed from the time spent in each health state
899: according to a model. More health states you consider, more time is
900: necessary to reach the Maximum Likelihood of the parameters involved
901: in the model. The simplest model is the multinomial logistic model
902: where pij is the probability to be observed in state j at the second
903: wave conditional to be observed in state i at the first
904: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
905: etc , where 'age' is age and 'sex' is a covariate. If you want to
906: have a more complex model than "constant and age", you should modify
907: the program where the markup *Covariates have to be included here
908: again* invites you to do it. More covariates you add, slower the
1.126 brouard 909: convergence.
910:
911: The advantage of this computer programme, compared to a simple
912: multinomial logistic model, is clear when the delay between waves is not
913: identical for each individual. Also, if a individual missed an
914: intermediate interview, the information is lost, but taken into
915: account using an interpolation or extrapolation.
916:
917: hPijx is the probability to be observed in state i at age x+h
918: conditional to the observed state i at age x. The delay 'h' can be
919: split into an exact number (nh*stepm) of unobserved intermediate
920: states. This elementary transition (by month, quarter,
921: semester or year) is modelled as a multinomial logistic. The hPx
922: matrix is simply the matrix product of nh*stepm elementary matrices
923: and the contribution of each individual to the likelihood is simply
924: hPijx.
925:
926: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 927: of the life expectancies. It also computes the period (stable) prevalence.
928:
929: Back prevalence and projections:
1.227 brouard 930:
931: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
932: double agemaxpar, double ftolpl, int *ncvyearp, double
933: dateprev1,double dateprev2, int firstpass, int lastpass, int
934: mobilavproj)
935:
936: Computes the back prevalence limit for any combination of
937: covariate values k at any age between ageminpar and agemaxpar and
938: returns it in **bprlim. In the loops,
939:
940: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
941: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
942:
943: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 944: Computes for any combination of covariates k and any age between bage and fage
945: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
946: oldm=oldms;savm=savms;
1.227 brouard 947:
1.267 brouard 948: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 949: Computes the transition matrix starting at age 'age' over
950: 'nhstepm*hstepm*stepm' months (i.e. until
951: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 952: nhstepm*hstepm matrices.
953:
954: Returns p3mat[i][j][h] after calling
955: p3mat[i][j][h]=matprod2(newm,
956: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
957: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
958: oldm);
1.226 brouard 959:
960: Important routines
961:
962: - func (or funcone), computes logit (pij) distinguishing
963: o fixed variables (single or product dummies or quantitative);
964: o varying variables by:
965: (1) wave (single, product dummies, quantitative),
966: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
967: % fixed dummy (treated) or quantitative (not done because time-consuming);
968: % varying dummy (not done) or quantitative (not done);
969: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
970: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
971: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
972: o There are 2*cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
973: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 974:
1.226 brouard 975:
976:
1.133 brouard 977: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
978: Institut national d'études démographiques, Paris.
1.126 brouard 979: This software have been partly granted by Euro-REVES, a concerted action
980: from the European Union.
981: It is copyrighted identically to a GNU software product, ie programme and
982: software can be distributed freely for non commercial use. Latest version
983: can be accessed at http://euroreves.ined.fr/imach .
984:
985: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
986: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
987:
988: **********************************************************************/
989: /*
990: main
991: read parameterfile
992: read datafile
993: concatwav
994: freqsummary
995: if (mle >= 1)
996: mlikeli
997: print results files
998: if mle==1
999: computes hessian
1000: read end of parameter file: agemin, agemax, bage, fage, estepm
1001: begin-prev-date,...
1002: open gnuplot file
1003: open html file
1.145 brouard 1004: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
1005: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
1006: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
1007: freexexit2 possible for memory heap.
1008:
1009: h Pij x | pij_nom ficrestpij
1010: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
1011: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
1012: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
1013:
1014: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
1015: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
1016: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
1017: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
1018: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
1019:
1.126 brouard 1020: forecasting if prevfcast==1 prevforecast call prevalence()
1021: health expectancies
1022: Variance-covariance of DFLE
1023: prevalence()
1024: movingaverage()
1025: varevsij()
1026: if popbased==1 varevsij(,popbased)
1027: total life expectancies
1028: Variance of period (stable) prevalence
1029: end
1030: */
1031:
1.187 brouard 1032: /* #define DEBUG */
1033: /* #define DEBUGBRENT */
1.203 brouard 1034: /* #define DEBUGLINMIN */
1035: /* #define DEBUGHESS */
1036: #define DEBUGHESSIJ
1.224 brouard 1037: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 1038: #define POWELL /* Instead of NLOPT */
1.224 brouard 1039: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 1040: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
1041: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.126 brouard 1042:
1043: #include <math.h>
1044: #include <stdio.h>
1045: #include <stdlib.h>
1046: #include <string.h>
1.226 brouard 1047: #include <ctype.h>
1.159 brouard 1048:
1049: #ifdef _WIN32
1050: #include <io.h>
1.172 brouard 1051: #include <windows.h>
1052: #include <tchar.h>
1.159 brouard 1053: #else
1.126 brouard 1054: #include <unistd.h>
1.159 brouard 1055: #endif
1.126 brouard 1056:
1057: #include <limits.h>
1058: #include <sys/types.h>
1.171 brouard 1059:
1060: #if defined(__GNUC__)
1061: #include <sys/utsname.h> /* Doesn't work on Windows */
1062: #endif
1063:
1.126 brouard 1064: #include <sys/stat.h>
1065: #include <errno.h>
1.159 brouard 1066: /* extern int errno; */
1.126 brouard 1067:
1.157 brouard 1068: /* #ifdef LINUX */
1069: /* #include <time.h> */
1070: /* #include "timeval.h" */
1071: /* #else */
1072: /* #include <sys/time.h> */
1073: /* #endif */
1074:
1.126 brouard 1075: #include <time.h>
1076:
1.136 brouard 1077: #ifdef GSL
1078: #include <gsl/gsl_errno.h>
1079: #include <gsl/gsl_multimin.h>
1080: #endif
1081:
1.167 brouard 1082:
1.162 brouard 1083: #ifdef NLOPT
1084: #include <nlopt.h>
1085: typedef struct {
1086: double (* function)(double [] );
1087: } myfunc_data ;
1088: #endif
1089:
1.126 brouard 1090: /* #include <libintl.h> */
1091: /* #define _(String) gettext (String) */
1092:
1.251 brouard 1093: #define MAXLINE 2048 /* Was 256 and 1024. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 1094:
1095: #define GNUPLOTPROGRAM "gnuplot"
1096: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
1097: #define FILENAMELENGTH 132
1098:
1099: #define GLOCK_ERROR_NOPATH -1 /* empty path */
1100: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
1101:
1.144 brouard 1102: #define MAXPARM 128 /**< Maximum number of parameters for the optimization */
1103: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 1104:
1105: #define NINTERVMAX 8
1.144 brouard 1106: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
1107: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
1.291 brouard 1108: #define NCOVMAX 20 /**< Maximum number of covariates, including generated covariates V1*V2 */
1.197 brouard 1109: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 1110: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
1111: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.290 brouard 1112: /*#define MAXN 20000 */ /* Should by replaced by nobs, real number of observations and unlimited */
1.144 brouard 1113: #define YEARM 12. /**< Number of months per year */
1.218 brouard 1114: /* #define AGESUP 130 */
1.288 brouard 1115: /* #define AGESUP 150 */
1116: #define AGESUP 200
1.268 brouard 1117: #define AGEINF 0
1.218 brouard 1118: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1119: #define AGEBASE 40
1.194 brouard 1120: #define AGEOVERFLOW 1.e20
1.164 brouard 1121: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1122: #ifdef _WIN32
1123: #define DIRSEPARATOR '\\'
1124: #define CHARSEPARATOR "\\"
1125: #define ODIRSEPARATOR '/'
1126: #else
1.126 brouard 1127: #define DIRSEPARATOR '/'
1128: #define CHARSEPARATOR "/"
1129: #define ODIRSEPARATOR '\\'
1130: #endif
1131:
1.304 ! brouard 1132: /* $Id: imach.c,v 1.303 2021/02/11 19:50:15 brouard Exp $ */
1.126 brouard 1133: /* $State: Exp $ */
1.196 brouard 1134: #include "version.h"
1135: char version[]=__IMACH_VERSION__;
1.300 brouard 1136: char copyright[]="May 2019,INED-EUROREVES-Institut de longevite-Japan Society for the Promotion of Science (Grant-in-Aid for Scientific Research 25293121), Intel Software 2015-2020";
1.304 ! brouard 1137: char fullversion[]="$Revision: 1.303 $ $Date: 2021/02/11 19:50:15 $";
1.126 brouard 1138: char strstart[80];
1139: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1140: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.187 brouard 1141: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.145 brouard 1142: /* Number of covariates model=V2+V1+ V3*age+V2*V4 */
1143: int cptcovn=0; /**< cptcovn number of covariates added in the model (excepting constant and age and age*product) */
1144: int cptcovt=0; /**< cptcovt number of covariates added in the model (excepting constant and age) */
1.225 brouard 1145: int cptcovs=0; /**< cptcovs number of simple covariates in the model V2+V1 =2 */
1146: int cptcovsnq=0; /**< cptcovsnq number of simple covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1147: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1148: int cptcovprodnoage=0; /**< Number of covariate products without age */
1149: int cptcoveff=0; /* Total number of covariates to vary for printing results */
1.233 brouard 1150: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1151: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.232 brouard 1152: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (dummy of quantitative) in the model */
1.234 brouard 1153: int nsd=0; /**< Total number of single dummy variables (output) */
1154: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1155: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1156: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1157: int ntveff=0; /**< ntveff number of effective time varying variables */
1158: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1159: int cptcov=0; /* Working variable */
1.290 brouard 1160: int nobs=10; /* Number of observations in the data lastobs-firstobs */
1.218 brouard 1161: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.302 brouard 1162: int npar=NPARMAX; /* Number of parameters (nlstate+ndeath-1)*nlstate*ncovmodel; */
1.126 brouard 1163: int nlstate=2; /* Number of live states */
1164: int ndeath=1; /* Number of dead states */
1.130 brouard 1165: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.223 brouard 1166: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable */
1.126 brouard 1167: int popbased=0;
1168:
1169: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1170: int maxwav=0; /* Maxim number of waves */
1171: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1172: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1173: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 1174: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1175: int mle=1, weightopt=0;
1.126 brouard 1176: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1177: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1178: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1179: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1180: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1181: int selected(int kvar); /* Is covariate kvar selected for printing results */
1182:
1.130 brouard 1183: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1184: double **matprod2(); /* test */
1.126 brouard 1185: double **oldm, **newm, **savm; /* Working pointers to matrices */
1186: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1187: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1188:
1.136 brouard 1189: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1190: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1191: FILE *ficlog, *ficrespow;
1.130 brouard 1192: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1193: double fretone; /* Only one call to likelihood */
1.130 brouard 1194: long ipmx=0; /* Number of contributions */
1.126 brouard 1195: double sw; /* Sum of weights */
1196: char filerespow[FILENAMELENGTH];
1197: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1198: FILE *ficresilk;
1199: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1200: FILE *ficresprobmorprev;
1201: FILE *fichtm, *fichtmcov; /* Html File */
1202: FILE *ficreseij;
1203: char filerese[FILENAMELENGTH];
1204: FILE *ficresstdeij;
1205: char fileresstde[FILENAMELENGTH];
1206: FILE *ficrescveij;
1207: char filerescve[FILENAMELENGTH];
1208: FILE *ficresvij;
1209: char fileresv[FILENAMELENGTH];
1.269 brouard 1210:
1.126 brouard 1211: char title[MAXLINE];
1.234 brouard 1212: char model[MAXLINE]; /**< The model line */
1.217 brouard 1213: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1214: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1215: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1216: char command[FILENAMELENGTH];
1217: int outcmd=0;
1218:
1.217 brouard 1219: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1220: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1221: char filelog[FILENAMELENGTH]; /* Log file */
1222: char filerest[FILENAMELENGTH];
1223: char fileregp[FILENAMELENGTH];
1224: char popfile[FILENAMELENGTH];
1225:
1226: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1227:
1.157 brouard 1228: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1229: /* struct timezone tzp; */
1230: /* extern int gettimeofday(); */
1231: struct tm tml, *gmtime(), *localtime();
1232:
1233: extern time_t time();
1234:
1235: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1236: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1237: struct tm tm;
1238:
1.126 brouard 1239: char strcurr[80], strfor[80];
1240:
1241: char *endptr;
1242: long lval;
1243: double dval;
1244:
1245: #define NR_END 1
1246: #define FREE_ARG char*
1247: #define FTOL 1.0e-10
1248:
1249: #define NRANSI
1.240 brouard 1250: #define ITMAX 200
1251: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1252:
1253: #define TOL 2.0e-4
1254:
1255: #define CGOLD 0.3819660
1256: #define ZEPS 1.0e-10
1257: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1258:
1259: #define GOLD 1.618034
1260: #define GLIMIT 100.0
1261: #define TINY 1.0e-20
1262:
1263: static double maxarg1,maxarg2;
1264: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1265: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1266:
1267: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1268: #define rint(a) floor(a+0.5)
1.166 brouard 1269: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1270: #define mytinydouble 1.0e-16
1.166 brouard 1271: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1272: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1273: /* static double dsqrarg; */
1274: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1275: static double sqrarg;
1276: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1277: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1278: int agegomp= AGEGOMP;
1279:
1280: int imx;
1281: int stepm=1;
1282: /* Stepm, step in month: minimum step interpolation*/
1283:
1284: int estepm;
1285: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1286:
1287: int m,nb;
1288: long *num;
1.197 brouard 1289: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1290: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1291: covariate for which somebody answered excluding
1292: undefined. Usually 2: 0 and 1. */
1293: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1294: covariate for which somebody answered including
1295: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1296: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1297: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1298: double ***mobaverage, ***mobaverages; /* New global variable */
1.126 brouard 1299: double *ageexmed,*agecens;
1300: double dateintmean=0;
1.296 brouard 1301: double anprojd, mprojd, jprojd; /* For eventual projections */
1302: double anprojf, mprojf, jprojf;
1.126 brouard 1303:
1.296 brouard 1304: double anbackd, mbackd, jbackd; /* For eventual backprojections */
1305: double anbackf, mbackf, jbackf;
1306: double jintmean,mintmean,aintmean;
1.126 brouard 1307: double *weight;
1308: int **s; /* Status */
1.141 brouard 1309: double *agedc;
1.145 brouard 1310: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1311: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1312: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1313: double **coqvar; /* Fixed quantitative covariate nqv */
1314: double ***cotvar; /* Time varying covariate ntv */
1.225 brouard 1315: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1316: double idx;
1317: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.234 brouard 1318: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1319: /*k 1 2 3 4 5 6 7 8 9 */
1320: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 */
1321: /* Tndvar[k] 1 2 3 4 5 */
1322: /*TDvar 4 3 6 7 1 */ /* For outputs only; combination of dummies fixed or varying */
1323: /* Tns[k] 1 2 2 4 5 */ /* Number of single cova */
1324: /* TvarsD[k] 1 2 3 */ /* Number of single dummy cova */
1325: /* TvarsDind 2 3 9 */ /* position K of single dummy cova */
1326: /* TvarsQ[k] 1 2 */ /* Number of single quantitative cova */
1327: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1328: /* Tprod[i]=k 4 7 */
1329: /* Tage[i]=k 5 8 */
1330: /* */
1331: /* Type */
1332: /* V 1 2 3 4 5 */
1333: /* F F V V V */
1334: /* D Q D D Q */
1335: /* */
1336: int *TvarsD;
1337: int *TvarsDind;
1338: int *TvarsQ;
1339: int *TvarsQind;
1340:
1.235 brouard 1341: #define MAXRESULTLINES 10
1342: int nresult=0;
1.258 brouard 1343: int parameterline=0; /* # of the parameter (type) line */
1.235 brouard 1344: int TKresult[MAXRESULTLINES];
1.237 brouard 1345: int Tresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */
1346: int Tinvresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */
1.235 brouard 1347: int Tvresult[MAXRESULTLINES][NCOVMAX]; /* For dummy variable , variable # (output) */
1348: double Tqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */
1.237 brouard 1349: double Tqinvresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */
1.235 brouard 1350: int Tvqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , variable # (output) */
1351:
1.234 brouard 1352: /* 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 1353: 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 */
1354: 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 */
1355: 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 */
1356: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1357: 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 */
1358: 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 1359: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1360: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1361: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1362: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1363: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1364: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1365: 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 */
1366: 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 */
1367:
1.230 brouard 1368: int *Tvarsel; /**< Selected covariates for output */
1369: double *Tvalsel; /**< Selected modality value of covariate for output */
1.226 brouard 1370: int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.227 brouard 1371: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1372: 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 1373: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1374: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1375: int *Tage;
1.227 brouard 1376: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1377: 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 1378: 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*/
1379: 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 1380: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1381: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1382: int **Tvard;
1383: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1384: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1385: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1386: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1387: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1388: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1389: double *lsurv, *lpop, *tpop;
1390:
1.231 brouard 1391: #define FD 1; /* Fixed dummy covariate */
1392: #define FQ 2; /* Fixed quantitative covariate */
1393: #define FP 3; /* Fixed product covariate */
1394: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1395: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1396: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1397: #define VD 10; /* Varying dummy covariate */
1398: #define VQ 11; /* Varying quantitative covariate */
1399: #define VP 12; /* Varying product covariate */
1400: #define VPDD 13; /* Varying product dummy*dummy covariate */
1401: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1402: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1403: #define APFD 16; /* Age product * fixed dummy covariate */
1404: #define APFQ 17; /* Age product * fixed quantitative covariate */
1405: #define APVD 18; /* Age product * varying dummy covariate */
1406: #define APVQ 19; /* Age product * varying quantitative covariate */
1407:
1408: #define FTYPE 1; /* Fixed covariate */
1409: #define VTYPE 2; /* Varying covariate (loop in wave) */
1410: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1411:
1412: struct kmodel{
1413: int maintype; /* main type */
1414: int subtype; /* subtype */
1415: };
1416: struct kmodel modell[NCOVMAX];
1417:
1.143 brouard 1418: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1419: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1420:
1421: /**************** split *************************/
1422: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1423: {
1424: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1425: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1426: */
1427: char *ss; /* pointer */
1.186 brouard 1428: int l1=0, l2=0; /* length counters */
1.126 brouard 1429:
1430: l1 = strlen(path ); /* length of path */
1431: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1432: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1433: if ( ss == NULL ) { /* no directory, so determine current directory */
1434: strcpy( name, path ); /* we got the fullname name because no directory */
1435: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1436: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1437: /* get current working directory */
1438: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1439: #ifdef WIN32
1440: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1441: #else
1442: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1443: #endif
1.126 brouard 1444: return( GLOCK_ERROR_GETCWD );
1445: }
1446: /* got dirc from getcwd*/
1447: printf(" DIRC = %s \n",dirc);
1.205 brouard 1448: } else { /* strip directory from path */
1.126 brouard 1449: ss++; /* after this, the filename */
1450: l2 = strlen( ss ); /* length of filename */
1451: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1452: strcpy( name, ss ); /* save file name */
1453: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1454: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1455: printf(" DIRC2 = %s \n",dirc);
1456: }
1457: /* We add a separator at the end of dirc if not exists */
1458: l1 = strlen( dirc ); /* length of directory */
1459: if( dirc[l1-1] != DIRSEPARATOR ){
1460: dirc[l1] = DIRSEPARATOR;
1461: dirc[l1+1] = 0;
1462: printf(" DIRC3 = %s \n",dirc);
1463: }
1464: ss = strrchr( name, '.' ); /* find last / */
1465: if (ss >0){
1466: ss++;
1467: strcpy(ext,ss); /* save extension */
1468: l1= strlen( name);
1469: l2= strlen(ss)+1;
1470: strncpy( finame, name, l1-l2);
1471: finame[l1-l2]= 0;
1472: }
1473:
1474: return( 0 ); /* we're done */
1475: }
1476:
1477:
1478: /******************************************/
1479:
1480: void replace_back_to_slash(char *s, char*t)
1481: {
1482: int i;
1483: int lg=0;
1484: i=0;
1485: lg=strlen(t);
1486: for(i=0; i<= lg; i++) {
1487: (s[i] = t[i]);
1488: if (t[i]== '\\') s[i]='/';
1489: }
1490: }
1491:
1.132 brouard 1492: char *trimbb(char *out, char *in)
1.137 brouard 1493: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1494: char *s;
1495: s=out;
1496: while (*in != '\0'){
1.137 brouard 1497: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1498: in++;
1499: }
1500: *out++ = *in++;
1501: }
1502: *out='\0';
1503: return s;
1504: }
1505:
1.187 brouard 1506: /* char *substrchaine(char *out, char *in, char *chain) */
1507: /* { */
1508: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1509: /* char *s, *t; */
1510: /* t=in;s=out; */
1511: /* while ((*in != *chain) && (*in != '\0')){ */
1512: /* *out++ = *in++; */
1513: /* } */
1514:
1515: /* /\* *in matches *chain *\/ */
1516: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1517: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1518: /* } */
1519: /* in--; chain--; */
1520: /* while ( (*in != '\0')){ */
1521: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1522: /* *out++ = *in++; */
1523: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1524: /* } */
1525: /* *out='\0'; */
1526: /* out=s; */
1527: /* return out; */
1528: /* } */
1529: char *substrchaine(char *out, char *in, char *chain)
1530: {
1531: /* Substract chain 'chain' from 'in', return and output 'out' */
1532: /* in="V1+V1*age+age*age+V2", chain="age*age" */
1533:
1534: char *strloc;
1535:
1536: strcpy (out, in);
1537: strloc = strstr(out, chain); /* strloc points to out at age*age+V2 */
1538: printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out);
1539: if(strloc != NULL){
1540: /* will affect out */ /* strloc+strlenc(chain)=+V2 */ /* Will also work in Unicode */
1541: memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1);
1542: /* strcpy (strloc, strloc +strlen(chain));*/
1543: }
1544: printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out);
1545: return out;
1546: }
1547:
1548:
1.145 brouard 1549: char *cutl(char *blocc, char *alocc, char *in, char occ)
1550: {
1.187 brouard 1551: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.145 brouard 1552: and alocc starts after first occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1.187 brouard 1553: gives blocc="abcdef" and alocc="ghi2j".
1.145 brouard 1554: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1555: */
1.160 brouard 1556: char *s, *t;
1.145 brouard 1557: t=in;s=in;
1558: while ((*in != occ) && (*in != '\0')){
1559: *alocc++ = *in++;
1560: }
1561: if( *in == occ){
1562: *(alocc)='\0';
1563: s=++in;
1564: }
1565:
1566: if (s == t) {/* occ not found */
1567: *(alocc-(in-s))='\0';
1568: in=s;
1569: }
1570: while ( *in != '\0'){
1571: *blocc++ = *in++;
1572: }
1573:
1574: *blocc='\0';
1575: return t;
1576: }
1.137 brouard 1577: char *cutv(char *blocc, char *alocc, char *in, char occ)
1578: {
1.187 brouard 1579: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1580: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1581: gives blocc="abcdef2ghi" and alocc="j".
1582: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1583: */
1584: char *s, *t;
1585: t=in;s=in;
1586: while (*in != '\0'){
1587: while( *in == occ){
1588: *blocc++ = *in++;
1589: s=in;
1590: }
1591: *blocc++ = *in++;
1592: }
1593: if (s == t) /* occ not found */
1594: *(blocc-(in-s))='\0';
1595: else
1596: *(blocc-(in-s)-1)='\0';
1597: in=s;
1598: while ( *in != '\0'){
1599: *alocc++ = *in++;
1600: }
1601:
1602: *alocc='\0';
1603: return s;
1604: }
1605:
1.126 brouard 1606: int nbocc(char *s, char occ)
1607: {
1608: int i,j=0;
1609: int lg=20;
1610: i=0;
1611: lg=strlen(s);
1612: for(i=0; i<= lg; i++) {
1.234 brouard 1613: if (s[i] == occ ) j++;
1.126 brouard 1614: }
1615: return j;
1616: }
1617:
1.137 brouard 1618: /* void cutv(char *u,char *v, char*t, char occ) */
1619: /* { */
1620: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1621: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1622: /* gives u="abcdef2ghi" and v="j" *\/ */
1623: /* int i,lg,j,p=0; */
1624: /* i=0; */
1625: /* lg=strlen(t); */
1626: /* for(j=0; j<=lg-1; j++) { */
1627: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1628: /* } */
1.126 brouard 1629:
1.137 brouard 1630: /* for(j=0; j<p; j++) { */
1631: /* (u[j] = t[j]); */
1632: /* } */
1633: /* u[p]='\0'; */
1.126 brouard 1634:
1.137 brouard 1635: /* for(j=0; j<= lg; j++) { */
1636: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1637: /* } */
1638: /* } */
1.126 brouard 1639:
1.160 brouard 1640: #ifdef _WIN32
1641: char * strsep(char **pp, const char *delim)
1642: {
1643: char *p, *q;
1644:
1645: if ((p = *pp) == NULL)
1646: return 0;
1647: if ((q = strpbrk (p, delim)) != NULL)
1648: {
1649: *pp = q + 1;
1650: *q = '\0';
1651: }
1652: else
1653: *pp = 0;
1654: return p;
1655: }
1656: #endif
1657:
1.126 brouard 1658: /********************** nrerror ********************/
1659:
1660: void nrerror(char error_text[])
1661: {
1662: fprintf(stderr,"ERREUR ...\n");
1663: fprintf(stderr,"%s\n",error_text);
1664: exit(EXIT_FAILURE);
1665: }
1666: /*********************** vector *******************/
1667: double *vector(int nl, int nh)
1668: {
1669: double *v;
1670: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
1671: if (!v) nrerror("allocation failure in vector");
1672: return v-nl+NR_END;
1673: }
1674:
1675: /************************ free vector ******************/
1676: void free_vector(double*v, int nl, int nh)
1677: {
1678: free((FREE_ARG)(v+nl-NR_END));
1679: }
1680:
1681: /************************ivector *******************************/
1682: int *ivector(long nl,long nh)
1683: {
1684: int *v;
1685: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
1686: if (!v) nrerror("allocation failure in ivector");
1687: return v-nl+NR_END;
1688: }
1689:
1690: /******************free ivector **************************/
1691: void free_ivector(int *v, long nl, long nh)
1692: {
1693: free((FREE_ARG)(v+nl-NR_END));
1694: }
1695:
1696: /************************lvector *******************************/
1697: long *lvector(long nl,long nh)
1698: {
1699: long *v;
1700: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
1701: if (!v) nrerror("allocation failure in ivector");
1702: return v-nl+NR_END;
1703: }
1704:
1705: /******************free lvector **************************/
1706: void free_lvector(long *v, long nl, long nh)
1707: {
1708: free((FREE_ARG)(v+nl-NR_END));
1709: }
1710:
1711: /******************* imatrix *******************************/
1712: int **imatrix(long nrl, long nrh, long ncl, long nch)
1713: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
1714: {
1715: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
1716: int **m;
1717:
1718: /* allocate pointers to rows */
1719: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
1720: if (!m) nrerror("allocation failure 1 in matrix()");
1721: m += NR_END;
1722: m -= nrl;
1723:
1724:
1725: /* allocate rows and set pointers to them */
1726: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
1727: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1728: m[nrl] += NR_END;
1729: m[nrl] -= ncl;
1730:
1731: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
1732:
1733: /* return pointer to array of pointers to rows */
1734: return m;
1735: }
1736:
1737: /****************** free_imatrix *************************/
1738: void free_imatrix(m,nrl,nrh,ncl,nch)
1739: int **m;
1740: long nch,ncl,nrh,nrl;
1741: /* free an int matrix allocated by imatrix() */
1742: {
1743: free((FREE_ARG) (m[nrl]+ncl-NR_END));
1744: free((FREE_ARG) (m+nrl-NR_END));
1745: }
1746:
1747: /******************* matrix *******************************/
1748: double **matrix(long nrl, long nrh, long ncl, long nch)
1749: {
1750: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
1751: double **m;
1752:
1753: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1754: if (!m) nrerror("allocation failure 1 in matrix()");
1755: m += NR_END;
1756: m -= nrl;
1757:
1758: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1759: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1760: m[nrl] += NR_END;
1761: m[nrl] -= ncl;
1762:
1763: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1764: return m;
1.145 brouard 1765: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
1766: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
1767: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 1768: */
1769: }
1770:
1771: /*************************free matrix ************************/
1772: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
1773: {
1774: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1775: free((FREE_ARG)(m+nrl-NR_END));
1776: }
1777:
1778: /******************* ma3x *******************************/
1779: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
1780: {
1781: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
1782: double ***m;
1783:
1784: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1785: if (!m) nrerror("allocation failure 1 in matrix()");
1786: m += NR_END;
1787: m -= nrl;
1788:
1789: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1790: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1791: m[nrl] += NR_END;
1792: m[nrl] -= ncl;
1793:
1794: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1795:
1796: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
1797: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
1798: m[nrl][ncl] += NR_END;
1799: m[nrl][ncl] -= nll;
1800: for (j=ncl+1; j<=nch; j++)
1801: m[nrl][j]=m[nrl][j-1]+nlay;
1802:
1803: for (i=nrl+1; i<=nrh; i++) {
1804: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
1805: for (j=ncl+1; j<=nch; j++)
1806: m[i][j]=m[i][j-1]+nlay;
1807: }
1808: return m;
1809: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
1810: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
1811: */
1812: }
1813:
1814: /*************************free ma3x ************************/
1815: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
1816: {
1817: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
1818: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1819: free((FREE_ARG)(m+nrl-NR_END));
1820: }
1821:
1822: /*************** function subdirf ***********/
1823: char *subdirf(char fileres[])
1824: {
1825: /* Caution optionfilefiname is hidden */
1826: strcpy(tmpout,optionfilefiname);
1827: strcat(tmpout,"/"); /* Add to the right */
1828: strcat(tmpout,fileres);
1829: return tmpout;
1830: }
1831:
1832: /*************** function subdirf2 ***********/
1833: char *subdirf2(char fileres[], char *preop)
1834: {
1835:
1836: /* Caution optionfilefiname is hidden */
1837: strcpy(tmpout,optionfilefiname);
1838: strcat(tmpout,"/");
1839: strcat(tmpout,preop);
1840: strcat(tmpout,fileres);
1841: return tmpout;
1842: }
1843:
1844: /*************** function subdirf3 ***********/
1845: char *subdirf3(char fileres[], char *preop, char *preop2)
1846: {
1847:
1848: /* Caution optionfilefiname is hidden */
1849: strcpy(tmpout,optionfilefiname);
1850: strcat(tmpout,"/");
1851: strcat(tmpout,preop);
1852: strcat(tmpout,preop2);
1853: strcat(tmpout,fileres);
1854: return tmpout;
1855: }
1.213 brouard 1856:
1857: /*************** function subdirfext ***********/
1858: char *subdirfext(char fileres[], char *preop, char *postop)
1859: {
1860:
1861: strcpy(tmpout,preop);
1862: strcat(tmpout,fileres);
1863: strcat(tmpout,postop);
1864: return tmpout;
1865: }
1.126 brouard 1866:
1.213 brouard 1867: /*************** function subdirfext3 ***********/
1868: char *subdirfext3(char fileres[], char *preop, char *postop)
1869: {
1870:
1871: /* Caution optionfilefiname is hidden */
1872: strcpy(tmpout,optionfilefiname);
1873: strcat(tmpout,"/");
1874: strcat(tmpout,preop);
1875: strcat(tmpout,fileres);
1876: strcat(tmpout,postop);
1877: return tmpout;
1878: }
1879:
1.162 brouard 1880: char *asc_diff_time(long time_sec, char ascdiff[])
1881: {
1882: long sec_left, days, hours, minutes;
1883: days = (time_sec) / (60*60*24);
1884: sec_left = (time_sec) % (60*60*24);
1885: hours = (sec_left) / (60*60) ;
1886: sec_left = (sec_left) %(60*60);
1887: minutes = (sec_left) /60;
1888: sec_left = (sec_left) % (60);
1889: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
1890: return ascdiff;
1891: }
1892:
1.126 brouard 1893: /***************** f1dim *************************/
1894: extern int ncom;
1895: extern double *pcom,*xicom;
1896: extern double (*nrfunc)(double []);
1897:
1898: double f1dim(double x)
1899: {
1900: int j;
1901: double f;
1902: double *xt;
1903:
1904: xt=vector(1,ncom);
1905: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
1906: f=(*nrfunc)(xt);
1907: free_vector(xt,1,ncom);
1908: return f;
1909: }
1910:
1911: /*****************brent *************************/
1912: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 1913: {
1914: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
1915: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
1916: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
1917: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
1918: * returned function value.
1919: */
1.126 brouard 1920: int iter;
1921: double a,b,d,etemp;
1.159 brouard 1922: double fu=0,fv,fw,fx;
1.164 brouard 1923: double ftemp=0.;
1.126 brouard 1924: double p,q,r,tol1,tol2,u,v,w,x,xm;
1925: double e=0.0;
1926:
1927: a=(ax < cx ? ax : cx);
1928: b=(ax > cx ? ax : cx);
1929: x=w=v=bx;
1930: fw=fv=fx=(*f)(x);
1931: for (iter=1;iter<=ITMAX;iter++) {
1932: xm=0.5*(a+b);
1933: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
1934: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
1935: printf(".");fflush(stdout);
1936: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 1937: #ifdef DEBUGBRENT
1.126 brouard 1938: 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);
1939: 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);
1940: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
1941: #endif
1942: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
1943: *xmin=x;
1944: return fx;
1945: }
1946: ftemp=fu;
1947: if (fabs(e) > tol1) {
1948: r=(x-w)*(fx-fv);
1949: q=(x-v)*(fx-fw);
1950: p=(x-v)*q-(x-w)*r;
1951: q=2.0*(q-r);
1952: if (q > 0.0) p = -p;
1953: q=fabs(q);
1954: etemp=e;
1955: e=d;
1956: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 1957: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 1958: else {
1.224 brouard 1959: d=p/q;
1960: u=x+d;
1961: if (u-a < tol2 || b-u < tol2)
1962: d=SIGN(tol1,xm-x);
1.126 brouard 1963: }
1964: } else {
1965: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1966: }
1967: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
1968: fu=(*f)(u);
1969: if (fu <= fx) {
1970: if (u >= x) a=x; else b=x;
1971: SHFT(v,w,x,u)
1.183 brouard 1972: SHFT(fv,fw,fx,fu)
1973: } else {
1974: if (u < x) a=u; else b=u;
1975: if (fu <= fw || w == x) {
1.224 brouard 1976: v=w;
1977: w=u;
1978: fv=fw;
1979: fw=fu;
1.183 brouard 1980: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 1981: v=u;
1982: fv=fu;
1.183 brouard 1983: }
1984: }
1.126 brouard 1985: }
1986: nrerror("Too many iterations in brent");
1987: *xmin=x;
1988: return fx;
1989: }
1990:
1991: /****************** mnbrak ***********************/
1992:
1993: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
1994: double (*func)(double))
1.183 brouard 1995: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
1996: the downhill direction (defined by the function as evaluated at the initial points) and returns
1997: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
1998: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
1999: */
1.126 brouard 2000: double ulim,u,r,q, dum;
2001: double fu;
1.187 brouard 2002:
2003: double scale=10.;
2004: int iterscale=0;
2005:
2006: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
2007: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
2008:
2009:
2010: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
2011: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
2012: /* *bx = *ax - (*ax - *bx)/scale; */
2013: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
2014: /* } */
2015:
1.126 brouard 2016: if (*fb > *fa) {
2017: SHFT(dum,*ax,*bx,dum)
1.183 brouard 2018: SHFT(dum,*fb,*fa,dum)
2019: }
1.126 brouard 2020: *cx=(*bx)+GOLD*(*bx-*ax);
2021: *fc=(*func)(*cx);
1.183 brouard 2022: #ifdef DEBUG
1.224 brouard 2023: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
2024: 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 2025: #endif
1.224 brouard 2026: 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 2027: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 2028: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 2029: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 2030: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
2031: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
2032: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 2033: fu=(*func)(u);
1.163 brouard 2034: #ifdef DEBUG
2035: /* f(x)=A(x-u)**2+f(u) */
2036: double A, fparabu;
2037: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2038: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 2039: 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);
2040: 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 2041: /* And thus,it can be that fu > *fc even if fparabu < *fc */
2042: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
2043: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
2044: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 2045: #endif
1.184 brouard 2046: #ifdef MNBRAKORIGINAL
1.183 brouard 2047: #else
1.191 brouard 2048: /* if (fu > *fc) { */
2049: /* #ifdef DEBUG */
2050: /* printf("mnbrak4 fu > fc \n"); */
2051: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
2052: /* #endif */
2053: /* /\* 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 *\\/ *\/ */
2054: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
2055: /* dum=u; /\* Shifting c and u *\/ */
2056: /* u = *cx; */
2057: /* *cx = dum; */
2058: /* dum = fu; */
2059: /* fu = *fc; */
2060: /* *fc =dum; */
2061: /* } else { /\* end *\/ */
2062: /* #ifdef DEBUG */
2063: /* printf("mnbrak3 fu < fc \n"); */
2064: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
2065: /* #endif */
2066: /* dum=u; /\* Shifting c and u *\/ */
2067: /* u = *cx; */
2068: /* *cx = dum; */
2069: /* dum = fu; */
2070: /* fu = *fc; */
2071: /* *fc =dum; */
2072: /* } */
1.224 brouard 2073: #ifdef DEBUGMNBRAK
2074: double A, fparabu;
2075: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2076: fparabu= *fa - A*(*ax-u)*(*ax-u);
2077: 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);
2078: 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 2079: #endif
1.191 brouard 2080: dum=u; /* Shifting c and u */
2081: u = *cx;
2082: *cx = dum;
2083: dum = fu;
2084: fu = *fc;
2085: *fc =dum;
1.183 brouard 2086: #endif
1.162 brouard 2087: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 2088: #ifdef DEBUG
1.224 brouard 2089: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
2090: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 2091: #endif
1.126 brouard 2092: fu=(*func)(u);
2093: if (fu < *fc) {
1.183 brouard 2094: #ifdef DEBUG
1.224 brouard 2095: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2096: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2097: #endif
2098: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
2099: SHFT(*fb,*fc,fu,(*func)(u))
2100: #ifdef DEBUG
2101: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 2102: #endif
2103: }
1.162 brouard 2104: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 2105: #ifdef DEBUG
1.224 brouard 2106: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
2107: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 2108: #endif
1.126 brouard 2109: u=ulim;
2110: fu=(*func)(u);
1.183 brouard 2111: } else { /* u could be left to b (if r > q parabola has a maximum) */
2112: #ifdef DEBUG
1.224 brouard 2113: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
2114: 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 2115: #endif
1.126 brouard 2116: u=(*cx)+GOLD*(*cx-*bx);
2117: fu=(*func)(u);
1.224 brouard 2118: #ifdef DEBUG
2119: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2120: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2121: #endif
1.183 brouard 2122: } /* end tests */
1.126 brouard 2123: SHFT(*ax,*bx,*cx,u)
1.183 brouard 2124: SHFT(*fa,*fb,*fc,fu)
2125: #ifdef DEBUG
1.224 brouard 2126: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2127: 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 2128: #endif
2129: } /* 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 2130: }
2131:
2132: /*************** linmin ************************/
1.162 brouard 2133: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2134: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2135: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2136: the value of func at the returned location p . This is actually all accomplished by calling the
2137: routines mnbrak and brent .*/
1.126 brouard 2138: int ncom;
2139: double *pcom,*xicom;
2140: double (*nrfunc)(double []);
2141:
1.224 brouard 2142: #ifdef LINMINORIGINAL
1.126 brouard 2143: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2144: #else
2145: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2146: #endif
1.126 brouard 2147: {
2148: double brent(double ax, double bx, double cx,
2149: double (*f)(double), double tol, double *xmin);
2150: double f1dim(double x);
2151: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2152: double *fc, double (*func)(double));
2153: int j;
2154: double xx,xmin,bx,ax;
2155: double fx,fb,fa;
1.187 brouard 2156:
1.203 brouard 2157: #ifdef LINMINORIGINAL
2158: #else
2159: double scale=10., axs, xxs; /* Scale added for infinity */
2160: #endif
2161:
1.126 brouard 2162: ncom=n;
2163: pcom=vector(1,n);
2164: xicom=vector(1,n);
2165: nrfunc=func;
2166: for (j=1;j<=n;j++) {
2167: pcom[j]=p[j];
1.202 brouard 2168: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2169: }
1.187 brouard 2170:
1.203 brouard 2171: #ifdef LINMINORIGINAL
2172: xx=1.;
2173: #else
2174: axs=0.0;
2175: xxs=1.;
2176: do{
2177: xx= xxs;
2178: #endif
1.187 brouard 2179: ax=0.;
2180: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2181: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2182: /* 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)) */
2183: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2184: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2185: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2186: /* 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 2187: #ifdef LINMINORIGINAL
2188: #else
2189: if (fx != fx){
1.224 brouard 2190: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2191: printf("|");
2192: fprintf(ficlog,"|");
1.203 brouard 2193: #ifdef DEBUGLINMIN
1.224 brouard 2194: 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 2195: #endif
2196: }
1.224 brouard 2197: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2198: #endif
2199:
1.191 brouard 2200: #ifdef DEBUGLINMIN
2201: 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 2202: 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 2203: #endif
1.224 brouard 2204: #ifdef LINMINORIGINAL
2205: #else
2206: if(fb == fx){ /* Flat function in the direction */
2207: xmin=xx;
2208: *flat=1;
2209: }else{
2210: *flat=0;
2211: #endif
2212: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2213: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2214: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2215: /* fmin = f(p[j] + xmin * xi[j]) */
2216: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2217: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2218: #ifdef DEBUG
1.224 brouard 2219: 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);
2220: 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);
2221: #endif
2222: #ifdef LINMINORIGINAL
2223: #else
2224: }
1.126 brouard 2225: #endif
1.191 brouard 2226: #ifdef DEBUGLINMIN
2227: printf("linmin end ");
1.202 brouard 2228: fprintf(ficlog,"linmin end ");
1.191 brouard 2229: #endif
1.126 brouard 2230: for (j=1;j<=n;j++) {
1.203 brouard 2231: #ifdef LINMINORIGINAL
2232: xi[j] *= xmin;
2233: #else
2234: #ifdef DEBUGLINMIN
2235: if(xxs <1.0)
2236: printf(" before xi[%d]=%12.8f", j,xi[j]);
2237: #endif
2238: 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) */
2239: #ifdef DEBUGLINMIN
2240: if(xxs <1.0)
2241: 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 );
2242: #endif
2243: #endif
1.187 brouard 2244: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2245: }
1.191 brouard 2246: #ifdef DEBUGLINMIN
1.203 brouard 2247: printf("\n");
1.191 brouard 2248: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2249: 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 2250: for (j=1;j<=n;j++) {
1.202 brouard 2251: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2252: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2253: if(j % ncovmodel == 0){
1.191 brouard 2254: printf("\n");
1.202 brouard 2255: fprintf(ficlog,"\n");
2256: }
1.191 brouard 2257: }
1.203 brouard 2258: #else
1.191 brouard 2259: #endif
1.126 brouard 2260: free_vector(xicom,1,n);
2261: free_vector(pcom,1,n);
2262: }
2263:
2264:
2265: /*************** powell ************************/
1.162 brouard 2266: /*
2267: Minimization of a function func of n variables. Input consists of an initial starting point
2268: p[1..n] ; an initial matrix xi[1..n][1..n] , whose columns contain the initial set of di-
2269: rections (usually the n unit vectors); and ftol , the fractional tolerance in the function value
2270: such that failure to decrease by more than this amount on one iteration signals doneness. On
2271: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2272: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2273: */
1.224 brouard 2274: #ifdef LINMINORIGINAL
2275: #else
2276: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2277: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2278: #endif
1.126 brouard 2279: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2280: double (*func)(double []))
2281: {
1.224 brouard 2282: #ifdef LINMINORIGINAL
2283: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2284: double (*func)(double []));
1.224 brouard 2285: #else
1.241 brouard 2286: void linmin(double p[], double xi[], int n, double *fret,
2287: double (*func)(double []),int *flat);
1.224 brouard 2288: #endif
1.239 brouard 2289: int i,ibig,j,jk,k;
1.126 brouard 2290: double del,t,*pt,*ptt,*xit;
1.181 brouard 2291: double directest;
1.126 brouard 2292: double fp,fptt;
2293: double *xits;
2294: int niterf, itmp;
1.224 brouard 2295: #ifdef LINMINORIGINAL
2296: #else
2297:
2298: flatdir=ivector(1,n);
2299: for (j=1;j<=n;j++) flatdir[j]=0;
2300: #endif
1.126 brouard 2301:
2302: pt=vector(1,n);
2303: ptt=vector(1,n);
2304: xit=vector(1,n);
2305: xits=vector(1,n);
2306: *fret=(*func)(p);
2307: for (j=1;j<=n;j++) pt[j]=p[j];
1.202 brouard 2308: rcurr_time = time(NULL);
1.126 brouard 2309: for (*iter=1;;++(*iter)) {
1.187 brouard 2310: fp=(*fret); /* From former iteration or initial value */
1.126 brouard 2311: ibig=0;
2312: del=0.0;
1.157 brouard 2313: rlast_time=rcurr_time;
2314: /* (void) gettimeofday(&curr_time,&tzp); */
2315: rcurr_time = time(NULL);
2316: curr_time = *localtime(&rcurr_time);
2317: printf("\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout);
2318: fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog);
2319: /* fprintf(ficrespow,"%d %.12f %ld",*iter,*fret,curr_time.tm_sec-start_time.tm_sec); */
1.192 brouard 2320: for (i=1;i<=n;i++) {
1.126 brouard 2321: fprintf(ficrespow," %.12lf", p[i]);
2322: }
1.239 brouard 2323: fprintf(ficrespow,"\n");fflush(ficrespow);
2324: printf("\n#model= 1 + age ");
2325: fprintf(ficlog,"\n#model= 1 + age ");
2326: if(nagesqr==1){
1.241 brouard 2327: printf(" + age*age ");
2328: fprintf(ficlog," + age*age ");
1.239 brouard 2329: }
2330: for(j=1;j <=ncovmodel-2;j++){
2331: if(Typevar[j]==0) {
2332: printf(" + V%d ",Tvar[j]);
2333: fprintf(ficlog," + V%d ",Tvar[j]);
2334: }else if(Typevar[j]==1) {
2335: printf(" + V%d*age ",Tvar[j]);
2336: fprintf(ficlog," + V%d*age ",Tvar[j]);
2337: }else if(Typevar[j]==2) {
2338: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2339: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2340: }
2341: }
1.126 brouard 2342: printf("\n");
1.239 brouard 2343: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2344: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2345: fprintf(ficlog,"\n");
1.239 brouard 2346: for(i=1,jk=1; i <=nlstate; i++){
2347: for(k=1; k <=(nlstate+ndeath); k++){
2348: if (k != i) {
2349: printf("%d%d ",i,k);
2350: fprintf(ficlog,"%d%d ",i,k);
2351: for(j=1; j <=ncovmodel; j++){
2352: printf("%12.7f ",p[jk]);
2353: fprintf(ficlog,"%12.7f ",p[jk]);
2354: jk++;
2355: }
2356: printf("\n");
2357: fprintf(ficlog,"\n");
2358: }
2359: }
2360: }
1.241 brouard 2361: if(*iter <=3 && *iter >1){
1.157 brouard 2362: tml = *localtime(&rcurr_time);
2363: strcpy(strcurr,asctime(&tml));
2364: rforecast_time=rcurr_time;
1.126 brouard 2365: itmp = strlen(strcurr);
2366: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2367: strcurr[itmp-1]='\0';
1.162 brouard 2368: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2369: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.126 brouard 2370: for(niterf=10;niterf<=30;niterf+=10){
1.241 brouard 2371: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2372: forecast_time = *localtime(&rforecast_time);
2373: strcpy(strfor,asctime(&forecast_time));
2374: itmp = strlen(strfor);
2375: if(strfor[itmp-1]=='\n')
2376: strfor[itmp-1]='\0';
2377: 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);
2378: 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 2379: }
2380: }
1.187 brouard 2381: for (i=1;i<=n;i++) { /* For each direction i */
2382: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2383: fptt=(*fret);
2384: #ifdef DEBUG
1.203 brouard 2385: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2386: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2387: #endif
1.203 brouard 2388: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2389: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2390: #ifdef LINMINORIGINAL
1.188 brouard 2391: linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.224 brouard 2392: #else
2393: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2394: flatdir[i]=flat; /* Function is vanishing in that direction i */
2395: #endif
2396: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2397: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2398: /* because that direction will be replaced unless the gain del is small */
2399: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2400: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2401: /* with the new direction. */
2402: del=fabs(fptt-(*fret));
2403: ibig=i;
1.126 brouard 2404: }
2405: #ifdef DEBUG
2406: printf("%d %.12e",i,(*fret));
2407: fprintf(ficlog,"%d %.12e",i,(*fret));
2408: for (j=1;j<=n;j++) {
1.224 brouard 2409: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2410: printf(" x(%d)=%.12e",j,xit[j]);
2411: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2412: }
2413: for(j=1;j<=n;j++) {
1.225 brouard 2414: printf(" p(%d)=%.12e",j,p[j]);
2415: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2416: }
2417: printf("\n");
2418: fprintf(ficlog,"\n");
2419: #endif
1.187 brouard 2420: } /* end loop on each direction i */
2421: /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
1.188 brouard 2422: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.187 brouard 2423: /* New value of last point Pn is not computed, P(n-1) */
1.224 brouard 2424: for(j=1;j<=n;j++) {
1.302 brouard 2425: if(flatdir[j] >0){
2426: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2427: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2428: }
2429: /* printf("\n"); */
2430: /* fprintf(ficlog,"\n"); */
2431: }
1.243 brouard 2432: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
2433: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2434: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2435: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2436: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2437: /* decreased of more than 3.84 */
2438: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2439: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2440: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2441:
1.188 brouard 2442: /* Starting the program with initial values given by a former maximization will simply change */
2443: /* the scales of the directions and the directions, because the are reset to canonical directions */
2444: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2445: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2446: #ifdef DEBUG
2447: int k[2],l;
2448: k[0]=1;
2449: k[1]=-1;
2450: printf("Max: %.12e",(*func)(p));
2451: fprintf(ficlog,"Max: %.12e",(*func)(p));
2452: for (j=1;j<=n;j++) {
2453: printf(" %.12e",p[j]);
2454: fprintf(ficlog," %.12e",p[j]);
2455: }
2456: printf("\n");
2457: fprintf(ficlog,"\n");
2458: for(l=0;l<=1;l++) {
2459: for (j=1;j<=n;j++) {
2460: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2461: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2462: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2463: }
2464: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2465: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2466: }
2467: #endif
2468:
1.224 brouard 2469: #ifdef LINMINORIGINAL
2470: #else
2471: free_ivector(flatdir,1,n);
2472: #endif
1.126 brouard 2473: free_vector(xit,1,n);
2474: free_vector(xits,1,n);
2475: free_vector(ptt,1,n);
2476: free_vector(pt,1,n);
2477: return;
1.192 brouard 2478: } /* enough precision */
1.240 brouard 2479: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2480: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2481: ptt[j]=2.0*p[j]-pt[j];
2482: xit[j]=p[j]-pt[j];
2483: pt[j]=p[j];
2484: }
1.181 brouard 2485: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2486: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2487: if (*iter <=4) {
1.225 brouard 2488: #else
2489: #endif
1.224 brouard 2490: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2491: #else
1.161 brouard 2492: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2493: #endif
1.162 brouard 2494: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2495: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2496: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2497: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2498: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2499: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2500: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2501: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2502: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2503: /* Even if f3 <f1, directest can be negative and t >0 */
2504: /* mu² and del² are equal when f3=f1 */
2505: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2506: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2507: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2508: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2509: #ifdef NRCORIGINAL
2510: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2511: #else
2512: 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 2513: t= t- del*SQR(fp-fptt);
1.183 brouard 2514: #endif
1.202 brouard 2515: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2516: #ifdef DEBUG
1.181 brouard 2517: 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);
2518: 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 2519: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2520: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2521: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2522: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2523: 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);
2524: 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);
2525: #endif
1.183 brouard 2526: #ifdef POWELLORIGINAL
2527: if (t < 0.0) { /* Then we use it for new direction */
2528: #else
1.182 brouard 2529: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2530: 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 2531: 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 2532: 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 2533: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2534: }
1.181 brouard 2535: if (directest < 0.0) { /* Then we use it for new direction */
2536: #endif
1.191 brouard 2537: #ifdef DEBUGLINMIN
1.234 brouard 2538: printf("Before linmin in direction P%d-P0\n",n);
2539: for (j=1;j<=n;j++) {
2540: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2541: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2542: if(j % ncovmodel == 0){
2543: printf("\n");
2544: fprintf(ficlog,"\n");
2545: }
2546: }
1.224 brouard 2547: #endif
2548: #ifdef LINMINORIGINAL
1.234 brouard 2549: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2550: #else
1.234 brouard 2551: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2552: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2553: #endif
1.234 brouard 2554:
1.191 brouard 2555: #ifdef DEBUGLINMIN
1.234 brouard 2556: for (j=1;j<=n;j++) {
2557: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2558: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2559: if(j % ncovmodel == 0){
2560: printf("\n");
2561: fprintf(ficlog,"\n");
2562: }
2563: }
1.224 brouard 2564: #endif
1.234 brouard 2565: for (j=1;j<=n;j++) {
2566: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2567: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2568: }
1.224 brouard 2569: #ifdef LINMINORIGINAL
2570: #else
1.234 brouard 2571: for (j=1, flatd=0;j<=n;j++) {
2572: if(flatdir[j]>0)
2573: flatd++;
2574: }
2575: if(flatd >0){
1.255 brouard 2576: printf("%d flat directions: ",flatd);
2577: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 2578: for (j=1;j<=n;j++) {
2579: if(flatdir[j]>0){
2580: printf("%d ",j);
2581: fprintf(ficlog,"%d ",j);
2582: }
2583: }
2584: printf("\n");
2585: fprintf(ficlog,"\n");
2586: }
1.191 brouard 2587: #endif
1.234 brouard 2588: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2589: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2590:
1.126 brouard 2591: #ifdef DEBUG
1.234 brouard 2592: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2593: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2594: for(j=1;j<=n;j++){
2595: printf(" %lf",xit[j]);
2596: fprintf(ficlog," %lf",xit[j]);
2597: }
2598: printf("\n");
2599: fprintf(ficlog,"\n");
1.126 brouard 2600: #endif
1.192 brouard 2601: } /* end of t or directest negative */
1.224 brouard 2602: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2603: #else
1.234 brouard 2604: } /* end if (fptt < fp) */
1.192 brouard 2605: #endif
1.225 brouard 2606: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2607: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2608: #else
1.224 brouard 2609: #endif
1.234 brouard 2610: } /* loop iteration */
1.126 brouard 2611: }
1.234 brouard 2612:
1.126 brouard 2613: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 2614:
1.235 brouard 2615: 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 2616: {
1.279 brouard 2617: /**< Computes the prevalence limit in each live state at age x and for covariate combination ij
2618: * (and selected quantitative values in nres)
2619: * by left multiplying the unit
2620: * matrix by transitions matrix until convergence is reached with precision ftolpl
2621: * Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I
2622: * Wx is row vector: population in state 1, population in state 2, population dead
2623: * or prevalence in state 1, prevalence in state 2, 0
2624: * newm is the matrix after multiplications, its rows are identical at a factor.
2625: * Inputs are the parameter, age, a tolerance for the prevalence limit ftolpl.
2626: * Output is prlim.
2627: * Initial matrix pimij
2628: */
1.206 brouard 2629: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2630: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2631: /* 0, 0 , 1} */
2632: /*
2633: * and after some iteration: */
2634: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2635: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2636: /* 0, 0 , 1} */
2637: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2638: /* {0.51571254859325999, 0.4842874514067399, */
2639: /* 0.51326036147820708, 0.48673963852179264} */
2640: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 2641:
1.126 brouard 2642: int i, ii,j,k;
1.209 brouard 2643: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 2644: /* double **matprod2(); */ /* test */
1.218 brouard 2645: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 2646: double **newm;
1.209 brouard 2647: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 2648: int ncvloop=0;
1.288 brouard 2649: int first=0;
1.169 brouard 2650:
1.209 brouard 2651: min=vector(1,nlstate);
2652: max=vector(1,nlstate);
2653: meandiff=vector(1,nlstate);
2654:
1.218 brouard 2655: /* Starting with matrix unity */
1.126 brouard 2656: for (ii=1;ii<=nlstate+ndeath;ii++)
2657: for (j=1;j<=nlstate+ndeath;j++){
2658: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2659: }
1.169 brouard 2660:
2661: cov[1]=1.;
2662:
2663: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 2664: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 2665: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 2666: ncvloop++;
1.126 brouard 2667: newm=savm;
2668: /* Covariates have to be included here again */
1.138 brouard 2669: cov[2]=agefin;
1.187 brouard 2670: if(nagesqr==1)
2671: cov[3]= agefin*agefin;;
1.234 brouard 2672: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2673: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2674: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.235 brouard 2675: /* 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 2676: }
2677: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2678: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
1.235 brouard 2679: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2680: /* 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 2681: }
1.237 brouard 2682: for (k=1; k<=cptcovage;k++){ /* For product with age */
1.234 brouard 2683: if(Dummy[Tvar[Tage[k]]]){
2684: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
2685: } else{
1.235 brouard 2686: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
1.234 brouard 2687: }
1.235 brouard 2688: /* 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 2689: }
1.237 brouard 2690: for (k=1; k<=cptcovprod;k++){ /* For product without age */
1.235 brouard 2691: /* 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 2692: if(Dummy[Tvard[k][1]==0]){
2693: if(Dummy[Tvard[k][2]==0]){
2694: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2695: }else{
2696: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2697: }
2698: }else{
2699: if(Dummy[Tvard[k][2]==0]){
2700: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2701: }else{
2702: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2703: }
2704: }
1.234 brouard 2705: }
1.138 brouard 2706: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2707: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2708: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 2709: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2710: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2711: /* age and covariate values of ij are in 'cov' */
1.142 brouard 2712: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 2713:
1.126 brouard 2714: savm=oldm;
2715: oldm=newm;
1.209 brouard 2716:
2717: for(j=1; j<=nlstate; j++){
2718: max[j]=0.;
2719: min[j]=1.;
2720: }
2721: for(i=1;i<=nlstate;i++){
2722: sumnew=0;
2723: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
2724: for(j=1; j<=nlstate; j++){
2725: prlim[i][j]= newm[i][j]/(1-sumnew);
2726: max[j]=FMAX(max[j],prlim[i][j]);
2727: min[j]=FMIN(min[j],prlim[i][j]);
2728: }
2729: }
2730:
1.126 brouard 2731: maxmax=0.;
1.209 brouard 2732: for(j=1; j<=nlstate; j++){
2733: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
2734: maxmax=FMAX(maxmax,meandiff[j]);
2735: /* 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 2736: } /* j loop */
1.203 brouard 2737: *ncvyear= (int)age- (int)agefin;
1.208 brouard 2738: /* 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 2739: if(maxmax < ftolpl){
1.209 brouard 2740: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
2741: free_vector(min,1,nlstate);
2742: free_vector(max,1,nlstate);
2743: free_vector(meandiff,1,nlstate);
1.126 brouard 2744: return prlim;
2745: }
1.288 brouard 2746: } /* agefin loop */
1.208 brouard 2747: /* After some age loop it doesn't converge */
1.288 brouard 2748: if(!first){
2749: first=1;
2750: printf("Warning: the stable prevalence at age %d did not converge with the required precision (%g > ftolpl=%g) within %.d years and %d loops. Try to lower 'ftolpl'. Youngest age to start was %d=(%d-%d). Others in log file only...\n", (int)age, maxmax, ftolpl, *ncvyear, ncvloop, (int)(agefin+stepm/YEARM), (int)(age-stepm/YEARM), (int)delaymax);
2751: }
2752: fprintf(ficlog, "Warning: the stable prevalence at age %d did not converge with the required precision (%g > ftolpl=%g) within %.d years and %d loops. Try to lower 'ftolpl'. Youngest age to start was %d=(%d-%d).\n", (int)age, maxmax, ftolpl, *ncvyear, ncvloop, (int)(agefin+stepm/YEARM), (int)(age-stepm/YEARM), (int)delaymax);
2753:
1.209 brouard 2754: /* 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); */
2755: free_vector(min,1,nlstate);
2756: free_vector(max,1,nlstate);
2757: free_vector(meandiff,1,nlstate);
1.208 brouard 2758:
1.169 brouard 2759: return prlim; /* should not reach here */
1.126 brouard 2760: }
2761:
1.217 brouard 2762:
2763: /**** Back Prevalence limit (stable or period prevalence) ****************/
2764:
1.218 brouard 2765: /* 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) */
2766: /* 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 2767: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 2768: {
1.264 brouard 2769: /* 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 2770: matrix by transitions matrix until convergence is reached with precision ftolpl */
2771: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
2772: /* Wx is row vector: population in state 1, population in state 2, population dead */
2773: /* or prevalence in state 1, prevalence in state 2, 0 */
2774: /* newm is the matrix after multiplications, its rows are identical at a factor */
2775: /* Initial matrix pimij */
2776: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2777: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2778: /* 0, 0 , 1} */
2779: /*
2780: * and after some iteration: */
2781: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2782: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2783: /* 0, 0 , 1} */
2784: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2785: /* {0.51571254859325999, 0.4842874514067399, */
2786: /* 0.51326036147820708, 0.48673963852179264} */
2787: /* If we start from prlim again, prlim tends to a constant matrix */
2788:
2789: int i, ii,j,k;
1.247 brouard 2790: int first=0;
1.217 brouard 2791: double *min, *max, *meandiff, maxmax,sumnew=0.;
2792: /* double **matprod2(); */ /* test */
2793: double **out, cov[NCOVMAX+1], **bmij();
2794: double **newm;
1.218 brouard 2795: double **dnewm, **doldm, **dsavm; /* for use */
2796: double **oldm, **savm; /* for use */
2797:
1.217 brouard 2798: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
2799: int ncvloop=0;
2800:
2801: min=vector(1,nlstate);
2802: max=vector(1,nlstate);
2803: meandiff=vector(1,nlstate);
2804:
1.266 brouard 2805: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
2806: oldm=oldms; savm=savms;
2807:
2808: /* Starting with matrix unity */
2809: for (ii=1;ii<=nlstate+ndeath;ii++)
2810: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 2811: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2812: }
2813:
2814: cov[1]=1.;
2815:
2816: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
2817: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 2818: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
1.288 brouard 2819: /* for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
2820: for(agefin=age; agefin<FMIN(AGESUP,age+delaymax); agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 2821: ncvloop++;
1.218 brouard 2822: newm=savm; /* oldm should be kept from previous iteration or unity at start */
2823: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 2824: /* Covariates have to be included here again */
2825: cov[2]=agefin;
2826: if(nagesqr==1)
2827: cov[3]= agefin*agefin;;
1.242 brouard 2828: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2829: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2830: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.264 brouard 2831: /* 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 2832: }
2833: /* for (k=1; k<=cptcovn;k++) { */
2834: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
2835: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
2836: /* /\* 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])]); *\/ */
2837: /* } */
2838: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2839: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
2840: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2841: /* 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]); */
2842: }
2843: /* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; */
2844: /* for (k=1; k<=cptcovprod;k++) /\* Useless *\/ */
2845: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\/ */
2846: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */
2847: for (k=1; k<=cptcovage;k++){ /* For product with age */
2848: if(Dummy[Tvar[Tage[k]]]){
2849: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
2850: } else{
2851: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
2852: }
2853: /* 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]); */
2854: }
2855: for (k=1; k<=cptcovprod;k++){ /* For product without age */
2856: /* 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]); */
2857: if(Dummy[Tvard[k][1]==0]){
2858: if(Dummy[Tvard[k][2]==0]){
2859: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2860: }else{
2861: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2862: }
2863: }else{
2864: if(Dummy[Tvard[k][2]==0]){
2865: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2866: }else{
2867: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2868: }
2869: }
1.217 brouard 2870: }
2871:
2872: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2873: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2874: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
2875: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2876: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2877: /* ij should be linked to the correct index of cov */
2878: /* age and covariate values ij are in 'cov', but we need to pass
2879: * ij for the observed prevalence at age and status and covariate
2880: * number: prevacurrent[(int)agefin][ii][ij]
2881: */
2882: /* 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 *\/ */
2883: /* 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 *\/ */
2884: 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 2885: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 2886: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
2887: /* for(i=1; i<=nlstate+ndeath; i++) { */
2888: /* printf("%d newm= ",i); */
2889: /* for(j=1;j<=nlstate+ndeath;j++) { */
2890: /* printf("%f ",newm[i][j]); */
2891: /* } */
2892: /* printf("oldm * "); */
2893: /* for(j=1;j<=nlstate+ndeath;j++) { */
2894: /* printf("%f ",oldm[i][j]); */
2895: /* } */
1.268 brouard 2896: /* printf(" bmmij "); */
1.266 brouard 2897: /* for(j=1;j<=nlstate+ndeath;j++) { */
2898: /* printf("%f ",pmmij[i][j]); */
2899: /* } */
2900: /* printf("\n"); */
2901: /* } */
2902: /* } */
1.217 brouard 2903: savm=oldm;
2904: oldm=newm;
1.266 brouard 2905:
1.217 brouard 2906: for(j=1; j<=nlstate; j++){
2907: max[j]=0.;
2908: min[j]=1.;
2909: }
2910: for(j=1; j<=nlstate; j++){
2911: for(i=1;i<=nlstate;i++){
1.234 brouard 2912: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
2913: bprlim[i][j]= newm[i][j];
2914: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
2915: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 2916: }
2917: }
1.218 brouard 2918:
1.217 brouard 2919: maxmax=0.;
2920: for(i=1; i<=nlstate; i++){
2921: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column */
2922: maxmax=FMAX(maxmax,meandiff[i]);
2923: /* 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 2924: } /* i loop */
1.217 brouard 2925: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 2926: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 2927: if(maxmax < ftolpl){
1.220 brouard 2928: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 2929: free_vector(min,1,nlstate);
2930: free_vector(max,1,nlstate);
2931: free_vector(meandiff,1,nlstate);
2932: return bprlim;
2933: }
1.288 brouard 2934: } /* agefin loop */
1.217 brouard 2935: /* After some age loop it doesn't converge */
1.288 brouard 2936: if(!first){
1.247 brouard 2937: first=1;
2938: 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\
2939: 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);
2940: }
2941: 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 2942: 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);
2943: /* 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); */
2944: free_vector(min,1,nlstate);
2945: free_vector(max,1,nlstate);
2946: free_vector(meandiff,1,nlstate);
2947:
2948: return bprlim; /* should not reach here */
2949: }
2950:
1.126 brouard 2951: /*************** transition probabilities ***************/
2952:
2953: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
2954: {
1.138 brouard 2955: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 2956: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 2957: model to the ncovmodel covariates (including constant and age).
2958: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
2959: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
2960: ncth covariate in the global vector x is given by the formula:
2961: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
2962: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
2963: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
2964: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 2965: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 2966: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 2967: Sum on j ps[i][j] should equal to 1.
1.138 brouard 2968: */
2969: double s1, lnpijopii;
1.126 brouard 2970: /*double t34;*/
1.164 brouard 2971: int i,j, nc, ii, jj;
1.126 brouard 2972:
1.223 brouard 2973: for(i=1; i<= nlstate; i++){
2974: for(j=1; j<i;j++){
2975: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2976: /*lnpijopii += param[i][j][nc]*cov[nc];*/
2977: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
2978: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2979: }
2980: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2981: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2982: }
2983: for(j=i+1; j<=nlstate+ndeath;j++){
2984: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2985: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
2986: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
2987: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
2988: }
2989: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2990: }
2991: }
1.218 brouard 2992:
1.223 brouard 2993: for(i=1; i<= nlstate; i++){
2994: s1=0;
2995: for(j=1; j<i; j++){
2996: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2997: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2998: }
2999: for(j=i+1; j<=nlstate+ndeath; j++){
3000: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3001: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3002: }
3003: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3004: ps[i][i]=1./(s1+1.);
3005: /* Computing other pijs */
3006: for(j=1; j<i; j++)
3007: ps[i][j]= exp(ps[i][j])*ps[i][i];
3008: for(j=i+1; j<=nlstate+ndeath; j++)
3009: ps[i][j]= exp(ps[i][j])*ps[i][i];
3010: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3011: } /* end i */
1.218 brouard 3012:
1.223 brouard 3013: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3014: for(jj=1; jj<= nlstate+ndeath; jj++){
3015: ps[ii][jj]=0;
3016: ps[ii][ii]=1;
3017: }
3018: }
1.294 brouard 3019:
3020:
1.223 brouard 3021: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3022: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3023: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3024: /* } */
3025: /* printf("\n "); */
3026: /* } */
3027: /* printf("\n ");printf("%lf ",cov[2]);*/
3028: /*
3029: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 3030: goto end;*/
1.266 brouard 3031: return ps; /* Pointer is unchanged since its call */
1.126 brouard 3032: }
3033:
1.218 brouard 3034: /*************** backward transition probabilities ***************/
3035:
3036: /* 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 ) */
3037: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
3038: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
3039: {
1.302 brouard 3040: /* Computes the backward probability at age agefin, cov[2], and covariate combination 'ij'. In fact cov is already filled and x too.
1.266 brouard 3041: * 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 3042: */
1.218 brouard 3043: int i, ii, j,k;
1.222 brouard 3044:
3045: double **out, **pmij();
3046: double sumnew=0.;
1.218 brouard 3047: double agefin;
1.292 brouard 3048: double k3=0.; /* constant of the w_x diagonal matrix (in order for B to sum to 1 even for death state) */
1.222 brouard 3049: double **dnewm, **dsavm, **doldm;
3050: double **bbmij;
3051:
1.218 brouard 3052: doldm=ddoldms; /* global pointers */
1.222 brouard 3053: dnewm=ddnewms;
3054: dsavm=ddsavms;
3055:
3056: agefin=cov[2];
1.268 brouard 3057: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 3058: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 3059: the observed prevalence (with this covariate ij) at beginning of transition */
3060: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 3061:
3062: /* P_x */
1.266 brouard 3063: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm */
1.268 brouard 3064: /* outputs pmmij which is a stochastic matrix in row */
3065:
3066: /* Diag(w_x) */
1.292 brouard 3067: /* Rescaling the cross-sectional prevalence: Problem with prevacurrent which can be zero */
1.268 brouard 3068: sumnew=0.;
1.269 brouard 3069: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 3070: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.297 brouard 3071: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 3072: sumnew+=prevacurrent[(int)agefin][ii][ij];
3073: }
3074: if(sumnew >0.01){ /* At least some value in the prevalence */
3075: for (ii=1;ii<=nlstate+ndeath;ii++){
3076: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 3077: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 3078: }
3079: }else{
3080: for (ii=1;ii<=nlstate+ndeath;ii++){
3081: for (j=1;j<=nlstate+ndeath;j++)
3082: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
3083: }
3084: /* if(sumnew <0.9){ */
3085: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
3086: /* } */
3087: }
3088: k3=0.0; /* We put the last diagonal to 0 */
3089: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
3090: doldm[ii][ii]= k3;
3091: }
3092: /* End doldm, At the end doldm is diag[(w_i)] */
3093:
1.292 brouard 3094: /* Left product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm): diag[(w_i)*Px */
3095: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* was a Bug Valgrind */
1.268 brouard 3096:
1.292 brouard 3097: /* Diag(Sum_i w^i_x p^ij_x, should be the prevalence at age x+stepm */
1.268 brouard 3098: /* 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 3099: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 3100: sumnew=0.;
1.222 brouard 3101: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 3102: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 3103: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 3104: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 3105: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 3106: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 3107: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3108: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 3109: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3110: /* }else */
1.268 brouard 3111: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
3112: } /*End ii */
3113: } /* 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 */
3114:
1.292 brouard 3115: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* was a Bug Valgrind */
1.268 brouard 3116: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 3117: /* end bmij */
1.266 brouard 3118: return ps; /*pointer is unchanged */
1.218 brouard 3119: }
1.217 brouard 3120: /*************** transition probabilities ***************/
3121:
1.218 brouard 3122: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 3123: {
3124: /* According to parameters values stored in x and the covariate's values stored in cov,
3125: computes the probability to be observed in state j being in state i by appying the
3126: model to the ncovmodel covariates (including constant and age).
3127: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3128: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3129: ncth covariate in the global vector x is given by the formula:
3130: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3131: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3132: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3133: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
3134: Outputs ps[i][j] the probability to be observed in j being in j according to
3135: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
3136: */
3137: double s1, lnpijopii;
3138: /*double t34;*/
3139: int i,j, nc, ii, jj;
3140:
1.234 brouard 3141: for(i=1; i<= nlstate; i++){
3142: for(j=1; j<i;j++){
3143: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3144: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3145: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3146: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3147: }
3148: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3149: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3150: }
3151: for(j=i+1; j<=nlstate+ndeath;j++){
3152: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3153: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3154: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3155: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3156: }
3157: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3158: }
3159: }
3160:
3161: for(i=1; i<= nlstate; i++){
3162: s1=0;
3163: for(j=1; j<i; j++){
3164: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3165: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3166: }
3167: for(j=i+1; j<=nlstate+ndeath; j++){
3168: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3169: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3170: }
3171: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3172: ps[i][i]=1./(s1+1.);
3173: /* Computing other pijs */
3174: for(j=1; j<i; j++)
3175: ps[i][j]= exp(ps[i][j])*ps[i][i];
3176: for(j=i+1; j<=nlstate+ndeath; j++)
3177: ps[i][j]= exp(ps[i][j])*ps[i][i];
3178: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3179: } /* end i */
3180:
3181: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3182: for(jj=1; jj<= nlstate+ndeath; jj++){
3183: ps[ii][jj]=0;
3184: ps[ii][ii]=1;
3185: }
3186: }
1.296 brouard 3187: /* Added for prevbcast */ /* Transposed matrix too */
1.234 brouard 3188: for(jj=1; jj<= nlstate+ndeath; jj++){
3189: s1=0.;
3190: for(ii=1; ii<= nlstate+ndeath; ii++){
3191: s1+=ps[ii][jj];
3192: }
3193: for(ii=1; ii<= nlstate; ii++){
3194: ps[ii][jj]=ps[ii][jj]/s1;
3195: }
3196: }
3197: /* Transposition */
3198: for(jj=1; jj<= nlstate+ndeath; jj++){
3199: for(ii=jj; ii<= nlstate+ndeath; ii++){
3200: s1=ps[ii][jj];
3201: ps[ii][jj]=ps[jj][ii];
3202: ps[jj][ii]=s1;
3203: }
3204: }
3205: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3206: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3207: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3208: /* } */
3209: /* printf("\n "); */
3210: /* } */
3211: /* printf("\n ");printf("%lf ",cov[2]);*/
3212: /*
3213: for(i=1; i<= npar; i++) printf("%f ",x[i]);
3214: goto end;*/
3215: return ps;
1.217 brouard 3216: }
3217:
3218:
1.126 brouard 3219: /**************** Product of 2 matrices ******************/
3220:
1.145 brouard 3221: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 3222: {
3223: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
3224: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
3225: /* in, b, out are matrice of pointers which should have been initialized
3226: before: only the contents of out is modified. The function returns
3227: a pointer to pointers identical to out */
1.145 brouard 3228: int i, j, k;
1.126 brouard 3229: for(i=nrl; i<= nrh; i++)
1.145 brouard 3230: for(k=ncolol; k<=ncoloh; k++){
3231: out[i][k]=0.;
3232: for(j=ncl; j<=nch; j++)
3233: out[i][k] +=in[i][j]*b[j][k];
3234: }
1.126 brouard 3235: return out;
3236: }
3237:
3238:
3239: /************* Higher Matrix Product ***************/
3240:
1.235 brouard 3241: 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 3242: {
1.218 brouard 3243: /* Computes the transition matrix starting at age 'age' and combination of covariate values corresponding to ij over
1.126 brouard 3244: 'nhstepm*hstepm*stepm' months (i.e. until
3245: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3246: nhstepm*hstepm matrices.
3247: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3248: (typically every 2 years instead of every month which is too big
3249: for the memory).
3250: Model is determined by parameters x and covariates have to be
3251: included manually here.
3252:
3253: */
3254:
3255: int i, j, d, h, k;
1.131 brouard 3256: double **out, cov[NCOVMAX+1];
1.126 brouard 3257: double **newm;
1.187 brouard 3258: double agexact;
1.214 brouard 3259: double agebegin, ageend;
1.126 brouard 3260:
3261: /* Hstepm could be zero and should return the unit matrix */
3262: for (i=1;i<=nlstate+ndeath;i++)
3263: for (j=1;j<=nlstate+ndeath;j++){
3264: oldm[i][j]=(i==j ? 1.0 : 0.0);
3265: po[i][j][0]=(i==j ? 1.0 : 0.0);
3266: }
3267: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3268: for(h=1; h <=nhstepm; h++){
3269: for(d=1; d <=hstepm; d++){
3270: newm=savm;
3271: /* Covariates have to be included here again */
3272: cov[1]=1.;
1.214 brouard 3273: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3274: cov[2]=agexact;
3275: if(nagesqr==1)
1.227 brouard 3276: cov[3]= agexact*agexact;
1.235 brouard 3277: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
3278: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
3279: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3280: /* 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)); */
3281: }
3282: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3283: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3284: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3285: /* 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]); */
3286: }
3287: for (k=1; k<=cptcovage;k++){
3288: if(Dummy[Tvar[Tage[k]]]){
3289: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
3290: } else{
3291: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3292: }
3293: /* 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]); */
3294: }
3295: for (k=1; k<=cptcovprod;k++){ /* */
3296: /* 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]); */
3297: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
3298: }
3299: /* for (k=1; k<=cptcovn;k++) */
3300: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3301: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3302: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3303: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3304: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3305:
3306:
1.126 brouard 3307: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3308: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.218 brouard 3309: /* right multiplication of oldm by the current matrix */
1.126 brouard 3310: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3311: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3312: /* if((int)age == 70){ */
3313: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3314: /* for(i=1; i<=nlstate+ndeath; i++) { */
3315: /* printf("%d pmmij ",i); */
3316: /* for(j=1;j<=nlstate+ndeath;j++) { */
3317: /* printf("%f ",pmmij[i][j]); */
3318: /* } */
3319: /* printf(" oldm "); */
3320: /* for(j=1;j<=nlstate+ndeath;j++) { */
3321: /* printf("%f ",oldm[i][j]); */
3322: /* } */
3323: /* printf("\n"); */
3324: /* } */
3325: /* } */
1.126 brouard 3326: savm=oldm;
3327: oldm=newm;
3328: }
3329: for(i=1; i<=nlstate+ndeath; i++)
3330: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 3331: po[i][j][h]=newm[i][j];
3332: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3333: }
1.128 brouard 3334: /*printf("h=%d ",h);*/
1.126 brouard 3335: } /* end h */
1.267 brouard 3336: /* printf("\n H=%d \n",h); */
1.126 brouard 3337: return po;
3338: }
3339:
1.217 brouard 3340: /************* Higher Back Matrix Product ***************/
1.218 brouard 3341: /* 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 3342: 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 3343: {
1.266 brouard 3344: /* For a combination of dummy covariate ij, computes the transition matrix starting at age 'age' over
1.217 brouard 3345: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3346: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3347: nhstepm*hstepm matrices.
3348: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3349: (typically every 2 years instead of every month which is too big
1.217 brouard 3350: for the memory).
1.218 brouard 3351: Model is determined by parameters x and covariates have to be
1.266 brouard 3352: included manually here. Then we use a call to bmij(x and cov)
3353: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 3354: */
1.217 brouard 3355:
3356: int i, j, d, h, k;
1.266 brouard 3357: double **out, cov[NCOVMAX+1], **bmij();
3358: double **newm, ***newmm;
1.217 brouard 3359: double agexact;
3360: double agebegin, ageend;
1.222 brouard 3361: double **oldm, **savm;
1.217 brouard 3362:
1.266 brouard 3363: newmm=po; /* To be saved */
3364: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 3365: /* Hstepm could be zero and should return the unit matrix */
3366: for (i=1;i<=nlstate+ndeath;i++)
3367: for (j=1;j<=nlstate+ndeath;j++){
3368: oldm[i][j]=(i==j ? 1.0 : 0.0);
3369: po[i][j][0]=(i==j ? 1.0 : 0.0);
3370: }
3371: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3372: for(h=1; h <=nhstepm; h++){
3373: for(d=1; d <=hstepm; d++){
3374: newm=savm;
3375: /* Covariates have to be included here again */
3376: cov[1]=1.;
1.271 brouard 3377: agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 3378: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
3379: cov[2]=agexact;
3380: if(nagesqr==1)
1.222 brouard 3381: cov[3]= agexact*agexact;
1.266 brouard 3382: for (k=1; k<=cptcovn;k++){
3383: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3384: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
3385: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3386: /* 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)); */
3387: }
1.267 brouard 3388: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3389: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3390: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3391: /* 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]); */
3392: }
3393: for (k=1; k<=cptcovage;k++){ /* Should start at cptcovn+1 */
3394: if(Dummy[Tvar[Tage[k]]]){
3395: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
3396: } else{
3397: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3398: }
3399: /* 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]); */
3400: }
3401: for (k=1; k<=cptcovprod;k++){ /* Useless because included in cptcovn */
1.222 brouard 3402: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.267 brouard 3403: }
1.217 brouard 3404: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3405: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.267 brouard 3406:
1.218 brouard 3407: /* Careful transposed matrix */
1.266 brouard 3408: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 3409: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3410: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3411: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.222 brouard 3412: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);
1.217 brouard 3413: /* if((int)age == 70){ */
3414: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3415: /* for(i=1; i<=nlstate+ndeath; i++) { */
3416: /* printf("%d pmmij ",i); */
3417: /* for(j=1;j<=nlstate+ndeath;j++) { */
3418: /* printf("%f ",pmmij[i][j]); */
3419: /* } */
3420: /* printf(" oldm "); */
3421: /* for(j=1;j<=nlstate+ndeath;j++) { */
3422: /* printf("%f ",oldm[i][j]); */
3423: /* } */
3424: /* printf("\n"); */
3425: /* } */
3426: /* } */
3427: savm=oldm;
3428: oldm=newm;
3429: }
3430: for(i=1; i<=nlstate+ndeath; i++)
3431: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 3432: po[i][j][h]=newm[i][j];
1.268 brouard 3433: /* if(h==nhstepm) */
3434: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 3435: }
1.268 brouard 3436: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 3437: } /* end h */
1.268 brouard 3438: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 3439: return po;
3440: }
3441:
3442:
1.162 brouard 3443: #ifdef NLOPT
3444: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
3445: double fret;
3446: double *xt;
3447: int j;
3448: myfunc_data *d2 = (myfunc_data *) pd;
3449: /* xt = (p1-1); */
3450: xt=vector(1,n);
3451: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
3452:
3453: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
3454: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
3455: printf("Function = %.12lf ",fret);
3456: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
3457: printf("\n");
3458: free_vector(xt,1,n);
3459: return fret;
3460: }
3461: #endif
1.126 brouard 3462:
3463: /*************** log-likelihood *************/
3464: double func( double *x)
3465: {
1.226 brouard 3466: int i, ii, j, k, mi, d, kk;
3467: int ioffset=0;
3468: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
3469: double **out;
3470: double lli; /* Individual log likelihood */
3471: int s1, s2;
1.228 brouard 3472: 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 3473: double bbh, survp;
3474: long ipmx;
3475: double agexact;
3476: /*extern weight */
3477: /* We are differentiating ll according to initial status */
3478: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3479: /*for(i=1;i<imx;i++)
3480: printf(" %d\n",s[4][i]);
3481: */
1.162 brouard 3482:
1.226 brouard 3483: ++countcallfunc;
1.162 brouard 3484:
1.226 brouard 3485: cov[1]=1.;
1.126 brouard 3486:
1.226 brouard 3487: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3488: ioffset=0;
1.226 brouard 3489: if(mle==1){
3490: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3491: /* Computes the values of the ncovmodel covariates of the model
3492: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
3493: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
3494: to be observed in j being in i according to the model.
3495: */
1.243 brouard 3496: ioffset=2+nagesqr ;
1.233 brouard 3497: /* Fixed */
1.234 brouard 3498: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */
3499: 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)*/
3500: }
1.226 brouard 3501: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
3502: is 6, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]
3503: has been calculated etc */
3504: /* For an individual i, wav[i] gives the number of effective waves */
3505: /* We compute the contribution to Likelihood of each effective transition
3506: mw[mi][i] is real wave of the mi th effectve wave */
3507: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
3508: s2=s[mw[mi+1][i]][i];
3509: And the iv th varying covariate is the cotvar[mw[mi+1][i]][iv][i]
3510: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
3511: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
3512: */
3513: for(mi=1; mi<= wav[i]-1; mi++){
1.234 brouard 3514: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 3515: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
3516: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
1.234 brouard 3517: }
3518: for (ii=1;ii<=nlstate+ndeath;ii++)
3519: for (j=1;j<=nlstate+ndeath;j++){
3520: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3521: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3522: }
3523: for(d=0; d<dh[mi][i]; d++){
3524: newm=savm;
3525: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3526: cov[2]=agexact;
3527: if(nagesqr==1)
3528: cov[3]= agexact*agexact; /* Should be changed here */
3529: for (kk=1; kk<=cptcovage;kk++) {
1.242 brouard 3530: if(!FixedV[Tvar[Tage[kk]]])
1.234 brouard 3531: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
1.242 brouard 3532: else
3533: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
1.234 brouard 3534: }
3535: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3536: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3537: savm=oldm;
3538: oldm=newm;
3539: } /* end mult */
3540:
3541: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
3542: /* But now since version 0.9 we anticipate for bias at large stepm.
3543: * If stepm is larger than one month (smallest stepm) and if the exact delay
3544: * (in months) between two waves is not a multiple of stepm, we rounded to
3545: * the nearest (and in case of equal distance, to the lowest) interval but now
3546: * we keep into memory the bias bh[mi][i] and also the previous matrix product
3547: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
3548: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 3549: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
3550: * -stepm/2 to stepm/2 .
3551: * For stepm=1 the results are the same as for previous versions of Imach.
3552: * For stepm > 1 the results are less biased than in previous versions.
3553: */
1.234 brouard 3554: s1=s[mw[mi][i]][i];
3555: s2=s[mw[mi+1][i]][i];
3556: bbh=(double)bh[mi][i]/(double)stepm;
3557: /* bias bh is positive if real duration
3558: * is higher than the multiple of stepm and negative otherwise.
3559: */
3560: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
3561: if( s2 > nlstate){
3562: /* i.e. if s2 is a death state and if the date of death is known
3563: then the contribution to the likelihood is the probability to
3564: die between last step unit time and current step unit time,
3565: which is also equal to probability to die before dh
3566: minus probability to die before dh-stepm .
3567: In version up to 0.92 likelihood was computed
3568: as if date of death was unknown. Death was treated as any other
3569: health state: the date of the interview describes the actual state
3570: and not the date of a change in health state. The former idea was
3571: to consider that at each interview the state was recorded
3572: (healthy, disable or death) and IMaCh was corrected; but when we
3573: introduced the exact date of death then we should have modified
3574: the contribution of an exact death to the likelihood. This new
3575: contribution is smaller and very dependent of the step unit
3576: stepm. It is no more the probability to die between last interview
3577: and month of death but the probability to survive from last
3578: interview up to one month before death multiplied by the
3579: probability to die within a month. Thanks to Chris
3580: Jackson for correcting this bug. Former versions increased
3581: mortality artificially. The bad side is that we add another loop
3582: which slows down the processing. The difference can be up to 10%
3583: lower mortality.
3584: */
3585: /* If, at the beginning of the maximization mostly, the
3586: cumulative probability or probability to be dead is
3587: constant (ie = 1) over time d, the difference is equal to
3588: 0. out[s1][3] = savm[s1][3]: probability, being at state
3589: s1 at precedent wave, to be dead a month before current
3590: wave is equal to probability, being at state s1 at
3591: precedent wave, to be dead at mont of the current
3592: wave. Then the observed probability (that this person died)
3593: is null according to current estimated parameter. In fact,
3594: it should be very low but not zero otherwise the log go to
3595: infinity.
3596: */
1.183 brouard 3597: /* #ifdef INFINITYORIGINAL */
3598: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3599: /* #else */
3600: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
3601: /* lli=log(mytinydouble); */
3602: /* else */
3603: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3604: /* #endif */
1.226 brouard 3605: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3606:
1.226 brouard 3607: } else if ( s2==-1 ) { /* alive */
3608: for (j=1,survp=0. ; j<=nlstate; j++)
3609: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3610: /*survp += out[s1][j]; */
3611: lli= log(survp);
3612: }
3613: else if (s2==-4) {
3614: for (j=3,survp=0. ; j<=nlstate; j++)
3615: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3616: lli= log(survp);
3617: }
3618: else if (s2==-5) {
3619: for (j=1,survp=0. ; j<=2; j++)
3620: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3621: lli= log(survp);
3622: }
3623: else{
3624: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3625: /* 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 */
3626: }
3627: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
3628: /*if(lli ==000.0)*/
3629: /*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); */
3630: ipmx +=1;
3631: sw += weight[i];
3632: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3633: /* if (lli < log(mytinydouble)){ */
3634: /* 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); */
3635: /* 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]); */
3636: /* } */
3637: } /* end of wave */
3638: } /* end of individual */
3639: } else if(mle==2){
3640: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3641: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3642: for(mi=1; mi<= wav[i]-1; mi++){
3643: for (ii=1;ii<=nlstate+ndeath;ii++)
3644: for (j=1;j<=nlstate+ndeath;j++){
3645: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3646: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3647: }
3648: for(d=0; d<=dh[mi][i]; d++){
3649: newm=savm;
3650: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3651: cov[2]=agexact;
3652: if(nagesqr==1)
3653: cov[3]= agexact*agexact;
3654: for (kk=1; kk<=cptcovage;kk++) {
3655: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3656: }
3657: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3658: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3659: savm=oldm;
3660: oldm=newm;
3661: } /* end mult */
3662:
3663: s1=s[mw[mi][i]][i];
3664: s2=s[mw[mi+1][i]][i];
3665: bbh=(double)bh[mi][i]/(double)stepm;
3666: 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 */
3667: ipmx +=1;
3668: sw += weight[i];
3669: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3670: } /* end of wave */
3671: } /* end of individual */
3672: } else if(mle==3){ /* exponential inter-extrapolation */
3673: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3674: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3675: for(mi=1; mi<= wav[i]-1; mi++){
3676: for (ii=1;ii<=nlstate+ndeath;ii++)
3677: for (j=1;j<=nlstate+ndeath;j++){
3678: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3679: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3680: }
3681: for(d=0; d<dh[mi][i]; d++){
3682: newm=savm;
3683: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3684: cov[2]=agexact;
3685: if(nagesqr==1)
3686: cov[3]= agexact*agexact;
3687: for (kk=1; kk<=cptcovage;kk++) {
3688: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3689: }
3690: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3691: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3692: savm=oldm;
3693: oldm=newm;
3694: } /* end mult */
3695:
3696: s1=s[mw[mi][i]][i];
3697: s2=s[mw[mi+1][i]][i];
3698: bbh=(double)bh[mi][i]/(double)stepm;
3699: 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 */
3700: ipmx +=1;
3701: sw += weight[i];
3702: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3703: } /* end of wave */
3704: } /* end of individual */
3705: }else if (mle==4){ /* ml=4 no inter-extrapolation */
3706: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3707: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3708: for(mi=1; mi<= wav[i]-1; mi++){
3709: for (ii=1;ii<=nlstate+ndeath;ii++)
3710: for (j=1;j<=nlstate+ndeath;j++){
3711: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3712: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3713: }
3714: for(d=0; d<dh[mi][i]; d++){
3715: newm=savm;
3716: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3717: cov[2]=agexact;
3718: if(nagesqr==1)
3719: cov[3]= agexact*agexact;
3720: for (kk=1; kk<=cptcovage;kk++) {
3721: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3722: }
1.126 brouard 3723:
1.226 brouard 3724: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3725: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3726: savm=oldm;
3727: oldm=newm;
3728: } /* end mult */
3729:
3730: s1=s[mw[mi][i]][i];
3731: s2=s[mw[mi+1][i]][i];
3732: if( s2 > nlstate){
3733: lli=log(out[s1][s2] - savm[s1][s2]);
3734: } else if ( s2==-1 ) { /* alive */
3735: for (j=1,survp=0. ; j<=nlstate; j++)
3736: survp += out[s1][j];
3737: lli= log(survp);
3738: }else{
3739: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3740: }
3741: ipmx +=1;
3742: sw += weight[i];
3743: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.126 brouard 3744: /* 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 3745: } /* end of wave */
3746: } /* end of individual */
3747: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
3748: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3749: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3750: for(mi=1; mi<= wav[i]-1; mi++){
3751: for (ii=1;ii<=nlstate+ndeath;ii++)
3752: for (j=1;j<=nlstate+ndeath;j++){
3753: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3754: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3755: }
3756: for(d=0; d<dh[mi][i]; d++){
3757: newm=savm;
3758: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3759: cov[2]=agexact;
3760: if(nagesqr==1)
3761: cov[3]= agexact*agexact;
3762: for (kk=1; kk<=cptcovage;kk++) {
3763: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3764: }
1.126 brouard 3765:
1.226 brouard 3766: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3767: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3768: savm=oldm;
3769: oldm=newm;
3770: } /* end mult */
3771:
3772: s1=s[mw[mi][i]][i];
3773: s2=s[mw[mi+1][i]][i];
3774: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3775: ipmx +=1;
3776: sw += weight[i];
3777: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3778: /*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]);*/
3779: } /* end of wave */
3780: } /* end of individual */
3781: } /* End of if */
3782: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3783: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3784: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3785: return -l;
1.126 brouard 3786: }
3787:
3788: /*************** log-likelihood *************/
3789: double funcone( double *x)
3790: {
1.228 brouard 3791: /* Same as func but slower because of a lot of printf and if */
1.126 brouard 3792: int i, ii, j, k, mi, d, kk;
1.228 brouard 3793: int ioffset=0;
1.131 brouard 3794: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 3795: double **out;
3796: double lli; /* Individual log likelihood */
3797: double llt;
3798: int s1, s2;
1.228 brouard 3799: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
3800:
1.126 brouard 3801: double bbh, survp;
1.187 brouard 3802: double agexact;
1.214 brouard 3803: double agebegin, ageend;
1.126 brouard 3804: /*extern weight */
3805: /* We are differentiating ll according to initial status */
3806: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3807: /*for(i=1;i<imx;i++)
3808: printf(" %d\n",s[4][i]);
3809: */
3810: cov[1]=1.;
3811:
3812: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3813: ioffset=0;
3814: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.243 brouard 3815: /* ioffset=2+nagesqr+cptcovage; */
3816: ioffset=2+nagesqr;
1.232 brouard 3817: /* Fixed */
1.224 brouard 3818: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 3819: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
3820: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */
3821: 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)*/
3822: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
3823: /* cov[2+6]=covar[Tvar[6]][i]; */
3824: /* cov[2+6]=covar[2][i]; V2 */
3825: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
3826: /* cov[2+7]=covar[Tvar[7]][i]; */
3827: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
3828: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
3829: /* cov[2+9]=covar[Tvar[9]][i]; */
3830: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 3831: }
1.232 brouard 3832: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
3833: /* 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?)*\/ */
3834: /* } */
1.231 brouard 3835: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
3836: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
3837: /* } */
1.225 brouard 3838:
1.233 brouard 3839:
3840: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.232 brouard 3841: /* Wave varying (but not age varying) */
3842: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 3843: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
3844: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
3845: }
1.232 brouard 3846: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates (single??)*\/ */
1.242 brouard 3847: /* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3848: /* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; */
3849: /* k=ioffset-2-nagesqr-cptcovage+itv; /\* position in simple model *\/ */
3850: /* cov[ioffset+itv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; */
3851: /* 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 3852: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 3853: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3854: /* /\* 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]); *\/ */
3855: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 3856: /* } */
1.126 brouard 3857: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 3858: for (j=1;j<=nlstate+ndeath;j++){
3859: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3860: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3861: }
1.214 brouard 3862:
3863: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
3864: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
3865: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 3866: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 3867: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
3868: and mw[mi+1][i]. dh depends on stepm.*/
3869: newm=savm;
1.247 brouard 3870: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 3871: cov[2]=agexact;
3872: if(nagesqr==1)
3873: cov[3]= agexact*agexact;
3874: for (kk=1; kk<=cptcovage;kk++) {
3875: if(!FixedV[Tvar[Tage[kk]]])
3876: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3877: else
3878: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
3879: }
3880: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
3881: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3882: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3883: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3884: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
3885: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
3886: savm=oldm;
3887: oldm=newm;
1.126 brouard 3888: } /* end mult */
3889:
3890: s1=s[mw[mi][i]][i];
3891: s2=s[mw[mi+1][i]][i];
1.217 brouard 3892: /* if(s2==-1){ */
1.268 brouard 3893: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 3894: /* /\* exit(1); *\/ */
3895: /* } */
1.126 brouard 3896: bbh=(double)bh[mi][i]/(double)stepm;
3897: /* bias is positive if real duration
3898: * is higher than the multiple of stepm and negative otherwise.
3899: */
3900: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 3901: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3902: } else if ( s2==-1 ) { /* alive */
1.242 brouard 3903: for (j=1,survp=0. ; j<=nlstate; j++)
3904: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3905: lli= log(survp);
1.126 brouard 3906: }else if (mle==1){
1.242 brouard 3907: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 3908: } else if(mle==2){
1.242 brouard 3909: 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 3910: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 3911: 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 3912: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 3913: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 3914: } else{ /* mle=0 back to 1 */
1.242 brouard 3915: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3916: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 3917: } /* End of if */
3918: ipmx +=1;
3919: sw += weight[i];
3920: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.132 brouard 3921: /*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 3922: if(globpr){
1.246 brouard 3923: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 3924: %11.6f %11.6f %11.6f ", \
1.242 brouard 3925: 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 3926: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.242 brouard 3927: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
3928: llt +=ll[k]*gipmx/gsw;
3929: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
3930: }
3931: fprintf(ficresilk," %10.6f\n", -llt);
1.126 brouard 3932: }
1.232 brouard 3933: } /* end of wave */
3934: } /* end of individual */
3935: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3936: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3937: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3938: if(globpr==0){ /* First time we count the contributions and weights */
3939: gipmx=ipmx;
3940: gsw=sw;
3941: }
3942: return -l;
1.126 brouard 3943: }
3944:
3945:
3946: /*************** function likelione ***********/
1.292 brouard 3947: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*func)(double []))
1.126 brouard 3948: {
3949: /* This routine should help understanding what is done with
3950: the selection of individuals/waves and
3951: to check the exact contribution to the likelihood.
3952: Plotting could be done.
3953: */
3954: int k;
3955:
3956: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 3957: strcpy(fileresilk,"ILK_");
1.202 brouard 3958: strcat(fileresilk,fileresu);
1.126 brouard 3959: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
3960: printf("Problem with resultfile: %s\n", fileresilk);
3961: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
3962: }
1.214 brouard 3963: 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");
3964: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 3965: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
3966: for(k=1; k<=nlstate; k++)
3967: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
3968: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total)\n");
3969: }
3970:
1.292 brouard 3971: *fretone=(*func)(p);
1.126 brouard 3972: if(*globpri !=0){
3973: fclose(ficresilk);
1.205 brouard 3974: if (mle ==0)
3975: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
3976: else if(mle >=1)
3977: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
3978: 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 3979: fprintf(fichtm,"\n<br>Equation of the model: <b>model=1+age+%s</b><br>\n",model);
1.208 brouard 3980:
3981: for (k=1; k<= nlstate ; k++) {
1.211 brouard 3982: 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 3983: <img src=\"%s-p%dj.png\">",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
3984: }
1.207 brouard 3985: 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 3986: <img src=\"%s-ori.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 3987: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.204 brouard 3988: <img src=\"%s-dest.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 3989: fflush(fichtm);
1.205 brouard 3990: }
1.126 brouard 3991: return;
3992: }
3993:
3994:
3995: /*********** Maximum Likelihood Estimation ***************/
3996:
3997: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
3998: {
1.165 brouard 3999: int i,j, iter=0;
1.126 brouard 4000: double **xi;
4001: double fret;
4002: double fretone; /* Only one call to likelihood */
4003: /* char filerespow[FILENAMELENGTH];*/
1.162 brouard 4004:
4005: #ifdef NLOPT
4006: int creturn;
4007: nlopt_opt opt;
4008: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
4009: double *lb;
4010: double minf; /* the minimum objective value, upon return */
4011: double * p1; /* Shifted parameters from 0 instead of 1 */
4012: myfunc_data dinst, *d = &dinst;
4013: #endif
4014:
4015:
1.126 brouard 4016: xi=matrix(1,npar,1,npar);
4017: for (i=1;i<=npar;i++)
4018: for (j=1;j<=npar;j++)
4019: xi[i][j]=(i==j ? 1.0 : 0.0);
4020: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 4021: strcpy(filerespow,"POW_");
1.126 brouard 4022: strcat(filerespow,fileres);
4023: if((ficrespow=fopen(filerespow,"w"))==NULL) {
4024: printf("Problem with resultfile: %s\n", filerespow);
4025: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
4026: }
4027: fprintf(ficrespow,"# Powell\n# iter -2*LL");
4028: for (i=1;i<=nlstate;i++)
4029: for(j=1;j<=nlstate+ndeath;j++)
4030: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
4031: fprintf(ficrespow,"\n");
1.162 brouard 4032: #ifdef POWELL
1.126 brouard 4033: powell(p,xi,npar,ftol,&iter,&fret,func);
1.162 brouard 4034: #endif
1.126 brouard 4035:
1.162 brouard 4036: #ifdef NLOPT
4037: #ifdef NEWUOA
4038: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
4039: #else
4040: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
4041: #endif
4042: lb=vector(0,npar-1);
4043: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
4044: nlopt_set_lower_bounds(opt, lb);
4045: nlopt_set_initial_step1(opt, 0.1);
4046:
4047: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
4048: d->function = func;
4049: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
4050: nlopt_set_min_objective(opt, myfunc, d);
4051: nlopt_set_xtol_rel(opt, ftol);
4052: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
4053: printf("nlopt failed! %d\n",creturn);
4054: }
4055: else {
4056: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
4057: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
4058: iter=1; /* not equal */
4059: }
4060: nlopt_destroy(opt);
4061: #endif
1.126 brouard 4062: free_matrix(xi,1,npar,1,npar);
4063: fclose(ficrespow);
1.203 brouard 4064: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
4065: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 4066: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 4067:
4068: }
4069:
4070: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 4071: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 4072: {
4073: double **a,**y,*x,pd;
1.203 brouard 4074: /* double **hess; */
1.164 brouard 4075: int i, j;
1.126 brouard 4076: int *indx;
4077:
4078: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 4079: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 4080: void lubksb(double **a, int npar, int *indx, double b[]) ;
4081: void ludcmp(double **a, int npar, int *indx, double *d) ;
4082: double gompertz(double p[]);
1.203 brouard 4083: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 4084:
4085: printf("\nCalculation of the hessian matrix. Wait...\n");
4086: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
4087: for (i=1;i<=npar;i++){
1.203 brouard 4088: printf("%d-",i);fflush(stdout);
4089: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 4090:
4091: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
4092:
4093: /* printf(" %f ",p[i]);
4094: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
4095: }
4096:
4097: for (i=1;i<=npar;i++) {
4098: for (j=1;j<=npar;j++) {
4099: if (j>i) {
1.203 brouard 4100: printf(".%d-%d",i,j);fflush(stdout);
4101: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
4102: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 4103:
4104: hess[j][i]=hess[i][j];
4105: /*printf(" %lf ",hess[i][j]);*/
4106: }
4107: }
4108: }
4109: printf("\n");
4110: fprintf(ficlog,"\n");
4111:
4112: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
4113: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
4114:
4115: a=matrix(1,npar,1,npar);
4116: y=matrix(1,npar,1,npar);
4117: x=vector(1,npar);
4118: indx=ivector(1,npar);
4119: for (i=1;i<=npar;i++)
4120: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
4121: ludcmp(a,npar,indx,&pd);
4122:
4123: for (j=1;j<=npar;j++) {
4124: for (i=1;i<=npar;i++) x[i]=0;
4125: x[j]=1;
4126: lubksb(a,npar,indx,x);
4127: for (i=1;i<=npar;i++){
4128: matcov[i][j]=x[i];
4129: }
4130: }
4131:
4132: printf("\n#Hessian matrix#\n");
4133: fprintf(ficlog,"\n#Hessian matrix#\n");
4134: for (i=1;i<=npar;i++) {
4135: for (j=1;j<=npar;j++) {
1.203 brouard 4136: printf("%.6e ",hess[i][j]);
4137: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 4138: }
4139: printf("\n");
4140: fprintf(ficlog,"\n");
4141: }
4142:
1.203 brouard 4143: /* printf("\n#Covariance matrix#\n"); */
4144: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
4145: /* for (i=1;i<=npar;i++) { */
4146: /* for (j=1;j<=npar;j++) { */
4147: /* printf("%.6e ",matcov[i][j]); */
4148: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
4149: /* } */
4150: /* printf("\n"); */
4151: /* fprintf(ficlog,"\n"); */
4152: /* } */
4153:
1.126 brouard 4154: /* Recompute Inverse */
1.203 brouard 4155: /* for (i=1;i<=npar;i++) */
4156: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
4157: /* ludcmp(a,npar,indx,&pd); */
4158:
4159: /* printf("\n#Hessian matrix recomputed#\n"); */
4160:
4161: /* for (j=1;j<=npar;j++) { */
4162: /* for (i=1;i<=npar;i++) x[i]=0; */
4163: /* x[j]=1; */
4164: /* lubksb(a,npar,indx,x); */
4165: /* for (i=1;i<=npar;i++){ */
4166: /* y[i][j]=x[i]; */
4167: /* printf("%.3e ",y[i][j]); */
4168: /* fprintf(ficlog,"%.3e ",y[i][j]); */
4169: /* } */
4170: /* printf("\n"); */
4171: /* fprintf(ficlog,"\n"); */
4172: /* } */
4173:
4174: /* Verifying the inverse matrix */
4175: #ifdef DEBUGHESS
4176: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 4177:
1.203 brouard 4178: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
4179: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 4180:
4181: for (j=1;j<=npar;j++) {
4182: for (i=1;i<=npar;i++){
1.203 brouard 4183: printf("%.2f ",y[i][j]);
4184: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 4185: }
4186: printf("\n");
4187: fprintf(ficlog,"\n");
4188: }
1.203 brouard 4189: #endif
1.126 brouard 4190:
4191: free_matrix(a,1,npar,1,npar);
4192: free_matrix(y,1,npar,1,npar);
4193: free_vector(x,1,npar);
4194: free_ivector(indx,1,npar);
1.203 brouard 4195: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 4196:
4197:
4198: }
4199:
4200: /*************** hessian matrix ****************/
4201: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 4202: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 4203: int i;
4204: int l=1, lmax=20;
1.203 brouard 4205: double k1,k2, res, fx;
1.132 brouard 4206: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 4207: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
4208: int k=0,kmax=10;
4209: double l1;
4210:
4211: fx=func(x);
4212: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 4213: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 4214: l1=pow(10,l);
4215: delts=delt;
4216: for(k=1 ; k <kmax; k=k+1){
4217: delt = delta*(l1*k);
4218: p2[theta]=x[theta] +delt;
1.145 brouard 4219: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 4220: p2[theta]=x[theta]-delt;
4221: k2=func(p2)-fx;
4222: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 4223: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 4224:
1.203 brouard 4225: #ifdef DEBUGHESSII
1.126 brouard 4226: 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);
4227: 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);
4228: #endif
4229: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
4230: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
4231: k=kmax;
4232: }
4233: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 4234: k=kmax; l=lmax*10;
1.126 brouard 4235: }
4236: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
4237: delts=delt;
4238: }
1.203 brouard 4239: } /* End loop k */
1.126 brouard 4240: }
4241: delti[theta]=delts;
4242: return res;
4243:
4244: }
4245:
1.203 brouard 4246: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 4247: {
4248: int i;
1.164 brouard 4249: int l=1, lmax=20;
1.126 brouard 4250: double k1,k2,k3,k4,res,fx;
1.132 brouard 4251: double p2[MAXPARM+1];
1.203 brouard 4252: int k, kmax=1;
4253: double v1, v2, cv12, lc1, lc2;
1.208 brouard 4254:
4255: int firstime=0;
1.203 brouard 4256:
1.126 brouard 4257: fx=func(x);
1.203 brouard 4258: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 4259: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 4260: p2[thetai]=x[thetai]+delti[thetai]*k;
4261: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4262: k1=func(p2)-fx;
4263:
1.203 brouard 4264: p2[thetai]=x[thetai]+delti[thetai]*k;
4265: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4266: k2=func(p2)-fx;
4267:
1.203 brouard 4268: p2[thetai]=x[thetai]-delti[thetai]*k;
4269: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4270: k3=func(p2)-fx;
4271:
1.203 brouard 4272: p2[thetai]=x[thetai]-delti[thetai]*k;
4273: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4274: k4=func(p2)-fx;
1.203 brouard 4275: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
4276: if(k1*k2*k3*k4 <0.){
1.208 brouard 4277: firstime=1;
1.203 brouard 4278: kmax=kmax+10;
1.208 brouard 4279: }
4280: if(kmax >=10 || firstime ==1){
1.246 brouard 4281: 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);
4282: 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 4283: 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);
4284: 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);
4285: }
4286: #ifdef DEBUGHESSIJ
4287: v1=hess[thetai][thetai];
4288: v2=hess[thetaj][thetaj];
4289: cv12=res;
4290: /* Computing eigen value of Hessian matrix */
4291: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4292: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4293: if ((lc2 <0) || (lc1 <0) ){
4294: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4295: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4296: 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);
4297: 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);
4298: }
1.126 brouard 4299: #endif
4300: }
4301: return res;
4302: }
4303:
1.203 brouard 4304: /* Not done yet: Was supposed to fix if not exactly at the maximum */
4305: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
4306: /* { */
4307: /* int i; */
4308: /* int l=1, lmax=20; */
4309: /* double k1,k2,k3,k4,res,fx; */
4310: /* double p2[MAXPARM+1]; */
4311: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
4312: /* int k=0,kmax=10; */
4313: /* double l1; */
4314:
4315: /* fx=func(x); */
4316: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
4317: /* l1=pow(10,l); */
4318: /* delts=delt; */
4319: /* for(k=1 ; k <kmax; k=k+1){ */
4320: /* delt = delti*(l1*k); */
4321: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
4322: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4323: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4324: /* k1=func(p2)-fx; */
4325:
4326: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4327: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4328: /* k2=func(p2)-fx; */
4329:
4330: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4331: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4332: /* k3=func(p2)-fx; */
4333:
4334: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4335: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4336: /* k4=func(p2)-fx; */
4337: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
4338: /* #ifdef DEBUGHESSIJ */
4339: /* 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); */
4340: /* 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); */
4341: /* #endif */
4342: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
4343: /* k=kmax; */
4344: /* } */
4345: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
4346: /* k=kmax; l=lmax*10; */
4347: /* } */
4348: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
4349: /* delts=delt; */
4350: /* } */
4351: /* } /\* End loop k *\/ */
4352: /* } */
4353: /* delti[theta]=delts; */
4354: /* return res; */
4355: /* } */
4356:
4357:
1.126 brouard 4358: /************** Inverse of matrix **************/
4359: void ludcmp(double **a, int n, int *indx, double *d)
4360: {
4361: int i,imax,j,k;
4362: double big,dum,sum,temp;
4363: double *vv;
4364:
4365: vv=vector(1,n);
4366: *d=1.0;
4367: for (i=1;i<=n;i++) {
4368: big=0.0;
4369: for (j=1;j<=n;j++)
4370: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 4371: if (big == 0.0){
4372: printf(" Singular Hessian matrix at row %d:\n",i);
4373: for (j=1;j<=n;j++) {
4374: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
4375: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
4376: }
4377: fflush(ficlog);
4378: fclose(ficlog);
4379: nrerror("Singular matrix in routine ludcmp");
4380: }
1.126 brouard 4381: vv[i]=1.0/big;
4382: }
4383: for (j=1;j<=n;j++) {
4384: for (i=1;i<j;i++) {
4385: sum=a[i][j];
4386: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
4387: a[i][j]=sum;
4388: }
4389: big=0.0;
4390: for (i=j;i<=n;i++) {
4391: sum=a[i][j];
4392: for (k=1;k<j;k++)
4393: sum -= a[i][k]*a[k][j];
4394: a[i][j]=sum;
4395: if ( (dum=vv[i]*fabs(sum)) >= big) {
4396: big=dum;
4397: imax=i;
4398: }
4399: }
4400: if (j != imax) {
4401: for (k=1;k<=n;k++) {
4402: dum=a[imax][k];
4403: a[imax][k]=a[j][k];
4404: a[j][k]=dum;
4405: }
4406: *d = -(*d);
4407: vv[imax]=vv[j];
4408: }
4409: indx[j]=imax;
4410: if (a[j][j] == 0.0) a[j][j]=TINY;
4411: if (j != n) {
4412: dum=1.0/(a[j][j]);
4413: for (i=j+1;i<=n;i++) a[i][j] *= dum;
4414: }
4415: }
4416: free_vector(vv,1,n); /* Doesn't work */
4417: ;
4418: }
4419:
4420: void lubksb(double **a, int n, int *indx, double b[])
4421: {
4422: int i,ii=0,ip,j;
4423: double sum;
4424:
4425: for (i=1;i<=n;i++) {
4426: ip=indx[i];
4427: sum=b[ip];
4428: b[ip]=b[i];
4429: if (ii)
4430: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
4431: else if (sum) ii=i;
4432: b[i]=sum;
4433: }
4434: for (i=n;i>=1;i--) {
4435: sum=b[i];
4436: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
4437: b[i]=sum/a[i][i];
4438: }
4439: }
4440:
4441: void pstamp(FILE *fichier)
4442: {
1.196 brouard 4443: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 4444: }
4445:
1.297 brouard 4446: void date2dmy(double date,double *day, double *month, double *year){
4447: double yp=0., yp1=0., yp2=0.;
4448:
4449: yp1=modf(date,&yp);/* extracts integral of date in yp and
4450: fractional in yp1 */
4451: *year=yp;
4452: yp2=modf((yp1*12),&yp);
4453: *month=yp;
4454: yp1=modf((yp2*30.5),&yp);
4455: *day=yp;
4456: if(*day==0) *day=1;
4457: if(*month==0) *month=1;
4458: }
4459:
1.253 brouard 4460:
4461:
1.126 brouard 4462: /************ Frequencies ********************/
1.251 brouard 4463: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 4464: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
4465: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 4466: { /* Some frequencies as well as proposing some starting values */
1.226 brouard 4467:
1.265 brouard 4468: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 4469: int iind=0, iage=0;
4470: int mi; /* Effective wave */
4471: int first;
4472: double ***freq; /* Frequencies */
1.268 brouard 4473: 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 */
4474: int no=0, linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb);
1.284 brouard 4475: double *meanq, *stdq, *idq;
1.226 brouard 4476: double **meanqt;
4477: double *pp, **prop, *posprop, *pospropt;
4478: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
4479: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
4480: double agebegin, ageend;
4481:
4482: pp=vector(1,nlstate);
1.251 brouard 4483: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4484: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
4485: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
4486: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
4487: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.284 brouard 4488: stdq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.283 brouard 4489: idq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.226 brouard 4490: meanqt=matrix(1,lastpass,1,nqtveff);
4491: strcpy(fileresp,"P_");
4492: strcat(fileresp,fileresu);
4493: /*strcat(fileresphtm,fileresu);*/
4494: if((ficresp=fopen(fileresp,"w"))==NULL) {
4495: printf("Problem with prevalence resultfile: %s\n", fileresp);
4496: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
4497: exit(0);
4498: }
1.240 brouard 4499:
1.226 brouard 4500: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
4501: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
4502: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4503: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4504: fflush(ficlog);
4505: exit(70);
4506: }
4507: else{
4508: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 4509: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4510: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4511: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4512: }
1.237 brouard 4513: 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 4514:
1.226 brouard 4515: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
4516: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
4517: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4518: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4519: fflush(ficlog);
4520: exit(70);
1.240 brouard 4521: } else{
1.226 brouard 4522: 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 4523: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4524: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4525: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4526: }
1.240 brouard 4527: 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);
4528:
1.253 brouard 4529: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
4530: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 4531: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4532: j1=0;
1.126 brouard 4533:
1.227 brouard 4534: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
4535: j=cptcoveff; /* Only dummy covariates of the model */
1.226 brouard 4536: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 4537:
4538:
1.226 brouard 4539: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
4540: reference=low_education V1=0,V2=0
4541: med_educ V1=1 V2=0,
4542: high_educ V1=0 V2=1
4543: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcoveff
4544: */
1.249 brouard 4545: dateintsum=0;
4546: k2cpt=0;
4547:
1.253 brouard 4548: if(cptcoveff == 0 )
1.265 brouard 4549: nl=1; /* Constant and age model only */
1.253 brouard 4550: else
4551: nl=2;
1.265 brouard 4552:
4553: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
4554: /* Loop on nj=1 or 2 if dummy covariates j!=0
4555: * Loop on j1(1 to 2**cptcoveff) covariate combination
4556: * freq[s1][s2][iage] =0.
4557: * Loop on iind
4558: * ++freq[s1][s2][iage] weighted
4559: * end iind
4560: * if covariate and j!0
4561: * headers Variable on one line
4562: * endif cov j!=0
4563: * header of frequency table by age
4564: * Loop on age
4565: * pp[s1]+=freq[s1][s2][iage] weighted
4566: * pos+=freq[s1][s2][iage] weighted
4567: * Loop on s1 initial state
4568: * fprintf(ficresp
4569: * end s1
4570: * end age
4571: * if j!=0 computes starting values
4572: * end compute starting values
4573: * end j1
4574: * end nl
4575: */
1.253 brouard 4576: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
4577: if(nj==1)
4578: j=0; /* First pass for the constant */
1.265 brouard 4579: else{
1.253 brouard 4580: j=cptcoveff; /* Other passes for the covariate values */
1.265 brouard 4581: }
1.251 brouard 4582: first=1;
1.265 brouard 4583: 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 4584: posproptt=0.;
4585: /*printf("cptcoveff=%d Tvaraff=%d", cptcoveff,Tvaraff[1]);
4586: scanf("%d", i);*/
4587: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 4588: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 4589: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 4590: freq[i][s2][m]=0;
1.251 brouard 4591:
4592: for (i=1; i<=nlstate; i++) {
1.240 brouard 4593: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 4594: prop[i][m]=0;
4595: posprop[i]=0;
4596: pospropt[i]=0;
4597: }
1.283 brouard 4598: for (z1=1; z1<= nqfveff; z1++) { /* zeroing for each combination j1 as well as for the total */
1.284 brouard 4599: idq[z1]=0.;
4600: meanq[z1]=0.;
4601: stdq[z1]=0.;
1.283 brouard 4602: }
4603: /* for (z1=1; z1<= nqtveff; z1++) { */
1.251 brouard 4604: /* for(m=1;m<=lastpass;m++){ */
1.283 brouard 4605: /* meanqt[m][z1]=0.; */
4606: /* } */
4607: /* } */
1.251 brouard 4608: /* dateintsum=0; */
4609: /* k2cpt=0; */
4610:
1.265 brouard 4611: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 4612: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
4613: bool=1;
4614: if(j !=0){
4615: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
4616: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
4617: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
4618: /* if(Tvaraff[z1] ==-20){ */
4619: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
4620: /* }else if(Tvaraff[z1] ==-10){ */
4621: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
4622: /* }else */
4623: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]){ /* for combination j1 of covariates */
1.265 brouard 4624: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 4625: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
4626: /* 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",
4627: bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),
4628: j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
4629: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
4630: } /* Onlyf fixed */
4631: } /* end z1 */
4632: } /* cptcovn > 0 */
4633: } /* end any */
4634: }/* end j==0 */
1.265 brouard 4635: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 4636: /* for(m=firstpass; m<=lastpass; m++){ */
1.284 brouard 4637: for(mi=1; mi<wav[iind];mi++){ /* For each wave */
1.251 brouard 4638: m=mw[mi][iind];
4639: if(j!=0){
4640: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
4641: for (z1=1; z1<=cptcoveff; z1++) {
4642: if( Fixed[Tmodelind[z1]]==1){
4643: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
4644: if (cotvar[m][iv][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality. If covariate's
4645: value is -1, we don't select. It differs from the
4646: constant and age model which counts them. */
4647: bool=0; /* not selected */
4648: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
4649: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
4650: bool=0;
4651: }
4652: }
4653: }
4654: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
4655: } /* end j==0 */
4656: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
1.284 brouard 4657: if(bool==1){ /*Selected */
1.251 brouard 4658: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
4659: and mw[mi+1][iind]. dh depends on stepm. */
4660: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
4661: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
4662: if(m >=firstpass && m <=lastpass){
4663: k2=anint[m][iind]+(mint[m][iind]/12.);
4664: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
4665: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
4666: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
4667: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
4668: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
4669: if (m<lastpass) {
4670: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
4671: /* 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]); */
4672: if(s[m][iind]==-1)
4673: 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.));
4674: freq[s[m][iind]][s[m+1][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
1.284 brouard 4675: for (z1=1; z1<= nqfveff; z1++) { /* Quantitative variables, calculating mean */
4676: idq[z1]=idq[z1]+weight[iind];
4677: meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /* Computes mean of quantitative with selected filter */
4678: stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /* *weight[iind];*/ /* Computes mean of quantitative with selected filter */
4679: }
1.251 brouard 4680: /* if((int)agev[m][iind] == 55) */
4681: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
4682: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
4683: 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 4684: }
1.251 brouard 4685: } /* end if between passes */
4686: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
4687: dateintsum=dateintsum+k2; /* on all covariates ?*/
4688: k2cpt++;
4689: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 4690: }
1.251 brouard 4691: }else{
4692: bool=1;
4693: }/* end bool 2 */
4694: } /* end m */
1.284 brouard 4695: /* for (z1=1; z1<= nqfveff; z1++) { /\* Quantitative variables, calculating mean *\/ */
4696: /* idq[z1]=idq[z1]+weight[iind]; */
4697: /* meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /\* Computes mean of quantitative with selected filter *\/ */
4698: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /\* *weight[iind];*\/ /\* Computes mean of quantitative with selected filter *\/ */
4699: /* } */
1.251 brouard 4700: } /* end bool */
4701: } /* end iind = 1 to imx */
4702: /* prop[s][age] is feeded for any initial and valid live state as well as
4703: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
4704:
4705:
4706: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.265 brouard 4707: if(cptcoveff==0 && nj==1) /* no covariate and first pass */
4708: pstamp(ficresp);
1.251 brouard 4709: if (cptcoveff>0 && j!=0){
1.265 brouard 4710: pstamp(ficresp);
1.251 brouard 4711: printf( "\n#********** Variable ");
4712: fprintf(ficresp, "\n#********** Variable ");
4713: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
4714: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
4715: fprintf(ficlog, "\n#********** Variable ");
4716: for (z1=1; z1<=cptcoveff; z1++){
4717: if(!FixedV[Tvaraff[z1]]){
4718: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4719: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4720: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4721: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4722: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.250 brouard 4723: }else{
1.251 brouard 4724: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4725: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4726: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4727: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4728: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4729: }
4730: }
4731: printf( "**********\n#");
4732: fprintf(ficresp, "**********\n#");
4733: fprintf(ficresphtm, "**********</h3>\n");
4734: fprintf(ficresphtmfr, "**********</h3>\n");
4735: fprintf(ficlog, "**********\n");
4736: }
1.284 brouard 4737: /*
4738: Printing means of quantitative variables if any
4739: */
4740: for (z1=1; z1<= nqfveff; z1++) {
1.285 brouard 4741: fprintf(ficlog,"Mean of fixed quantitative variable V%d on %.0f individuals sum=%f", ncovcol+z1, idq[z1], meanq[z1]);
1.284 brouard 4742: fprintf(ficlog,", mean=%.3g\n",meanq[z1]/idq[z1]);
4743: if(weightopt==1){
4744: printf(" Weighted mean and standard deviation of");
4745: fprintf(ficlog," Weighted mean and standard deviation of");
4746: fprintf(ficresphtmfr," Weighted mean and standard deviation of");
4747: }
1.285 brouard 4748: printf(" fixed quantitative variable V%d on %.0f representatives of the population : %6.3g (%6.3g)\n", ncovcol+z1, idq[z1],meanq[z1]/idq[z1], sqrt((stdq[z1]-meanq[z1]*meanq[z1]/idq[z1])/idq[z1]));
4749: fprintf(ficlog," fixed quantitative variable V%d on %.0f representatives of the population : %6.3g (%6.3g)\n", ncovcol+z1, idq[z1],meanq[z1]/idq[z1], sqrt((stdq[z1]-meanq[z1]*meanq[z1]/idq[z1])/idq[z1]));
4750: fprintf(ficresphtmfr," fixed quantitative variable V%d on %.0f representatives of the population : %6.3g (%6.3g)<p>\n", ncovcol+z1, idq[z1],meanq[z1]/idq[z1], sqrt((stdq[z1]-meanq[z1]*meanq[z1]/idq[z1])/idq[z1]));
1.284 brouard 4751: }
4752: /* for (z1=1; z1<= nqtveff; z1++) { */
4753: /* for(m=1;m<=lastpass;m++){ */
4754: /* fprintf(ficresphtmfr,"V quantitative id %d, pass id=%d, mean=%f<p>\n", z1, m, meanqt[m][z1]); */
4755: /* } */
4756: /* } */
1.283 brouard 4757:
1.251 brouard 4758: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.265 brouard 4759: if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
4760: fprintf(ficresp, " Age");
4761: 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 4762: for(i=1; i<=nlstate;i++) {
1.265 brouard 4763: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 4764: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
4765: }
1.265 brouard 4766: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 4767: fprintf(ficresphtm, "\n");
4768:
4769: /* Header of frequency table by age */
4770: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
4771: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 4772: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 4773: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 4774: if(s2!=0 && m!=0)
4775: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 4776: }
1.226 brouard 4777: }
1.251 brouard 4778: fprintf(ficresphtmfr, "\n");
4779:
4780: /* For each age */
4781: for(iage=iagemin; iage <= iagemax+3; iage++){
4782: fprintf(ficresphtm,"<tr>");
4783: if(iage==iagemax+1){
4784: fprintf(ficlog,"1");
4785: fprintf(ficresphtmfr,"<tr><th>0</th> ");
4786: }else if(iage==iagemax+2){
4787: fprintf(ficlog,"0");
4788: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
4789: }else if(iage==iagemax+3){
4790: fprintf(ficlog,"Total");
4791: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
4792: }else{
1.240 brouard 4793: if(first==1){
1.251 brouard 4794: first=0;
4795: printf("See log file for details...\n");
4796: }
4797: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
4798: fprintf(ficlog,"Age %d", iage);
4799: }
1.265 brouard 4800: for(s1=1; s1 <=nlstate ; s1++){
4801: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
4802: pp[s1] += freq[s1][m][iage];
1.251 brouard 4803: }
1.265 brouard 4804: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 4805: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 4806: pos += freq[s1][m][iage];
4807: if(pp[s1]>=1.e-10){
1.251 brouard 4808: if(first==1){
1.265 brouard 4809: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 4810: }
1.265 brouard 4811: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 4812: }else{
4813: if(first==1)
1.265 brouard 4814: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
4815: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 4816: }
4817: }
4818:
1.265 brouard 4819: for(s1=1; s1 <=nlstate ; s1++){
4820: /* posprop[s1]=0; */
4821: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
4822: pp[s1] += freq[s1][m][iage];
4823: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
4824:
4825: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
4826: pos += pp[s1]; /* pos is the total number of transitions until this age */
4827: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
4828: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
4829: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
4830: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
4831: }
4832:
4833: /* Writing ficresp */
4834: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
4835: if( iage <= iagemax){
4836: fprintf(ficresp," %d",iage);
4837: }
4838: }else if( nj==2){
4839: if( iage <= iagemax){
4840: fprintf(ficresp," %d",iage);
4841: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4842: }
1.240 brouard 4843: }
1.265 brouard 4844: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 4845: if(pos>=1.e-5){
1.251 brouard 4846: if(first==1)
1.265 brouard 4847: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
4848: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 4849: }else{
4850: if(first==1)
1.265 brouard 4851: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
4852: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 4853: }
4854: if( iage <= iagemax){
4855: if(pos>=1.e-5){
1.265 brouard 4856: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
4857: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4858: }else if( nj==2){
4859: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4860: }
4861: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4862: /*probs[iage][s1][j1]= pp[s1]/pos;*/
4863: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
4864: } else{
4865: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
4866: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 4867: }
1.240 brouard 4868: }
1.265 brouard 4869: pospropt[s1] +=posprop[s1];
4870: } /* end loop s1 */
1.251 brouard 4871: /* pospropt=0.; */
1.265 brouard 4872: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 4873: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 4874: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 4875: if(first==1){
1.265 brouard 4876: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 4877: }
1.265 brouard 4878: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
4879: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 4880: }
1.265 brouard 4881: if(s1!=0 && m!=0)
4882: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 4883: }
1.265 brouard 4884: } /* end loop s1 */
1.251 brouard 4885: posproptt=0.;
1.265 brouard 4886: for(s1=1; s1 <=nlstate; s1++){
4887: posproptt += pospropt[s1];
1.251 brouard 4888: }
4889: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 4890: fprintf(ficresphtm,"</tr>\n");
4891: if((cptcoveff==0 && nj==1)|| nj==2 ) {
4892: if(iage <= iagemax)
4893: fprintf(ficresp,"\n");
1.240 brouard 4894: }
1.251 brouard 4895: if(first==1)
4896: printf("Others in log...\n");
4897: fprintf(ficlog,"\n");
4898: } /* end loop age iage */
1.265 brouard 4899:
1.251 brouard 4900: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 4901: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 4902: if(posproptt < 1.e-5){
1.265 brouard 4903: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 4904: }else{
1.265 brouard 4905: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 4906: }
1.226 brouard 4907: }
1.251 brouard 4908: fprintf(ficresphtm,"</tr>\n");
4909: fprintf(ficresphtm,"</table>\n");
4910: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 4911: if(posproptt < 1.e-5){
1.251 brouard 4912: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
4913: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 4914: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
4915: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 4916: invalidvarcomb[j1]=1;
1.226 brouard 4917: }else{
1.251 brouard 4918: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced.</p>",j1);
4919: invalidvarcomb[j1]=0;
1.226 brouard 4920: }
1.251 brouard 4921: fprintf(ficresphtmfr,"</table>\n");
4922: fprintf(ficlog,"\n");
4923: if(j!=0){
4924: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 4925: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 4926: for(k=1; k <=(nlstate+ndeath); k++){
4927: if (k != i) {
1.265 brouard 4928: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 4929: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 4930: if(j1==1){ /* All dummy covariates to zero */
4931: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
4932: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 4933: printf("%d%d ",i,k);
4934: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 4935: 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]));
4936: 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]));
4937: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 4938: }
1.253 brouard 4939: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
4940: for(iage=iagemin; iage <= iagemax+3; iage++){
4941: x[iage]= (double)iage;
4942: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 4943: /* 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 4944: }
1.268 brouard 4945: /* Some are not finite, but linreg will ignore these ages */
4946: no=0;
1.253 brouard 4947: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 4948: pstart[s1]=b;
4949: pstart[s1-1]=a;
1.252 brouard 4950: }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 */
4951: 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]);
4952: 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 4953: 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 4954: printf("%d%d ",i,k);
4955: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 4956: 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 4957: }else{ /* Other cases, like quantitative fixed or varying covariates */
4958: ;
4959: }
4960: /* printf("%12.7f )", param[i][jj][k]); */
4961: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 4962: s1++;
1.251 brouard 4963: } /* end jj */
4964: } /* end k!= i */
4965: } /* end k */
1.265 brouard 4966: } /* end i, s1 */
1.251 brouard 4967: } /* end j !=0 */
4968: } /* end selected combination of covariate j1 */
4969: if(j==0){ /* We can estimate starting values from the occurences in each case */
4970: printf("#Freqsummary: Starting values for the constants:\n");
4971: fprintf(ficlog,"\n");
1.265 brouard 4972: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 4973: for(k=1; k <=(nlstate+ndeath); k++){
4974: if (k != i) {
4975: printf("%d%d ",i,k);
4976: fprintf(ficlog,"%d%d ",i,k);
4977: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 4978: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 4979: if(jj==1){ /* Age has to be done */
1.265 brouard 4980: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
4981: 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]));
4982: 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 4983: }
4984: /* printf("%12.7f )", param[i][jj][k]); */
4985: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 4986: s1++;
1.250 brouard 4987: }
1.251 brouard 4988: printf("\n");
4989: fprintf(ficlog,"\n");
1.250 brouard 4990: }
4991: }
1.284 brouard 4992: } /* end of state i */
1.251 brouard 4993: printf("#Freqsummary\n");
4994: fprintf(ficlog,"\n");
1.265 brouard 4995: for(s1=-1; s1 <=nlstate+ndeath; s1++){
4996: for(s2=-1; s2 <=nlstate+ndeath; s2++){
4997: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
4998: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
4999: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
5000: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
5001: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
5002: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 5003: /* } */
5004: }
1.265 brouard 5005: } /* end loop s1 */
1.251 brouard 5006:
5007: printf("\n");
5008: fprintf(ficlog,"\n");
5009: } /* end j=0 */
1.249 brouard 5010: } /* end j */
1.252 brouard 5011:
1.253 brouard 5012: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 5013: for(i=1, jk=1; i <=nlstate; i++){
5014: for(j=1; j <=nlstate+ndeath; j++){
5015: if(j!=i){
5016: /*ca[0]= k+'a'-1;ca[1]='\0';*/
5017: printf("%1d%1d",i,j);
5018: fprintf(ficparo,"%1d%1d",i,j);
5019: for(k=1; k<=ncovmodel;k++){
5020: /* printf(" %lf",param[i][j][k]); */
5021: /* fprintf(ficparo," %lf",param[i][j][k]); */
5022: p[jk]=pstart[jk];
5023: printf(" %f ",pstart[jk]);
5024: fprintf(ficparo," %f ",pstart[jk]);
5025: jk++;
5026: }
5027: printf("\n");
5028: fprintf(ficparo,"\n");
5029: }
5030: }
5031: }
5032: } /* end mle=-2 */
1.226 brouard 5033: dateintmean=dateintsum/k2cpt;
1.296 brouard 5034: date2dmy(dateintmean,&jintmean,&mintmean,&aintmean);
1.240 brouard 5035:
1.226 brouard 5036: fclose(ficresp);
5037: fclose(ficresphtm);
5038: fclose(ficresphtmfr);
1.283 brouard 5039: free_vector(idq,1,nqfveff);
1.226 brouard 5040: free_vector(meanq,1,nqfveff);
1.284 brouard 5041: free_vector(stdq,1,nqfveff);
1.226 brouard 5042: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 5043: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
5044: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 5045: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 5046: free_vector(pospropt,1,nlstate);
5047: free_vector(posprop,1,nlstate);
1.251 brouard 5048: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 5049: free_vector(pp,1,nlstate);
5050: /* End of freqsummary */
5051: }
1.126 brouard 5052:
1.268 brouard 5053: /* Simple linear regression */
5054: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
5055:
5056: /* y=a+bx regression */
5057: double sumx = 0.0; /* sum of x */
5058: double sumx2 = 0.0; /* sum of x**2 */
5059: double sumxy = 0.0; /* sum of x * y */
5060: double sumy = 0.0; /* sum of y */
5061: double sumy2 = 0.0; /* sum of y**2 */
5062: double sume2 = 0.0; /* sum of square or residuals */
5063: double yhat;
5064:
5065: double denom=0;
5066: int i;
5067: int ne=*no;
5068:
5069: for ( i=ifi, ne=0;i<=ila;i++) {
5070: if(!isfinite(x[i]) || !isfinite(y[i])){
5071: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5072: continue;
5073: }
5074: ne=ne+1;
5075: sumx += x[i];
5076: sumx2 += x[i]*x[i];
5077: sumxy += x[i] * y[i];
5078: sumy += y[i];
5079: sumy2 += y[i]*y[i];
5080: denom = (ne * sumx2 - sumx*sumx);
5081: /* 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); */
5082: }
5083:
5084: denom = (ne * sumx2 - sumx*sumx);
5085: if (denom == 0) {
5086: // vertical, slope m is infinity
5087: *b = INFINITY;
5088: *a = 0;
5089: if (r) *r = 0;
5090: return 1;
5091: }
5092:
5093: *b = (ne * sumxy - sumx * sumy) / denom;
5094: *a = (sumy * sumx2 - sumx * sumxy) / denom;
5095: if (r!=NULL) {
5096: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
5097: sqrt((sumx2 - sumx*sumx/ne) *
5098: (sumy2 - sumy*sumy/ne));
5099: }
5100: *no=ne;
5101: for ( i=ifi, ne=0;i<=ila;i++) {
5102: if(!isfinite(x[i]) || !isfinite(y[i])){
5103: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5104: continue;
5105: }
5106: ne=ne+1;
5107: yhat = y[i] - *a -*b* x[i];
5108: sume2 += yhat * yhat ;
5109:
5110: denom = (ne * sumx2 - sumx*sumx);
5111: /* 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); */
5112: }
5113: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
5114: *sa= *sb * sqrt(sumx2/ne);
5115:
5116: return 0;
5117: }
5118:
1.126 brouard 5119: /************ Prevalence ********************/
1.227 brouard 5120: 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)
5121: {
5122: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
5123: in each health status at the date of interview (if between dateprev1 and dateprev2).
5124: We still use firstpass and lastpass as another selection.
5125: */
1.126 brouard 5126:
1.227 brouard 5127: int i, m, jk, j1, bool, z1,j, iv;
5128: int mi; /* Effective wave */
5129: int iage;
5130: double agebegin, ageend;
5131:
5132: double **prop;
5133: double posprop;
5134: double y2; /* in fractional years */
5135: int iagemin, iagemax;
5136: int first; /** to stop verbosity which is redirected to log file */
5137:
5138: iagemin= (int) agemin;
5139: iagemax= (int) agemax;
5140: /*pp=vector(1,nlstate);*/
1.251 brouard 5141: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5142: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
5143: j1=0;
1.222 brouard 5144:
1.227 brouard 5145: /*j=cptcoveff;*/
5146: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 5147:
1.288 brouard 5148: first=0;
1.227 brouard 5149: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of covariate */
5150: for (i=1; i<=nlstate; i++)
1.251 brouard 5151: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 5152: prop[i][iage]=0.0;
5153: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
5154: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
5155: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
5156:
5157: for (i=1; i<=imx; i++) { /* Each individual */
5158: bool=1;
5159: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
5160: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
5161: m=mw[mi][i];
5162: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
5163: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
5164: for (z1=1; z1<=cptcoveff; z1++){
5165: if( Fixed[Tmodelind[z1]]==1){
5166: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
5167: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality */
5168: bool=0;
5169: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
5170: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
5171: bool=0;
5172: }
5173: }
5174: if(bool==1){ /* Otherwise we skip that wave/person */
5175: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
5176: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
5177: if(m >=firstpass && m <=lastpass){
5178: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
5179: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
5180: if(agev[m][i]==0) agev[m][i]=iagemax+1;
5181: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 5182: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 5183: 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);
5184: exit(1);
5185: }
5186: if (s[m][i]>0 && s[m][i]<=nlstate) {
5187: /*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]]);*/
5188: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
5189: prop[s[m][i]][iagemax+3] += weight[i];
5190: } /* end valid statuses */
5191: } /* end selection of dates */
5192: } /* end selection of waves */
5193: } /* end bool */
5194: } /* end wave */
5195: } /* end individual */
5196: for(i=iagemin; i <= iagemax+3; i++){
5197: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
5198: posprop += prop[jk][i];
5199: }
5200:
5201: for(jk=1; jk <=nlstate ; jk++){
5202: if( i <= iagemax){
5203: if(posprop>=1.e-5){
5204: probs[i][jk][j1]= prop[jk][i]/posprop;
5205: } else{
1.288 brouard 5206: if(!first){
5207: first=1;
1.266 brouard 5208: 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]);
5209: }else{
1.288 brouard 5210: fprintf(ficlog,"Warning Observed prevalence doesn't sum to 1 for state %d: probs[%d][%d][%d]=%lf because of lack of cases.\n",jk,i,jk, j1,probs[i][jk][j1]);
1.227 brouard 5211: }
5212: }
5213: }
5214: }/* end jk */
5215: }/* end i */
1.222 brouard 5216: /*} *//* end i1 */
1.227 brouard 5217: } /* end j1 */
1.222 brouard 5218:
1.227 brouard 5219: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
5220: /*free_vector(pp,1,nlstate);*/
1.251 brouard 5221: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5222: } /* End of prevalence */
1.126 brouard 5223:
5224: /************* Waves Concatenation ***************/
5225:
5226: 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)
5227: {
1.298 brouard 5228: /* Concatenates waves: wav[i] is the number of effective (useful waves in the sense that a non interview is useless) of individual i.
1.126 brouard 5229: Death is a valid wave (if date is known).
5230: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
5231: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
1.298 brouard 5232: and mw[mi+1][i]. dh depends on stepm. s[m][i] exists for any wave from firstpass to lastpass
1.227 brouard 5233: */
1.126 brouard 5234:
1.224 brouard 5235: int i=0, mi=0, m=0, mli=0;
1.126 brouard 5236: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
5237: double sum=0., jmean=0.;*/
1.224 brouard 5238: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 5239: int j, k=0,jk, ju, jl;
5240: double sum=0.;
5241: first=0;
1.214 brouard 5242: firstwo=0;
1.217 brouard 5243: firsthree=0;
1.218 brouard 5244: firstfour=0;
1.164 brouard 5245: jmin=100000;
1.126 brouard 5246: jmax=-1;
5247: jmean=0.;
1.224 brouard 5248:
5249: /* Treating live states */
1.214 brouard 5250: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 5251: mi=0; /* First valid wave */
1.227 brouard 5252: mli=0; /* Last valid wave */
1.126 brouard 5253: m=firstpass;
1.214 brouard 5254: while(s[m][i] <= nlstate){ /* a live state */
1.227 brouard 5255: 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 */
5256: mli=m-1;/* mw[++mi][i]=m-1; */
5257: }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 */
5258: mw[++mi][i]=m;
5259: mli=m;
1.224 brouard 5260: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
5261: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 5262: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 5263: }
1.227 brouard 5264: else{ /* m >= lastpass, eventual special issue with warning */
1.224 brouard 5265: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 5266: break;
1.224 brouard 5267: #else
1.227 brouard 5268: if(s[m][i]==-1 && (int) andc[i] == 9999 && (int)anint[m][i] != 9999){
5269: if(firsthree == 0){
1.302 brouard 5270: 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 5271: firsthree=1;
5272: }
1.302 brouard 5273: 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 5274: mw[++mi][i]=m;
5275: mli=m;
5276: }
5277: if(s[m][i]==-2){ /* Vital status is really unknown */
5278: nbwarn++;
5279: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified? */
5280: 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);
5281: 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);
5282: }
5283: break;
5284: }
5285: break;
1.224 brouard 5286: #endif
1.227 brouard 5287: }/* End m >= lastpass */
1.126 brouard 5288: }/* end while */
1.224 brouard 5289:
1.227 brouard 5290: /* 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 5291: /* After last pass */
1.224 brouard 5292: /* Treating death states */
1.214 brouard 5293: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 5294: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
5295: /* } */
1.126 brouard 5296: mi++; /* Death is another wave */
5297: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 5298: /* Only death is a correct wave */
1.126 brouard 5299: mw[mi][i]=m;
1.257 brouard 5300: } /* else not in a death state */
1.224 brouard 5301: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 5302: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 5303: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.227 brouard 5304: 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 */
5305: nbwarn++;
5306: if(firstfiv==0){
5307: 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 );
5308: firstfiv=1;
5309: }else{
5310: 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 );
5311: }
5312: }else{ /* Death occured afer last wave potential bias */
5313: nberr++;
5314: if(firstwo==0){
1.257 brouard 5315: 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 5316: firstwo=1;
5317: }
1.257 brouard 5318: 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 5319: }
1.257 brouard 5320: }else{ /* if date of interview is unknown */
1.227 brouard 5321: /* death is known but not confirmed by death status at any wave */
5322: if(firstfour==0){
5323: 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 );
5324: firstfour=1;
5325: }
5326: 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 5327: }
1.224 brouard 5328: } /* end if date of death is known */
5329: #endif
5330: wav[i]=mi; /* mi should be the last effective wave (or mli) */
5331: /* wav[i]=mw[mi][i]; */
1.126 brouard 5332: if(mi==0){
5333: nbwarn++;
5334: if(first==0){
1.227 brouard 5335: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
5336: first=1;
1.126 brouard 5337: }
5338: if(first==1){
1.227 brouard 5339: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 5340: }
5341: } /* end mi==0 */
5342: } /* End individuals */
1.214 brouard 5343: /* wav and mw are no more changed */
1.223 brouard 5344:
1.214 brouard 5345:
1.126 brouard 5346: for(i=1; i<=imx; i++){
5347: for(mi=1; mi<wav[i];mi++){
5348: if (stepm <=0)
1.227 brouard 5349: dh[mi][i]=1;
1.126 brouard 5350: else{
1.260 brouard 5351: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 5352: if (agedc[i] < 2*AGESUP) {
5353: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
5354: if(j==0) j=1; /* Survives at least one month after exam */
5355: else if(j<0){
5356: nberr++;
5357: 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]);
5358: j=1; /* Temporary Dangerous patch */
5359: 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);
5360: 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]);
5361: 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);
5362: }
5363: k=k+1;
5364: if (j >= jmax){
5365: jmax=j;
5366: ijmax=i;
5367: }
5368: if (j <= jmin){
5369: jmin=j;
5370: ijmin=i;
5371: }
5372: sum=sum+j;
5373: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
5374: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
5375: }
5376: }
5377: else{
5378: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 5379: /* 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 5380:
1.227 brouard 5381: k=k+1;
5382: if (j >= jmax) {
5383: jmax=j;
5384: ijmax=i;
5385: }
5386: else if (j <= jmin){
5387: jmin=j;
5388: ijmin=i;
5389: }
5390: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
5391: /*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]);*/
5392: if(j<0){
5393: nberr++;
5394: 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]);
5395: 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]);
5396: }
5397: sum=sum+j;
5398: }
5399: jk= j/stepm;
5400: jl= j -jk*stepm;
5401: ju= j -(jk+1)*stepm;
5402: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
5403: if(jl==0){
5404: dh[mi][i]=jk;
5405: bh[mi][i]=0;
5406: }else{ /* We want a negative bias in order to only have interpolation ie
5407: * to avoid the price of an extra matrix product in likelihood */
5408: dh[mi][i]=jk+1;
5409: bh[mi][i]=ju;
5410: }
5411: }else{
5412: if(jl <= -ju){
5413: dh[mi][i]=jk;
5414: bh[mi][i]=jl; /* bias is positive if real duration
5415: * is higher than the multiple of stepm and negative otherwise.
5416: */
5417: }
5418: else{
5419: dh[mi][i]=jk+1;
5420: bh[mi][i]=ju;
5421: }
5422: if(dh[mi][i]==0){
5423: dh[mi][i]=1; /* At least one step */
5424: bh[mi][i]=ju; /* At least one step */
5425: /* 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);*/
5426: }
5427: } /* end if mle */
1.126 brouard 5428: }
5429: } /* end wave */
5430: }
5431: jmean=sum/k;
5432: 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 5433: 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 5434: }
1.126 brouard 5435:
5436: /*********** Tricode ****************************/
1.220 brouard 5437: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 5438: {
5439: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
5440: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
5441: * Boring subroutine which should only output nbcode[Tvar[j]][k]
5442: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
5443: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
5444: */
1.130 brouard 5445:
1.242 brouard 5446: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
5447: int modmaxcovj=0; /* Modality max of covariates j */
5448: int cptcode=0; /* Modality max of covariates j */
5449: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 5450:
5451:
1.242 brouard 5452: /* cptcoveff=0; */
5453: /* *cptcov=0; */
1.126 brouard 5454:
1.242 brouard 5455: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.285 brouard 5456: for (k=1; k <= maxncov; k++)
5457: for(j=1; j<=2; j++)
5458: nbcode[k][j]=0; /* Valgrind */
1.126 brouard 5459:
1.242 brouard 5460: /* Loop on covariates without age and products and no quantitative variable */
5461: for (k=1; k<=cptcovt; k++) { /* From model V1 + V2*age + V3 + V3*V4 keeps V1 + V3 = 2 only */
5462: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
5463: if(Dummy[k]==0 && Typevar[k] !=1){ /* Dummy covariate and not age product */
5464: switch(Fixed[k]) {
5465: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
5466: 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*/
5467: ij=(int)(covar[Tvar[k]][i]);
5468: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
5469: * If product of Vn*Vm, still boolean *:
5470: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
5471: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
5472: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
5473: modality of the nth covariate of individual i. */
5474: if (ij > modmaxcovj)
5475: modmaxcovj=ij;
5476: else if (ij < modmincovj)
5477: modmincovj=ij;
1.287 brouard 5478: if (ij <0 || ij >1 ){
5479: printf("Information, IMaCh doesn't treat covariate with missing values (-1), individual %d will be skipped.\n",i);
5480: fprintf(ficlog,"Information, currently IMaCh doesn't treat covariate with missing values (-1), individual %d will be skipped.\n",i);
5481: }
5482: if ((ij < -1) || (ij > NCOVMAX)){
1.242 brouard 5483: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
5484: exit(1);
5485: }else
5486: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
5487: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
5488: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
5489: /* getting the maximum value of the modality of the covariate
5490: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
5491: female ies 1, then modmaxcovj=1.
5492: */
5493: } /* end for loop on individuals i */
5494: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5495: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5496: cptcode=modmaxcovj;
5497: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
5498: /*for (i=0; i<=cptcode; i++) {*/
5499: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
5500: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5501: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5502: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
5503: if( j != -1){
5504: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
5505: covariate for which somebody answered excluding
5506: undefined. Usually 2: 0 and 1. */
5507: }
5508: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
5509: covariate for which somebody answered including
5510: undefined. Usually 3: -1, 0 and 1. */
5511: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
5512: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
5513: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 5514:
1.242 brouard 5515: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
5516: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
5517: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
5518: /* modmincovj=3; modmaxcovj = 7; */
5519: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
5520: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
5521: /* defining two dummy variables: variables V1_1 and V1_2.*/
5522: /* nbcode[Tvar[j]][ij]=k; */
5523: /* nbcode[Tvar[j]][1]=0; */
5524: /* nbcode[Tvar[j]][2]=1; */
5525: /* nbcode[Tvar[j]][3]=2; */
5526: /* To be continued (not working yet). */
5527: ij=0; /* ij is similar to i but can jump over null modalities */
1.287 brouard 5528:
5529: /* 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*/
5530: /* Skipping the case of missing values by reducing nbcode to 0 and 1 and not -1, 0, 1 */
5531: /* model=V1+V2+V3, if V2=-1, 0 or 1, then nbcode[2][1]=0 and nbcode[2][2]=1 instead of
5532: * nbcode[2][1]=-1, nbcode[2][2]=0 and nbcode[2][3]=1 */
5533: /*, could be restored in the future */
5534: for (i=0; i<=1; i++) { /* i= 1 to 2 for dichotomous, or from 1 to 3 or from -1 or 0 to 1 currently*/
1.242 brouard 5535: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
5536: break;
5537: }
5538: ij++;
1.287 brouard 5539: nbcode[Tvar[k]][ij]=i; /* stores the original value of modality i in an array nbcode, ij modality from 1 to last non-nul modality. nbcode[1][1]=0 nbcode[1][2]=1 . Could be -1*/
1.242 brouard 5540: cptcode = ij; /* New max modality for covar j */
5541: } /* end of loop on modality i=-1 to 1 or more */
5542: break;
5543: case 1: /* Testing on varying covariate, could be simple and
5544: * should look at waves or product of fixed *
5545: * varying. No time to test -1, assuming 0 and 1 only */
5546: ij=0;
5547: for(i=0; i<=1;i++){
5548: nbcode[Tvar[k]][++ij]=i;
5549: }
5550: break;
5551: default:
5552: break;
5553: } /* end switch */
5554: } /* end dummy test */
1.287 brouard 5555: } /* end of loop on model-covariate k. nbcode[Tvark][1]=-1, nbcode[Tvark][1]=0 and nbcode[Tvark][2]=1 sets the value of covariate k*/
1.242 brouard 5556:
5557: for (k=-1; k< maxncov; k++) Ndum[k]=0;
5558: /* Look at fixed dummy (single or product) covariates to check empty modalities */
5559: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
5560: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
5561: 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 */
5562: 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 */
5563: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
5564: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
5565:
5566: ij=0;
5567: /* for (i=0; i<= maxncov-1; i++) { /\* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) *\/ */
5568: for (k=1; k<= cptcovt; k++) { /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
5569: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
5570: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
5571: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy and non empty in the model */
5572: /* If product not in single variable we don't print results */
5573: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
5574: ++ij;/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, */
5575: 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*/
5576: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
5577: 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 */
5578: if(Fixed[k]!=0)
5579: anyvaryingduminmodel=1;
5580: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
5581: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
5582: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
5583: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
5584: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
5585: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
5586: }
5587: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
5588: /* ij--; */
5589: /* cptcoveff=ij; /\*Number of total covariates*\/ */
5590: *cptcov=ij; /*Number of total real effective covariates: effective
5591: * because they can be excluded from the model and real
5592: * if in the model but excluded because missing values, but how to get k from ij?*/
5593: for(j=ij+1; j<= cptcovt; j++){
5594: Tvaraff[j]=0;
5595: Tmodelind[j]=0;
5596: }
5597: for(j=ntveff+1; j<= cptcovt; j++){
5598: TmodelInvind[j]=0;
5599: }
5600: /* To be sorted */
5601: ;
5602: }
1.126 brouard 5603:
1.145 brouard 5604:
1.126 brouard 5605: /*********** Health Expectancies ****************/
5606:
1.235 brouard 5607: 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 5608:
5609: {
5610: /* Health expectancies, no variances */
1.164 brouard 5611: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 5612: int nhstepma, nstepma; /* Decreasing with age */
5613: double age, agelim, hf;
5614: double ***p3mat;
5615: double eip;
5616:
1.238 brouard 5617: /* pstamp(ficreseij); */
1.126 brouard 5618: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
5619: fprintf(ficreseij,"# Age");
5620: for(i=1; i<=nlstate;i++){
5621: for(j=1; j<=nlstate;j++){
5622: fprintf(ficreseij," e%1d%1d ",i,j);
5623: }
5624: fprintf(ficreseij," e%1d. ",i);
5625: }
5626: fprintf(ficreseij,"\n");
5627:
5628:
5629: if(estepm < stepm){
5630: printf ("Problem %d lower than %d\n",estepm, stepm);
5631: }
5632: else hstepm=estepm;
5633: /* We compute the life expectancy from trapezoids spaced every estepm months
5634: * This is mainly to measure the difference between two models: for example
5635: * if stepm=24 months pijx are given only every 2 years and by summing them
5636: * we are calculating an estimate of the Life Expectancy assuming a linear
5637: * progression in between and thus overestimating or underestimating according
5638: * to the curvature of the survival function. If, for the same date, we
5639: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5640: * to compare the new estimate of Life expectancy with the same linear
5641: * hypothesis. A more precise result, taking into account a more precise
5642: * curvature will be obtained if estepm is as small as stepm. */
5643:
5644: /* For example we decided to compute the life expectancy with the smallest unit */
5645: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5646: nhstepm is the number of hstepm from age to agelim
5647: nstepm is the number of stepm from age to agelin.
1.270 brouard 5648: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 5649: and note for a fixed period like estepm months */
5650: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5651: survival function given by stepm (the optimization length). Unfortunately it
5652: means that if the survival funtion is printed only each two years of age and if
5653: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5654: results. So we changed our mind and took the option of the best precision.
5655: */
5656: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5657:
5658: agelim=AGESUP;
5659: /* If stepm=6 months */
5660: /* Computed by stepm unit matrices, product of hstepm matrices, stored
5661: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
5662:
5663: /* nhstepm age range expressed in number of stepm */
5664: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5665: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5666: /* if (stepm >= YEARM) hstepm=1;*/
5667: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5668: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5669:
5670: for (age=bage; age<=fage; age ++){
5671: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5672: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5673: /* if (stepm >= YEARM) hstepm=1;*/
5674: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
5675:
5676: /* If stepm=6 months */
5677: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5678: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5679:
1.235 brouard 5680: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 5681:
5682: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
5683:
5684: printf("%d|",(int)age);fflush(stdout);
5685: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5686:
5687: /* Computing expectancies */
5688: for(i=1; i<=nlstate;i++)
5689: for(j=1; j<=nlstate;j++)
5690: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5691: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
5692:
5693: /* 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]);*/
5694:
5695: }
5696:
5697: fprintf(ficreseij,"%3.0f",age );
5698: for(i=1; i<=nlstate;i++){
5699: eip=0;
5700: for(j=1; j<=nlstate;j++){
5701: eip +=eij[i][j][(int)age];
5702: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
5703: }
5704: fprintf(ficreseij,"%9.4f", eip );
5705: }
5706: fprintf(ficreseij,"\n");
5707:
5708: }
5709: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5710: printf("\n");
5711: fprintf(ficlog,"\n");
5712:
5713: }
5714:
1.235 brouard 5715: 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 5716:
5717: {
5718: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 5719: to initial status i, ei. .
1.126 brouard 5720: */
5721: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
5722: int nhstepma, nstepma; /* Decreasing with age */
5723: double age, agelim, hf;
5724: double ***p3matp, ***p3matm, ***varhe;
5725: double **dnewm,**doldm;
5726: double *xp, *xm;
5727: double **gp, **gm;
5728: double ***gradg, ***trgradg;
5729: int theta;
5730:
5731: double eip, vip;
5732:
5733: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
5734: xp=vector(1,npar);
5735: xm=vector(1,npar);
5736: dnewm=matrix(1,nlstate*nlstate,1,npar);
5737: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
5738:
5739: pstamp(ficresstdeij);
5740: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
5741: fprintf(ficresstdeij,"# Age");
5742: for(i=1; i<=nlstate;i++){
5743: for(j=1; j<=nlstate;j++)
5744: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
5745: fprintf(ficresstdeij," e%1d. ",i);
5746: }
5747: fprintf(ficresstdeij,"\n");
5748:
5749: pstamp(ficrescveij);
5750: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
5751: fprintf(ficrescveij,"# Age");
5752: for(i=1; i<=nlstate;i++)
5753: for(j=1; j<=nlstate;j++){
5754: cptj= (j-1)*nlstate+i;
5755: for(i2=1; i2<=nlstate;i2++)
5756: for(j2=1; j2<=nlstate;j2++){
5757: cptj2= (j2-1)*nlstate+i2;
5758: if(cptj2 <= cptj)
5759: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
5760: }
5761: }
5762: fprintf(ficrescveij,"\n");
5763:
5764: if(estepm < stepm){
5765: printf ("Problem %d lower than %d\n",estepm, stepm);
5766: }
5767: else hstepm=estepm;
5768: /* We compute the life expectancy from trapezoids spaced every estepm months
5769: * This is mainly to measure the difference between two models: for example
5770: * if stepm=24 months pijx are given only every 2 years and by summing them
5771: * we are calculating an estimate of the Life Expectancy assuming a linear
5772: * progression in between and thus overestimating or underestimating according
5773: * to the curvature of the survival function. If, for the same date, we
5774: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5775: * to compare the new estimate of Life expectancy with the same linear
5776: * hypothesis. A more precise result, taking into account a more precise
5777: * curvature will be obtained if estepm is as small as stepm. */
5778:
5779: /* For example we decided to compute the life expectancy with the smallest unit */
5780: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5781: nhstepm is the number of hstepm from age to agelim
5782: nstepm is the number of stepm from age to agelin.
5783: Look at hpijx to understand the reason of that which relies in memory size
5784: and note for a fixed period like estepm months */
5785: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5786: survival function given by stepm (the optimization length). Unfortunately it
5787: means that if the survival funtion is printed only each two years of age and if
5788: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5789: results. So we changed our mind and took the option of the best precision.
5790: */
5791: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5792:
5793: /* If stepm=6 months */
5794: /* nhstepm age range expressed in number of stepm */
5795: agelim=AGESUP;
5796: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
5797: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5798: /* if (stepm >= YEARM) hstepm=1;*/
5799: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5800:
5801: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5802: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5803: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
5804: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
5805: gp=matrix(0,nhstepm,1,nlstate*nlstate);
5806: gm=matrix(0,nhstepm,1,nlstate*nlstate);
5807:
5808: for (age=bage; age<=fage; age ++){
5809: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5810: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5811: /* if (stepm >= YEARM) hstepm=1;*/
5812: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 5813:
1.126 brouard 5814: /* If stepm=6 months */
5815: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5816: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5817:
5818: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 5819:
1.126 brouard 5820: /* Computing Variances of health expectancies */
5821: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
5822: decrease memory allocation */
5823: for(theta=1; theta <=npar; theta++){
5824: for(i=1; i<=npar; i++){
1.222 brouard 5825: xp[i] = x[i] + (i==theta ?delti[theta]:0);
5826: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 5827: }
1.235 brouard 5828: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
5829: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 5830:
1.126 brouard 5831: for(j=1; j<= nlstate; j++){
1.222 brouard 5832: for(i=1; i<=nlstate; i++){
5833: for(h=0; h<=nhstepm-1; h++){
5834: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
5835: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
5836: }
5837: }
1.126 brouard 5838: }
1.218 brouard 5839:
1.126 brouard 5840: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 5841: for(h=0; h<=nhstepm-1; h++){
5842: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
5843: }
1.126 brouard 5844: }/* End theta */
5845:
5846:
5847: for(h=0; h<=nhstepm-1; h++)
5848: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 5849: for(theta=1; theta <=npar; theta++)
5850: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 5851:
1.218 brouard 5852:
1.222 brouard 5853: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 5854: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 5855: varhe[ij][ji][(int)age] =0.;
1.218 brouard 5856:
1.222 brouard 5857: printf("%d|",(int)age);fflush(stdout);
5858: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5859: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 5860: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 5861: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
5862: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
5863: for(ij=1;ij<=nlstate*nlstate;ij++)
5864: for(ji=1;ji<=nlstate*nlstate;ji++)
5865: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 5866: }
5867: }
1.218 brouard 5868:
1.126 brouard 5869: /* Computing expectancies */
1.235 brouard 5870: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 5871: for(i=1; i<=nlstate;i++)
5872: for(j=1; j<=nlstate;j++)
1.222 brouard 5873: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5874: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 5875:
1.222 brouard 5876: /* 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 5877:
1.222 brouard 5878: }
1.269 brouard 5879:
5880: /* Standard deviation of expectancies ij */
1.126 brouard 5881: fprintf(ficresstdeij,"%3.0f",age );
5882: for(i=1; i<=nlstate;i++){
5883: eip=0.;
5884: vip=0.;
5885: for(j=1; j<=nlstate;j++){
1.222 brouard 5886: eip += eij[i][j][(int)age];
5887: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
5888: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
5889: 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 5890: }
5891: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
5892: }
5893: fprintf(ficresstdeij,"\n");
1.218 brouard 5894:
1.269 brouard 5895: /* Variance of expectancies ij */
1.126 brouard 5896: fprintf(ficrescveij,"%3.0f",age );
5897: for(i=1; i<=nlstate;i++)
5898: for(j=1; j<=nlstate;j++){
1.222 brouard 5899: cptj= (j-1)*nlstate+i;
5900: for(i2=1; i2<=nlstate;i2++)
5901: for(j2=1; j2<=nlstate;j2++){
5902: cptj2= (j2-1)*nlstate+i2;
5903: if(cptj2 <= cptj)
5904: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
5905: }
1.126 brouard 5906: }
5907: fprintf(ficrescveij,"\n");
1.218 brouard 5908:
1.126 brouard 5909: }
5910: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
5911: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
5912: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
5913: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
5914: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5915: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5916: printf("\n");
5917: fprintf(ficlog,"\n");
1.218 brouard 5918:
1.126 brouard 5919: free_vector(xm,1,npar);
5920: free_vector(xp,1,npar);
5921: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
5922: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
5923: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
5924: }
1.218 brouard 5925:
1.126 brouard 5926: /************ Variance ******************/
1.235 brouard 5927: 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 5928: {
1.279 brouard 5929: /** Variance of health expectancies
5930: * double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);
5931: * double **newm;
5932: * int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)
5933: */
1.218 brouard 5934:
5935: /* int movingaverage(); */
5936: double **dnewm,**doldm;
5937: double **dnewmp,**doldmp;
5938: int i, j, nhstepm, hstepm, h, nstepm ;
1.288 brouard 5939: int first=0;
1.218 brouard 5940: int k;
5941: double *xp;
1.279 brouard 5942: double **gp, **gm; /**< for var eij */
5943: double ***gradg, ***trgradg; /**< for var eij */
5944: double **gradgp, **trgradgp; /**< for var p point j */
5945: double *gpp, *gmp; /**< for var p point j */
5946: double **varppt; /**< for var p point j nlstate to nlstate+ndeath */
1.218 brouard 5947: double ***p3mat;
5948: double age,agelim, hf;
5949: /* double ***mobaverage; */
5950: int theta;
5951: char digit[4];
5952: char digitp[25];
5953:
5954: char fileresprobmorprev[FILENAMELENGTH];
5955:
5956: if(popbased==1){
5957: if(mobilav!=0)
5958: strcpy(digitp,"-POPULBASED-MOBILAV_");
5959: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
5960: }
5961: else
5962: strcpy(digitp,"-STABLBASED_");
1.126 brouard 5963:
1.218 brouard 5964: /* if (mobilav!=0) { */
5965: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
5966: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
5967: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
5968: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
5969: /* } */
5970: /* } */
5971:
5972: strcpy(fileresprobmorprev,"PRMORPREV-");
5973: sprintf(digit,"%-d",ij);
5974: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
5975: strcat(fileresprobmorprev,digit); /* Tvar to be done */
5976: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
5977: strcat(fileresprobmorprev,fileresu);
5978: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
5979: printf("Problem with resultfile: %s\n", fileresprobmorprev);
5980: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
5981: }
5982: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
5983: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
5984: pstamp(ficresprobmorprev);
5985: 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 5986: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
5987: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
5988: fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
5989: }
5990: for(j=1;j<=cptcoveff;j++)
5991: fprintf(ficresprobmorprev,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,j)]);
5992: fprintf(ficresprobmorprev,"\n");
5993:
1.218 brouard 5994: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
5995: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
5996: fprintf(ficresprobmorprev," p.%-d SE",j);
5997: for(i=1; i<=nlstate;i++)
5998: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
5999: }
6000: fprintf(ficresprobmorprev,"\n");
6001:
6002: fprintf(ficgp,"\n# Routine varevsij");
6003: fprintf(ficgp,"\nunset title \n");
6004: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
6005: 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");
6006: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
1.279 brouard 6007:
1.218 brouard 6008: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6009: pstamp(ficresvij);
6010: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
6011: if(popbased==1)
6012: 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);
6013: else
6014: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
6015: fprintf(ficresvij,"# Age");
6016: for(i=1; i<=nlstate;i++)
6017: for(j=1; j<=nlstate;j++)
6018: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
6019: fprintf(ficresvij,"\n");
6020:
6021: xp=vector(1,npar);
6022: dnewm=matrix(1,nlstate,1,npar);
6023: doldm=matrix(1,nlstate,1,nlstate);
6024: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
6025: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6026:
6027: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
6028: gpp=vector(nlstate+1,nlstate+ndeath);
6029: gmp=vector(nlstate+1,nlstate+ndeath);
6030: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 6031:
1.218 brouard 6032: if(estepm < stepm){
6033: printf ("Problem %d lower than %d\n",estepm, stepm);
6034: }
6035: else hstepm=estepm;
6036: /* For example we decided to compute the life expectancy with the smallest unit */
6037: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6038: nhstepm is the number of hstepm from age to agelim
6039: nstepm is the number of stepm from age to agelim.
6040: Look at function hpijx to understand why because of memory size limitations,
6041: we decided (b) to get a life expectancy respecting the most precise curvature of the
6042: survival function given by stepm (the optimization length). Unfortunately it
6043: means that if the survival funtion is printed every two years of age and if
6044: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6045: results. So we changed our mind and took the option of the best precision.
6046: */
6047: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6048: agelim = AGESUP;
6049: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6050: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6051: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6052: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6053: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
6054: gp=matrix(0,nhstepm,1,nlstate);
6055: gm=matrix(0,nhstepm,1,nlstate);
6056:
6057:
6058: for(theta=1; theta <=npar; theta++){
6059: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
6060: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6061: }
1.279 brouard 6062: /**< Computes the prevalence limit with parameter theta shifted of delta up to ftolpl precision and
6063: * returns into prlim .
1.288 brouard 6064: */
1.242 brouard 6065: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.279 brouard 6066:
6067: /* If popbased = 1 we use crossection prevalences. Previous step is useless but prlim is created */
1.218 brouard 6068: if (popbased==1) {
6069: if(mobilav ==0){
6070: for(i=1; i<=nlstate;i++)
6071: prlim[i][i]=probs[(int)age][i][ij];
6072: }else{ /* mobilav */
6073: for(i=1; i<=nlstate;i++)
6074: prlim[i][i]=mobaverage[(int)age][i][ij];
6075: }
6076: }
1.295 brouard 6077: /**< Computes the shifted transition matrix \f$ {}{h}_p^{ij}x\f$ at horizon h.
1.279 brouard 6078: */
6079: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres); /* Returns p3mat[i][j][h] for h=0 to nhstepm */
1.292 brouard 6080: /**< And for each alive state j, sums over i \f$ w^i_x {}{h}_p^{ij}x\f$, which are the probability
1.279 brouard 6081: * at horizon h in state j including mortality.
6082: */
1.218 brouard 6083: for(j=1; j<= nlstate; j++){
6084: for(h=0; h<=nhstepm; h++){
6085: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
6086: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
6087: }
6088: }
1.279 brouard 6089: /* Next for computing shifted+ probability of death (h=1 means
1.218 brouard 6090: computed over hstepm matrices product = hstepm*stepm months)
1.279 brouard 6091: as a weighted average of prlim(i) * p(i,j) p.3=w1*p13 + w2*p23 .
1.218 brouard 6092: */
6093: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6094: for(i=1,gpp[j]=0.; i<= nlstate; i++)
6095: gpp[j] += prlim[i][i]*p3mat[i][j][1];
1.279 brouard 6096: }
6097:
6098: /* Again with minus shift */
1.218 brouard 6099:
6100: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
6101: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 6102:
1.242 brouard 6103: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 6104:
6105: if (popbased==1) {
6106: if(mobilav ==0){
6107: for(i=1; i<=nlstate;i++)
6108: prlim[i][i]=probs[(int)age][i][ij];
6109: }else{ /* mobilav */
6110: for(i=1; i<=nlstate;i++)
6111: prlim[i][i]=mobaverage[(int)age][i][ij];
6112: }
6113: }
6114:
1.235 brouard 6115: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 6116:
6117: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
6118: for(h=0; h<=nhstepm; h++){
6119: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
6120: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
6121: }
6122: }
6123: /* This for computing probability of death (h=1 means
6124: computed over hstepm matrices product = hstepm*stepm months)
6125: as a weighted average of prlim.
6126: */
6127: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6128: for(i=1,gmp[j]=0.; i<= nlstate; i++)
6129: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6130: }
1.279 brouard 6131: /* end shifting computations */
6132:
6133: /**< Computing gradient matrix at horizon h
6134: */
1.218 brouard 6135: for(j=1; j<= nlstate; j++) /* vareij */
6136: for(h=0; h<=nhstepm; h++){
6137: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
6138: }
1.279 brouard 6139: /**< Gradient of overall mortality p.3 (or p.j)
6140: */
6141: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu mortality from j */
1.218 brouard 6142: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
6143: }
6144:
6145: } /* End theta */
1.279 brouard 6146:
6147: /* We got the gradient matrix for each theta and state j */
1.218 brouard 6148: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
6149:
6150: for(h=0; h<=nhstepm; h++) /* veij */
6151: for(j=1; j<=nlstate;j++)
6152: for(theta=1; theta <=npar; theta++)
6153: trgradg[h][j][theta]=gradg[h][theta][j];
6154:
6155: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
6156: for(theta=1; theta <=npar; theta++)
6157: trgradgp[j][theta]=gradgp[theta][j];
1.279 brouard 6158: /**< as well as its transposed matrix
6159: */
1.218 brouard 6160:
6161: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6162: for(i=1;i<=nlstate;i++)
6163: for(j=1;j<=nlstate;j++)
6164: vareij[i][j][(int)age] =0.;
1.279 brouard 6165:
6166: /* Computing trgradg by matcov by gradg at age and summing over h
6167: * and k (nhstepm) formula 15 of article
6168: * Lievre-Brouard-Heathcote
6169: */
6170:
1.218 brouard 6171: for(h=0;h<=nhstepm;h++){
6172: for(k=0;k<=nhstepm;k++){
6173: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
6174: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
6175: for(i=1;i<=nlstate;i++)
6176: for(j=1;j<=nlstate;j++)
6177: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
6178: }
6179: }
6180:
1.279 brouard 6181: /* pptj is p.3 or p.j = trgradgp by cov by gradgp, variance of
6182: * p.j overall mortality formula 49 but computed directly because
6183: * we compute the grad (wix pijx) instead of grad (pijx),even if
6184: * wix is independent of theta.
6185: */
1.218 brouard 6186: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
6187: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
6188: for(j=nlstate+1;j<=nlstate+ndeath;j++)
6189: for(i=nlstate+1;i<=nlstate+ndeath;i++)
6190: varppt[j][i]=doldmp[j][i];
6191: /* end ppptj */
6192: /* x centered again */
6193:
1.242 brouard 6194: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 6195:
6196: if (popbased==1) {
6197: if(mobilav ==0){
6198: for(i=1; i<=nlstate;i++)
6199: prlim[i][i]=probs[(int)age][i][ij];
6200: }else{ /* mobilav */
6201: for(i=1; i<=nlstate;i++)
6202: prlim[i][i]=mobaverage[(int)age][i][ij];
6203: }
6204: }
6205:
6206: /* This for computing probability of death (h=1 means
6207: computed over hstepm (estepm) matrices product = hstepm*stepm months)
6208: as a weighted average of prlim.
6209: */
1.235 brouard 6210: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 6211: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6212: for(i=1,gmp[j]=0.;i<= nlstate; i++)
6213: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6214: }
6215: /* end probability of death */
6216:
6217: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
6218: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6219: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
6220: for(i=1; i<=nlstate;i++){
6221: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
6222: }
6223: }
6224: fprintf(ficresprobmorprev,"\n");
6225:
6226: fprintf(ficresvij,"%.0f ",age );
6227: for(i=1; i<=nlstate;i++)
6228: for(j=1; j<=nlstate;j++){
6229: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
6230: }
6231: fprintf(ficresvij,"\n");
6232: free_matrix(gp,0,nhstepm,1,nlstate);
6233: free_matrix(gm,0,nhstepm,1,nlstate);
6234: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
6235: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
6236: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6237: } /* End age */
6238: free_vector(gpp,nlstate+1,nlstate+ndeath);
6239: free_vector(gmp,nlstate+1,nlstate+ndeath);
6240: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
6241: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
6242: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
6243: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
6244: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
6245: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
6246: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
6247: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
6248: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
6249: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
6250: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
6251: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
6252: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
6253: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
6254: 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);
6255: /* 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 6256: */
1.218 brouard 6257: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
6258: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 6259:
1.218 brouard 6260: free_vector(xp,1,npar);
6261: free_matrix(doldm,1,nlstate,1,nlstate);
6262: free_matrix(dnewm,1,nlstate,1,npar);
6263: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6264: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
6265: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6266: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6267: fclose(ficresprobmorprev);
6268: fflush(ficgp);
6269: fflush(fichtm);
6270: } /* end varevsij */
1.126 brouard 6271:
6272: /************ Variance of prevlim ******************/
1.269 brouard 6273: 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 6274: {
1.205 brouard 6275: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 6276: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 6277:
1.268 brouard 6278: double **dnewmpar,**doldm;
1.126 brouard 6279: int i, j, nhstepm, hstepm;
6280: double *xp;
6281: double *gp, *gm;
6282: double **gradg, **trgradg;
1.208 brouard 6283: double **mgm, **mgp;
1.126 brouard 6284: double age,agelim;
6285: int theta;
6286:
6287: pstamp(ficresvpl);
1.288 brouard 6288: fprintf(ficresvpl,"# Standard deviation of period (forward stable) prevalences \n");
1.241 brouard 6289: fprintf(ficresvpl,"# Age ");
6290: if(nresult >=1)
6291: fprintf(ficresvpl," Result# ");
1.126 brouard 6292: for(i=1; i<=nlstate;i++)
6293: fprintf(ficresvpl," %1d-%1d",i,i);
6294: fprintf(ficresvpl,"\n");
6295:
6296: xp=vector(1,npar);
1.268 brouard 6297: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 6298: doldm=matrix(1,nlstate,1,nlstate);
6299:
6300: hstepm=1*YEARM; /* Every year of age */
6301: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6302: agelim = AGESUP;
6303: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6304: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6305: if (stepm >= YEARM) hstepm=1;
6306: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6307: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 6308: mgp=matrix(1,npar,1,nlstate);
6309: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 6310: gp=vector(1,nlstate);
6311: gm=vector(1,nlstate);
6312:
6313: for(theta=1; theta <=npar; theta++){
6314: for(i=1; i<=npar; i++){ /* Computes gradient */
6315: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6316: }
1.288 brouard 6317: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
6318: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
6319: /* else */
6320: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6321: for(i=1;i<=nlstate;i++){
1.126 brouard 6322: gp[i] = prlim[i][i];
1.208 brouard 6323: mgp[theta][i] = prlim[i][i];
6324: }
1.126 brouard 6325: for(i=1; i<=npar; i++) /* Computes gradient */
6326: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 6327: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
6328: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
6329: /* else */
6330: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6331: for(i=1;i<=nlstate;i++){
1.126 brouard 6332: gm[i] = prlim[i][i];
1.208 brouard 6333: mgm[theta][i] = prlim[i][i];
6334: }
1.126 brouard 6335: for(i=1;i<=nlstate;i++)
6336: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 6337: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 6338: } /* End theta */
6339:
6340: trgradg =matrix(1,nlstate,1,npar);
6341:
6342: for(j=1; j<=nlstate;j++)
6343: for(theta=1; theta <=npar; theta++)
6344: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 6345: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6346: /* printf("\nmgm mgp %d ",(int)age); */
6347: /* for(j=1; j<=nlstate;j++){ */
6348: /* printf(" %d ",j); */
6349: /* for(theta=1; theta <=npar; theta++) */
6350: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6351: /* printf("\n "); */
6352: /* } */
6353: /* } */
6354: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6355: /* printf("\n gradg %d ",(int)age); */
6356: /* for(j=1; j<=nlstate;j++){ */
6357: /* printf("%d ",j); */
6358: /* for(theta=1; theta <=npar; theta++) */
6359: /* printf("%d %lf ",theta,gradg[theta][j]); */
6360: /* printf("\n "); */
6361: /* } */
6362: /* } */
1.126 brouard 6363:
6364: for(i=1;i<=nlstate;i++)
6365: varpl[i][(int)age] =0.;
1.209 brouard 6366: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 brouard 6367: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6368: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6369: }else{
1.268 brouard 6370: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6371: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6372: }
1.126 brouard 6373: for(i=1;i<=nlstate;i++)
6374: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6375:
6376: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 6377: if(nresult >=1)
6378: fprintf(ficresvpl,"%d ",nres );
1.288 brouard 6379: for(i=1; i<=nlstate;i++){
1.126 brouard 6380: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
1.288 brouard 6381: /* for(j=1;j<=nlstate;j++) */
6382: /* fprintf(ficresvpl," %d %.5f ",j,prlim[j][i]); */
6383: }
1.126 brouard 6384: fprintf(ficresvpl,"\n");
6385: free_vector(gp,1,nlstate);
6386: free_vector(gm,1,nlstate);
1.208 brouard 6387: free_matrix(mgm,1,npar,1,nlstate);
6388: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 6389: free_matrix(gradg,1,npar,1,nlstate);
6390: free_matrix(trgradg,1,nlstate,1,npar);
6391: } /* End age */
6392:
6393: free_vector(xp,1,npar);
6394: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 6395: free_matrix(dnewmpar,1,nlstate,1,nlstate);
6396:
6397: }
6398:
6399:
6400: /************ Variance of backprevalence limit ******************/
1.269 brouard 6401: 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 6402: {
6403: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
6404: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
6405:
6406: double **dnewmpar,**doldm;
6407: int i, j, nhstepm, hstepm;
6408: double *xp;
6409: double *gp, *gm;
6410: double **gradg, **trgradg;
6411: double **mgm, **mgp;
6412: double age,agelim;
6413: int theta;
6414:
6415: pstamp(ficresvbl);
6416: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
6417: fprintf(ficresvbl,"# Age ");
6418: if(nresult >=1)
6419: fprintf(ficresvbl," Result# ");
6420: for(i=1; i<=nlstate;i++)
6421: fprintf(ficresvbl," %1d-%1d",i,i);
6422: fprintf(ficresvbl,"\n");
6423:
6424: xp=vector(1,npar);
6425: dnewmpar=matrix(1,nlstate,1,npar);
6426: doldm=matrix(1,nlstate,1,nlstate);
6427:
6428: hstepm=1*YEARM; /* Every year of age */
6429: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6430: agelim = AGEINF;
6431: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
6432: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6433: if (stepm >= YEARM) hstepm=1;
6434: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6435: gradg=matrix(1,npar,1,nlstate);
6436: mgp=matrix(1,npar,1,nlstate);
6437: mgm=matrix(1,npar,1,nlstate);
6438: gp=vector(1,nlstate);
6439: gm=vector(1,nlstate);
6440:
6441: for(theta=1; theta <=npar; theta++){
6442: for(i=1; i<=npar; i++){ /* Computes gradient */
6443: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6444: }
6445: if(mobilavproj > 0 )
6446: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6447: else
6448: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6449: for(i=1;i<=nlstate;i++){
6450: gp[i] = bprlim[i][i];
6451: mgp[theta][i] = bprlim[i][i];
6452: }
6453: for(i=1; i<=npar; i++) /* Computes gradient */
6454: xp[i] = x[i] - (i==theta ?delti[theta]:0);
6455: if(mobilavproj > 0 )
6456: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6457: else
6458: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6459: for(i=1;i<=nlstate;i++){
6460: gm[i] = bprlim[i][i];
6461: mgm[theta][i] = bprlim[i][i];
6462: }
6463: for(i=1;i<=nlstate;i++)
6464: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
6465: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
6466: } /* End theta */
6467:
6468: trgradg =matrix(1,nlstate,1,npar);
6469:
6470: for(j=1; j<=nlstate;j++)
6471: for(theta=1; theta <=npar; theta++)
6472: trgradg[j][theta]=gradg[theta][j];
6473: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6474: /* printf("\nmgm mgp %d ",(int)age); */
6475: /* for(j=1; j<=nlstate;j++){ */
6476: /* printf(" %d ",j); */
6477: /* for(theta=1; theta <=npar; theta++) */
6478: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6479: /* printf("\n "); */
6480: /* } */
6481: /* } */
6482: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6483: /* printf("\n gradg %d ",(int)age); */
6484: /* for(j=1; j<=nlstate;j++){ */
6485: /* printf("%d ",j); */
6486: /* for(theta=1; theta <=npar; theta++) */
6487: /* printf("%d %lf ",theta,gradg[theta][j]); */
6488: /* printf("\n "); */
6489: /* } */
6490: /* } */
6491:
6492: for(i=1;i<=nlstate;i++)
6493: varbpl[i][(int)age] =0.;
6494: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
6495: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6496: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6497: }else{
6498: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6499: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6500: }
6501: for(i=1;i<=nlstate;i++)
6502: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6503:
6504: fprintf(ficresvbl,"%.0f ",age );
6505: if(nresult >=1)
6506: fprintf(ficresvbl,"%d ",nres );
6507: for(i=1; i<=nlstate;i++)
6508: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
6509: fprintf(ficresvbl,"\n");
6510: free_vector(gp,1,nlstate);
6511: free_vector(gm,1,nlstate);
6512: free_matrix(mgm,1,npar,1,nlstate);
6513: free_matrix(mgp,1,npar,1,nlstate);
6514: free_matrix(gradg,1,npar,1,nlstate);
6515: free_matrix(trgradg,1,nlstate,1,npar);
6516: } /* End age */
6517:
6518: free_vector(xp,1,npar);
6519: free_matrix(doldm,1,nlstate,1,npar);
6520: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 6521:
6522: }
6523:
6524: /************ Variance of one-step probabilities ******************/
6525: 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 6526: {
6527: int i, j=0, k1, l1, tj;
6528: int k2, l2, j1, z1;
6529: int k=0, l;
6530: int first=1, first1, first2;
6531: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
6532: double **dnewm,**doldm;
6533: double *xp;
6534: double *gp, *gm;
6535: double **gradg, **trgradg;
6536: double **mu;
6537: double age, cov[NCOVMAX+1];
6538: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
6539: int theta;
6540: char fileresprob[FILENAMELENGTH];
6541: char fileresprobcov[FILENAMELENGTH];
6542: char fileresprobcor[FILENAMELENGTH];
6543: double ***varpij;
6544:
6545: strcpy(fileresprob,"PROB_");
6546: strcat(fileresprob,fileres);
6547: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
6548: printf("Problem with resultfile: %s\n", fileresprob);
6549: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
6550: }
6551: strcpy(fileresprobcov,"PROBCOV_");
6552: strcat(fileresprobcov,fileresu);
6553: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
6554: printf("Problem with resultfile: %s\n", fileresprobcov);
6555: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
6556: }
6557: strcpy(fileresprobcor,"PROBCOR_");
6558: strcat(fileresprobcor,fileresu);
6559: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
6560: printf("Problem with resultfile: %s\n", fileresprobcor);
6561: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
6562: }
6563: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6564: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6565: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6566: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6567: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6568: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6569: pstamp(ficresprob);
6570: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
6571: fprintf(ficresprob,"# Age");
6572: pstamp(ficresprobcov);
6573: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
6574: fprintf(ficresprobcov,"# Age");
6575: pstamp(ficresprobcor);
6576: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
6577: fprintf(ficresprobcor,"# Age");
1.126 brouard 6578:
6579:
1.222 brouard 6580: for(i=1; i<=nlstate;i++)
6581: for(j=1; j<=(nlstate+ndeath);j++){
6582: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
6583: fprintf(ficresprobcov," p%1d-%1d ",i,j);
6584: fprintf(ficresprobcor," p%1d-%1d ",i,j);
6585: }
6586: /* fprintf(ficresprob,"\n");
6587: fprintf(ficresprobcov,"\n");
6588: fprintf(ficresprobcor,"\n");
6589: */
6590: xp=vector(1,npar);
6591: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6592: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6593: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
6594: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
6595: first=1;
6596: fprintf(ficgp,"\n# Routine varprob");
6597: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
6598: fprintf(fichtm,"\n");
6599:
1.288 brouard 6600: fprintf(fichtm,"\n<li><h4> <a href=\"%s\">Matrix of variance-covariance of one-step probabilities (drawings)</a></h4> this page is important in order to visualize confidence intervals and especially correlation between disability and recovery, or more generally, way in and way back. File %s</li>\n",optionfilehtmcov,optionfilehtmcov);
1.222 brouard 6601: 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);
6602: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 6603: and drawn. It helps understanding how is the covariance between two incidences.\
6604: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 6605: 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 6606: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
6607: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
6608: standard deviations wide on each axis. <br>\
6609: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
6610: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
6611: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
6612:
1.222 brouard 6613: cov[1]=1;
6614: /* tj=cptcoveff; */
1.225 brouard 6615: tj = (int) pow(2,cptcoveff);
1.222 brouard 6616: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
6617: j1=0;
1.224 brouard 6618: for(j1=1; j1<=tj;j1++){ /* For each valid combination of covariates or only once*/
1.222 brouard 6619: if (cptcovn>0) {
6620: fprintf(ficresprob, "\n#********** Variable ");
1.225 brouard 6621: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6622: fprintf(ficresprob, "**********\n#\n");
6623: fprintf(ficresprobcov, "\n#********** Variable ");
1.225 brouard 6624: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcov, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6625: fprintf(ficresprobcov, "**********\n#\n");
1.220 brouard 6626:
1.222 brouard 6627: fprintf(ficgp, "\n#********** Variable ");
1.225 brouard 6628: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficgp, " V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6629: fprintf(ficgp, "**********\n#\n");
1.220 brouard 6630:
6631:
1.222 brouard 6632: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
1.225 brouard 6633: for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtm, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6634: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 6635:
1.222 brouard 6636: fprintf(ficresprobcor, "\n#********** Variable ");
1.225 brouard 6637: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcor, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6638: fprintf(ficresprobcor, "**********\n#");
6639: if(invalidvarcomb[j1]){
6640: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
6641: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
6642: continue;
6643: }
6644: }
6645: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
6646: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6647: gp=vector(1,(nlstate)*(nlstate+ndeath));
6648: gm=vector(1,(nlstate)*(nlstate+ndeath));
6649: for (age=bage; age<=fage; age ++){
6650: cov[2]=age;
6651: if(nagesqr==1)
6652: cov[3]= age*age;
6653: for (k=1; k<=cptcovn;k++) {
6654: cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)];
6655: /*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*//* j1 1 2 3 4
6656: * 1 1 1 1 1
6657: * 2 2 1 1 1
6658: * 3 1 2 1 1
6659: */
6660: /* nbcode[1][1]=0 nbcode[1][2]=1;*/
6661: }
6662: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; */
6663: for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
6664: for (k=1; k<=cptcovprod;k++)
6665: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.220 brouard 6666:
6667:
1.222 brouard 6668: for(theta=1; theta <=npar; theta++){
6669: for(i=1; i<=npar; i++)
6670: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 6671:
1.222 brouard 6672: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 6673:
1.222 brouard 6674: k=0;
6675: for(i=1; i<= (nlstate); i++){
6676: for(j=1; j<=(nlstate+ndeath);j++){
6677: k=k+1;
6678: gp[k]=pmmij[i][j];
6679: }
6680: }
1.220 brouard 6681:
1.222 brouard 6682: for(i=1; i<=npar; i++)
6683: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 6684:
1.222 brouard 6685: pmij(pmmij,cov,ncovmodel,xp,nlstate);
6686: k=0;
6687: for(i=1; i<=(nlstate); i++){
6688: for(j=1; j<=(nlstate+ndeath);j++){
6689: k=k+1;
6690: gm[k]=pmmij[i][j];
6691: }
6692: }
1.220 brouard 6693:
1.222 brouard 6694: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
6695: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
6696: }
1.126 brouard 6697:
1.222 brouard 6698: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
6699: for(theta=1; theta <=npar; theta++)
6700: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 6701:
1.222 brouard 6702: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
6703: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 6704:
1.222 brouard 6705: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 6706:
1.222 brouard 6707: k=0;
6708: for(i=1; i<=(nlstate); i++){
6709: for(j=1; j<=(nlstate+ndeath);j++){
6710: k=k+1;
6711: mu[k][(int) age]=pmmij[i][j];
6712: }
6713: }
6714: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
6715: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
6716: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 6717:
1.222 brouard 6718: /*printf("\n%d ",(int)age);
6719: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6720: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6721: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6722: }*/
1.220 brouard 6723:
1.222 brouard 6724: fprintf(ficresprob,"\n%d ",(int)age);
6725: fprintf(ficresprobcov,"\n%d ",(int)age);
6726: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 6727:
1.222 brouard 6728: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
6729: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
6730: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6731: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
6732: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
6733: }
6734: i=0;
6735: for (k=1; k<=(nlstate);k++){
6736: for (l=1; l<=(nlstate+ndeath);l++){
6737: i++;
6738: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
6739: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
6740: for (j=1; j<=i;j++){
6741: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
6742: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
6743: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
6744: }
6745: }
6746: }/* end of loop for state */
6747: } /* end of loop for age */
6748: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
6749: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
6750: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
6751: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
6752:
6753: /* Confidence intervalle of pij */
6754: /*
6755: fprintf(ficgp,"\nunset parametric;unset label");
6756: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
6757: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
6758: 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);
6759: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
6760: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
6761: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
6762: */
6763:
6764: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
6765: first1=1;first2=2;
6766: for (k2=1; k2<=(nlstate);k2++){
6767: for (l2=1; l2<=(nlstate+ndeath);l2++){
6768: if(l2==k2) continue;
6769: j=(k2-1)*(nlstate+ndeath)+l2;
6770: for (k1=1; k1<=(nlstate);k1++){
6771: for (l1=1; l1<=(nlstate+ndeath);l1++){
6772: if(l1==k1) continue;
6773: i=(k1-1)*(nlstate+ndeath)+l1;
6774: if(i<=j) continue;
6775: for (age=bage; age<=fage; age ++){
6776: if ((int)age %5==0){
6777: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
6778: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
6779: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
6780: mu1=mu[i][(int) age]/stepm*YEARM ;
6781: mu2=mu[j][(int) age]/stepm*YEARM;
6782: c12=cv12/sqrt(v1*v2);
6783: /* Computing eigen value of matrix of covariance */
6784: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6785: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6786: if ((lc2 <0) || (lc1 <0) ){
6787: if(first2==1){
6788: first1=0;
6789: 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);
6790: }
6791: 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);
6792: /* lc1=fabs(lc1); */ /* If we want to have them positive */
6793: /* lc2=fabs(lc2); */
6794: }
1.220 brouard 6795:
1.222 brouard 6796: /* Eigen vectors */
1.280 brouard 6797: if(1+(v1-lc1)*(v1-lc1)/cv12/cv12 <1.e-5){
6798: printf(" Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
6799: fprintf(ficlog," Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
6800: v11=(1./sqrt(fabs(1+(v1-lc1)*(v1-lc1)/cv12/cv12)));
6801: }else
6802: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
1.222 brouard 6803: /*v21=sqrt(1.-v11*v11); *//* error */
6804: v21=(lc1-v1)/cv12*v11;
6805: v12=-v21;
6806: v22=v11;
6807: tnalp=v21/v11;
6808: if(first1==1){
6809: first1=0;
6810: 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);
6811: }
6812: 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);
6813: /*printf(fignu*/
6814: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
6815: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
6816: if(first==1){
6817: first=0;
6818: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
6819: fprintf(ficgp,"\nset parametric;unset label");
6820: 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);
6821: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 6822: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 6823: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 6824: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 6825: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
6826: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6827: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6828: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
6829: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6830: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
6831: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
6832: 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 6833: mu1,std,v11,sqrt(fabs(lc1)),v12,sqrt(fabs(lc2)), \
6834: mu2,std,v21,sqrt(fabs(lc1)),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 6835: }else{
6836: first=0;
6837: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
6838: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
6839: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
6840: 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 6841: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
6842: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 6843: }/* if first */
6844: } /* age mod 5 */
6845: } /* end loop age */
6846: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6847: first=1;
6848: } /*l12 */
6849: } /* k12 */
6850: } /*l1 */
6851: }/* k1 */
6852: } /* loop on combination of covariates j1 */
6853: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
6854: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
6855: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6856: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
6857: free_vector(xp,1,npar);
6858: fclose(ficresprob);
6859: fclose(ficresprobcov);
6860: fclose(ficresprobcor);
6861: fflush(ficgp);
6862: fflush(fichtmcov);
6863: }
1.126 brouard 6864:
6865:
6866: /******************* Printing html file ***********/
1.201 brouard 6867: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 6868: int lastpass, int stepm, int weightopt, char model[],\
6869: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.296 brouard 6870: int popforecast, int mobilav, int prevfcast, int mobilavproj, int prevbcast, int estepm , \
6871: double jprev1, double mprev1,double anprev1, double dateprev1, double dateprojd, double dateback1, \
6872: double jprev2, double mprev2,double anprev2, double dateprev2, double dateprojf, double dateback2){
1.237 brouard 6873: int jj1, k1, i1, cpt, k4, nres;
1.126 brouard 6874:
6875: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
6876: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
6877: </ul>");
1.237 brouard 6878: fprintf(fichtm,"<ul><li> model=1+age+%s\n \
6879: </ul>", model);
1.214 brouard 6880: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
6881: 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",
6882: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
6883: 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 6884: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
6885: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 6886: fprintf(fichtm,"\
6887: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 6888: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 6889: fprintf(fichtm,"\
1.217 brouard 6890: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
6891: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
6892: fprintf(fichtm,"\
1.288 brouard 6893: - Period (forward) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 6894: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 6895: fprintf(fichtm,"\
1.288 brouard 6896: - Backward prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.217 brouard 6897: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
6898: fprintf(fichtm,"\
1.211 brouard 6899: - (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 6900: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 6901: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 6902: if(prevfcast==1){
6903: fprintf(fichtm,"\
6904: - Prevalence projections by age and states: \
1.201 brouard 6905: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 6906: }
1.126 brouard 6907:
6908:
1.225 brouard 6909: m=pow(2,cptcoveff);
1.222 brouard 6910: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 6911:
1.264 brouard 6912: fprintf(fichtm," \n<ul><li><b>Graphs</b></li><p>");
6913:
6914: jj1=0;
6915:
6916: fprintf(fichtm," \n<ul>");
6917: for(nres=1; nres <= nresult; nres++) /* For each resultline */
6918: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
6919: if(m != 1 && TKresult[nres]!= k1)
6920: continue;
6921: jj1++;
6922: if (cptcovn > 0) {
6923: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
6924: for (cpt=1; cpt<=cptcoveff;cpt++){
6925: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6926: }
6927: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6928: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
6929: }
6930: fprintf(fichtm,"\">");
6931:
6932: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
6933: fprintf(fichtm,"************ Results for covariates");
6934: for (cpt=1; cpt<=cptcoveff;cpt++){
6935: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6936: }
6937: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6938: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6939: }
6940: if(invalidvarcomb[k1]){
6941: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
6942: continue;
6943: }
6944: fprintf(fichtm,"</a></li>");
6945: } /* cptcovn >0 */
6946: }
6947: fprintf(fichtm," \n</ul>");
6948:
1.222 brouard 6949: jj1=0;
1.237 brouard 6950:
6951: for(nres=1; nres <= nresult; nres++) /* For each resultline */
1.241 brouard 6952: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
1.253 brouard 6953: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 6954: continue;
1.220 brouard 6955:
1.222 brouard 6956: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
6957: jj1++;
6958: if (cptcovn > 0) {
1.264 brouard 6959: fprintf(fichtm,"\n<p><a name=\"rescov");
6960: for (cpt=1; cpt<=cptcoveff;cpt++){
6961: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6962: }
6963: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6964: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
6965: }
6966: fprintf(fichtm,"\"</a>");
6967:
1.222 brouard 6968: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 6969: for (cpt=1; cpt<=cptcoveff;cpt++){
1.237 brouard 6970: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6971: printf(" V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);fflush(stdout);
6972: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
6973: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 6974: }
1.237 brouard 6975: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6976: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6977: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);fflush(stdout);
6978: }
6979:
1.230 brouard 6980: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.222 brouard 6981: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
6982: if(invalidvarcomb[k1]){
6983: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
6984: printf("\nCombination (%d) ignored because no cases \n",k1);
6985: continue;
6986: }
6987: }
6988: /* aij, bij */
1.259 brouard 6989: 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 6990: <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 6991: /* Pij */
1.241 brouard 6992: 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> \
6993: <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 6994: /* Quasi-incidences */
6995: 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 6996: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 6997: 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 6998: 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> \
6999: <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 7000: /* Survival functions (period) in state j */
7001: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 7002: fprintf(fichtm,"<br>\n- Survival functions in state %d. And probability to be observed in state %d being in state (1 to %d) at different ages. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br> \
1.241 brouard 7003: <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 7004: }
7005: /* State specific survival functions (period) */
7006: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 7007: fprintf(fichtm,"<br>\n- Survival functions in state %d and in any other live state (total).\
7008: And probability to be observed in various states (up to %d) being in state %d at different ages. \
1.283 brouard 7009: <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 7010: }
1.288 brouard 7011: /* Period (forward stable) prevalence in each health state */
1.222 brouard 7012: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 7013: 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> \
7014: <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 7015: }
1.296 brouard 7016: if(prevbcast==1){
1.288 brouard 7017: /* Backward prevalence in each health state */
1.222 brouard 7018: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 7019: 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 7020: <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 7021: }
1.217 brouard 7022: }
1.222 brouard 7023: if(prevfcast==1){
1.288 brouard 7024: /* Projection of prevalence up to period (forward stable) prevalence in each health state */
1.222 brouard 7025: for(cpt=1; cpt<=nlstate;cpt++){
1.288 brouard 7026: fprintf(fichtm,"<br>\n- Projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), from year %.1f up to year %.1f tending to period (stable) forward prevalence in state %d. Or probability to be in state %d being in an observed weighted state (from 1 to %d). <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br> \
1.296 brouard 7027: <img src=\"%s_%d-%d-%d.svg\">", dateprev1, dateprev2, mobilavproj, dateprojd, dateprojf, cpt, cpt, nlstate, subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.222 brouard 7028: }
7029: }
1.296 brouard 7030: if(prevbcast==1){
1.268 brouard 7031: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
7032: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 7033: fprintf(fichtm,"<br>\n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), \
7034: 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 \
7035: 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) \
7036: with weights corresponding to observed prevalence at different ages. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br> \
7037: <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 7038: }
7039: }
1.220 brouard 7040:
1.222 brouard 7041: for(cpt=1; cpt<=nlstate;cpt++) {
1.241 brouard 7042: 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> \
7043: <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 7044: }
7045: /* } /\* end i1 *\/ */
7046: }/* End k1 */
7047: fprintf(fichtm,"</ul>");
1.126 brouard 7048:
1.222 brouard 7049: fprintf(fichtm,"\
1.126 brouard 7050: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 7051: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 7052: - 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 7053: But because parameters are usually highly correlated (a higher incidence of disability \
7054: and a higher incidence of recovery can give very close observed transition) it might \
7055: be very useful to look not only at linear confidence intervals estimated from the \
7056: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
7057: (parameters) of the logistic regression, it might be more meaningful to visualize the \
7058: covariance matrix of the one-step probabilities. \
7059: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 7060:
1.222 brouard 7061: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
7062: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
7063: fprintf(fichtm,"\
1.126 brouard 7064: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 7065: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 7066:
1.222 brouard 7067: fprintf(fichtm,"\
1.126 brouard 7068: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 7069: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
7070: fprintf(fichtm,"\
1.126 brouard 7071: - 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): \
7072: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 7073: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 7074: fprintf(fichtm,"\
1.126 brouard 7075: - (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): \
7076: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 7077: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 7078: fprintf(fichtm,"\
1.288 brouard 7079: - Variances and covariances of health expectancies by age. Status (i) based health expectancies (in state j), e<sup>ij</sup> are weighted by the forward (period) prevalences in each state i (if popbased=1, an additional computation is done using the cross-sectional prevalences, i.e population based) (estepm=%d months): <a href=\"%s\">%s</a><br>\n",
1.222 brouard 7080: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
7081: fprintf(fichtm,"\
1.128 brouard 7082: - 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 7083: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
7084: fprintf(fichtm,"\
1.288 brouard 7085: - Standard deviation of forward (period) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 7086: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 7087:
7088: /* if(popforecast==1) fprintf(fichtm,"\n */
7089: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
7090: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
7091: /* <br>",fileres,fileres,fileres,fileres); */
7092: /* else */
7093: /* 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 7094: fflush(fichtm);
7095: fprintf(fichtm," <ul><li><b>Graphs</b></li><p>");
1.126 brouard 7096:
1.225 brouard 7097: m=pow(2,cptcoveff);
1.222 brouard 7098: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 7099:
1.222 brouard 7100: jj1=0;
1.237 brouard 7101:
1.241 brouard 7102: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.222 brouard 7103: for(k1=1; k1<=m;k1++){
1.253 brouard 7104: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7105: continue;
1.222 brouard 7106: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
7107: jj1++;
1.126 brouard 7108: if (cptcovn > 0) {
7109: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 7110: for (cpt=1; cpt<=cptcoveff;cpt++) /**< cptcoveff number of variables */
1.237 brouard 7111: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);
7112: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
7113: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7114: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7115: }
7116:
1.126 brouard 7117: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 7118:
1.222 brouard 7119: if(invalidvarcomb[k1]){
7120: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
7121: continue;
7122: }
1.126 brouard 7123: }
7124: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 7125: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.241 brouard 7126: 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 7127: <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 7128: }
7129: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.128 brouard 7130: health expectancies in states (1) and (2). If popbased=1 the smooth (due to the model) \
7131: true period expectancies (those weighted with period prevalences are also\
7132: drawn in addition to the population based expectancies computed using\
1.241 brouard 7133: observed and cahotic prevalences: <a href=\"%s_%d-%d.svg\">%s_%d-%d.svg</a>\n<br>\
7134: <img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 7135: /* } /\* end i1 *\/ */
7136: }/* End k1 */
1.241 brouard 7137: }/* End nres */
1.222 brouard 7138: fprintf(fichtm,"</ul>");
7139: fflush(fichtm);
1.126 brouard 7140: }
7141:
7142: /******************* Gnuplot file **************/
1.296 brouard 7143: void printinggnuplot(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double bage, double fage , int prevfcast, int prevbcast, char pathc[], double p[], int offyear, int offbyear){
1.126 brouard 7144:
7145: char dirfileres[132],optfileres[132];
1.264 brouard 7146: char gplotcondition[132], gplotlabel[132];
1.237 brouard 7147: 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 7148: int lv=0, vlv=0, kl=0;
1.130 brouard 7149: int ng=0;
1.201 brouard 7150: int vpopbased;
1.223 brouard 7151: int ioffset; /* variable offset for columns */
1.270 brouard 7152: int iyearc=1; /* variable column for year of projection */
7153: int iagec=1; /* variable column for age of projection */
1.235 brouard 7154: int nres=0; /* Index of resultline */
1.266 brouard 7155: int istart=1; /* For starting graphs in projections */
1.219 brouard 7156:
1.126 brouard 7157: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
7158: /* printf("Problem with file %s",optionfilegnuplot); */
7159: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
7160: /* } */
7161:
7162: /*#ifdef windows */
7163: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 7164: /*#endif */
1.225 brouard 7165: m=pow(2,cptcoveff);
1.126 brouard 7166:
1.274 brouard 7167: /* diagram of the model */
7168: fprintf(ficgp,"\n#Diagram of the model \n");
7169: fprintf(ficgp,"\ndelta=0.03;delta2=0.07;unset arrow;\n");
7170: fprintf(ficgp,"yoff=(%d > 2? 0:1);\n",nlstate);
7171: 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);
7172:
7173: 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);
7174: fprintf(ficgp,"\n#show arrow\nunset label\n");
7175: 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);
7176: fprintf(ficgp,"\nset label %d+1 sprintf(\"State %%d\",%d+1) center at 0.,0. font \"helvetica, 16\" tc rgbcolor \"red\"\n",nlstate,nlstate);
7177: fprintf(ficgp,"\n#show label\nunset border;unset xtics; unset ytics;\n");
7178: fprintf(ficgp,"\n\nset ter svg size 640, 480;set out \"%s_.svg\" \n",subdirf2(optionfilefiname,"D_"));
7179: fprintf(ficgp,"unset log y; plot [-1.2:1.2][yoff-1.2:1.2] 1/0 not; set out;reset;\n");
7180:
1.202 brouard 7181: /* Contribution to likelihood */
7182: /* Plot the probability implied in the likelihood */
1.223 brouard 7183: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
7184: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
7185: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
7186: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 7187: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 7188: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
7189: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 7190: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
7191: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
7192: 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));
7193: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
7194: 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));
7195: for (i=1; i<= nlstate ; i ++) {
7196: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
7197: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
7198: 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);
7199: for (j=2; j<= nlstate+ndeath ; j ++) {
7200: 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);
7201: }
7202: fprintf(ficgp,";\nset out; unset ylabel;\n");
7203: }
7204: /* 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 */
7205: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
7206: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
7207: fprintf(ficgp,"\nset out;unset log\n");
7208: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 7209:
1.126 brouard 7210: strcpy(dirfileres,optionfilefiname);
7211: strcpy(optfileres,"vpl");
1.223 brouard 7212: /* 1eme*/
1.238 brouard 7213: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
7214: for (k1=1; k1<= m ; k1 ++){ /* For each valid combination of covariate */
1.236 brouard 7215: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.238 brouard 7216: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.253 brouard 7217: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7218: continue;
7219: /* We are interested in selected combination by the resultline */
1.246 brouard 7220: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.288 brouard 7221: fprintf(ficgp,"\n# 1st: Forward (stable period) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 7222: strcpy(gplotlabel,"(");
1.238 brouard 7223: for (k=1; k<=cptcoveff; k++){ /* For each covariate k get corresponding value lv for combination k1 */
7224: lv= decodtabm(k1,k,cptcoveff); /* Should be the value of the covariate corresponding to k1 combination */
7225: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7226: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7227: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7228: vlv= nbcode[Tvaraff[k]][lv]; /* vlv is the value of the covariate lv, 0 or 1 */
7229: /* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv */
1.246 brouard 7230: /* printf(" V%d=%d ",Tvaraff[k],vlv); */
1.238 brouard 7231: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7232: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7233: }
7234: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.246 brouard 7235: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 7236: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7237: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7238: }
7239: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 7240: /* printf("\n#\n"); */
1.238 brouard 7241: fprintf(ficgp,"\n#\n");
7242: if(invalidvarcomb[k1]){
1.260 brouard 7243: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 7244: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7245: continue;
7246: }
1.235 brouard 7247:
1.241 brouard 7248: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
7249: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.276 brouard 7250: /* fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel); */
7251: fprintf(ficgp,"set title \"Alive state %d %s\" font \"Helvetica,12\"\n",cpt,gplotlabel);
1.260 brouard 7252: 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);
7253: /* 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); */
7254: /* k1-1 error should be nres-1*/
1.238 brouard 7255: for (i=1; i<= nlstate ; i ++) {
7256: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7257: else fprintf(ficgp," %%*lf (%%*lf)");
7258: }
1.288 brouard 7259: fprintf(ficgp,"\" t\"Forward prevalence\" w l lt 0,\"%s\" every :::%d::%d u 1:($2==%d ? $3+1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 7260: for (i=1; i<= nlstate ; i ++) {
7261: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7262: else fprintf(ficgp," %%*lf (%%*lf)");
7263: }
1.260 brouard 7264: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 7265: for (i=1; i<= nlstate ; i ++) {
7266: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7267: else fprintf(ficgp," %%*lf (%%*lf)");
7268: }
1.265 brouard 7269: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
7270:
7271: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
7272: if(cptcoveff ==0){
1.271 brouard 7273: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+3*(cpt-1), cpt );
1.265 brouard 7274: }else{
7275: kl=0;
7276: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7277: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7278: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7279: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7280: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7281: vlv= nbcode[Tvaraff[k]][lv];
7282: kl++;
7283: /* 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 *\/ */
7284: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7285: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7286: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7287: if(k==cptcoveff){
7288: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
7289: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
7290: }else{
7291: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7292: kl++;
7293: }
7294: } /* end covariate */
7295: } /* end if no covariate */
7296:
1.296 brouard 7297: if(prevbcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
1.238 brouard 7298: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 7299: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 7300: if(cptcoveff ==0){
1.245 brouard 7301: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 7302: }else{
7303: kl=0;
7304: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7305: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7306: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7307: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7308: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7309: vlv= nbcode[Tvaraff[k]][lv];
1.223 brouard 7310: kl++;
1.238 brouard 7311: /* 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 *\/ */
7312: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7313: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7314: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7315: if(k==cptcoveff){
1.245 brouard 7316: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 7317: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 7318: }else{
7319: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7320: kl++;
7321: }
7322: } /* end covariate */
7323: } /* end if no covariate */
1.296 brouard 7324: if(prevbcast == 1){
1.268 brouard 7325: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
7326: /* k1-1 error should be nres-1*/
7327: for (i=1; i<= nlstate ; i ++) {
7328: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7329: else fprintf(ficgp," %%*lf (%%*lf)");
7330: }
1.271 brouard 7331: 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 7332: for (i=1; i<= nlstate ; i ++) {
7333: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7334: else fprintf(ficgp," %%*lf (%%*lf)");
7335: }
1.276 brouard 7336: 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 7337: for (i=1; i<= nlstate ; i ++) {
7338: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7339: else fprintf(ficgp," %%*lf (%%*lf)");
7340: }
1.274 brouard 7341: fprintf(ficgp,"\" t\"\" w l lt 4");
1.268 brouard 7342: } /* end if backprojcast */
1.296 brouard 7343: } /* end if prevbcast */
1.276 brouard 7344: /* fprintf(ficgp,"\nset out ;unset label;\n"); */
7345: fprintf(ficgp,"\nset out ;unset title;\n");
1.238 brouard 7346: } /* nres */
1.201 brouard 7347: } /* k1 */
7348: } /* cpt */
1.235 brouard 7349:
7350:
1.126 brouard 7351: /*2 eme*/
1.238 brouard 7352: for (k1=1; k1<= m ; k1 ++){
7353: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7354: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7355: continue;
7356: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 7357: strcpy(gplotlabel,"(");
1.238 brouard 7358: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.225 brouard 7359: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
1.223 brouard 7360: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7361: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7362: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7363: vlv= nbcode[Tvaraff[k]][lv];
7364: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7365: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7366: }
1.237 brouard 7367: /* for(k=1; k <= ncovds; k++){ */
1.236 brouard 7368: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 7369: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.236 brouard 7370: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7371: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7372: }
1.264 brouard 7373: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7374: fprintf(ficgp,"\n#\n");
1.223 brouard 7375: if(invalidvarcomb[k1]){
7376: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7377: continue;
7378: }
1.219 brouard 7379:
1.241 brouard 7380: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 7381: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 7382: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
7383: if(vpopbased==0){
1.238 brouard 7384: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 7385: }else
1.238 brouard 7386: fprintf(ficgp,"\nreplot ");
7387: for (i=1; i<= nlstate+1 ; i ++) {
7388: k=2*i;
1.261 brouard 7389: 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 7390: for (j=1; j<= nlstate+1 ; j ++) {
7391: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7392: else fprintf(ficgp," %%*lf (%%*lf)");
7393: }
7394: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
7395: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
1.261 brouard 7396: 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 7397: for (j=1; j<= nlstate+1 ; j ++) {
7398: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7399: else fprintf(ficgp," %%*lf (%%*lf)");
7400: }
7401: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 7402: 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 7403: for (j=1; j<= nlstate+1 ; j ++) {
7404: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7405: else fprintf(ficgp," %%*lf (%%*lf)");
7406: }
7407: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
7408: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
7409: } /* state */
7410: } /* vpopbased */
1.264 brouard 7411: 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 7412: } /* end nres */
7413: } /* k1 end 2 eme*/
7414:
7415:
7416: /*3eme*/
7417: for (k1=1; k1<= m ; k1 ++){
7418: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7419: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7420: continue;
7421:
7422: for (cpt=1; cpt<= nlstate ; cpt ++) {
1.261 brouard 7423: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 7424: strcpy(gplotlabel,"(");
1.238 brouard 7425: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7426: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7427: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7428: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7429: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7430: vlv= nbcode[Tvaraff[k]][lv];
7431: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7432: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7433: }
7434: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7435: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7436: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7437: }
1.264 brouard 7438: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7439: fprintf(ficgp,"\n#\n");
7440: if(invalidvarcomb[k1]){
7441: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7442: continue;
7443: }
7444:
7445: /* k=2+nlstate*(2*cpt-2); */
7446: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 7447: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 7448: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 7449: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 7450: 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 7451: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7452: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7453: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
7454: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7455: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7456: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 7457:
1.238 brouard 7458: */
7459: for (i=1; i< nlstate ; i ++) {
1.261 brouard 7460: 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 7461: /* 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 7462:
1.238 brouard 7463: }
1.261 brouard 7464: 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 7465: }
1.264 brouard 7466: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 7467: } /* end nres */
7468: } /* end kl 3eme */
1.126 brouard 7469:
1.223 brouard 7470: /* 4eme */
1.201 brouard 7471: /* Survival functions (period) from state i in state j by initial state i */
1.238 brouard 7472: for (k1=1; k1<=m; k1++){ /* For each covariate and each value */
7473: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7474: if(m != 1 && TKresult[nres]!= k1)
1.223 brouard 7475: continue;
1.238 brouard 7476: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 7477: strcpy(gplotlabel,"(");
1.238 brouard 7478: fprintf(ficgp,"\n#\n#\n# Survival functions in state j : 'LIJ_' files, cov=%d state=%d",k1, cpt);
7479: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7480: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7481: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7482: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7483: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7484: vlv= nbcode[Tvaraff[k]][lv];
7485: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7486: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7487: }
7488: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7489: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7490: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7491: }
1.264 brouard 7492: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7493: fprintf(ficgp,"\n#\n");
7494: if(invalidvarcomb[k1]){
7495: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7496: continue;
1.223 brouard 7497: }
1.238 brouard 7498:
1.241 brouard 7499: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 7500: 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 7501: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7502: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7503: k=3;
7504: for (i=1; i<= nlstate ; i ++){
7505: if(i==1){
7506: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7507: }else{
7508: fprintf(ficgp,", '' ");
7509: }
7510: l=(nlstate+ndeath)*(i-1)+1;
7511: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7512: for (j=2; j<= nlstate+ndeath ; j ++)
7513: fprintf(ficgp,"+$%d",k+l+j-1);
7514: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
7515: } /* nlstate */
1.264 brouard 7516: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7517: } /* end cpt state*/
7518: } /* end nres */
7519: } /* end covariate k1 */
7520:
1.220 brouard 7521: /* 5eme */
1.201 brouard 7522: /* Survival functions (period) from state i in state j by final state j */
1.238 brouard 7523: for (k1=1; k1<= m ; k1++){ /* For each covariate combination if any */
7524: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7525: if(m != 1 && TKresult[nres]!= k1)
1.227 brouard 7526: continue;
1.238 brouard 7527: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 7528: strcpy(gplotlabel,"(");
1.238 brouard 7529: 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);
7530: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7531: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7532: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7533: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7534: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7535: vlv= nbcode[Tvaraff[k]][lv];
7536: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7537: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7538: }
7539: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7540: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7541: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7542: }
1.264 brouard 7543: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7544: fprintf(ficgp,"\n#\n");
7545: if(invalidvarcomb[k1]){
7546: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7547: continue;
7548: }
1.227 brouard 7549:
1.241 brouard 7550: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 7551: fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
1.238 brouard 7552: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7553: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7554: k=3;
7555: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7556: if(j==1)
7557: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7558: else
7559: fprintf(ficgp,", '' ");
7560: l=(nlstate+ndeath)*(cpt-1) +j;
7561: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
7562: /* for (i=2; i<= nlstate+ndeath ; i ++) */
7563: /* fprintf(ficgp,"+$%d",k+l+i-1); */
7564: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
7565: } /* nlstate */
7566: fprintf(ficgp,", '' ");
7567: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
7568: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7569: l=(nlstate+ndeath)*(cpt-1) +j;
7570: if(j < nlstate)
7571: fprintf(ficgp,"$%d +",k+l);
7572: else
7573: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
7574: }
1.264 brouard 7575: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7576: } /* end cpt state*/
7577: } /* end covariate */
7578: } /* end nres */
1.227 brouard 7579:
1.220 brouard 7580: /* 6eme */
1.202 brouard 7581: /* CV preval stable (period) for each covariate */
1.237 brouard 7582: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7583: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7584: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7585: continue;
1.255 brouard 7586: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 7587: strcpy(gplotlabel,"(");
1.288 brouard 7588: fprintf(ficgp,"\n#\n#\n#CV preval stable (forward): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.225 brouard 7589: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.227 brouard 7590: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7591: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7592: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7593: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7594: vlv= nbcode[Tvaraff[k]][lv];
7595: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7596: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7597: }
1.237 brouard 7598: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7599: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7600: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7601: }
1.264 brouard 7602: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7603: fprintf(ficgp,"\n#\n");
1.223 brouard 7604: if(invalidvarcomb[k1]){
1.227 brouard 7605: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7606: continue;
1.223 brouard 7607: }
1.227 brouard 7608:
1.241 brouard 7609: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 7610: 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 7611: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7612: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 7613: k=3; /* Offset */
1.255 brouard 7614: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 7615: if(i==1)
7616: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7617: else
7618: fprintf(ficgp,", '' ");
1.255 brouard 7619: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7620: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7621: for (j=2; j<= nlstate ; j ++)
7622: fprintf(ficgp,"+$%d",k+l+j-1);
7623: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 7624: } /* nlstate */
1.264 brouard 7625: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 7626: } /* end cpt state*/
7627: } /* end covariate */
1.227 brouard 7628:
7629:
1.220 brouard 7630: /* 7eme */
1.296 brouard 7631: if(prevbcast == 1){
1.288 brouard 7632: /* CV backward prevalence for each covariate */
1.237 brouard 7633: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7634: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7635: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7636: continue;
1.268 brouard 7637: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 7638: strcpy(gplotlabel,"(");
1.288 brouard 7639: fprintf(ficgp,"\n#\n#\n#CV Backward stable prevalence: 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 7640: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7641: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7642: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7643: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
1.223 brouard 7644: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.227 brouard 7645: vlv= nbcode[Tvaraff[k]][lv];
7646: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7647: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 7648: }
1.237 brouard 7649: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7650: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7651: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7652: }
1.264 brouard 7653: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 7654: fprintf(ficgp,"\n#\n");
7655: if(invalidvarcomb[k1]){
7656: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7657: continue;
7658: }
7659:
1.241 brouard 7660: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 7661: 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 7662: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7663: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 7664: k=3; /* Offset */
1.268 brouard 7665: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 7666: if(i==1)
7667: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
7668: else
7669: fprintf(ficgp,", '' ");
7670: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 7671: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7672: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
7673: /* 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 7674: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 7675: /* for (j=2; j<= nlstate ; j ++) */
7676: /* fprintf(ficgp,"+$%d",k+l+j-1); */
7677: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 7678: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 7679: } /* nlstate */
1.264 brouard 7680: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 7681: } /* end cpt state*/
7682: } /* end covariate */
1.296 brouard 7683: } /* End if prevbcast */
1.218 brouard 7684:
1.223 brouard 7685: /* 8eme */
1.218 brouard 7686: if(prevfcast==1){
1.288 brouard 7687: /* Projection from cross-sectional to forward stable (period) prevalence for each covariate */
1.218 brouard 7688:
1.237 brouard 7689: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7690: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7691: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7692: continue;
1.211 brouard 7693: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 7694: strcpy(gplotlabel,"(");
1.288 brouard 7695: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to forward stable prevalence (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 7696: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7697: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7698: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7699: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7700: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7701: vlv= nbcode[Tvaraff[k]][lv];
7702: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7703: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 7704: }
1.237 brouard 7705: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7706: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7707: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7708: }
1.264 brouard 7709: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 7710: fprintf(ficgp,"\n#\n");
7711: if(invalidvarcomb[k1]){
7712: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7713: continue;
7714: }
7715:
7716: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 7717: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 7718: 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 7719: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 7720: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 7721:
7722: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
7723: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
7724: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
7725: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 7726: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7727: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7728: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7729: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 7730: if(i==istart){
1.227 brouard 7731: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
7732: }else{
7733: fprintf(ficgp,",\\\n '' ");
7734: }
7735: if(cptcoveff ==0){ /* No covariate */
7736: ioffset=2; /* Age is in 2 */
7737: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7738: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7739: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7740: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7741: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 7742: if(i==nlstate+1){
1.270 brouard 7743: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 7744: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
7745: fprintf(ficgp,",\\\n '' ");
7746: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 7747: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 7748: offyear, \
1.268 brouard 7749: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 7750: }else
1.227 brouard 7751: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
7752: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
7753: }else{ /* more than 2 covariates */
1.270 brouard 7754: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
7755: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7756: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7757: iyearc=ioffset-1;
7758: iagec=ioffset;
1.227 brouard 7759: fprintf(ficgp," u %d:(",ioffset);
7760: kl=0;
7761: strcpy(gplotcondition,"(");
7762: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
7763: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
7764: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7765: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7766: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7767: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
7768: kl++;
7769: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
7770: kl++;
7771: if(k <cptcoveff && cptcoveff>1)
7772: sprintf(gplotcondition+strlen(gplotcondition)," && ");
7773: }
7774: strcpy(gplotcondition+strlen(gplotcondition),")");
7775: /* 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 *\/ */
7776: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7777: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7778: /* '' 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*/
7779: if(i==nlstate+1){
1.270 brouard 7780: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
7781: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 7782: fprintf(ficgp,",\\\n '' ");
1.270 brouard 7783: fprintf(ficgp," u %d:(",iagec);
7784: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
7785: iyearc, iagec, offyear, \
7786: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 7787: /* '' 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 7788: }else{
7789: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
7790: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
7791: }
7792: } /* end if covariate */
7793: } /* nlstate */
1.264 brouard 7794: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 7795: } /* end cpt state*/
7796: } /* end covariate */
7797: } /* End if prevfcast */
1.227 brouard 7798:
1.296 brouard 7799: if(prevbcast==1){
1.268 brouard 7800: /* Back projection from cross-sectional to stable (mixed) for each covariate */
7801:
7802: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7803: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
7804: if(m != 1 && TKresult[nres]!= k1)
7805: continue;
7806: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
7807: strcpy(gplotlabel,"(");
7808: fprintf(ficgp,"\n#\n#\n#Back projection of prevalence to stable (mixed) back prevalence: 'BPROJ_' files, covariatecombination#=%d originstate=%d",k1, cpt);
7809: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7810: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7811: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7812: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7813: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7814: vlv= nbcode[Tvaraff[k]][lv];
7815: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
7816: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
7817: }
7818: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7819: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7820: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7821: }
7822: strcpy(gplotlabel+strlen(gplotlabel),")");
7823: fprintf(ficgp,"\n#\n");
7824: if(invalidvarcomb[k1]){
7825: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7826: continue;
7827: }
7828:
7829: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
7830: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
7831: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
7832: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
7833: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7834:
7835: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
7836: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
7837: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
7838: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
7839: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7840: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7841: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7842: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7843: if(i==istart){
7844: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
7845: }else{
7846: fprintf(ficgp,",\\\n '' ");
7847: }
7848: if(cptcoveff ==0){ /* No covariate */
7849: ioffset=2; /* Age is in 2 */
7850: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7851: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7852: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7853: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7854: fprintf(ficgp," u %d:(", ioffset);
7855: if(i==nlstate+1){
1.270 brouard 7856: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 7857: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
7858: fprintf(ficgp,",\\\n '' ");
7859: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 7860: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 7861: offbyear, \
7862: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
7863: }else
7864: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
7865: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
7866: }else{ /* more than 2 covariates */
1.270 brouard 7867: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
7868: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7869: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7870: iyearc=ioffset-1;
7871: iagec=ioffset;
1.268 brouard 7872: fprintf(ficgp," u %d:(",ioffset);
7873: kl=0;
7874: strcpy(gplotcondition,"(");
7875: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
7876: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
7877: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7878: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7879: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7880: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
7881: kl++;
7882: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
7883: kl++;
7884: if(k <cptcoveff && cptcoveff>1)
7885: sprintf(gplotcondition+strlen(gplotcondition)," && ");
7886: }
7887: strcpy(gplotcondition+strlen(gplotcondition),")");
7888: /* 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 *\/ */
7889: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7890: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7891: /* '' 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*/
7892: if(i==nlstate+1){
1.270 brouard 7893: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
7894: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 7895: fprintf(ficgp,",\\\n '' ");
1.270 brouard 7896: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 7897: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 brouard 7898: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
7899: iyearc,iagec,offbyear, \
7900: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 7901: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
7902: }else{
7903: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
7904: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
7905: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
7906: }
7907: } /* end if covariate */
7908: } /* nlstate */
7909: fprintf(ficgp,"\nset out; unset label;\n");
7910: } /* end cpt state*/
7911: } /* end covariate */
1.296 brouard 7912: } /* End if prevbcast */
1.268 brouard 7913:
1.227 brouard 7914:
1.238 brouard 7915: /* 9eme writing MLE parameters */
7916: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 7917: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 7918: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 7919: for(k=1; k <=(nlstate+ndeath); k++){
7920: if (k != i) {
1.227 brouard 7921: fprintf(ficgp,"# current state %d\n",k);
7922: for(j=1; j <=ncovmodel; j++){
7923: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
7924: jk++;
7925: }
7926: fprintf(ficgp,"\n");
1.126 brouard 7927: }
7928: }
1.223 brouard 7929: }
1.187 brouard 7930: fprintf(ficgp,"##############\n#\n");
1.227 brouard 7931:
1.145 brouard 7932: /*goto avoid;*/
1.238 brouard 7933: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
7934: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 7935: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
7936: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
7937: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
7938: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
7939: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7940: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
7941: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7942: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
7943: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
7944: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7945: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
7946: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
7947: fprintf(ficgp,"#\n");
1.223 brouard 7948: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 7949: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.237 brouard 7950: fprintf(ficgp,"#model=%s \n",model);
1.238 brouard 7951: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.264 brouard 7952: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/* to be checked */
7953: for(k1=1; k1 <=m; k1++) /* For each combination of covariate */
1.237 brouard 7954: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.264 brouard 7955: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7956: continue;
1.264 brouard 7957: fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1);
7958: strcpy(gplotlabel,"(");
1.276 brouard 7959: /*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*/
1.264 brouard 7960: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7961: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7962: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7963: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7964: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7965: vlv= nbcode[Tvaraff[k]][lv];
7966: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
7967: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
7968: }
1.237 brouard 7969: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7970: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7971: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7972: }
1.264 brouard 7973: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 7974: fprintf(ficgp,"\n#\n");
1.264 brouard 7975: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
1.276 brouard 7976: fprintf(ficgp,"\nset key outside ");
7977: /* fprintf(ficgp,"\nset label \"%s\" at graph 1.2,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel); */
7978: fprintf(ficgp,"\nset title \"%s\" font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 7979: fprintf(ficgp,"\nset ter svg size 640, 480 ");
7980: if (ng==1){
7981: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
7982: fprintf(ficgp,"\nunset log y");
7983: }else if (ng==2){
7984: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
7985: fprintf(ficgp,"\nset log y");
7986: }else if (ng==3){
7987: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
7988: fprintf(ficgp,"\nset log y");
7989: }else
7990: fprintf(ficgp,"\nunset title ");
7991: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
7992: i=1;
7993: for(k2=1; k2<=nlstate; k2++) {
7994: k3=i;
7995: for(k=1; k<=(nlstate+ndeath); k++) {
7996: if (k != k2){
7997: switch( ng) {
7998: case 1:
7999: if(nagesqr==0)
8000: fprintf(ficgp," p%d+p%d*x",i,i+1);
8001: else /* nagesqr =1 */
8002: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
8003: break;
8004: case 2: /* ng=2 */
8005: if(nagesqr==0)
8006: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
8007: else /* nagesqr =1 */
8008: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
8009: break;
8010: case 3:
8011: if(nagesqr==0)
8012: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
8013: else /* nagesqr =1 */
8014: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
8015: break;
8016: }
8017: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 8018: ijp=1; /* product no age */
8019: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
8020: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 8021: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.268 brouard 8022: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
8023: if(j==Tage[ij]) { /* Product by age To be looked at!!*/
8024: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
8025: if(DummyV[j]==0){
8026: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
8027: }else{ /* quantitative */
8028: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
8029: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
8030: }
8031: ij++;
1.237 brouard 8032: }
1.268 brouard 8033: }
8034: }else if(cptcovprod >0){
8035: if(j==Tprod[ijp]) { /* */
8036: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
8037: if(ijp <=cptcovprod) { /* Product */
8038: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
8039: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
8040: /* 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)]); */
8041: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
8042: }else{ /* Vn is dummy and Vm is quanti */
8043: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
8044: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
8045: }
8046: }else{ /* Vn*Vm Vn is quanti */
8047: if(DummyV[Tvard[ijp][2]]==0){
8048: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
8049: }else{ /* Both quanti */
8050: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
8051: }
1.237 brouard 8052: }
1.268 brouard 8053: ijp++;
1.237 brouard 8054: }
1.268 brouard 8055: } /* end Tprod */
1.237 brouard 8056: } else{ /* simple covariate */
1.264 brouard 8057: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 8058: if(Dummy[j]==0){
8059: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
8060: }else{ /* quantitative */
8061: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 8062: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 8063: }
1.237 brouard 8064: } /* end simple */
8065: } /* end j */
1.223 brouard 8066: }else{
8067: i=i-ncovmodel;
8068: if(ng !=1 ) /* For logit formula of log p11 is more difficult to get */
8069: fprintf(ficgp," (1.");
8070: }
1.227 brouard 8071:
1.223 brouard 8072: if(ng != 1){
8073: fprintf(ficgp,")/(1");
1.227 brouard 8074:
1.264 brouard 8075: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 8076: if(nagesqr==0)
1.264 brouard 8077: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 8078: else /* nagesqr =1 */
1.264 brouard 8079: 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 8080:
1.223 brouard 8081: ij=1;
8082: for(j=3; j <=ncovmodel-nagesqr; j++){
1.268 brouard 8083: if(cptcovage >0){
8084: if((j-2)==Tage[ij]) { /* Bug valgrind */
8085: if(ij <=cptcovage) { /* Bug valgrind */
8086: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);
8087: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
8088: ij++;
8089: }
8090: }
8091: }else
8092: 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 8093: }
8094: fprintf(ficgp,")");
8095: }
8096: fprintf(ficgp,")");
8097: if(ng ==2)
1.276 brouard 8098: 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 8099: else /* ng= 3 */
1.276 brouard 8100: 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 8101: }else{ /* end ng <> 1 */
8102: if( k !=k2) /* logit p11 is hard to draw */
1.276 brouard 8103: 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 8104: }
8105: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
8106: fprintf(ficgp,",");
8107: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
8108: fprintf(ficgp,",");
8109: i=i+ncovmodel;
8110: } /* end k */
8111: } /* end k2 */
1.276 brouard 8112: /* fprintf(ficgp,"\n set out; unset label;set key default;\n"); */
8113: fprintf(ficgp,"\n set out; unset title;set key default;\n");
1.264 brouard 8114: } /* end k1 */
1.223 brouard 8115: } /* end ng */
8116: /* avoid: */
8117: fflush(ficgp);
1.126 brouard 8118: } /* end gnuplot */
8119:
8120:
8121: /*************** Moving average **************/
1.219 brouard 8122: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 8123: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 8124:
1.222 brouard 8125: int i, cpt, cptcod;
8126: int modcovmax =1;
8127: int mobilavrange, mob;
8128: int iage=0;
1.288 brouard 8129: int firstA1=0, firstA2=0;
1.222 brouard 8130:
1.266 brouard 8131: double sum=0., sumr=0.;
1.222 brouard 8132: double age;
1.266 brouard 8133: double *sumnewp, *sumnewm, *sumnewmr;
8134: double *agemingood, *agemaxgood;
8135: double *agemingoodr, *agemaxgoodr;
1.222 brouard 8136:
8137:
1.278 brouard 8138: /* modcovmax=2*cptcoveff; Max number of modalities. We suppose */
8139: /* a covariate has 2 modalities, should be equal to ncovcombmax */
1.222 brouard 8140:
8141: sumnewp = vector(1,ncovcombmax);
8142: sumnewm = vector(1,ncovcombmax);
1.266 brouard 8143: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 8144: agemingood = vector(1,ncovcombmax);
1.266 brouard 8145: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 8146: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 8147: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 8148:
8149: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 8150: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 8151: sumnewp[cptcod]=0.;
1.266 brouard 8152: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
8153: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 8154: }
8155: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
8156:
1.266 brouard 8157: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
8158: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 8159: else mobilavrange=mobilav;
8160: for (age=bage; age<=fage; age++)
8161: for (i=1; i<=nlstate;i++)
8162: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
8163: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8164: /* We keep the original values on the extreme ages bage, fage and for
8165: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
8166: we use a 5 terms etc. until the borders are no more concerned.
8167: */
8168: for (mob=3;mob <=mobilavrange;mob=mob+2){
8169: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 8170: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
8171: sumnewm[cptcod]=0.;
8172: for (i=1; i<=nlstate;i++){
1.222 brouard 8173: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
8174: for (cpt=1;cpt<=(mob-1)/2;cpt++){
8175: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
8176: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
8177: }
8178: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 8179: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8180: } /* end i */
8181: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
8182: } /* end cptcod */
1.222 brouard 8183: }/* end age */
8184: }/* end mob */
1.266 brouard 8185: }else{
8186: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 8187: return -1;
1.266 brouard 8188: }
8189:
8190: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 8191: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
8192: if(invalidvarcomb[cptcod]){
8193: printf("\nCombination (%d) ignored because no cases \n",cptcod);
8194: continue;
8195: }
1.219 brouard 8196:
1.266 brouard 8197: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
8198: sumnewm[cptcod]=0.;
8199: sumnewmr[cptcod]=0.;
8200: for (i=1; i<=nlstate;i++){
8201: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8202: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8203: }
8204: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8205: agemingoodr[cptcod]=age;
8206: }
8207: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8208: agemingood[cptcod]=age;
8209: }
8210: } /* age */
8211: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 8212: sumnewm[cptcod]=0.;
1.266 brouard 8213: sumnewmr[cptcod]=0.;
1.222 brouard 8214: for (i=1; i<=nlstate;i++){
8215: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8216: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8217: }
8218: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8219: agemaxgoodr[cptcod]=age;
1.222 brouard 8220: }
8221: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 8222: agemaxgood[cptcod]=age;
8223: }
8224: } /* age */
8225: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
8226: /* but they will change */
1.288 brouard 8227: firstA1=0;firstA2=0;
1.266 brouard 8228: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
8229: sumnewm[cptcod]=0.;
8230: sumnewmr[cptcod]=0.;
8231: for (i=1; i<=nlstate;i++){
8232: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8233: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8234: }
8235: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8236: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8237: agemaxgoodr[cptcod]=age; /* age min */
8238: for (i=1; i<=nlstate;i++)
8239: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8240: }else{ /* bad we change the value with the values of good ages */
8241: for (i=1; i<=nlstate;i++){
8242: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
8243: } /* i */
8244: } /* end bad */
8245: }else{
8246: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8247: agemaxgood[cptcod]=age;
8248: }else{ /* bad we change the value with the values of good ages */
8249: for (i=1; i<=nlstate;i++){
8250: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
8251: } /* i */
8252: } /* end bad */
8253: }/* end else */
8254: sum=0.;sumr=0.;
8255: for (i=1; i<=nlstate;i++){
8256: sum+=mobaverage[(int)age][i][cptcod];
8257: sumr+=probs[(int)age][i][cptcod];
8258: }
8259: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.288 brouard 8260: if(!firstA1){
8261: firstA1=1;
8262: printf("Moving average A1: For this combination of covariate cptcod=%d, we can't get a smoothed prevalence which sums to one (%f) at any descending age! age=%d, could you increase bage=%d. Others in log file...\n",cptcod,sumr, (int)age, (int)bage);
8263: }
8264: fprintf(ficlog,"Moving average A1: For this combination of covariate cptcod=%d, we can't get a smoothed prevalence which sums to one (%f) at any descending age! age=%d, could you increase bage=%d\n",cptcod,sumr, (int)age, (int)bage);
1.266 brouard 8265: } /* end bad */
8266: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8267: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.288 brouard 8268: if(!firstA2){
8269: firstA2=1;
8270: printf("Moving average A2: For this combination of covariate cptcod=%d, the raw prevalence doesn't sums to one (%f) even with smoothed values at young ages! age=%d, could you increase bage=%d. Others in log file...\n",cptcod,sumr, (int)age, (int)bage);
8271: }
8272: fprintf(ficlog,"Moving average A2: For this combination of covariate cptcod=%d, the raw prevalence doesn't sums to one (%f) even with smoothed values at young ages! age=%d, could you increase bage=%d\n",cptcod,sumr, (int)age, (int)bage);
1.222 brouard 8273: } /* end bad */
8274: }/* age */
1.266 brouard 8275:
8276: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 8277: sumnewm[cptcod]=0.;
1.266 brouard 8278: sumnewmr[cptcod]=0.;
1.222 brouard 8279: for (i=1; i<=nlstate;i++){
8280: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8281: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8282: }
8283: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8284: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
8285: agemingoodr[cptcod]=age;
8286: for (i=1; i<=nlstate;i++)
8287: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8288: }else{ /* bad we change the value with the values of good ages */
8289: for (i=1; i<=nlstate;i++){
8290: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
8291: } /* i */
8292: } /* end bad */
8293: }else{
8294: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8295: agemingood[cptcod]=age;
8296: }else{ /* bad */
8297: for (i=1; i<=nlstate;i++){
8298: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
8299: } /* i */
8300: } /* end bad */
8301: }/* end else */
8302: sum=0.;sumr=0.;
8303: for (i=1; i<=nlstate;i++){
8304: sum+=mobaverage[(int)age][i][cptcod];
8305: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 8306: }
1.266 brouard 8307: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 8308: 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 8309: } /* end bad */
8310: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8311: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 8312: 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 8313: } /* end bad */
8314: }/* age */
1.266 brouard 8315:
1.222 brouard 8316:
8317: for (age=bage; age<=fage; age++){
1.235 brouard 8318: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 8319: sumnewp[cptcod]=0.;
8320: sumnewm[cptcod]=0.;
8321: for (i=1; i<=nlstate;i++){
8322: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
8323: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8324: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
8325: }
8326: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
8327: }
8328: /* printf("\n"); */
8329: /* } */
1.266 brouard 8330:
1.222 brouard 8331: /* brutal averaging */
1.266 brouard 8332: /* for (i=1; i<=nlstate;i++){ */
8333: /* for (age=1; age<=bage; age++){ */
8334: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
8335: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8336: /* } */
8337: /* for (age=fage; age<=AGESUP; age++){ */
8338: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
8339: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8340: /* } */
8341: /* } /\* end i status *\/ */
8342: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
8343: /* for (age=1; age<=AGESUP; age++){ */
8344: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
8345: /* mobaverage[(int)age][i][cptcod]=0.; */
8346: /* } */
8347: /* } */
1.222 brouard 8348: }/* end cptcod */
1.266 brouard 8349: free_vector(agemaxgoodr,1, ncovcombmax);
8350: free_vector(agemaxgood,1, ncovcombmax);
8351: free_vector(agemingood,1, ncovcombmax);
8352: free_vector(agemingoodr,1, ncovcombmax);
8353: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 8354: free_vector(sumnewm,1, ncovcombmax);
8355: free_vector(sumnewp,1, ncovcombmax);
8356: return 0;
8357: }/* End movingaverage */
1.218 brouard 8358:
1.126 brouard 8359:
1.296 brouard 8360:
1.126 brouard 8361: /************** Forecasting ******************/
1.296 brouard 8362: /* void prevforecast(char fileres[], double dateintmean, double anprojd, double mprojd, double jprojd, double ageminpar, double agemax, double dateprev1, double dateprev2, int mobilav, double ***prev, double bage, double fage, int firstpass, int lastpass, double anprojf, double p[], int cptcoveff)*/
8363: void prevforecast(char fileres[], double dateintmean, double dateprojd, double dateprojf, double ageminpar, double agemax, double dateprev1, double dateprev2, int mobilav, double ***prev, double bage, double fage, int firstpass, int lastpass, double p[], int cptcoveff){
8364: /* dateintemean, mean date of interviews
8365: dateprojd, year, month, day of starting projection
8366: dateprojf date of end of projection;year of end of projection (same day and month as proj1).
1.126 brouard 8367: agemin, agemax range of age
8368: dateprev1 dateprev2 range of dates during which prevalence is computed
8369: */
1.296 brouard 8370: /* double anprojd, mprojd, jprojd; */
8371: /* double anprojf, mprojf, jprojf; */
1.267 brouard 8372: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 8373: double agec; /* generic age */
1.296 brouard 8374: double agelim, ppij, yp,yp1,yp2;
1.126 brouard 8375: double *popeffectif,*popcount;
8376: double ***p3mat;
1.218 brouard 8377: /* double ***mobaverage; */
1.126 brouard 8378: char fileresf[FILENAMELENGTH];
8379:
8380: agelim=AGESUP;
1.211 brouard 8381: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8382: in each health status at the date of interview (if between dateprev1 and dateprev2).
8383: We still use firstpass and lastpass as another selection.
8384: */
1.214 brouard 8385: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8386: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 8387:
1.201 brouard 8388: strcpy(fileresf,"F_");
8389: strcat(fileresf,fileresu);
1.126 brouard 8390: if((ficresf=fopen(fileresf,"w"))==NULL) {
8391: printf("Problem with forecast resultfile: %s\n", fileresf);
8392: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
8393: }
1.235 brouard 8394: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
8395: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 8396:
1.225 brouard 8397: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 8398:
8399:
8400: stepsize=(int) (stepm+YEARM-1)/YEARM;
8401: if (stepm<=12) stepsize=1;
8402: if(estepm < stepm){
8403: printf ("Problem %d lower than %d\n",estepm, stepm);
8404: }
1.270 brouard 8405: else{
8406: hstepm=estepm;
8407: }
8408: if(estepm > stepm){ /* Yes every two year */
8409: stepsize=2;
8410: }
1.296 brouard 8411: hstepm=hstepm/stepm;
1.126 brouard 8412:
1.296 brouard 8413:
8414: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
8415: /* fractional in yp1 *\/ */
8416: /* aintmean=yp; */
8417: /* yp2=modf((yp1*12),&yp); */
8418: /* mintmean=yp; */
8419: /* yp1=modf((yp2*30.5),&yp); */
8420: /* jintmean=yp; */
8421: /* if(jintmean==0) jintmean=1; */
8422: /* if(mintmean==0) mintmean=1; */
1.126 brouard 8423:
1.296 brouard 8424:
8425: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */
8426: /* date2dmy(dateprojd,&jprojd, &mprojd, &anprojd); */
8427: /* date2dmy(dateprojf,&jprojf, &mprojf, &anprojf); */
1.227 brouard 8428: i1=pow(2,cptcoveff);
1.126 brouard 8429: if (cptcovn < 1){i1=1;}
8430:
1.296 brouard 8431: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.126 brouard 8432:
8433: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 8434:
1.126 brouard 8435: /* if (h==(int)(YEARM*yearp)){ */
1.235 brouard 8436: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8437: for(k=1; k<=i1;k++){
1.253 brouard 8438: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 8439: continue;
1.227 brouard 8440: if(invalidvarcomb[k]){
8441: printf("\nCombination (%d) projection ignored because no cases \n",k);
8442: continue;
8443: }
8444: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
8445: for(j=1;j<=cptcoveff;j++) {
8446: fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8447: }
1.235 brouard 8448: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 8449: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.235 brouard 8450: }
1.227 brouard 8451: fprintf(ficresf," yearproj age");
8452: for(j=1; j<=nlstate+ndeath;j++){
8453: for(i=1; i<=nlstate;i++)
8454: fprintf(ficresf," p%d%d",i,j);
8455: fprintf(ficresf," wp.%d",j);
8456: }
1.296 brouard 8457: for (yearp=0; yearp<=(anprojf-anprojd);yearp +=stepsize) {
1.227 brouard 8458: fprintf(ficresf,"\n");
1.296 brouard 8459: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jprojd,mprojd,anprojd+yearp);
1.270 brouard 8460: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
8461: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 8462: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
8463: nhstepm = nhstepm/hstepm;
8464: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8465: oldm=oldms;savm=savms;
1.268 brouard 8466: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 8467: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 8468: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 8469: for (h=0; h<=nhstepm; h++){
8470: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 8471: break;
8472: }
8473: }
8474: fprintf(ficresf,"\n");
8475: for(j=1;j<=cptcoveff;j++)
8476: fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.296 brouard 8477: fprintf(ficresf,"%.f %.f ",anprojd+yearp,agec+h*hstepm/YEARM*stepm);
1.268 brouard 8478:
8479: for(j=1; j<=nlstate+ndeath;j++) {
8480: ppij=0.;
8481: for(i=1; i<=nlstate;i++) {
1.278 brouard 8482: if (mobilav>=1)
8483: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
8484: else { /* even if mobilav==-1 we use mobaverage, probs may not sums to 1 */
8485: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
8486: }
1.268 brouard 8487: fprintf(ficresf," %.3f", p3mat[i][j][h]);
8488: } /* end i */
8489: fprintf(ficresf," %.3f", ppij);
8490: }/* end j */
1.227 brouard 8491: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8492: } /* end agec */
1.266 brouard 8493: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
8494: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 8495: } /* end yearp */
8496: } /* end k */
1.219 brouard 8497:
1.126 brouard 8498: fclose(ficresf);
1.215 brouard 8499: printf("End of Computing forecasting \n");
8500: fprintf(ficlog,"End of Computing forecasting\n");
8501:
1.126 brouard 8502: }
8503:
1.269 brouard 8504: /************** Back Forecasting ******************/
1.296 brouard 8505: /* 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){ */
8506: void prevbackforecast(char fileres[], double ***prevacurrent, double dateintmean, double dateprojd, double dateprojf, double ageminpar, double agemax, double dateprev1, double dateprev2, int mobilav, double bage, double fage, int firstpass, int lastpass, double p[], int cptcoveff){
8507: /* back1, year, month, day of starting backprojection
1.267 brouard 8508: agemin, agemax range of age
8509: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 8510: anback2 year of end of backprojection (same day and month as back1).
8511: prevacurrent and prev are prevalences.
1.267 brouard 8512: */
8513: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
8514: double agec; /* generic age */
1.302 brouard 8515: double agelim, ppij, ppi, yp,yp1,yp2; /* ,jintmean,mintmean,aintmean;*/
1.267 brouard 8516: double *popeffectif,*popcount;
8517: double ***p3mat;
8518: /* double ***mobaverage; */
8519: char fileresfb[FILENAMELENGTH];
8520:
1.268 brouard 8521: agelim=AGEINF;
1.267 brouard 8522: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8523: in each health status at the date of interview (if between dateprev1 and dateprev2).
8524: We still use firstpass and lastpass as another selection.
8525: */
8526: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8527: /* firstpass, lastpass, stepm, weightopt, model); */
8528:
8529: /*Do we need to compute prevalence again?*/
8530:
8531: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
8532:
8533: strcpy(fileresfb,"FB_");
8534: strcat(fileresfb,fileresu);
8535: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
8536: printf("Problem with back forecast resultfile: %s\n", fileresfb);
8537: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
8538: }
8539: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8540: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8541:
8542: if (cptcoveff==0) ncodemax[cptcoveff]=1;
8543:
8544:
8545: stepsize=(int) (stepm+YEARM-1)/YEARM;
8546: if (stepm<=12) stepsize=1;
8547: if(estepm < stepm){
8548: printf ("Problem %d lower than %d\n",estepm, stepm);
8549: }
1.270 brouard 8550: else{
8551: hstepm=estepm;
8552: }
8553: if(estepm >= stepm){ /* Yes every two year */
8554: stepsize=2;
8555: }
1.267 brouard 8556:
8557: hstepm=hstepm/stepm;
1.296 brouard 8558: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
8559: /* fractional in yp1 *\/ */
8560: /* aintmean=yp; */
8561: /* yp2=modf((yp1*12),&yp); */
8562: /* mintmean=yp; */
8563: /* yp1=modf((yp2*30.5),&yp); */
8564: /* jintmean=yp; */
8565: /* if(jintmean==0) jintmean=1; */
8566: /* if(mintmean==0) jintmean=1; */
1.267 brouard 8567:
8568: i1=pow(2,cptcoveff);
8569: if (cptcovn < 1){i1=1;}
8570:
1.296 brouard 8571: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
8572: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 8573:
8574: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
8575:
8576: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8577: for(k=1; k<=i1;k++){
8578: if(i1 != 1 && TKresult[nres]!= k)
8579: continue;
8580: if(invalidvarcomb[k]){
8581: printf("\nCombination (%d) projection ignored because no cases \n",k);
8582: continue;
8583: }
1.268 brouard 8584: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.267 brouard 8585: for(j=1;j<=cptcoveff;j++) {
8586: fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8587: }
8588: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8589: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
8590: }
8591: fprintf(ficresfb," yearbproj age");
8592: for(j=1; j<=nlstate+ndeath;j++){
8593: for(i=1; i<=nlstate;i++)
1.268 brouard 8594: fprintf(ficresfb," b%d%d",i,j);
8595: fprintf(ficresfb," b.%d",j);
1.267 brouard 8596: }
1.296 brouard 8597: for (yearp=0; yearp>=(anbackf-anbackd);yearp -=stepsize) {
1.267 brouard 8598: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
8599: fprintf(ficresfb,"\n");
1.296 brouard 8600: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jbackd,mbackd,anbackd+yearp);
1.273 brouard 8601: /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
1.270 brouard 8602: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
8603: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 8604: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
1.271 brouard 8605: nhstepm=(int) (agec-agelim) *YEARM/stepm;/* nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
1.267 brouard 8606: nhstepm = nhstepm/hstepm;
8607: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8608: oldm=oldms;savm=savms;
1.268 brouard 8609: /* computes hbxij at age agec over 1 to nhstepm */
1.271 brouard 8610: /* printf("####prevbackforecast debug agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
1.267 brouard 8611: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 8612: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
8613: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
8614: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 8615: for (h=0; h<=nhstepm; h++){
1.268 brouard 8616: if (h*hstepm/YEARM*stepm ==-yearp) {
8617: break;
8618: }
8619: }
8620: fprintf(ficresfb,"\n");
8621: for(j=1;j<=cptcoveff;j++)
8622: fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.296 brouard 8623: fprintf(ficresfb,"%.f %.f ",anbackd+yearp,agec-h*hstepm/YEARM*stepm);
1.268 brouard 8624: for(i=1; i<=nlstate+ndeath;i++) {
8625: ppij=0.;ppi=0.;
8626: for(j=1; j<=nlstate;j++) {
8627: /* if (mobilav==1) */
1.269 brouard 8628: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
8629: ppi=ppi+prevacurrent[(int)agec][j][k];
8630: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
8631: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 8632: /* else { */
8633: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
8634: /* } */
1.268 brouard 8635: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
8636: } /* end j */
8637: if(ppi <0.99){
8638: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
8639: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
8640: }
8641: fprintf(ficresfb," %.3f", ppij);
8642: }/* end j */
1.267 brouard 8643: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8644: } /* end agec */
8645: } /* end yearp */
8646: } /* end k */
1.217 brouard 8647:
1.267 brouard 8648: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 8649:
1.267 brouard 8650: fclose(ficresfb);
8651: printf("End of Computing Back forecasting \n");
8652: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 8653:
1.267 brouard 8654: }
1.217 brouard 8655:
1.269 brouard 8656: /* Variance of prevalence limit: varprlim */
8657: void varprlim(char fileresu[], int nresult, double ***prevacurrent, int mobilavproj, double bage, double fage, double **prlim, int *ncvyearp, double ftolpl, double p[], double **matcov, double *delti, int stepm, int cptcoveff){
1.288 brouard 8658: /*------- Variance of forward period (stable) prevalence------*/
1.269 brouard 8659:
8660: char fileresvpl[FILENAMELENGTH];
8661: FILE *ficresvpl;
8662: double **oldm, **savm;
8663: double **varpl; /* Variances of prevalence limits by age */
8664: int i1, k, nres, j ;
8665:
8666: strcpy(fileresvpl,"VPL_");
8667: strcat(fileresvpl,fileresu);
8668: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
1.288 brouard 8669: printf("Problem with variance of forward period (stable) prevalence resultfile: %s\n", fileresvpl);
1.269 brouard 8670: exit(0);
8671: }
1.288 brouard 8672: printf("Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
8673: fprintf(ficlog, "Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
1.269 brouard 8674:
8675: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
8676: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
8677:
8678: i1=pow(2,cptcoveff);
8679: if (cptcovn < 1){i1=1;}
8680:
8681: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8682: for(k=1; k<=i1;k++){
8683: if(i1 != 1 && TKresult[nres]!= k)
8684: continue;
8685: fprintf(ficresvpl,"\n#****** ");
8686: printf("\n#****** ");
8687: fprintf(ficlog,"\n#****** ");
8688: for(j=1;j<=cptcoveff;j++) {
8689: fprintf(ficresvpl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8690: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8691: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8692: }
8693: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
8694: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8695: fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8696: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8697: }
8698: fprintf(ficresvpl,"******\n");
8699: printf("******\n");
8700: fprintf(ficlog,"******\n");
8701:
8702: varpl=matrix(1,nlstate,(int) bage, (int) fage);
8703: oldm=oldms;savm=savms;
8704: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
8705: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
8706: /*}*/
8707: }
8708:
8709: fclose(ficresvpl);
1.288 brouard 8710: printf("done variance-covariance of forward period prevalence\n");fflush(stdout);
8711: fprintf(ficlog,"done variance-covariance of forward period prevalence\n");fflush(ficlog);
1.269 brouard 8712:
8713: }
8714: /* Variance of back prevalence: varbprlim */
8715: 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){
8716: /*------- Variance of back (stable) prevalence------*/
8717:
8718: char fileresvbl[FILENAMELENGTH];
8719: FILE *ficresvbl;
8720:
8721: double **oldm, **savm;
8722: double **varbpl; /* Variances of back prevalence limits by age */
8723: int i1, k, nres, j ;
8724:
8725: strcpy(fileresvbl,"VBL_");
8726: strcat(fileresvbl,fileresu);
8727: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
8728: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
8729: exit(0);
8730: }
8731: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
8732: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
8733:
8734:
8735: i1=pow(2,cptcoveff);
8736: if (cptcovn < 1){i1=1;}
8737:
8738: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8739: for(k=1; k<=i1;k++){
8740: if(i1 != 1 && TKresult[nres]!= k)
8741: continue;
8742: fprintf(ficresvbl,"\n#****** ");
8743: printf("\n#****** ");
8744: fprintf(ficlog,"\n#****** ");
8745: for(j=1;j<=cptcoveff;j++) {
8746: fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8747: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8748: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8749: }
8750: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
8751: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8752: fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8753: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8754: }
8755: fprintf(ficresvbl,"******\n");
8756: printf("******\n");
8757: fprintf(ficlog,"******\n");
8758:
8759: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
8760: oldm=oldms;savm=savms;
8761:
8762: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
8763: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
8764: /*}*/
8765: }
8766:
8767: fclose(ficresvbl);
8768: printf("done variance-covariance of back prevalence\n");fflush(stdout);
8769: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
8770:
8771: } /* End of varbprlim */
8772:
1.126 brouard 8773: /************** Forecasting *****not tested NB*************/
1.227 brouard 8774: /* 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 8775:
1.227 brouard 8776: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
8777: /* int *popage; */
8778: /* double calagedatem, agelim, kk1, kk2; */
8779: /* double *popeffectif,*popcount; */
8780: /* double ***p3mat,***tabpop,***tabpopprev; */
8781: /* /\* double ***mobaverage; *\/ */
8782: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 8783:
1.227 brouard 8784: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8785: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8786: /* agelim=AGESUP; */
8787: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 8788:
1.227 brouard 8789: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 8790:
8791:
1.227 brouard 8792: /* strcpy(filerespop,"POP_"); */
8793: /* strcat(filerespop,fileresu); */
8794: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
8795: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
8796: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
8797: /* } */
8798: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
8799: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 8800:
1.227 brouard 8801: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 8802:
1.227 brouard 8803: /* /\* if (mobilav!=0) { *\/ */
8804: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
8805: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
8806: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
8807: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
8808: /* /\* } *\/ */
8809: /* /\* } *\/ */
1.126 brouard 8810:
1.227 brouard 8811: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
8812: /* if (stepm<=12) stepsize=1; */
1.126 brouard 8813:
1.227 brouard 8814: /* agelim=AGESUP; */
1.126 brouard 8815:
1.227 brouard 8816: /* hstepm=1; */
8817: /* hstepm=hstepm/stepm; */
1.218 brouard 8818:
1.227 brouard 8819: /* if (popforecast==1) { */
8820: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
8821: /* printf("Problem with population file : %s\n",popfile);exit(0); */
8822: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
8823: /* } */
8824: /* popage=ivector(0,AGESUP); */
8825: /* popeffectif=vector(0,AGESUP); */
8826: /* popcount=vector(0,AGESUP); */
1.126 brouard 8827:
1.227 brouard 8828: /* i=1; */
8829: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 8830:
1.227 brouard 8831: /* imx=i; */
8832: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
8833: /* } */
1.218 brouard 8834:
1.227 brouard 8835: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
8836: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
8837: /* k=k+1; */
8838: /* fprintf(ficrespop,"\n#******"); */
8839: /* for(j=1;j<=cptcoveff;j++) { */
8840: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
8841: /* } */
8842: /* fprintf(ficrespop,"******\n"); */
8843: /* fprintf(ficrespop,"# Age"); */
8844: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
8845: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 8846:
1.227 brouard 8847: /* for (cpt=0; cpt<=0;cpt++) { */
8848: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 8849:
1.227 brouard 8850: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
8851: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
8852: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 8853:
1.227 brouard 8854: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8855: /* oldm=oldms;savm=savms; */
8856: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 8857:
1.227 brouard 8858: /* for (h=0; h<=nhstepm; h++){ */
8859: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
8860: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
8861: /* } */
8862: /* for(j=1; j<=nlstate+ndeath;j++) { */
8863: /* kk1=0.;kk2=0; */
8864: /* for(i=1; i<=nlstate;i++) { */
8865: /* if (mobilav==1) */
8866: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
8867: /* else { */
8868: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
8869: /* } */
8870: /* } */
8871: /* if (h==(int)(calagedatem+12*cpt)){ */
8872: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
8873: /* /\*fprintf(ficrespop," %.3f", kk1); */
8874: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
8875: /* } */
8876: /* } */
8877: /* for(i=1; i<=nlstate;i++){ */
8878: /* kk1=0.; */
8879: /* for(j=1; j<=nlstate;j++){ */
8880: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
8881: /* } */
8882: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
8883: /* } */
1.218 brouard 8884:
1.227 brouard 8885: /* if (h==(int)(calagedatem+12*cpt)) */
8886: /* for(j=1; j<=nlstate;j++) */
8887: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
8888: /* } */
8889: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8890: /* } */
8891: /* } */
1.218 brouard 8892:
1.227 brouard 8893: /* /\******\/ */
1.218 brouard 8894:
1.227 brouard 8895: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
8896: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
8897: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
8898: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
8899: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 8900:
1.227 brouard 8901: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8902: /* oldm=oldms;savm=savms; */
8903: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
8904: /* for (h=0; h<=nhstepm; h++){ */
8905: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
8906: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
8907: /* } */
8908: /* for(j=1; j<=nlstate+ndeath;j++) { */
8909: /* kk1=0.;kk2=0; */
8910: /* for(i=1; i<=nlstate;i++) { */
8911: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
8912: /* } */
8913: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
8914: /* } */
8915: /* } */
8916: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8917: /* } */
8918: /* } */
8919: /* } */
8920: /* } */
1.218 brouard 8921:
1.227 brouard 8922: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 8923:
1.227 brouard 8924: /* if (popforecast==1) { */
8925: /* free_ivector(popage,0,AGESUP); */
8926: /* free_vector(popeffectif,0,AGESUP); */
8927: /* free_vector(popcount,0,AGESUP); */
8928: /* } */
8929: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8930: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8931: /* fclose(ficrespop); */
8932: /* } /\* End of popforecast *\/ */
1.218 brouard 8933:
1.126 brouard 8934: int fileappend(FILE *fichier, char *optionfich)
8935: {
8936: if((fichier=fopen(optionfich,"a"))==NULL) {
8937: printf("Problem with file: %s\n", optionfich);
8938: fprintf(ficlog,"Problem with file: %s\n", optionfich);
8939: return (0);
8940: }
8941: fflush(fichier);
8942: return (1);
8943: }
8944:
8945:
8946: /**************** function prwizard **********************/
8947: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
8948: {
8949:
8950: /* Wizard to print covariance matrix template */
8951:
1.164 brouard 8952: char ca[32], cb[32];
8953: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 8954: int numlinepar;
8955:
8956: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
8957: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
8958: for(i=1; i <=nlstate; i++){
8959: jj=0;
8960: for(j=1; j <=nlstate+ndeath; j++){
8961: if(j==i) continue;
8962: jj++;
8963: /*ca[0]= k+'a'-1;ca[1]='\0';*/
8964: printf("%1d%1d",i,j);
8965: fprintf(ficparo,"%1d%1d",i,j);
8966: for(k=1; k<=ncovmodel;k++){
8967: /* printf(" %lf",param[i][j][k]); */
8968: /* fprintf(ficparo," %lf",param[i][j][k]); */
8969: printf(" 0.");
8970: fprintf(ficparo," 0.");
8971: }
8972: printf("\n");
8973: fprintf(ficparo,"\n");
8974: }
8975: }
8976: printf("# Scales (for hessian or gradient estimation)\n");
8977: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
8978: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
8979: for(i=1; i <=nlstate; i++){
8980: jj=0;
8981: for(j=1; j <=nlstate+ndeath; j++){
8982: if(j==i) continue;
8983: jj++;
8984: fprintf(ficparo,"%1d%1d",i,j);
8985: printf("%1d%1d",i,j);
8986: fflush(stdout);
8987: for(k=1; k<=ncovmodel;k++){
8988: /* printf(" %le",delti3[i][j][k]); */
8989: /* fprintf(ficparo," %le",delti3[i][j][k]); */
8990: printf(" 0.");
8991: fprintf(ficparo," 0.");
8992: }
8993: numlinepar++;
8994: printf("\n");
8995: fprintf(ficparo,"\n");
8996: }
8997: }
8998: printf("# Covariance matrix\n");
8999: /* # 121 Var(a12)\n\ */
9000: /* # 122 Cov(b12,a12) Var(b12)\n\ */
9001: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
9002: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
9003: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
9004: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
9005: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
9006: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
9007: fflush(stdout);
9008: fprintf(ficparo,"# Covariance matrix\n");
9009: /* # 121 Var(a12)\n\ */
9010: /* # 122 Cov(b12,a12) Var(b12)\n\ */
9011: /* # ...\n\ */
9012: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
9013:
9014: for(itimes=1;itimes<=2;itimes++){
9015: jj=0;
9016: for(i=1; i <=nlstate; i++){
9017: for(j=1; j <=nlstate+ndeath; j++){
9018: if(j==i) continue;
9019: for(k=1; k<=ncovmodel;k++){
9020: jj++;
9021: ca[0]= k+'a'-1;ca[1]='\0';
9022: if(itimes==1){
9023: printf("#%1d%1d%d",i,j,k);
9024: fprintf(ficparo,"#%1d%1d%d",i,j,k);
9025: }else{
9026: printf("%1d%1d%d",i,j,k);
9027: fprintf(ficparo,"%1d%1d%d",i,j,k);
9028: /* printf(" %.5le",matcov[i][j]); */
9029: }
9030: ll=0;
9031: for(li=1;li <=nlstate; li++){
9032: for(lj=1;lj <=nlstate+ndeath; lj++){
9033: if(lj==li) continue;
9034: for(lk=1;lk<=ncovmodel;lk++){
9035: ll++;
9036: if(ll<=jj){
9037: cb[0]= lk +'a'-1;cb[1]='\0';
9038: if(ll<jj){
9039: if(itimes==1){
9040: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
9041: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
9042: }else{
9043: printf(" 0.");
9044: fprintf(ficparo," 0.");
9045: }
9046: }else{
9047: if(itimes==1){
9048: printf(" Var(%s%1d%1d)",ca,i,j);
9049: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
9050: }else{
9051: printf(" 0.");
9052: fprintf(ficparo," 0.");
9053: }
9054: }
9055: }
9056: } /* end lk */
9057: } /* end lj */
9058: } /* end li */
9059: printf("\n");
9060: fprintf(ficparo,"\n");
9061: numlinepar++;
9062: } /* end k*/
9063: } /*end j */
9064: } /* end i */
9065: } /* end itimes */
9066:
9067: } /* end of prwizard */
9068: /******************* Gompertz Likelihood ******************************/
9069: double gompertz(double x[])
9070: {
1.302 brouard 9071: double A=0.0,B=0.,L=0.0,sump=0.,num=0.;
1.126 brouard 9072: int i,n=0; /* n is the size of the sample */
9073:
1.220 brouard 9074: for (i=1;i<=imx ; i++) {
1.126 brouard 9075: sump=sump+weight[i];
9076: /* sump=sump+1;*/
9077: num=num+1;
9078: }
1.302 brouard 9079: L=0.0;
9080: /* agegomp=AGEGOMP; */
1.126 brouard 9081: /* for (i=0; i<=imx; i++)
9082: 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]);*/
9083:
1.302 brouard 9084: for (i=1;i<=imx ; i++) {
9085: /* mu(a)=mu(agecomp)*exp(teta*(age-agegomp))
9086: mu(a)=x[1]*exp(x[2]*(age-agegomp)); x[1] and x[2] are per year.
9087: * L= Product mu(agedeces)exp(-\int_ageexam^agedc mu(u) du ) for a death between agedc (in month)
9088: * and agedc +1 month, cens[i]=0: log(x[1]/YEARM)
9089: * +
9090: * exp(-\int_ageexam^agecens mu(u) du ) when censored, cens[i]=1
9091: */
9092: if (wav[i] > 1 || agedc[i] < AGESUP) {
9093: if (cens[i] == 1){
9094: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
9095: } else if (cens[i] == 0){
1.126 brouard 9096: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
1.302 brouard 9097: +log(x[1]/YEARM) +x[2]*(agedc[i]-agegomp)+log(YEARM);
9098: } else
9099: printf("Gompertz cens[%d] neither 1 nor 0\n",i);
1.126 brouard 9100: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
1.302 brouard 9101: L=L+A*weight[i];
1.126 brouard 9102: /* 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]);*/
1.302 brouard 9103: }
9104: }
1.126 brouard 9105:
1.302 brouard 9106: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
1.126 brouard 9107:
9108: return -2*L*num/sump;
9109: }
9110:
1.136 brouard 9111: #ifdef GSL
9112: /******************* Gompertz_f Likelihood ******************************/
9113: double gompertz_f(const gsl_vector *v, void *params)
9114: {
1.302 brouard 9115: double A=0.,B=0.,LL=0.0,sump=0.,num=0.;
1.136 brouard 9116: double *x= (double *) v->data;
9117: int i,n=0; /* n is the size of the sample */
9118:
9119: for (i=0;i<=imx-1 ; i++) {
9120: sump=sump+weight[i];
9121: /* sump=sump+1;*/
9122: num=num+1;
9123: }
9124:
9125:
9126: /* for (i=0; i<=imx; i++)
9127: 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]);*/
9128: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
9129: for (i=1;i<=imx ; i++)
9130: {
9131: if (cens[i] == 1 && wav[i]>1)
9132: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
9133:
9134: if (cens[i] == 0 && wav[i]>1)
9135: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
9136: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
9137:
9138: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
9139: if (wav[i] > 1 ) { /* ??? */
9140: LL=LL+A*weight[i];
9141: /* 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]);*/
9142: }
9143: }
9144:
9145: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
9146: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
9147:
9148: return -2*LL*num/sump;
9149: }
9150: #endif
9151:
1.126 brouard 9152: /******************* Printing html file ***********/
1.201 brouard 9153: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 9154: int lastpass, int stepm, int weightopt, char model[],\
9155: int imx, double p[],double **matcov,double agemortsup){
9156: int i,k;
9157:
9158: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
9159: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
9160: for (i=1;i<=2;i++)
9161: 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 9162: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 9163: fprintf(fichtm,"</ul>");
9164:
9165: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
9166:
9167: 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>");
9168:
9169: for (k=agegomp;k<(agemortsup-2);k++)
9170: 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]);
9171:
9172:
9173: fflush(fichtm);
9174: }
9175:
9176: /******************* Gnuplot file **************/
1.201 brouard 9177: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 9178:
9179: char dirfileres[132],optfileres[132];
1.164 brouard 9180:
1.126 brouard 9181: int ng;
9182:
9183:
9184: /*#ifdef windows */
9185: fprintf(ficgp,"cd \"%s\" \n",pathc);
9186: /*#endif */
9187:
9188:
9189: strcpy(dirfileres,optionfilefiname);
9190: strcpy(optfileres,"vpl");
1.199 brouard 9191: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 9192: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 9193: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 9194: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 9195: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
9196:
9197: }
9198:
1.136 brouard 9199: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
9200: {
1.126 brouard 9201:
1.136 brouard 9202: /*-------- data file ----------*/
9203: FILE *fic;
9204: char dummy[]=" ";
1.240 brouard 9205: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 9206: int lstra;
1.136 brouard 9207: int linei, month, year,iout;
1.302 brouard 9208: int noffset=0; /* This is the offset if BOM data file */
1.136 brouard 9209: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 9210: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 9211: char *stratrunc;
1.223 brouard 9212:
1.240 brouard 9213: DummyV=ivector(1,NCOVMAX); /* 1 to 3 */
9214: FixedV=ivector(1,NCOVMAX); /* 1 to 3 */
1.126 brouard 9215:
1.240 brouard 9216: for(v=1; v <=ncovcol;v++){
9217: DummyV[v]=0;
9218: FixedV[v]=0;
9219: }
9220: for(v=ncovcol+1; v <=ncovcol+nqv;v++){
9221: DummyV[v]=1;
9222: FixedV[v]=0;
9223: }
9224: for(v=ncovcol+nqv+1; v <=ncovcol+nqv+ntv;v++){
9225: DummyV[v]=0;
9226: FixedV[v]=1;
9227: }
9228: for(v=ncovcol+nqv+ntv+1; v <=ncovcol+nqv+ntv+nqtv;v++){
9229: DummyV[v]=1;
9230: FixedV[v]=1;
9231: }
9232: for(v=1; v <=ncovcol+nqv+ntv+nqtv;v++){
9233: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",v,v,DummyV[v],v,FixedV[v]);
9234: 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]);
9235: }
1.126 brouard 9236:
1.136 brouard 9237: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 9238: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
9239: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 9240: }
1.126 brouard 9241:
1.302 brouard 9242: /* Is it a BOM UTF-8 Windows file? */
9243: /* First data line */
9244: linei=0;
9245: while(fgets(line, MAXLINE, fic)) {
9246: noffset=0;
9247: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
9248: {
9249: noffset=noffset+3;
9250: printf("# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);fflush(stdout);
9251: fprintf(ficlog,"# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);
9252: fflush(ficlog); return 1;
9253: }
9254: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
9255: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
9256: {
9257: noffset=noffset+2;
1.304 ! brouard 9258: printf("# Error Data file '%s' is a huge UTF16BE BOM file, please convert to UTF8 or ascii file (for example with dos2unix) and rerun.\n",datafile);fflush(stdout);
! 9259: fprintf(ficlog,"# Error Data file '%s' is a huge UTF16BE BOM file, please convert to UTF8 or ascii file (for example with dos2unix) and rerun.\n",datafile);
1.302 brouard 9260: fflush(ficlog); return 1;
9261: }
9262: else if( line[0] == 0 && line[1] == 0)
9263: {
9264: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
9265: noffset=noffset+4;
1.304 ! brouard 9266: printf("# Error Data file '%s' is a huge UTF16BE BOM file, please convert to UTF8 or ascii file (for example with dos2unix) and rerun.\n",datafile);fflush(stdout);
! 9267: fprintf(ficlog,"# Error Data file '%s' is a huge UTF16BE BOM file, please convert to UTF8 or ascii file (for example with dos2unix) and rerun.\n",datafile);
1.302 brouard 9268: fflush(ficlog); return 1;
9269: }
9270: } else{
9271: ;/*printf(" Not a BOM file\n");*/
9272: }
9273: /* If line starts with a # it is a comment */
9274: if (line[noffset] == '#') {
9275: linei=linei+1;
9276: break;
9277: }else{
9278: break;
9279: }
9280: }
9281: fclose(fic);
9282: if((fic=fopen(datafile,"r"))==NULL) {
9283: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
9284: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
9285: }
9286: /* Not a Bom file */
9287:
1.136 brouard 9288: i=1;
9289: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
9290: linei=linei+1;
9291: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
9292: if(line[j] == '\t')
9293: line[j] = ' ';
9294: }
9295: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
9296: ;
9297: };
9298: line[j+1]=0; /* Trims blanks at end of line */
9299: if(line[0]=='#'){
9300: fprintf(ficlog,"Comment line\n%s\n",line);
9301: printf("Comment line\n%s\n",line);
9302: continue;
9303: }
9304: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 9305: strcpy(line, linetmp);
1.223 brouard 9306:
9307: /* Loops on waves */
9308: for (j=maxwav;j>=1;j--){
9309: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 9310: cutv(stra, strb, line, ' ');
9311: if(strb[0]=='.') { /* Missing value */
9312: lval=-1;
9313: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
9314: cotvar[j][ntv+iv][i]=-1; /* For performance reasons */
9315: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
9316: 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);
9317: 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);
9318: return 1;
9319: }
9320: }else{
9321: errno=0;
9322: /* what_kind_of_number(strb); */
9323: dval=strtod(strb,&endptr);
9324: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
9325: /* if(strb != endptr && *endptr == '\0') */
9326: /* dval=dlval; */
9327: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9328: if( strb[0]=='\0' || (*endptr != '\0')){
9329: 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);
9330: 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);
9331: return 1;
9332: }
9333: cotqvar[j][iv][i]=dval;
9334: cotvar[j][ntv+iv][i]=dval;
9335: }
9336: strcpy(line,stra);
1.223 brouard 9337: }/* end loop ntqv */
1.225 brouard 9338:
1.223 brouard 9339: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 9340: cutv(stra, strb, line, ' ');
9341: if(strb[0]=='.') { /* Missing value */
9342: lval=-1;
9343: }else{
9344: errno=0;
9345: lval=strtol(strb,&endptr,10);
9346: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9347: if( strb[0]=='\0' || (*endptr != '\0')){
9348: 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);
9349: 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);
9350: return 1;
9351: }
9352: }
9353: if(lval <-1 || lval >1){
9354: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.223 brouard 9355: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9356: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9357: For example, for multinomial values like 1, 2 and 3,\n \
9358: build V1=0 V2=0 for the reference value (1),\n \
9359: V1=1 V2=0 for (2) \n \
1.223 brouard 9360: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9361: output of IMaCh is often meaningless.\n \
1.223 brouard 9362: Exiting.\n",lval,linei, i,line,j);
1.238 brouard 9363: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.223 brouard 9364: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9365: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9366: For example, for multinomial values like 1, 2 and 3,\n \
9367: build V1=0 V2=0 for the reference value (1),\n \
9368: V1=1 V2=0 for (2) \n \
1.223 brouard 9369: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9370: output of IMaCh is often meaningless.\n \
1.223 brouard 9371: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.238 brouard 9372: return 1;
9373: }
9374: cotvar[j][iv][i]=(double)(lval);
9375: strcpy(line,stra);
1.223 brouard 9376: }/* end loop ntv */
1.225 brouard 9377:
1.223 brouard 9378: /* Statuses at wave */
1.137 brouard 9379: cutv(stra, strb, line, ' ');
1.223 brouard 9380: if(strb[0]=='.') { /* Missing value */
1.238 brouard 9381: lval=-1;
1.136 brouard 9382: }else{
1.238 brouard 9383: errno=0;
9384: lval=strtol(strb,&endptr,10);
9385: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9386: if( strb[0]=='\0' || (*endptr != '\0')){
9387: 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);
9388: 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);
9389: return 1;
9390: }
1.136 brouard 9391: }
1.225 brouard 9392:
1.136 brouard 9393: s[j][i]=lval;
1.225 brouard 9394:
1.223 brouard 9395: /* Date of Interview */
1.136 brouard 9396: strcpy(line,stra);
9397: cutv(stra, strb,line,' ');
1.169 brouard 9398: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9399: }
1.169 brouard 9400: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 9401: month=99;
9402: year=9999;
1.136 brouard 9403: }else{
1.225 brouard 9404: 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);
9405: 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);
9406: return 1;
1.136 brouard 9407: }
9408: anint[j][i]= (double) year;
1.302 brouard 9409: mint[j][i]= (double)month;
9410: /* if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){ */
9411: /* printf("Warning reading data around '%s' at line number %d for individual %d, '%s'\nThe date of interview (%2d/%4d) at wave %d occurred before the date of birth (%2d/%4d).\n",strb, linei,i, line, mint[j][i],anint[j][i], moisnais[i],annais[i]); */
9412: /* fprintf(ficlog,"Warning reading data around '%s' at line number %d for individual %d, '%s'\nThe date of interview (%2d/%4d) at wave %d occurred before the date of birth (%2d/%4d).\n",strb, linei,i, line, mint[j][i],anint[j][i], moisnais[i],annais[i]); */
9413: /* } */
1.136 brouard 9414: strcpy(line,stra);
1.223 brouard 9415: } /* End loop on waves */
1.225 brouard 9416:
1.223 brouard 9417: /* Date of death */
1.136 brouard 9418: cutv(stra, strb,line,' ');
1.169 brouard 9419: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9420: }
1.169 brouard 9421: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 9422: month=99;
9423: year=9999;
9424: }else{
1.141 brouard 9425: 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 9426: 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);
9427: return 1;
1.136 brouard 9428: }
9429: andc[i]=(double) year;
9430: moisdc[i]=(double) month;
9431: strcpy(line,stra);
9432:
1.223 brouard 9433: /* Date of birth */
1.136 brouard 9434: cutv(stra, strb,line,' ');
1.169 brouard 9435: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9436: }
1.169 brouard 9437: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 9438: month=99;
9439: year=9999;
9440: }else{
1.141 brouard 9441: 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);
9442: 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 9443: return 1;
1.136 brouard 9444: }
9445: if (year==9999) {
1.141 brouard 9446: 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);
9447: 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 9448: return 1;
9449:
1.136 brouard 9450: }
9451: annais[i]=(double)(year);
1.302 brouard 9452: moisnais[i]=(double)(month);
9453: for (j=1;j<=maxwav;j++){
9454: if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){
9455: printf("Warning reading data around '%s' at line number %d for individual %d, '%s'\nThe date of interview (%2d/%4d) at wave %d occurred before the date of birth (%2d/%4d).\n",strb, linei,i, line, (int)mint[j][i],(int)anint[j][i], j,(int)moisnais[i],(int)annais[i]);
9456: fprintf(ficlog,"Warning reading data around '%s' at line number %d for individual %d, '%s'\nThe date of interview (%2d/%4d) at wave %d occurred before the date of birth (%2d/%4d).\n",strb, linei,i, line, (int)mint[j][i],(int)anint[j][i], j, (int)moisnais[i],(int)annais[i]);
9457: }
9458: }
9459:
1.136 brouard 9460: strcpy(line,stra);
1.225 brouard 9461:
1.223 brouard 9462: /* Sample weight */
1.136 brouard 9463: cutv(stra, strb,line,' ');
9464: errno=0;
9465: dval=strtod(strb,&endptr);
9466: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 9467: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
9468: 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 9469: fflush(ficlog);
9470: return 1;
9471: }
9472: weight[i]=dval;
9473: strcpy(line,stra);
1.225 brouard 9474:
1.223 brouard 9475: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
9476: cutv(stra, strb, line, ' ');
9477: if(strb[0]=='.') { /* Missing value */
1.225 brouard 9478: lval=-1;
1.223 brouard 9479: }else{
1.225 brouard 9480: errno=0;
9481: /* what_kind_of_number(strb); */
9482: dval=strtod(strb,&endptr);
9483: /* if(strb != endptr && *endptr == '\0') */
9484: /* dval=dlval; */
9485: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9486: if( strb[0]=='\0' || (*endptr != '\0')){
9487: 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);
9488: 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);
9489: return 1;
9490: }
9491: coqvar[iv][i]=dval;
1.226 brouard 9492: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 9493: }
9494: strcpy(line,stra);
9495: }/* end loop nqv */
1.136 brouard 9496:
1.223 brouard 9497: /* Covariate values */
1.136 brouard 9498: for (j=ncovcol;j>=1;j--){
9499: cutv(stra, strb,line,' ');
1.223 brouard 9500: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 9501: lval=-1;
1.136 brouard 9502: }else{
1.225 brouard 9503: errno=0;
9504: lval=strtol(strb,&endptr,10);
9505: if( strb[0]=='\0' || (*endptr != '\0')){
9506: 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);
9507: 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);
9508: return 1;
9509: }
1.136 brouard 9510: }
9511: if(lval <-1 || lval >1){
1.225 brouard 9512: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9513: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9514: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9515: For example, for multinomial values like 1, 2 and 3,\n \
9516: build V1=0 V2=0 for the reference value (1),\n \
9517: V1=1 V2=0 for (2) \n \
1.136 brouard 9518: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9519: output of IMaCh is often meaningless.\n \
1.136 brouard 9520: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 9521: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9522: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9523: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9524: For example, for multinomial values like 1, 2 and 3,\n \
9525: build V1=0 V2=0 for the reference value (1),\n \
9526: V1=1 V2=0 for (2) \n \
1.136 brouard 9527: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9528: output of IMaCh is often meaningless.\n \
1.136 brouard 9529: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 9530: return 1;
1.136 brouard 9531: }
9532: covar[j][i]=(double)(lval);
9533: strcpy(line,stra);
9534: }
9535: lstra=strlen(stra);
1.225 brouard 9536:
1.136 brouard 9537: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
9538: stratrunc = &(stra[lstra-9]);
9539: num[i]=atol(stratrunc);
9540: }
9541: else
9542: num[i]=atol(stra);
9543: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
9544: 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;}*/
9545:
9546: i=i+1;
9547: } /* End loop reading data */
1.225 brouard 9548:
1.136 brouard 9549: *imax=i-1; /* Number of individuals */
9550: fclose(fic);
1.225 brouard 9551:
1.136 brouard 9552: return (0);
1.164 brouard 9553: /* endread: */
1.225 brouard 9554: printf("Exiting readdata: ");
9555: fclose(fic);
9556: return (1);
1.223 brouard 9557: }
1.126 brouard 9558:
1.234 brouard 9559: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 9560: char *p1 = *stri, *p2 = *stri;
1.235 brouard 9561: while (*p2 == ' ')
1.234 brouard 9562: p2++;
9563: /* while ((*p1++ = *p2++) !=0) */
9564: /* ; */
9565: /* do */
9566: /* while (*p2 == ' ') */
9567: /* p2++; */
9568: /* while (*p1++ == *p2++); */
9569: *stri=p2;
1.145 brouard 9570: }
9571:
1.235 brouard 9572: int decoderesult ( char resultline[], int nres)
1.230 brouard 9573: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
9574: {
1.235 brouard 9575: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 9576: char resultsav[MAXLINE];
1.234 brouard 9577: int resultmodel[MAXLINE];
9578: int modelresult[MAXLINE];
1.230 brouard 9579: char stra[80], strb[80], strc[80], strd[80],stre[80];
9580:
1.234 brouard 9581: removefirstspace(&resultline);
1.233 brouard 9582: printf("decoderesult:%s\n",resultline);
1.230 brouard 9583:
9584: if (strstr(resultline,"v") !=0){
9585: printf("Error. 'v' must be in upper case 'V' result: %s ",resultline);
9586: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultline);fflush(ficlog);
9587: return 1;
9588: }
9589: trimbb(resultsav, resultline);
9590: if (strlen(resultsav) >1){
9591: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' */
9592: }
1.253 brouard 9593: if(j == 0){ /* Resultline but no = */
9594: TKresult[nres]=0; /* Combination for the nresult and the model */
9595: return (0);
9596: }
9597:
1.234 brouard 9598: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
9599: 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);
9600: 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);
9601: }
9602: for(k=1; k<=j;k++){ /* Loop on any covariate of the result line */
9603: if(nbocc(resultsav,'=') >1){
9604: cutl(stra,strb,resultsav,' '); /* keeps in strb after the first ' '
9605: resultsav= V4=1 V5=25.1 V3=0 strb=V3=0 stra= V4=1 V5=25.1 */
9606: cutl(strc,strd,strb,'='); /* strb:V4=1 strc=1 strd=V4 */
9607: }else
9608: cutl(strc,strd,resultsav,'=');
1.230 brouard 9609: Tvalsel[k]=atof(strc); /* 1 */
1.234 brouard 9610:
1.230 brouard 9611: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
9612: Tvarsel[k]=atoi(strc);
9613: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
9614: /* cptcovsel++; */
9615: if (nbocc(stra,'=') >0)
9616: strcpy(resultsav,stra); /* and analyzes it */
9617: }
1.235 brouard 9618: /* Checking for missing or useless values in comparison of current model needs */
1.236 brouard 9619: for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9620: if(Typevar[k1]==0){ /* Single covariate in model */
1.234 brouard 9621: match=0;
1.236 brouard 9622: for(k2=1; k2 <=j;k2++){/* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.237 brouard 9623: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar[1]=5 == Tvarsel[2]=5 */
1.236 brouard 9624: modelresult[k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.234 brouard 9625: match=1;
9626: break;
9627: }
9628: }
9629: if(match == 0){
9630: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
9631: }
9632: }
9633: }
1.235 brouard 9634: /* Checking for missing or useless values in comparison of current model needs */
9635: for(k2=1; k2 <=j;k2++){ /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 9636: match=0;
1.235 brouard 9637: for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9638: if(Typevar[k1]==0){ /* Single */
1.237 brouard 9639: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 */
1.235 brouard 9640: resultmodel[k1]=k2; /* resultmodel[2]=1 resultmodel[1]=2 resultmodel[3]=3 resultmodel[6]=4 resultmodel[9]=5 */
1.234 brouard 9641: ++match;
9642: }
9643: }
9644: }
9645: if(match == 0){
9646: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
9647: }else if(match > 1){
9648: printf("Error in result line: %d doubled; result: %s, model=%s\n",k2, resultline, model);
9649: }
9650: }
1.235 brouard 9651:
1.234 brouard 9652: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 9653: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9654: /* result line V4=1 V5=25.1 V3=0 V2=8 V1=1 */
9655: /* should give a combination of dummy V4=1, V3=0, V1=1 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 5 + (1offset) = 6*/
9656: /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
9657: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
9658: /* 1 0 0 0 */
9659: /* 2 1 0 0 */
9660: /* 3 0 1 0 */
9661: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 */
9662: /* 5 0 0 1 */
9663: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 */
9664: /* 7 0 1 1 */
9665: /* 8 1 1 1 */
1.237 brouard 9666: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
9667: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
9668: /* V5*age V5 known which value for nres? */
9669: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.235 brouard 9670: for(k1=1, k=0, k4=0, k4q=0; k1 <=cptcovt;k1++){ /* model line */
9671: if( Dummy[k1]==0 && Typevar[k1]==0 ){ /* Single dummy */
1.237 brouard 9672: k3= resultmodel[k1]; /* resultmodel[2(V4)] = 1=k3 */
1.235 brouard 9673: k2=(int)Tvarsel[k3]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
9674: k+=Tvalsel[k3]*pow(2,k4); /* Tvalsel[1]=1 */
1.237 brouard 9675: Tresult[nres][k4+1]=Tvalsel[k3];/* Tresult[nres][1]=1(V4=1) Tresult[nres][2]=0(V3=0) */
9676: Tvresult[nres][k4+1]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
9677: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.235 brouard 9678: printf("Decoderesult Dummy k=%d, V(k2=V%d)= Tvalsel[%d]=%d, 2**(%d)\n",k, k2, k3, (int)Tvalsel[k3], k4);
9679: k4++;;
9680: } else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Single quantitative */
9681: k3q= resultmodel[k1]; /* resultmodel[2] = 1=k3 */
9682: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
1.237 brouard 9683: Tqresult[nres][k4q+1]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
9684: Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
9685: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.235 brouard 9686: printf("Decoderesult Quantitative nres=%d, V(k2q=V%d)= Tvalsel[%d]=%d, Tvarsel[%d]=%f\n",nres, k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]);
9687: k4q++;;
9688: }
9689: }
1.234 brouard 9690:
1.235 brouard 9691: TKresult[nres]=++k; /* Combination for the nresult and the model */
1.230 brouard 9692: return (0);
9693: }
1.235 brouard 9694:
1.230 brouard 9695: int decodemodel( char model[], int lastobs)
9696: /**< This routine decodes the model and returns:
1.224 brouard 9697: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
9698: * - nagesqr = 1 if age*age in the model, otherwise 0.
9699: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
9700: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
9701: * - cptcovage number of covariates with age*products =2
9702: * - cptcovs number of simple covariates
9703: * - 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
9704: * which is a new column after the 9 (ncovcol) variables.
9705: * - if k is a product Vn*Vm covar[k][i] is filled with correct values for each individual
9706: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
9707: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
9708: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
9709: */
1.136 brouard 9710: {
1.238 brouard 9711: int i, j, k, ks, v;
1.227 brouard 9712: int j1, k1, k2, k3, k4;
1.136 brouard 9713: char modelsav[80];
1.145 brouard 9714: char stra[80], strb[80], strc[80], strd[80],stre[80];
1.187 brouard 9715: char *strpt;
1.136 brouard 9716:
1.145 brouard 9717: /*removespace(model);*/
1.136 brouard 9718: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.145 brouard 9719: j=0, j1=0, k1=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 9720: if (strstr(model,"AGE") !=0){
1.192 brouard 9721: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
9722: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 9723: return 1;
9724: }
1.141 brouard 9725: if (strstr(model,"v") !=0){
9726: printf("Error. 'v' must be in upper case 'V' model=%s ",model);
9727: fprintf(ficlog,"Error. 'v' must be in upper case model=%s ",model);fflush(ficlog);
9728: return 1;
9729: }
1.187 brouard 9730: strcpy(modelsav,model);
9731: if ((strpt=strstr(model,"age*age")) !=0){
9732: printf(" strpt=%s, model=%s\n",strpt, model);
9733: if(strpt != model){
1.234 brouard 9734: printf("Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 9735: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 9736: corresponding column of parameters.\n",model);
1.234 brouard 9737: fprintf(ficlog,"Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 9738: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 9739: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 9740: return 1;
1.225 brouard 9741: }
1.187 brouard 9742: nagesqr=1;
9743: if (strstr(model,"+age*age") !=0)
1.234 brouard 9744: substrchaine(modelsav, model, "+age*age");
1.187 brouard 9745: else if (strstr(model,"age*age+") !=0)
1.234 brouard 9746: substrchaine(modelsav, model, "age*age+");
1.187 brouard 9747: else
1.234 brouard 9748: substrchaine(modelsav, model, "age*age");
1.187 brouard 9749: }else
9750: nagesqr=0;
9751: if (strlen(modelsav) >1){
9752: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
9753: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.224 brouard 9754: cptcovs=j+1-j1; /**< Number of simple covariates V1+V1*age+V3 +V3*V4+age*age=> V1 + V3 =5-3=2 */
1.187 brouard 9755: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 9756: * cst, age and age*age
9757: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
9758: /* including age products which are counted in cptcovage.
9759: * but the covariates which are products must be treated
9760: * separately: ncovn=4- 2=2 (V1+V3). */
1.187 brouard 9761: cptcovprod=j1; /**< Number of products V1*V2 +v3*age = 2 */
9762: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.225 brouard 9763:
9764:
1.187 brouard 9765: /* Design
9766: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
9767: * < ncovcol=8 >
9768: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
9769: * k= 1 2 3 4 5 6 7 8
9770: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
9771: * covar[k,i], value of kth covariate if not including age for individual i:
1.224 brouard 9772: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
9773: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 9774: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
9775: * Tage[++cptcovage]=k
9776: * if products, new covar are created after ncovcol with k1
9777: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
9778: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
9779: * 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
9780: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
9781: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
9782: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
9783: * < ncovcol=8 >
9784: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
9785: * k= 1 2 3 4 5 6 7 8 9 10 11 12
9786: * Tvar[k]= 2 1 3 3 10 11 8 8 5 6 7 8
9787: * p Tvar[1]@12={2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
9788: * p Tprod[1]@2={ 6, 5}
9789: *p Tvard[1][1]@4= {7, 8, 5, 6}
9790: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
9791: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
9792: *How to reorganize?
9793: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
9794: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
9795: * {2, 1, 4, 8, 5, 6, 3, 7}
9796: * Struct []
9797: */
1.225 brouard 9798:
1.187 brouard 9799: /* This loop fills the array Tvar from the string 'model'.*/
9800: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
9801: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
9802: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
9803: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
9804: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
9805: /* k=1 Tvar[1]=2 (from V2) */
9806: /* k=5 Tvar[5] */
9807: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 9808: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 9809: /* } */
1.198 brouard 9810: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 9811: /*
9812: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 9813: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
9814: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
9815: }
1.187 brouard 9816: cptcovage=0;
9817: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model */
1.234 brouard 9818: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+'
1.225 brouard 9819: modelsav==V2+V1+V4+V3*age strb=V3*age stra=V2+V1+V4 */
1.234 brouard 9820: if (nbocc(modelsav,'+')==0) strcpy(strb,modelsav); /* and analyzes it */
9821: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
9822: /*scanf("%d",i);*/
9823: if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V4+V3*age strb=V3*age */
9824: cutl(strc,strd,strb,'*'); /**< strd*strc Vm*Vn: strb=V3*age(input) strc=age strd=V3 ; V3*V2 strc=V2, strd=V3 */
9825: if (strcmp(strc,"age")==0) { /**< Model includes age: Vn*age */
9826: /* covar is not filled and then is empty */
9827: cptcovprod--;
9828: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
9829: Tvar[k]=atoi(stre); /* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1 */
9830: Typevar[k]=1; /* 1 for age product */
9831: cptcovage++; /* Sums the number of covariates which include age as a product */
9832: Tage[cptcovage]=k; /* Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */
9833: /*printf("stre=%s ", stre);*/
9834: } else if (strcmp(strd,"age")==0) { /* or age*Vn */
9835: cptcovprod--;
9836: cutl(stre,strb,strc,'V');
9837: Tvar[k]=atoi(stre);
9838: Typevar[k]=1; /* 1 for age product */
9839: cptcovage++;
9840: Tage[cptcovage]=k;
9841: } else { /* Age is not in the model product V2+V1+V1*V4+V3*age+V3*V2 strb=V3*V2*/
9842: /* loops on k1=1 (V3*V2) and k1=2 V4*V3 */
9843: cptcovn++;
9844: cptcovprodnoage++;k1++;
9845: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
9846: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* For model-covariate k tells which data-covariate to use but
9847: because this model-covariate is a construction we invent a new column
9848: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
9849: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2
9850: Tvar[3=V1*V4]=4+1 Tvar[5=V3*V2]=4 + 2= 6, etc */
9851: Typevar[k]=2; /* 2 for double fixed dummy covariates */
9852: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
9853: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 */
9854: Tposprod[k]=k1; /* Tpsprod[3]=1, Tposprod[2]=5 */
9855: Tvard[k1][1] =atoi(strc); /* m 1 for V1*/
9856: Tvard[k1][2] =atoi(stre); /* n 4 for V4*/
9857: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
9858: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
9859: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
1.225 brouard 9860: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
1.234 brouard 9861: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
9862: for (i=1; i<=lastobs;i++){
9863: /* Computes the new covariate which is a product of
9864: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
9865: covar[ncovcol+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
9866: }
9867: } /* End age is not in the model */
9868: } /* End if model includes a product */
9869: else { /* no more sum */
9870: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
9871: /* scanf("%d",i);*/
9872: cutl(strd,strc,strb,'V');
9873: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
9874: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
9875: Tvar[k]=atoi(strd);
9876: Typevar[k]=0; /* 0 for simple covariates */
9877: }
9878: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 9879: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 9880: scanf("%d",i);*/
1.187 brouard 9881: } /* end of loop + on total covariates */
9882: } /* end if strlen(modelsave == 0) age*age might exist */
9883: } /* end if strlen(model == 0) */
1.136 brouard 9884:
9885: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
9886: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 9887:
1.136 brouard 9888: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 9889: printf("cptcovprod=%d ", cptcovprod);
9890: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
9891: scanf("%d ",i);*/
9892:
9893:
1.230 brouard 9894: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
9895: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 9896: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
9897: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
9898: k = 1 2 3 4 5 6 7 8 9
9899: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
9900: Typevar[k]= 0 0 0 2 1 0 2 1 1
1.227 brouard 9901: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
9902: Dummy[k] 1 0 0 0 3 1 1 2 3
9903: Tmodelind[combination of covar]=k;
1.225 brouard 9904: */
9905: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 9906: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 9907: /* 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 9908: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.227 brouard 9909: printf("Model=%s\n\
9910: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
9911: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
9912: 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);
9913: fprintf(ficlog,"Model=%s\n\
9914: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
9915: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
9916: Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product\n",model);
1.285 brouard 9917: for(k=-1;k<=cptcovt; k++){ Fixed[k]=0; Dummy[k]=0;}
1.234 brouard 9918: 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 */
9919: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 9920: Fixed[k]= 0;
9921: Dummy[k]= 0;
1.225 brouard 9922: ncoveff++;
1.232 brouard 9923: ncovf++;
1.234 brouard 9924: nsd++;
9925: modell[k].maintype= FTYPE;
9926: TvarsD[nsd]=Tvar[k];
9927: TvarsDind[nsd]=k;
9928: TvarF[ncovf]=Tvar[k];
9929: TvarFind[ncovf]=k;
9930: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9931: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9932: }else if( Tvar[k] <=ncovcol && Typevar[k]==2){ /* Product of fixed dummy (<=ncovcol) covariates */
9933: Fixed[k]= 0;
9934: Dummy[k]= 0;
9935: ncoveff++;
9936: ncovf++;
9937: modell[k].maintype= FTYPE;
9938: TvarF[ncovf]=Tvar[k];
9939: TvarFind[ncovf]=k;
1.230 brouard 9940: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.231 brouard 9941: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.240 brouard 9942: }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 9943: Fixed[k]= 0;
9944: Dummy[k]= 1;
1.230 brouard 9945: nqfveff++;
1.234 brouard 9946: modell[k].maintype= FTYPE;
9947: modell[k].subtype= FQ;
9948: nsq++;
9949: TvarsQ[nsq]=Tvar[k];
9950: TvarsQind[nsq]=k;
1.232 brouard 9951: ncovf++;
1.234 brouard 9952: TvarF[ncovf]=Tvar[k];
9953: TvarFind[ncovf]=k;
1.231 brouard 9954: 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 9955: 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 9956: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.227 brouard 9957: Fixed[k]= 1;
9958: Dummy[k]= 0;
1.225 brouard 9959: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 9960: modell[k].maintype= VTYPE;
9961: modell[k].subtype= VD;
9962: nsd++;
9963: TvarsD[nsd]=Tvar[k];
9964: TvarsDind[nsd]=k;
9965: ncovv++; /* Only simple time varying variables */
9966: TvarV[ncovv]=Tvar[k];
1.242 brouard 9967: 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 9968: 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 */
9969: 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 9970: 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);
9971: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 9972: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.234 brouard 9973: Fixed[k]= 1;
9974: Dummy[k]= 1;
9975: nqtveff++;
9976: modell[k].maintype= VTYPE;
9977: modell[k].subtype= VQ;
9978: ncovv++; /* Only simple time varying variables */
9979: nsq++;
9980: TvarsQ[nsq]=Tvar[k];
9981: TvarsQind[nsq]=k;
9982: TvarV[ncovv]=Tvar[k];
1.242 brouard 9983: 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 9984: 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 */
9985: 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 9986: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
9987: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
9988: 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 9989: printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv);
1.227 brouard 9990: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 9991: ncova++;
9992: TvarA[ncova]=Tvar[k];
9993: TvarAind[ncova]=k;
1.231 brouard 9994: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 9995: Fixed[k]= 2;
9996: Dummy[k]= 2;
9997: modell[k].maintype= ATYPE;
9998: modell[k].subtype= APFD;
9999: /* ncoveff++; */
1.227 brouard 10000: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 10001: Fixed[k]= 2;
10002: Dummy[k]= 3;
10003: modell[k].maintype= ATYPE;
10004: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
10005: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 10006: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 10007: Fixed[k]= 3;
10008: Dummy[k]= 2;
10009: modell[k].maintype= ATYPE;
10010: modell[k].subtype= APVD; /* Product age * varying dummy */
10011: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 10012: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 10013: Fixed[k]= 3;
10014: Dummy[k]= 3;
10015: modell[k].maintype= ATYPE;
10016: modell[k].subtype= APVQ; /* Product age * varying quantitative */
10017: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 10018: }
10019: }else if (Typevar[k] == 2) { /* product without age */
10020: k1=Tposprod[k];
10021: if(Tvard[k1][1] <=ncovcol){
1.240 brouard 10022: if(Tvard[k1][2] <=ncovcol){
10023: Fixed[k]= 1;
10024: Dummy[k]= 0;
10025: modell[k].maintype= FTYPE;
10026: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
10027: ncovf++; /* Fixed variables without age */
10028: TvarF[ncovf]=Tvar[k];
10029: TvarFind[ncovf]=k;
10030: }else if(Tvard[k1][2] <=ncovcol+nqv){
10031: Fixed[k]= 0; /* or 2 ?*/
10032: Dummy[k]= 1;
10033: modell[k].maintype= FTYPE;
10034: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
10035: ncovf++; /* Varying variables without age */
10036: TvarF[ncovf]=Tvar[k];
10037: TvarFind[ncovf]=k;
10038: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10039: Fixed[k]= 1;
10040: Dummy[k]= 0;
10041: modell[k].maintype= VTYPE;
10042: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
10043: ncovv++; /* Varying variables without age */
10044: TvarV[ncovv]=Tvar[k];
10045: TvarVind[ncovv]=k;
10046: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10047: Fixed[k]= 1;
10048: Dummy[k]= 1;
10049: modell[k].maintype= VTYPE;
10050: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
10051: ncovv++; /* Varying variables without age */
10052: TvarV[ncovv]=Tvar[k];
10053: TvarVind[ncovv]=k;
10054: }
1.227 brouard 10055: }else if(Tvard[k1][1] <=ncovcol+nqv){
1.240 brouard 10056: if(Tvard[k1][2] <=ncovcol){
10057: Fixed[k]= 0; /* or 2 ?*/
10058: Dummy[k]= 1;
10059: modell[k].maintype= FTYPE;
10060: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
10061: ncovf++; /* Fixed variables without age */
10062: TvarF[ncovf]=Tvar[k];
10063: TvarFind[ncovf]=k;
10064: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10065: Fixed[k]= 1;
10066: Dummy[k]= 1;
10067: modell[k].maintype= VTYPE;
10068: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
10069: ncovv++; /* Varying variables without age */
10070: TvarV[ncovv]=Tvar[k];
10071: TvarVind[ncovv]=k;
10072: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10073: Fixed[k]= 1;
10074: Dummy[k]= 1;
10075: modell[k].maintype= VTYPE;
10076: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
10077: ncovv++; /* Varying variables without age */
10078: TvarV[ncovv]=Tvar[k];
10079: TvarVind[ncovv]=k;
10080: ncovv++; /* Varying variables without age */
10081: TvarV[ncovv]=Tvar[k];
10082: TvarVind[ncovv]=k;
10083: }
1.227 brouard 10084: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){
1.240 brouard 10085: if(Tvard[k1][2] <=ncovcol){
10086: Fixed[k]= 1;
10087: Dummy[k]= 1;
10088: modell[k].maintype= VTYPE;
10089: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
10090: ncovv++; /* Varying variables without age */
10091: TvarV[ncovv]=Tvar[k];
10092: TvarVind[ncovv]=k;
10093: }else if(Tvard[k1][2] <=ncovcol+nqv){
10094: Fixed[k]= 1;
10095: Dummy[k]= 1;
10096: modell[k].maintype= VTYPE;
10097: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
10098: ncovv++; /* Varying variables without age */
10099: TvarV[ncovv]=Tvar[k];
10100: TvarVind[ncovv]=k;
10101: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10102: Fixed[k]= 1;
10103: Dummy[k]= 0;
10104: modell[k].maintype= VTYPE;
10105: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
10106: ncovv++; /* Varying variables without age */
10107: TvarV[ncovv]=Tvar[k];
10108: TvarVind[ncovv]=k;
10109: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10110: Fixed[k]= 1;
10111: Dummy[k]= 1;
10112: modell[k].maintype= VTYPE;
10113: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
10114: ncovv++; /* Varying variables without age */
10115: TvarV[ncovv]=Tvar[k];
10116: TvarVind[ncovv]=k;
10117: }
1.227 brouard 10118: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 10119: if(Tvard[k1][2] <=ncovcol){
10120: Fixed[k]= 1;
10121: Dummy[k]= 1;
10122: modell[k].maintype= VTYPE;
10123: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
10124: ncovv++; /* Varying variables without age */
10125: TvarV[ncovv]=Tvar[k];
10126: TvarVind[ncovv]=k;
10127: }else if(Tvard[k1][2] <=ncovcol+nqv){
10128: Fixed[k]= 1;
10129: Dummy[k]= 1;
10130: modell[k].maintype= VTYPE;
10131: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
10132: ncovv++; /* Varying variables without age */
10133: TvarV[ncovv]=Tvar[k];
10134: TvarVind[ncovv]=k;
10135: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10136: Fixed[k]= 1;
10137: Dummy[k]= 1;
10138: modell[k].maintype= VTYPE;
10139: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
10140: ncovv++; /* Varying variables without age */
10141: TvarV[ncovv]=Tvar[k];
10142: TvarVind[ncovv]=k;
10143: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10144: Fixed[k]= 1;
10145: Dummy[k]= 1;
10146: modell[k].maintype= VTYPE;
10147: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
10148: ncovv++; /* Varying variables without age */
10149: TvarV[ncovv]=Tvar[k];
10150: TvarVind[ncovv]=k;
10151: }
1.227 brouard 10152: }else{
1.240 brouard 10153: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
10154: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
10155: } /*end k1*/
1.225 brouard 10156: }else{
1.226 brouard 10157: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
10158: 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 10159: }
1.227 brouard 10160: 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 10161: printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype);
1.227 brouard 10162: 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]);
10163: }
10164: /* Searching for doublons in the model */
10165: for(k1=1; k1<= cptcovt;k1++){
10166: for(k2=1; k2 <k1;k2++){
1.285 brouard 10167: /* if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){ */
10168: if((Typevar[k1]==Typevar[k2]) && (Fixed[k1]==Fixed[k2]) && (Dummy[k1]==Dummy[k2] )){
1.234 brouard 10169: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
10170: if(Tvar[k1]==Tvar[k2]){
1.285 brouard 10171: printf("Error duplication in the model=%s at positions (+) %d and %d, Tvar[%d]=V%d, Tvar[%d]=V%d, Typevar=%d, Fixed=%d, Dummy=%d\n", model, k1,k2, k1, Tvar[k1], k2, Tvar[k2],Typevar[k1],Fixed[k1],Dummy[k1]);
10172: fprintf(ficlog,"Error duplication in the model=%s at positions (+) %d and %d, Tvar[%d]=V%d, Tvar[%d]=V%d, Typevar=%d, Fixed=%d, Dummy=%d\n", model, k1,k2, k1, Tvar[k1], k2, Tvar[k2],Typevar[k1],Fixed[k1],Dummy[k1]); fflush(ficlog);
1.234 brouard 10173: return(1);
10174: }
10175: }else if (Typevar[k1] ==2){
10176: k3=Tposprod[k1];
10177: k4=Tposprod[k2];
10178: 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])) ){
10179: 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]]);
10180: 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);
10181: return(1);
10182: }
10183: }
1.227 brouard 10184: }
10185: }
1.225 brouard 10186: }
10187: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
10188: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 10189: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
10190: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.137 brouard 10191: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 10192: /*endread:*/
1.225 brouard 10193: printf("Exiting decodemodel: ");
10194: return (1);
1.136 brouard 10195: }
10196:
1.169 brouard 10197: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 10198: {/* Check ages at death */
1.136 brouard 10199: int i, m;
1.218 brouard 10200: int firstone=0;
10201:
1.136 brouard 10202: for (i=1; i<=imx; i++) {
10203: for(m=2; (m<= maxwav); m++) {
10204: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
10205: anint[m][i]=9999;
1.216 brouard 10206: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
10207: s[m][i]=-1;
1.136 brouard 10208: }
10209: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 10210: *nberr = *nberr + 1;
1.218 brouard 10211: if(firstone == 0){
10212: firstone=1;
1.260 brouard 10213: 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 10214: }
1.262 brouard 10215: 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 10216: s[m][i]=-1; /* Droping the death status */
1.136 brouard 10217: }
10218: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 10219: (*nberr)++;
1.259 brouard 10220: 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 10221: 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 10222: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 10223: }
10224: }
10225: }
10226:
10227: for (i=1; i<=imx; i++) {
10228: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
10229: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 10230: 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 10231: if (s[m][i] >= nlstate+1) {
1.169 brouard 10232: if(agedc[i]>0){
10233: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 10234: agev[m][i]=agedc[i];
1.214 brouard 10235: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 10236: }else {
1.136 brouard 10237: if ((int)andc[i]!=9999){
10238: nbwarn++;
10239: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
10240: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
10241: agev[m][i]=-1;
10242: }
10243: }
1.169 brouard 10244: } /* agedc > 0 */
1.214 brouard 10245: } /* end if */
1.136 brouard 10246: else if(s[m][i] !=9){ /* Standard case, age in fractional
10247: years but with the precision of a month */
10248: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
10249: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
10250: agev[m][i]=1;
10251: else if(agev[m][i] < *agemin){
10252: *agemin=agev[m][i];
10253: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
10254: }
10255: else if(agev[m][i] >*agemax){
10256: *agemax=agev[m][i];
1.156 brouard 10257: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 10258: }
10259: /*agev[m][i]=anint[m][i]-annais[i];*/
10260: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 10261: } /* en if 9*/
1.136 brouard 10262: else { /* =9 */
1.214 brouard 10263: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 10264: agev[m][i]=1;
10265: s[m][i]=-1;
10266: }
10267: }
1.214 brouard 10268: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 10269: agev[m][i]=1;
1.214 brouard 10270: else{
10271: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
10272: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
10273: agev[m][i]=0;
10274: }
10275: } /* End for lastpass */
10276: }
1.136 brouard 10277:
10278: for (i=1; i<=imx; i++) {
10279: for(m=firstpass; (m<=lastpass); m++){
10280: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 10281: (*nberr)++;
1.136 brouard 10282: 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);
10283: 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);
10284: return 1;
10285: }
10286: }
10287: }
10288:
10289: /*for (i=1; i<=imx; i++){
10290: for (m=firstpass; (m<lastpass); m++){
10291: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
10292: }
10293:
10294: }*/
10295:
10296:
1.139 brouard 10297: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
10298: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 10299:
10300: return (0);
1.164 brouard 10301: /* endread:*/
1.136 brouard 10302: printf("Exiting calandcheckages: ");
10303: return (1);
10304: }
10305:
1.172 brouard 10306: #if defined(_MSC_VER)
10307: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
10308: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
10309: //#include "stdafx.h"
10310: //#include <stdio.h>
10311: //#include <tchar.h>
10312: //#include <windows.h>
10313: //#include <iostream>
10314: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
10315:
10316: LPFN_ISWOW64PROCESS fnIsWow64Process;
10317:
10318: BOOL IsWow64()
10319: {
10320: BOOL bIsWow64 = FALSE;
10321:
10322: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
10323: // (HANDLE, PBOOL);
10324:
10325: //LPFN_ISWOW64PROCESS fnIsWow64Process;
10326:
10327: HMODULE module = GetModuleHandle(_T("kernel32"));
10328: const char funcName[] = "IsWow64Process";
10329: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
10330: GetProcAddress(module, funcName);
10331:
10332: if (NULL != fnIsWow64Process)
10333: {
10334: if (!fnIsWow64Process(GetCurrentProcess(),
10335: &bIsWow64))
10336: //throw std::exception("Unknown error");
10337: printf("Unknown error\n");
10338: }
10339: return bIsWow64 != FALSE;
10340: }
10341: #endif
1.177 brouard 10342:
1.191 brouard 10343: void syscompilerinfo(int logged)
1.292 brouard 10344: {
10345: #include <stdint.h>
10346:
10347: /* #include "syscompilerinfo.h"*/
1.185 brouard 10348: /* command line Intel compiler 32bit windows, XP compatible:*/
10349: /* /GS /W3 /Gy
10350: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
10351: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
10352: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 10353: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
10354: */
10355: /* 64 bits */
1.185 brouard 10356: /*
10357: /GS /W3 /Gy
10358: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
10359: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
10360: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
10361: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
10362: /* Optimization are useless and O3 is slower than O2 */
10363: /*
10364: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
10365: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
10366: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
10367: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
10368: */
1.186 brouard 10369: /* Link is */ /* /OUT:"visual studio
1.185 brouard 10370: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
10371: /PDB:"visual studio
10372: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
10373: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
10374: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
10375: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
10376: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
10377: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
10378: uiAccess='false'"
10379: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
10380: /NOLOGO /TLBID:1
10381: */
1.292 brouard 10382:
10383:
1.177 brouard 10384: #if defined __INTEL_COMPILER
1.178 brouard 10385: #if defined(__GNUC__)
10386: struct utsname sysInfo; /* For Intel on Linux and OS/X */
10387: #endif
1.177 brouard 10388: #elif defined(__GNUC__)
1.179 brouard 10389: #ifndef __APPLE__
1.174 brouard 10390: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 10391: #endif
1.177 brouard 10392: struct utsname sysInfo;
1.178 brouard 10393: int cross = CROSS;
10394: if (cross){
10395: printf("Cross-");
1.191 brouard 10396: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 10397: }
1.174 brouard 10398: #endif
10399:
1.191 brouard 10400: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 10401: #if defined(__clang__)
1.191 brouard 10402: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 10403: #endif
10404: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 10405: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 10406: #endif
10407: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 10408: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 10409: #endif
10410: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 10411: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 10412: #endif
10413: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 10414: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 10415: #endif
10416: #if defined(_MSC_VER)
1.191 brouard 10417: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 10418: #endif
10419: #if defined(__PGI)
1.191 brouard 10420: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 10421: #endif
10422: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 10423: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 10424: #endif
1.191 brouard 10425: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 10426:
1.167 brouard 10427: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
10428: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
10429: // Windows (x64 and x86)
1.191 brouard 10430: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 10431: #elif __unix__ // all unices, not all compilers
10432: // Unix
1.191 brouard 10433: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 10434: #elif __linux__
10435: // linux
1.191 brouard 10436: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 10437: #elif __APPLE__
1.174 brouard 10438: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 10439: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 10440: #endif
10441:
10442: /* __MINGW32__ */
10443: /* __CYGWIN__ */
10444: /* __MINGW64__ */
10445: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
10446: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
10447: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
10448: /* _WIN64 // Defined for applications for Win64. */
10449: /* _M_X64 // Defined for compilations that target x64 processors. */
10450: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 10451:
1.167 brouard 10452: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 10453: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 10454: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 10455: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 10456: #else
1.191 brouard 10457: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 10458: #endif
10459:
1.169 brouard 10460: #if defined(__GNUC__)
10461: # if defined(__GNUC_PATCHLEVEL__)
10462: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10463: + __GNUC_MINOR__ * 100 \
10464: + __GNUC_PATCHLEVEL__)
10465: # else
10466: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10467: + __GNUC_MINOR__ * 100)
10468: # endif
1.174 brouard 10469: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 10470: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 10471:
10472: if (uname(&sysInfo) != -1) {
10473: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 10474: 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 10475: }
10476: else
10477: perror("uname() error");
1.179 brouard 10478: //#ifndef __INTEL_COMPILER
10479: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 10480: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 10481: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 10482: #endif
1.169 brouard 10483: #endif
1.172 brouard 10484:
1.286 brouard 10485: // void main ()
1.172 brouard 10486: // {
1.169 brouard 10487: #if defined(_MSC_VER)
1.174 brouard 10488: if (IsWow64()){
1.191 brouard 10489: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
10490: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 10491: }
10492: else{
1.191 brouard 10493: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
10494: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 10495: }
1.172 brouard 10496: // printf("\nPress Enter to continue...");
10497: // getchar();
10498: // }
10499:
1.169 brouard 10500: #endif
10501:
1.167 brouard 10502:
1.219 brouard 10503: }
1.136 brouard 10504:
1.219 brouard 10505: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.288 brouard 10506: /*--------------- Prevalence limit (forward period or forward stable prevalence) --------------*/
1.235 brouard 10507: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 10508: /* double ftolpl = 1.e-10; */
1.180 brouard 10509: double age, agebase, agelim;
1.203 brouard 10510: double tot;
1.180 brouard 10511:
1.202 brouard 10512: strcpy(filerespl,"PL_");
10513: strcat(filerespl,fileresu);
10514: if((ficrespl=fopen(filerespl,"w"))==NULL) {
1.288 brouard 10515: printf("Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
10516: fprintf(ficlog,"Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
1.202 brouard 10517: }
1.288 brouard 10518: printf("\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
10519: fprintf(ficlog,"\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 10520: pstamp(ficrespl);
1.288 brouard 10521: fprintf(ficrespl,"# Forward period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 10522: fprintf(ficrespl,"#Age ");
10523: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
10524: fprintf(ficrespl,"\n");
1.180 brouard 10525:
1.219 brouard 10526: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 10527:
1.219 brouard 10528: agebase=ageminpar;
10529: agelim=agemaxpar;
1.180 brouard 10530:
1.227 brouard 10531: /* i1=pow(2,ncoveff); */
1.234 brouard 10532: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 10533: if (cptcovn < 1){i1=1;}
1.180 brouard 10534:
1.238 brouard 10535: for(k=1; k<=i1;k++){ /* For each combination k of dummy covariates in the model */
10536: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 10537: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10538: continue;
1.235 brouard 10539:
1.238 brouard 10540: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10541: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
10542: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
10543: /* k=k+1; */
10544: /* to clean */
10545: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10546: fprintf(ficrespl,"#******");
10547: printf("#******");
10548: fprintf(ficlog,"#******");
10549: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10550: fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); /* Here problem for varying dummy*/
10551: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10552: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10553: }
10554: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
10555: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10556: fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10557: fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10558: }
10559: fprintf(ficrespl,"******\n");
10560: printf("******\n");
10561: fprintf(ficlog,"******\n");
10562: if(invalidvarcomb[k]){
10563: printf("\nCombination (%d) ignored because no case \n",k);
10564: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
10565: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
10566: continue;
10567: }
1.219 brouard 10568:
1.238 brouard 10569: fprintf(ficrespl,"#Age ");
10570: for(j=1;j<=cptcoveff;j++) {
10571: fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10572: }
10573: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
10574: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 10575:
1.238 brouard 10576: for (age=agebase; age<=agelim; age++){
10577: /* for (age=agebase; age<=agebase; age++){ */
10578: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres);
10579: fprintf(ficrespl,"%.0f ",age );
10580: for(j=1;j<=cptcoveff;j++)
10581: fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10582: tot=0.;
10583: for(i=1; i<=nlstate;i++){
10584: tot += prlim[i][i];
10585: fprintf(ficrespl," %.5f", prlim[i][i]);
10586: }
10587: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
10588: } /* Age */
10589: /* was end of cptcod */
10590: } /* cptcov */
10591: } /* nres */
1.219 brouard 10592: return 0;
1.180 brouard 10593: }
10594:
1.218 brouard 10595: int back_prevalence_limit(double *p, double **bprlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp, double dateprev1,double dateprev2, int firstpass, int lastpass, int mobilavproj){
1.288 brouard 10596: /*--------------- Back Prevalence limit (backward stable prevalence) --------------*/
1.218 brouard 10597:
10598: /* Computes the back prevalence limit for any combination of covariate values
10599: * at any age between ageminpar and agemaxpar
10600: */
1.235 brouard 10601: int i, j, k, i1, nres=0 ;
1.217 brouard 10602: /* double ftolpl = 1.e-10; */
10603: double age, agebase, agelim;
10604: double tot;
1.218 brouard 10605: /* double ***mobaverage; */
10606: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 10607:
10608: strcpy(fileresplb,"PLB_");
10609: strcat(fileresplb,fileresu);
10610: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
1.288 brouard 10611: printf("Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
10612: fprintf(ficlog,"Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
1.217 brouard 10613: }
1.288 brouard 10614: printf("Computing backward prevalence: result on file '%s' \n", fileresplb);
10615: fprintf(ficlog,"Computing backward prevalence: result on file '%s' \n", fileresplb);
1.217 brouard 10616: pstamp(ficresplb);
1.288 brouard 10617: fprintf(ficresplb,"# Backward prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.217 brouard 10618: fprintf(ficresplb,"#Age ");
10619: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
10620: fprintf(ficresplb,"\n");
10621:
1.218 brouard 10622:
10623: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
10624:
10625: agebase=ageminpar;
10626: agelim=agemaxpar;
10627:
10628:
1.227 brouard 10629: i1=pow(2,cptcoveff);
1.218 brouard 10630: if (cptcovn < 1){i1=1;}
1.227 brouard 10631:
1.238 brouard 10632: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10633: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 10634: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10635: continue;
10636: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10637: fprintf(ficresplb,"#******");
10638: printf("#******");
10639: fprintf(ficlog,"#******");
10640: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10641: fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10642: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10643: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10644: }
10645: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
10646: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10647: fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10648: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10649: }
10650: fprintf(ficresplb,"******\n");
10651: printf("******\n");
10652: fprintf(ficlog,"******\n");
10653: if(invalidvarcomb[k]){
10654: printf("\nCombination (%d) ignored because no cases \n",k);
10655: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
10656: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
10657: continue;
10658: }
1.218 brouard 10659:
1.238 brouard 10660: fprintf(ficresplb,"#Age ");
10661: for(j=1;j<=cptcoveff;j++) {
10662: fprintf(ficresplb,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10663: }
10664: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
10665: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 10666:
10667:
1.238 brouard 10668: for (age=agebase; age<=agelim; age++){
10669: /* for (age=agebase; age<=agebase; age++){ */
10670: if(mobilavproj > 0){
10671: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
10672: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 10673: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 10674: }else if (mobilavproj == 0){
10675: 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);
10676: 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);
10677: exit(1);
10678: }else{
10679: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 10680: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 10681: /* printf("TOTOT\n"); */
10682: /* exit(1); */
1.238 brouard 10683: }
10684: fprintf(ficresplb,"%.0f ",age );
10685: for(j=1;j<=cptcoveff;j++)
10686: fprintf(ficresplb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10687: tot=0.;
10688: for(i=1; i<=nlstate;i++){
10689: tot += bprlim[i][i];
10690: fprintf(ficresplb," %.5f", bprlim[i][i]);
10691: }
10692: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
10693: } /* Age */
10694: /* was end of cptcod */
1.255 brouard 10695: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.238 brouard 10696: } /* end of any combination */
10697: } /* end of nres */
1.218 brouard 10698: /* hBijx(p, bage, fage); */
10699: /* fclose(ficrespijb); */
10700:
10701: return 0;
1.217 brouard 10702: }
1.218 brouard 10703:
1.180 brouard 10704: int hPijx(double *p, int bage, int fage){
10705: /*------------- h Pij x at various ages ------------*/
10706:
10707: int stepsize;
10708: int agelim;
10709: int hstepm;
10710: int nhstepm;
1.235 brouard 10711: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 10712:
10713: double agedeb;
10714: double ***p3mat;
10715:
1.201 brouard 10716: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
1.180 brouard 10717: if((ficrespij=fopen(filerespij,"w"))==NULL) {
10718: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
10719: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
10720: }
10721: printf("Computing pij: result on file '%s' \n", filerespij);
10722: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
10723:
10724: stepsize=(int) (stepm+YEARM-1)/YEARM;
10725: /*if (stepm<=24) stepsize=2;*/
10726:
10727: agelim=AGESUP;
10728: hstepm=stepsize*YEARM; /* Every year of age */
10729: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
1.218 brouard 10730:
1.180 brouard 10731: /* hstepm=1; aff par mois*/
10732: pstamp(ficrespij);
10733: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
1.227 brouard 10734: i1= pow(2,cptcoveff);
1.218 brouard 10735: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10736: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
10737: /* k=k+1; */
1.235 brouard 10738: for(nres=1; nres <= nresult; nres++) /* For each resultline */
10739: for(k=1; k<=i1;k++){
1.253 brouard 10740: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 10741: continue;
1.183 brouard 10742: fprintf(ficrespij,"\n#****** ");
1.227 brouard 10743: for(j=1;j<=cptcoveff;j++)
1.198 brouard 10744: fprintf(ficrespij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 10745: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
10746: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10747: fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10748: }
1.183 brouard 10749: fprintf(ficrespij,"******\n");
10750:
10751: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
10752: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
10753: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
10754:
10755: /* nhstepm=nhstepm*YEARM; aff par mois*/
1.180 brouard 10756:
1.183 brouard 10757: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10758: oldm=oldms;savm=savms;
1.235 brouard 10759: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.183 brouard 10760: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
10761: for(i=1; i<=nlstate;i++)
10762: for(j=1; j<=nlstate+ndeath;j++)
10763: fprintf(ficrespij," %1d-%1d",i,j);
10764: fprintf(ficrespij,"\n");
10765: for (h=0; h<=nhstepm; h++){
10766: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
10767: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.180 brouard 10768: for(i=1; i<=nlstate;i++)
10769: for(j=1; j<=nlstate+ndeath;j++)
1.183 brouard 10770: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.180 brouard 10771: fprintf(ficrespij,"\n");
10772: }
1.183 brouard 10773: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10774: fprintf(ficrespij,"\n");
10775: }
1.180 brouard 10776: /*}*/
10777: }
1.218 brouard 10778: return 0;
1.180 brouard 10779: }
1.218 brouard 10780:
10781: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 10782: /*------------- h Bij x at various ages ------------*/
10783:
10784: int stepsize;
1.218 brouard 10785: /* int agelim; */
10786: int ageminl;
1.217 brouard 10787: int hstepm;
10788: int nhstepm;
1.238 brouard 10789: int h, i, i1, j, k, nres;
1.218 brouard 10790:
1.217 brouard 10791: double agedeb;
10792: double ***p3mat;
1.218 brouard 10793:
10794: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
10795: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
10796: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
10797: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
10798: }
10799: printf("Computing pij back: result on file '%s' \n", filerespijb);
10800: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
10801:
10802: stepsize=(int) (stepm+YEARM-1)/YEARM;
10803: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 10804:
1.218 brouard 10805: /* agelim=AGESUP; */
1.289 brouard 10806: ageminl=AGEINF; /* was 30 */
1.218 brouard 10807: hstepm=stepsize*YEARM; /* Every year of age */
10808: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
10809:
10810: /* hstepm=1; aff par mois*/
10811: pstamp(ficrespijb);
1.255 brouard 10812: 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 10813: i1= pow(2,cptcoveff);
1.218 brouard 10814: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10815: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
10816: /* k=k+1; */
1.238 brouard 10817: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10818: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 10819: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10820: continue;
10821: fprintf(ficrespijb,"\n#****** ");
10822: for(j=1;j<=cptcoveff;j++)
10823: fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10824: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
10825: fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10826: }
10827: fprintf(ficrespijb,"******\n");
1.264 brouard 10828: if(invalidvarcomb[k]){ /* Is it necessary here? */
1.238 brouard 10829: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
10830: continue;
10831: }
10832:
10833: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
10834: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
10835: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
1.297 brouard 10836: nhstepm=(int) rint((agedeb-ageminl)*YEARM/stepm+0.1)-1; /* Typically 20 years = 20*12/6=40 or 55*12/24=27.5-1.1=>27 */
10837: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 or 28*/
1.238 brouard 10838:
10839: /* nhstepm=nhstepm*YEARM; aff par mois*/
10840:
1.266 brouard 10841: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
10842: /* and memory limitations if stepm is small */
10843:
1.238 brouard 10844: /* oldm=oldms;savm=savms; */
10845: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.267 brouard 10846: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.238 brouard 10847: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
1.255 brouard 10848: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
1.217 brouard 10849: for(i=1; i<=nlstate;i++)
10850: for(j=1; j<=nlstate+ndeath;j++)
1.238 brouard 10851: fprintf(ficrespijb," %1d-%1d",i,j);
1.217 brouard 10852: fprintf(ficrespijb,"\n");
1.238 brouard 10853: for (h=0; h<=nhstepm; h++){
10854: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
10855: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
10856: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
10857: for(i=1; i<=nlstate;i++)
10858: for(j=1; j<=nlstate+ndeath;j++)
10859: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);
10860: fprintf(ficrespijb,"\n");
10861: }
10862: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10863: fprintf(ficrespijb,"\n");
10864: } /* end age deb */
10865: } /* end combination */
10866: } /* end nres */
1.218 brouard 10867: return 0;
10868: } /* hBijx */
1.217 brouard 10869:
1.180 brouard 10870:
1.136 brouard 10871: /***********************************************/
10872: /**************** Main Program *****************/
10873: /***********************************************/
10874:
10875: int main(int argc, char *argv[])
10876: {
10877: #ifdef GSL
10878: const gsl_multimin_fminimizer_type *T;
10879: size_t iteri = 0, it;
10880: int rval = GSL_CONTINUE;
10881: int status = GSL_SUCCESS;
10882: double ssval;
10883: #endif
10884: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.290 brouard 10885: int i,j, k, iter=0,m,size=100, cptcod; /* Suppressing because nobs */
10886: /* int i,j, k, n=MAXN,iter=0,m,size=100, cptcod; */
1.209 brouard 10887: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 10888: int jj, ll, li, lj, lk;
1.136 brouard 10889: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 10890: int num_filled;
1.136 brouard 10891: int itimes;
10892: int NDIM=2;
10893: int vpopbased=0;
1.235 brouard 10894: int nres=0;
1.258 brouard 10895: int endishere=0;
1.277 brouard 10896: int noffset=0;
1.274 brouard 10897: int ncurrv=0; /* Temporary variable */
10898:
1.164 brouard 10899: char ca[32], cb[32];
1.136 brouard 10900: /* FILE *fichtm; *//* Html File */
10901: /* FILE *ficgp;*/ /*Gnuplot File */
10902: struct stat info;
1.191 brouard 10903: double agedeb=0.;
1.194 brouard 10904:
10905: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 10906: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 10907:
1.165 brouard 10908: double fret;
1.191 brouard 10909: double dum=0.; /* Dummy variable */
1.136 brouard 10910: double ***p3mat;
1.218 brouard 10911: /* double ***mobaverage; */
1.164 brouard 10912:
10913: char line[MAXLINE];
1.197 brouard 10914: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
10915:
1.234 brouard 10916: char modeltemp[MAXLINE];
1.230 brouard 10917: char resultline[MAXLINE];
10918:
1.136 brouard 10919: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 10920: char *tok, *val; /* pathtot */
1.290 brouard 10921: int firstobs=1, lastobs=10; /* nobs = lastobs-firstobs declared globally ;*/
1.195 brouard 10922: int c, h , cpt, c2;
1.191 brouard 10923: int jl=0;
10924: int i1, j1, jk, stepsize=0;
1.194 brouard 10925: int count=0;
10926:
1.164 brouard 10927: int *tab;
1.136 brouard 10928: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.296 brouard 10929: /* double anprojd, mprojd, jprojd; /\* For eventual projections *\/ */
10930: /* double anprojf, mprojf, jprojf; */
10931: /* double jintmean,mintmean,aintmean; */
10932: int prvforecast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
10933: int prvbackcast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
10934: double yrfproj= 10.0; /* Number of years of forward projections */
10935: double yrbproj= 10.0; /* Number of years of backward projections */
10936: int prevbcast=0; /* defined as global for mlikeli and mle, replacing backcast */
1.136 brouard 10937: int mobilav=0,popforecast=0;
1.191 brouard 10938: int hstepm=0, nhstepm=0;
1.136 brouard 10939: int agemortsup;
10940: float sumlpop=0.;
10941: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
10942: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
10943:
1.191 brouard 10944: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 10945: double ftolpl=FTOL;
10946: double **prlim;
1.217 brouard 10947: double **bprlim;
1.136 brouard 10948: double ***param; /* Matrix of parameters */
1.251 brouard 10949: double ***paramstart; /* Matrix of starting parameter values */
10950: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 10951: double **matcov; /* Matrix of covariance */
1.203 brouard 10952: double **hess; /* Hessian matrix */
1.136 brouard 10953: double ***delti3; /* Scale */
10954: double *delti; /* Scale */
10955: double ***eij, ***vareij;
10956: double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 10957:
1.136 brouard 10958: double *epj, vepp;
1.164 brouard 10959:
1.273 brouard 10960: double dateprev1, dateprev2;
1.296 brouard 10961: double jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000, dateproj1=0, dateproj2=0, dateprojd=0, dateprojf=0;
10962: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000, dateback1=0, dateback2=0, datebackd=0, datebackf=0;
10963:
1.217 brouard 10964:
1.136 brouard 10965: double **ximort;
1.145 brouard 10966: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 10967: int *dcwave;
10968:
1.164 brouard 10969: char z[1]="c";
1.136 brouard 10970:
10971: /*char *strt;*/
10972: char strtend[80];
1.126 brouard 10973:
1.164 brouard 10974:
1.126 brouard 10975: /* setlocale (LC_ALL, ""); */
10976: /* bindtextdomain (PACKAGE, LOCALEDIR); */
10977: /* textdomain (PACKAGE); */
10978: /* setlocale (LC_CTYPE, ""); */
10979: /* setlocale (LC_MESSAGES, ""); */
10980:
10981: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 10982: rstart_time = time(NULL);
10983: /* (void) gettimeofday(&start_time,&tzp);*/
10984: start_time = *localtime(&rstart_time);
1.126 brouard 10985: curr_time=start_time;
1.157 brouard 10986: /*tml = *localtime(&start_time.tm_sec);*/
10987: /* strcpy(strstart,asctime(&tml)); */
10988: strcpy(strstart,asctime(&start_time));
1.126 brouard 10989:
10990: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 10991: /* tp.tm_sec = tp.tm_sec +86400; */
10992: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 10993: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
10994: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
10995: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 10996: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 10997: /* strt=asctime(&tmg); */
10998: /* printf("Time(after) =%s",strstart); */
10999: /* (void) time (&time_value);
11000: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
11001: * tm = *localtime(&time_value);
11002: * strstart=asctime(&tm);
11003: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
11004: */
11005:
11006: nberr=0; /* Number of errors and warnings */
11007: nbwarn=0;
1.184 brouard 11008: #ifdef WIN32
11009: _getcwd(pathcd, size);
11010: #else
1.126 brouard 11011: getcwd(pathcd, size);
1.184 brouard 11012: #endif
1.191 brouard 11013: syscompilerinfo(0);
1.196 brouard 11014: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 11015: if(argc <=1){
11016: printf("\nEnter the parameter file name: ");
1.205 brouard 11017: if(!fgets(pathr,FILENAMELENGTH,stdin)){
11018: printf("ERROR Empty parameter file name\n");
11019: goto end;
11020: }
1.126 brouard 11021: i=strlen(pathr);
11022: if(pathr[i-1]=='\n')
11023: pathr[i-1]='\0';
1.156 brouard 11024: i=strlen(pathr);
1.205 brouard 11025: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 11026: pathr[i-1]='\0';
1.205 brouard 11027: }
11028: i=strlen(pathr);
11029: if( i==0 ){
11030: printf("ERROR Empty parameter file name\n");
11031: goto end;
11032: }
11033: for (tok = pathr; tok != NULL; ){
1.126 brouard 11034: printf("Pathr |%s|\n",pathr);
11035: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
11036: printf("val= |%s| pathr=%s\n",val,pathr);
11037: strcpy (pathtot, val);
11038: if(pathr[0] == '\0') break; /* Dirty */
11039: }
11040: }
1.281 brouard 11041: else if (argc<=2){
11042: strcpy(pathtot,argv[1]);
11043: }
1.126 brouard 11044: else{
11045: strcpy(pathtot,argv[1]);
1.281 brouard 11046: strcpy(z,argv[2]);
11047: printf("\nargv[2]=%s z=%c\n",argv[2],z[0]);
1.126 brouard 11048: }
11049: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
11050: /*cygwin_split_path(pathtot,path,optionfile);
11051: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
11052: /* cutv(path,optionfile,pathtot,'\\');*/
11053:
11054: /* Split argv[0], imach program to get pathimach */
11055: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
11056: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
11057: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
11058: /* strcpy(pathimach,argv[0]); */
11059: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
11060: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
11061: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 11062: #ifdef WIN32
11063: _chdir(path); /* Can be a relative path */
11064: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
11065: #else
1.126 brouard 11066: chdir(path); /* Can be a relative path */
1.184 brouard 11067: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
11068: #endif
11069: printf("Current directory %s!\n",pathcd);
1.126 brouard 11070: strcpy(command,"mkdir ");
11071: strcat(command,optionfilefiname);
11072: if((outcmd=system(command)) != 0){
1.169 brouard 11073: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 11074: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
11075: /* fclose(ficlog); */
11076: /* exit(1); */
11077: }
11078: /* if((imk=mkdir(optionfilefiname))<0){ */
11079: /* perror("mkdir"); */
11080: /* } */
11081:
11082: /*-------- arguments in the command line --------*/
11083:
1.186 brouard 11084: /* Main Log file */
1.126 brouard 11085: strcat(filelog, optionfilefiname);
11086: strcat(filelog,".log"); /* */
11087: if((ficlog=fopen(filelog,"w"))==NULL) {
11088: printf("Problem with logfile %s\n",filelog);
11089: goto end;
11090: }
11091: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 11092: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 11093: fprintf(ficlog,"\nEnter the parameter file name: \n");
11094: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
11095: path=%s \n\
11096: optionfile=%s\n\
11097: optionfilext=%s\n\
1.156 brouard 11098: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 11099:
1.197 brouard 11100: syscompilerinfo(1);
1.167 brouard 11101:
1.126 brouard 11102: printf("Local time (at start):%s",strstart);
11103: fprintf(ficlog,"Local time (at start): %s",strstart);
11104: fflush(ficlog);
11105: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 11106: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 11107:
11108: /* */
11109: strcpy(fileres,"r");
11110: strcat(fileres, optionfilefiname);
1.201 brouard 11111: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 11112: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 11113: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 11114:
1.186 brouard 11115: /* Main ---------arguments file --------*/
1.126 brouard 11116:
11117: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 11118: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
11119: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 11120: fflush(ficlog);
1.149 brouard 11121: /* goto end; */
11122: exit(70);
1.126 brouard 11123: }
11124:
11125: strcpy(filereso,"o");
1.201 brouard 11126: strcat(filereso,fileresu);
1.126 brouard 11127: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
11128: printf("Problem with Output resultfile: %s\n", filereso);
11129: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
11130: fflush(ficlog);
11131: goto end;
11132: }
1.278 brouard 11133: /*-------- Rewriting parameter file ----------*/
11134: strcpy(rfileres,"r"); /* "Rparameterfile */
11135: strcat(rfileres,optionfilefiname); /* Parameter file first name */
11136: strcat(rfileres,"."); /* */
11137: strcat(rfileres,optionfilext); /* Other files have txt extension */
11138: if((ficres =fopen(rfileres,"w"))==NULL) {
11139: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
11140: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
11141: fflush(ficlog);
11142: goto end;
11143: }
11144: fprintf(ficres,"#IMaCh %s\n",version);
1.126 brouard 11145:
1.278 brouard 11146:
1.126 brouard 11147: /* Reads comments: lines beginning with '#' */
11148: numlinepar=0;
1.277 brouard 11149: /* Is it a BOM UTF-8 Windows file? */
11150: /* First parameter line */
1.197 brouard 11151: while(fgets(line, MAXLINE, ficpar)) {
1.277 brouard 11152: noffset=0;
11153: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
11154: {
11155: noffset=noffset+3;
11156: printf("# File is an UTF8 Bom.\n"); // 0xBF
11157: }
1.302 brouard 11158: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
11159: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
1.277 brouard 11160: {
11161: noffset=noffset+2;
11162: printf("# File is an UTF16BE BOM file\n");
11163: }
11164: else if( line[0] == 0 && line[1] == 0)
11165: {
11166: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
11167: noffset=noffset+4;
11168: printf("# File is an UTF16BE BOM file\n");
11169: }
11170: } else{
11171: ;/*printf(" Not a BOM file\n");*/
11172: }
11173:
1.197 brouard 11174: /* If line starts with a # it is a comment */
1.277 brouard 11175: if (line[noffset] == '#') {
1.197 brouard 11176: numlinepar++;
11177: fputs(line,stdout);
11178: fputs(line,ficparo);
1.278 brouard 11179: fputs(line,ficres);
1.197 brouard 11180: fputs(line,ficlog);
11181: continue;
11182: }else
11183: break;
11184: }
11185: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
11186: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
11187: if (num_filled != 5) {
11188: printf("Should be 5 parameters\n");
1.283 brouard 11189: fprintf(ficlog,"Should be 5 parameters\n");
1.197 brouard 11190: }
1.126 brouard 11191: numlinepar++;
1.197 brouard 11192: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.283 brouard 11193: fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
11194: fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
11195: fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.197 brouard 11196: }
11197: /* Second parameter line */
11198: while(fgets(line, MAXLINE, ficpar)) {
1.283 brouard 11199: /* while(fscanf(ficpar,"%[^\n]", line)) { */
11200: /* If line starts with a # it is a comment. Strangely fgets reads the EOL and fputs doesn't */
1.197 brouard 11201: if (line[0] == '#') {
11202: numlinepar++;
1.283 brouard 11203: printf("%s",line);
11204: fprintf(ficres,"%s",line);
11205: fprintf(ficparo,"%s",line);
11206: fprintf(ficlog,"%s",line);
1.197 brouard 11207: continue;
11208: }else
11209: break;
11210: }
1.223 brouard 11211: 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", \
11212: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
11213: if (num_filled != 11) {
11214: 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 11215: printf("but line=%s\n",line);
1.283 brouard 11216: fprintf(ficlog,"Not 11 parameters, for example:ftol=1.e-8 stepm=12 ncovcol=2 nqv=1 ntv=2 nqtv=1 nlstate=2 ndeath=1 maxwav=3 mle=1 weight=1\n");
11217: fprintf(ficlog,"but line=%s\n",line);
1.197 brouard 11218: }
1.286 brouard 11219: if( lastpass > maxwav){
11220: printf("Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
11221: fprintf(ficlog,"Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
11222: fflush(ficlog);
11223: goto end;
11224: }
11225: printf("ftol=%e stepm=%d ncovcol=%d nqv=%d ntv=%d nqtv=%d nlstate=%d ndeath=%d maxwav=%d mle=%d weight=%d\n",ftol, stepm, ncovcol, nqv, ntv, nqtv, nlstate, ndeath, maxwav, mle, weightopt);
1.283 brouard 11226: fprintf(ficparo,"ftol=%e stepm=%d ncovcol=%d nqv=%d ntv=%d nqtv=%d nlstate=%d ndeath=%d maxwav=%d mle=%d weight=%d\n",ftol, stepm, ncovcol, nqv, ntv, nqtv, nlstate, ndeath, maxwav, mle, weightopt);
1.286 brouard 11227: fprintf(ficres,"ftol=%e stepm=%d ncovcol=%d nqv=%d ntv=%d nqtv=%d nlstate=%d ndeath=%d maxwav=%d mle=%d weight=%d\n",ftol, stepm, ncovcol, nqv, ntv, nqtv, nlstate, ndeath, maxwav, 0, weightopt);
1.283 brouard 11228: fprintf(ficlog,"ftol=%e stepm=%d ncovcol=%d nqv=%d ntv=%d nqtv=%d nlstate=%d ndeath=%d maxwav=%d mle=%d weight=%d\n",ftol, stepm, ncovcol, nqv, ntv, nqtv, nlstate, ndeath, maxwav, mle, weightopt);
1.126 brouard 11229: }
1.203 brouard 11230: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 11231: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 11232: /* Third parameter line */
11233: while(fgets(line, MAXLINE, ficpar)) {
11234: /* If line starts with a # it is a comment */
11235: if (line[0] == '#') {
11236: numlinepar++;
1.283 brouard 11237: printf("%s",line);
11238: fprintf(ficres,"%s",line);
11239: fprintf(ficparo,"%s",line);
11240: fprintf(ficlog,"%s",line);
1.197 brouard 11241: continue;
11242: }else
11243: break;
11244: }
1.201 brouard 11245: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){
1.279 brouard 11246: if (num_filled != 1){
1.302 brouard 11247: printf("ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
11248: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
1.197 brouard 11249: model[0]='\0';
11250: goto end;
11251: }
11252: else{
11253: if (model[0]=='+'){
11254: for(i=1; i<=strlen(model);i++)
11255: modeltemp[i-1]=model[i];
1.201 brouard 11256: strcpy(model,modeltemp);
1.197 brouard 11257: }
11258: }
1.199 brouard 11259: /* printf(" model=1+age%s modeltemp= %s, model=%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 11260: printf("model=1+age+%s\n",model);fflush(stdout);
1.283 brouard 11261: fprintf(ficparo,"model=1+age+%s\n",model);fflush(stdout);
11262: fprintf(ficres,"model=1+age+%s\n",model);fflush(stdout);
11263: fprintf(ficlog,"model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 11264: }
11265: /* 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); */
11266: /* numlinepar=numlinepar+3; /\* In general *\/ */
11267: /* printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\nftol=%e stepm=%d ncovcol=%d nlstate=%d ndeath=%d maxwav=%d mle=%d weight=%d\nmodel=1+age+%s\n", title, datafile, lastobs, firstpass,lastpass,ftol, stepm, ncovcol, nlstate,ndeath, maxwav, mle, weightopt,model); */
1.283 brouard 11268: /* 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); */
11269: /* 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 11270: fflush(ficlog);
1.190 brouard 11271: /* if(model[0]=='#'|| model[0]== '\0'){ */
11272: if(model[0]=='#'){
1.279 brouard 11273: printf("Error in 'model' line: model should start with 'model=1+age+' and end without space \n \
11274: 'model=1+age+' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age' or \n \
11275: 'model=1+age+V1+V2' or 'model=1+age+V1+V2+V1*V2' etc. \n"); \
1.187 brouard 11276: if(mle != -1){
1.279 brouard 11277: 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 11278: exit(1);
11279: }
11280: }
1.126 brouard 11281: while((c=getc(ficpar))=='#' && c!= EOF){
11282: ungetc(c,ficpar);
11283: fgets(line, MAXLINE, ficpar);
11284: numlinepar++;
1.195 brouard 11285: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
11286: z[0]=line[1];
11287: }
11288: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 11289: fputs(line, stdout);
11290: //puts(line);
1.126 brouard 11291: fputs(line,ficparo);
11292: fputs(line,ficlog);
11293: }
11294: ungetc(c,ficpar);
11295:
11296:
1.290 brouard 11297: covar=matrix(0,NCOVMAX,firstobs,lastobs); /**< used in readdata */
11298: if(nqv>=1)coqvar=matrix(1,nqv,firstobs,lastobs); /**< Fixed quantitative covariate */
11299: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,firstobs,lastobs); /**< Time varying quantitative covariate */
11300: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,firstobs,lastobs); /**< Time varying covariate (dummy and quantitative)*/
1.136 brouard 11301: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
11302: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
11303: v1+v2*age+v2*v3 makes cptcovn = 3
11304: */
11305: if (strlen(model)>1)
1.187 brouard 11306: 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 11307: else
1.187 brouard 11308: ncovmodel=2; /* Constant and age */
1.133 brouard 11309: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
11310: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 11311: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
11312: 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);
11313: 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);
11314: fflush(stdout);
11315: fclose (ficlog);
11316: goto end;
11317: }
1.126 brouard 11318: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
11319: delti=delti3[1][1];
11320: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
11321: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 11322: /* We could also provide initial parameters values giving by simple logistic regression
11323: * only one way, that is without matrix product. We will have nlstate maximizations */
11324: /* for(i=1;i<nlstate;i++){ */
11325: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
11326: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
11327: /* } */
1.126 brouard 11328: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 11329: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
11330: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 11331: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
11332: fclose (ficparo);
11333: fclose (ficlog);
11334: goto end;
11335: exit(0);
1.220 brouard 11336: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 11337: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 11338: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
11339: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 11340: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
11341: matcov=matrix(1,npar,1,npar);
1.203 brouard 11342: hess=matrix(1,npar,1,npar);
1.220 brouard 11343: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 11344: /* Read guessed parameters */
1.126 brouard 11345: /* Reads comments: lines beginning with '#' */
11346: while((c=getc(ficpar))=='#' && c!= EOF){
11347: ungetc(c,ficpar);
11348: fgets(line, MAXLINE, ficpar);
11349: numlinepar++;
1.141 brouard 11350: fputs(line,stdout);
1.126 brouard 11351: fputs(line,ficparo);
11352: fputs(line,ficlog);
11353: }
11354: ungetc(c,ficpar);
11355:
11356: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 11357: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 11358: for(i=1; i <=nlstate; i++){
1.234 brouard 11359: j=0;
1.126 brouard 11360: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 11361: if(jj==i) continue;
11362: j++;
1.292 brouard 11363: while((c=getc(ficpar))=='#' && c!= EOF){
11364: ungetc(c,ficpar);
11365: fgets(line, MAXLINE, ficpar);
11366: numlinepar++;
11367: fputs(line,stdout);
11368: fputs(line,ficparo);
11369: fputs(line,ficlog);
11370: }
11371: ungetc(c,ficpar);
1.234 brouard 11372: fscanf(ficpar,"%1d%1d",&i1,&j1);
11373: if ((i1 != i) || (j1 != jj)){
11374: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 11375: It might be a problem of design; if ncovcol and the model are correct\n \
11376: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 11377: exit(1);
11378: }
11379: fprintf(ficparo,"%1d%1d",i1,j1);
11380: if(mle==1)
11381: printf("%1d%1d",i,jj);
11382: fprintf(ficlog,"%1d%1d",i,jj);
11383: for(k=1; k<=ncovmodel;k++){
11384: fscanf(ficpar," %lf",¶m[i][j][k]);
11385: if(mle==1){
11386: printf(" %lf",param[i][j][k]);
11387: fprintf(ficlog," %lf",param[i][j][k]);
11388: }
11389: else
11390: fprintf(ficlog," %lf",param[i][j][k]);
11391: fprintf(ficparo," %lf",param[i][j][k]);
11392: }
11393: fscanf(ficpar,"\n");
11394: numlinepar++;
11395: if(mle==1)
11396: printf("\n");
11397: fprintf(ficlog,"\n");
11398: fprintf(ficparo,"\n");
1.126 brouard 11399: }
11400: }
11401: fflush(ficlog);
1.234 brouard 11402:
1.251 brouard 11403: /* Reads parameters values */
1.126 brouard 11404: p=param[1][1];
1.251 brouard 11405: pstart=paramstart[1][1];
1.126 brouard 11406:
11407: /* Reads comments: lines beginning with '#' */
11408: while((c=getc(ficpar))=='#' && c!= EOF){
11409: ungetc(c,ficpar);
11410: fgets(line, MAXLINE, ficpar);
11411: numlinepar++;
1.141 brouard 11412: fputs(line,stdout);
1.126 brouard 11413: fputs(line,ficparo);
11414: fputs(line,ficlog);
11415: }
11416: ungetc(c,ficpar);
11417:
11418: for(i=1; i <=nlstate; i++){
11419: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 11420: fscanf(ficpar,"%1d%1d",&i1,&j1);
11421: if ( (i1-i) * (j1-j) != 0){
11422: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
11423: exit(1);
11424: }
11425: printf("%1d%1d",i,j);
11426: fprintf(ficparo,"%1d%1d",i1,j1);
11427: fprintf(ficlog,"%1d%1d",i1,j1);
11428: for(k=1; k<=ncovmodel;k++){
11429: fscanf(ficpar,"%le",&delti3[i][j][k]);
11430: printf(" %le",delti3[i][j][k]);
11431: fprintf(ficparo," %le",delti3[i][j][k]);
11432: fprintf(ficlog," %le",delti3[i][j][k]);
11433: }
11434: fscanf(ficpar,"\n");
11435: numlinepar++;
11436: printf("\n");
11437: fprintf(ficparo,"\n");
11438: fprintf(ficlog,"\n");
1.126 brouard 11439: }
11440: }
11441: fflush(ficlog);
1.234 brouard 11442:
1.145 brouard 11443: /* Reads covariance matrix */
1.126 brouard 11444: delti=delti3[1][1];
1.220 brouard 11445:
11446:
1.126 brouard 11447: /* 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 11448:
1.126 brouard 11449: /* Reads comments: lines beginning with '#' */
11450: while((c=getc(ficpar))=='#' && c!= EOF){
11451: ungetc(c,ficpar);
11452: fgets(line, MAXLINE, ficpar);
11453: numlinepar++;
1.141 brouard 11454: fputs(line,stdout);
1.126 brouard 11455: fputs(line,ficparo);
11456: fputs(line,ficlog);
11457: }
11458: ungetc(c,ficpar);
1.220 brouard 11459:
1.126 brouard 11460: matcov=matrix(1,npar,1,npar);
1.203 brouard 11461: hess=matrix(1,npar,1,npar);
1.131 brouard 11462: for(i=1; i <=npar; i++)
11463: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 11464:
1.194 brouard 11465: /* Scans npar lines */
1.126 brouard 11466: for(i=1; i <=npar; i++){
1.226 brouard 11467: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 11468: if(count != 3){
1.226 brouard 11469: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11470: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11471: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11472: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11473: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11474: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11475: exit(1);
1.220 brouard 11476: }else{
1.226 brouard 11477: if(mle==1)
11478: printf("%1d%1d%d",i1,j1,jk);
11479: }
11480: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
11481: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 11482: for(j=1; j <=i; j++){
1.226 brouard 11483: fscanf(ficpar," %le",&matcov[i][j]);
11484: if(mle==1){
11485: printf(" %.5le",matcov[i][j]);
11486: }
11487: fprintf(ficlog," %.5le",matcov[i][j]);
11488: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 11489: }
11490: fscanf(ficpar,"\n");
11491: numlinepar++;
11492: if(mle==1)
1.220 brouard 11493: printf("\n");
1.126 brouard 11494: fprintf(ficlog,"\n");
11495: fprintf(ficparo,"\n");
11496: }
1.194 brouard 11497: /* End of read covariance matrix npar lines */
1.126 brouard 11498: for(i=1; i <=npar; i++)
11499: for(j=i+1;j<=npar;j++)
1.226 brouard 11500: matcov[i][j]=matcov[j][i];
1.126 brouard 11501:
11502: if(mle==1)
11503: printf("\n");
11504: fprintf(ficlog,"\n");
11505:
11506: fflush(ficlog);
11507:
11508: } /* End of mle != -3 */
1.218 brouard 11509:
1.186 brouard 11510: /* Main data
11511: */
1.290 brouard 11512: nobs=lastobs-firstobs+1; /* was = lastobs;*/
11513: /* num=lvector(1,n); */
11514: /* moisnais=vector(1,n); */
11515: /* annais=vector(1,n); */
11516: /* moisdc=vector(1,n); */
11517: /* andc=vector(1,n); */
11518: /* weight=vector(1,n); */
11519: /* agedc=vector(1,n); */
11520: /* cod=ivector(1,n); */
11521: /* for(i=1;i<=n;i++){ */
11522: num=lvector(firstobs,lastobs);
11523: moisnais=vector(firstobs,lastobs);
11524: annais=vector(firstobs,lastobs);
11525: moisdc=vector(firstobs,lastobs);
11526: andc=vector(firstobs,lastobs);
11527: weight=vector(firstobs,lastobs);
11528: agedc=vector(firstobs,lastobs);
11529: cod=ivector(firstobs,lastobs);
11530: for(i=firstobs;i<=lastobs;i++){
1.234 brouard 11531: num[i]=0;
11532: moisnais[i]=0;
11533: annais[i]=0;
11534: moisdc[i]=0;
11535: andc[i]=0;
11536: agedc[i]=0;
11537: cod[i]=0;
11538: weight[i]=1.0; /* Equal weights, 1 by default */
11539: }
1.290 brouard 11540: mint=matrix(1,maxwav,firstobs,lastobs);
11541: anint=matrix(1,maxwav,firstobs,lastobs);
11542: s=imatrix(1,maxwav+1,firstobs,lastobs); /* s[i][j] health state for wave i and individual j */
1.126 brouard 11543: tab=ivector(1,NCOVMAX);
1.144 brouard 11544: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 11545: 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 11546:
1.136 brouard 11547: /* Reads data from file datafile */
11548: if (readdata(datafile, firstobs, lastobs, &imx)==1)
11549: goto end;
11550:
11551: /* Calculation of the number of parameters from char model */
1.234 brouard 11552: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 11553: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
11554: k=3 V4 Tvar[k=3]= 4 (from V4)
11555: k=2 V1 Tvar[k=2]= 1 (from V1)
11556: k=1 Tvar[1]=2 (from V2)
1.234 brouard 11557: */
11558:
11559: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
11560: TvarsDind=ivector(1,NCOVMAX); /* */
11561: TvarsD=ivector(1,NCOVMAX); /* */
11562: TvarsQind=ivector(1,NCOVMAX); /* */
11563: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 11564: TvarF=ivector(1,NCOVMAX); /* */
11565: TvarFind=ivector(1,NCOVMAX); /* */
11566: TvarV=ivector(1,NCOVMAX); /* */
11567: TvarVind=ivector(1,NCOVMAX); /* */
11568: TvarA=ivector(1,NCOVMAX); /* */
11569: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 11570: TvarFD=ivector(1,NCOVMAX); /* */
11571: TvarFDind=ivector(1,NCOVMAX); /* */
11572: TvarFQ=ivector(1,NCOVMAX); /* */
11573: TvarFQind=ivector(1,NCOVMAX); /* */
11574: TvarVD=ivector(1,NCOVMAX); /* */
11575: TvarVDind=ivector(1,NCOVMAX); /* */
11576: TvarVQ=ivector(1,NCOVMAX); /* */
11577: TvarVQind=ivector(1,NCOVMAX); /* */
11578:
1.230 brouard 11579: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 11580: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 11581: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
11582: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
11583: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.137 brouard 11584: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
11585: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
11586: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
11587: */
11588: /* For model-covariate k tells which data-covariate to use but
11589: because this model-covariate is a construction we invent a new column
11590: ncovcol + k1
11591: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
11592: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 11593: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
11594: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 11595: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
11596: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 11597: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 11598: */
1.145 brouard 11599: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
11600: 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 11601: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
11602: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.145 brouard 11603: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 11604: 4 covariates (3 plus signs)
11605: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
11606: */
1.230 brouard 11607: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 11608: * individual dummy, fixed or varying:
11609: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
11610: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 11611: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
11612: * V1 df, V2 qf, V3 & V4 dv, V5 qv
11613: * Tmodelind[1]@9={9,0,3,2,}*/
11614: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
11615: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 11616: * individual quantitative, fixed or varying:
11617: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
11618: * 3, 1, 0, 0, 0, 0, 0, 0},
11619: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.186 brouard 11620: /* Main decodemodel */
11621:
1.187 brouard 11622:
1.223 brouard 11623: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 11624: goto end;
11625:
1.137 brouard 11626: if((double)(lastobs-imx)/(double)imx > 1.10){
11627: nbwarn++;
11628: 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);
11629: 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);
11630: }
1.136 brouard 11631: /* if(mle==1){*/
1.137 brouard 11632: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
11633: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 11634: }
11635:
11636: /*-calculation of age at interview from date of interview and age at death -*/
11637: agev=matrix(1,maxwav,1,imx);
11638:
11639: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
11640: goto end;
11641:
1.126 brouard 11642:
1.136 brouard 11643: agegomp=(int)agemin;
1.290 brouard 11644: free_vector(moisnais,firstobs,lastobs);
11645: free_vector(annais,firstobs,lastobs);
1.126 brouard 11646: /* free_matrix(mint,1,maxwav,1,n);
11647: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 11648: /* free_vector(moisdc,1,n); */
11649: /* free_vector(andc,1,n); */
1.145 brouard 11650: /* */
11651:
1.126 brouard 11652: wav=ivector(1,imx);
1.214 brouard 11653: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
11654: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
11655: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
11656: 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.*/
11657: bh=imatrix(1,lastpass-firstpass+2,1,imx);
11658: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 11659:
11660: /* Concatenates waves */
1.214 brouard 11661: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
11662: Death is a valid wave (if date is known).
11663: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
11664: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
11665: and mw[mi+1][i]. dh depends on stepm.
11666: */
11667:
1.126 brouard 11668: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 11669: /* Concatenates waves */
1.145 brouard 11670:
1.290 brouard 11671: free_vector(moisdc,firstobs,lastobs);
11672: free_vector(andc,firstobs,lastobs);
1.215 brouard 11673:
1.126 brouard 11674: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
11675: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
11676: ncodemax[1]=1;
1.145 brouard 11677: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 11678: cptcoveff=0;
1.220 brouard 11679: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
11680: tricode(&cptcoveff,Tvar,nbcode,imx, Ndum); /**< Fills nbcode[Tvar[j]][l]; */
1.227 brouard 11681: }
11682:
11683: ncovcombmax=pow(2,cptcoveff);
11684: invalidvarcomb=ivector(1, ncovcombmax);
11685: for(i=1;i<ncovcombmax;i++)
11686: invalidvarcomb[i]=0;
11687:
1.211 brouard 11688: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 11689: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 11690: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 11691:
1.200 brouard 11692: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 11693: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 11694: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 11695: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
11696: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
11697: * (currently 0 or 1) in the data.
11698: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
11699: * corresponding modality (h,j).
11700: */
11701:
1.145 brouard 11702: h=0;
11703: /*if (cptcovn > 0) */
1.126 brouard 11704: m=pow(2,cptcoveff);
11705:
1.144 brouard 11706: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 11707: * For k=4 covariates, h goes from 1 to m=2**k
11708: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
11709: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.186 brouard 11710: * h\k 1 2 3 4
1.143 brouard 11711: *______________________________
11712: * 1 i=1 1 i=1 1 i=1 1 i=1 1
11713: * 2 2 1 1 1
11714: * 3 i=2 1 2 1 1
11715: * 4 2 2 1 1
11716: * 5 i=3 1 i=2 1 2 1
11717: * 6 2 1 2 1
11718: * 7 i=4 1 2 2 1
11719: * 8 2 2 2 1
1.197 brouard 11720: * 9 i=5 1 i=3 1 i=2 1 2
11721: * 10 2 1 1 2
11722: * 11 i=6 1 2 1 2
11723: * 12 2 2 1 2
11724: * 13 i=7 1 i=4 1 2 2
11725: * 14 2 1 2 2
11726: * 15 i=8 1 2 2 2
11727: * 16 2 2 2 2
1.143 brouard 11728: */
1.212 brouard 11729: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 11730: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
11731: * and the value of each covariate?
11732: * V1=1, V2=1, V3=2, V4=1 ?
11733: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
11734: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
11735: * In order to get the real value in the data, we use nbcode
11736: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
11737: * We are keeping this crazy system in order to be able (in the future?)
11738: * to have more than 2 values (0 or 1) for a covariate.
11739: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
11740: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
11741: * bbbbbbbb
11742: * 76543210
11743: * h-1 00000101 (6-1=5)
1.219 brouard 11744: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 11745: * &
11746: * 1 00000001 (1)
1.219 brouard 11747: * 00000000 = 1 & ((h-1) >> (k-1))
11748: * +1= 00000001 =1
1.211 brouard 11749: *
11750: * h=14, k=3 => h'=h-1=13, k'=k-1=2
11751: * h' 1101 =2^3+2^2+0x2^1+2^0
11752: * >>k' 11
11753: * & 00000001
11754: * = 00000001
11755: * +1 = 00000010=2 = codtabm(14,3)
11756: * Reverse h=6 and m=16?
11757: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
11758: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
11759: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
11760: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
11761: * V3=decodtabm(14,3,2**4)=2
11762: * h'=13 1101 =2^3+2^2+0x2^1+2^0
11763: *(h-1) >> (j-1) 0011 =13 >> 2
11764: * &1 000000001
11765: * = 000000001
11766: * +1= 000000010 =2
11767: * 2211
11768: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
11769: * V3=2
1.220 brouard 11770: * codtabm and decodtabm are identical
1.211 brouard 11771: */
11772:
1.145 brouard 11773:
11774: free_ivector(Ndum,-1,NCOVMAX);
11775:
11776:
1.126 brouard 11777:
1.186 brouard 11778: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 11779: strcpy(optionfilegnuplot,optionfilefiname);
11780: if(mle==-3)
1.201 brouard 11781: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 11782: strcat(optionfilegnuplot,".gp");
11783:
11784: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
11785: printf("Problem with file %s",optionfilegnuplot);
11786: }
11787: else{
1.204 brouard 11788: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 11789: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 11790: //fprintf(ficgp,"set missing 'NaNq'\n");
11791: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 11792: }
11793: /* fclose(ficgp);*/
1.186 brouard 11794:
11795:
11796: /* Initialisation of --------- index.htm --------*/
1.126 brouard 11797:
11798: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
11799: if(mle==-3)
1.201 brouard 11800: strcat(optionfilehtm,"-MORT_");
1.126 brouard 11801: strcat(optionfilehtm,".htm");
11802: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 11803: printf("Problem with %s \n",optionfilehtm);
11804: exit(0);
1.126 brouard 11805: }
11806:
11807: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
11808: strcat(optionfilehtmcov,"-cov.htm");
11809: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
11810: printf("Problem with %s \n",optionfilehtmcov), exit(0);
11811: }
11812: else{
11813: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
11814: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 11815: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 11816: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
11817: }
11818:
1.213 brouard 11819: 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 11820: <hr size=\"2\" color=\"#EC5E5E\"> \n\
11821: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 11822: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 11823: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n\
1.126 brouard 11824: \n\
11825: <hr size=\"2\" color=\"#EC5E5E\">\
11826: <ul><li><h4>Parameter files</h4>\n\
11827: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
11828: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
11829: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
11830: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
11831: - Date and time at start: %s</ul>\n",\
11832: optionfilehtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model,\
11833: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
11834: fileres,fileres,\
11835: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
11836: fflush(fichtm);
11837:
11838: strcpy(pathr,path);
11839: strcat(pathr,optionfilefiname);
1.184 brouard 11840: #ifdef WIN32
11841: _chdir(optionfilefiname); /* Move to directory named optionfile */
11842: #else
1.126 brouard 11843: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 11844: #endif
11845:
1.126 brouard 11846:
1.220 brouard 11847: /* Calculates basic frequencies. Computes observed prevalence at single age
11848: and for any valid combination of covariates
1.126 brouard 11849: and prints on file fileres'p'. */
1.251 brouard 11850: freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 11851: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 11852:
11853: fprintf(fichtm,"\n");
1.286 brouard 11854: fprintf(fichtm,"<h4>Parameter line 2</h4><ul><li>Tolerance for the convergence of the likelihood: ftol=%g \n<li>Interval for the elementary matrix (in month): stepm=%d",\
1.274 brouard 11855: ftol, stepm);
11856: fprintf(fichtm,"\n<li>Number of fixed dummy covariates: ncovcol=%d ", ncovcol);
11857: ncurrv=1;
11858: for(i=ncurrv; i <=ncovcol; i++) fprintf(fichtm,"V%d ", i);
11859: fprintf(fichtm,"\n<li> Number of fixed quantitative variables: nqv=%d ", nqv);
11860: ncurrv=i;
11861: for(i=ncurrv; i <=ncurrv-1+nqv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 11862: fprintf(fichtm,"\n<li> Number of time varying (wave varying) dummy covariates: ntv=%d ", ntv);
1.274 brouard 11863: ncurrv=i;
11864: for(i=ncurrv; i <=ncurrv-1+ntv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 11865: fprintf(fichtm,"\n<li>Number of time varying quantitative covariates: nqtv=%d ", nqtv);
1.274 brouard 11866: ncurrv=i;
11867: for(i=ncurrv; i <=ncurrv-1+nqtv; i++) fprintf(fichtm,"V%d ", i);
11868: 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", \
11869: nlstate, ndeath, maxwav, mle, weightopt);
11870:
11871: fprintf(fichtm,"<h4> Diagram of states <a href=\"%s_.svg\">%s_.svg</a></h4> \n\
11872: <img src=\"%s_.svg\">", subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"));
11873:
11874:
11875: fprintf(fichtm,"\n<h4>Some descriptive statistics </h4>\n<br>Total number of observations=%d <br>\n\
1.126 brouard 11876: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
11877: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
1.274 brouard 11878: imx,agemin,agemax,jmin,jmax,jmean);
1.126 brouard 11879: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 11880: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11881: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11882: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11883: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 11884:
1.126 brouard 11885: /* For Powell, parameters are in a vector p[] starting at p[1]
11886: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
11887: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
11888:
11889: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 11890: /* For mortality only */
1.126 brouard 11891: if (mle==-3){
1.136 brouard 11892: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 11893: for(i=1;i<=NDIM;i++)
11894: for(j=1;j<=NDIM;j++)
11895: ximort[i][j]=0.;
1.186 brouard 11896: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.290 brouard 11897: cens=ivector(firstobs,lastobs);
11898: ageexmed=vector(firstobs,lastobs);
11899: agecens=vector(firstobs,lastobs);
11900: dcwave=ivector(firstobs,lastobs);
1.223 brouard 11901:
1.126 brouard 11902: for (i=1; i<=imx; i++){
11903: dcwave[i]=-1;
11904: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 11905: if (s[m][i]>nlstate) {
11906: dcwave[i]=m;
11907: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
11908: break;
11909: }
1.126 brouard 11910: }
1.226 brouard 11911:
1.126 brouard 11912: for (i=1; i<=imx; i++) {
11913: if (wav[i]>0){
1.226 brouard 11914: ageexmed[i]=agev[mw[1][i]][i];
11915: j=wav[i];
11916: agecens[i]=1.;
11917:
11918: if (ageexmed[i]> 1 && wav[i] > 0){
11919: agecens[i]=agev[mw[j][i]][i];
11920: cens[i]= 1;
11921: }else if (ageexmed[i]< 1)
11922: cens[i]= -1;
11923: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
11924: cens[i]=0 ;
1.126 brouard 11925: }
11926: else cens[i]=-1;
11927: }
11928:
11929: for (i=1;i<=NDIM;i++) {
11930: for (j=1;j<=NDIM;j++)
1.226 brouard 11931: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 11932: }
11933:
1.302 brouard 11934: p[1]=0.0268; p[NDIM]=0.083;
11935: /* printf("%lf %lf", p[1], p[2]); */
1.126 brouard 11936:
11937:
1.136 brouard 11938: #ifdef GSL
11939: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 11940: #else
1.126 brouard 11941: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 11942: #endif
1.201 brouard 11943: strcpy(filerespow,"POW-MORT_");
11944: strcat(filerespow,fileresu);
1.126 brouard 11945: if((ficrespow=fopen(filerespow,"w"))==NULL) {
11946: printf("Problem with resultfile: %s\n", filerespow);
11947: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
11948: }
1.136 brouard 11949: #ifdef GSL
11950: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 11951: #else
1.126 brouard 11952: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 11953: #endif
1.126 brouard 11954: /* for (i=1;i<=nlstate;i++)
11955: for(j=1;j<=nlstate+ndeath;j++)
11956: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
11957: */
11958: fprintf(ficrespow,"\n");
1.136 brouard 11959: #ifdef GSL
11960: /* gsl starts here */
11961: T = gsl_multimin_fminimizer_nmsimplex;
11962: gsl_multimin_fminimizer *sfm = NULL;
11963: gsl_vector *ss, *x;
11964: gsl_multimin_function minex_func;
11965:
11966: /* Initial vertex size vector */
11967: ss = gsl_vector_alloc (NDIM);
11968:
11969: if (ss == NULL){
11970: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
11971: }
11972: /* Set all step sizes to 1 */
11973: gsl_vector_set_all (ss, 0.001);
11974:
11975: /* Starting point */
1.126 brouard 11976:
1.136 brouard 11977: x = gsl_vector_alloc (NDIM);
11978:
11979: if (x == NULL){
11980: gsl_vector_free(ss);
11981: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
11982: }
11983:
11984: /* Initialize method and iterate */
11985: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 11986: /* gsl_vector_set(x, 0, 0.0268); */
11987: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 11988: gsl_vector_set(x, 0, p[1]);
11989: gsl_vector_set(x, 1, p[2]);
11990:
11991: minex_func.f = &gompertz_f;
11992: minex_func.n = NDIM;
11993: minex_func.params = (void *)&p; /* ??? */
11994:
11995: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
11996: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
11997:
11998: printf("Iterations beginning .....\n\n");
11999: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
12000:
12001: iteri=0;
12002: while (rval == GSL_CONTINUE){
12003: iteri++;
12004: status = gsl_multimin_fminimizer_iterate(sfm);
12005:
12006: if (status) printf("error: %s\n", gsl_strerror (status));
12007: fflush(0);
12008:
12009: if (status)
12010: break;
12011:
12012: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
12013: ssval = gsl_multimin_fminimizer_size (sfm);
12014:
12015: if (rval == GSL_SUCCESS)
12016: printf ("converged to a local maximum at\n");
12017:
12018: printf("%5d ", iteri);
12019: for (it = 0; it < NDIM; it++){
12020: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
12021: }
12022: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
12023: }
12024:
12025: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
12026:
12027: gsl_vector_free(x); /* initial values */
12028: gsl_vector_free(ss); /* inital step size */
12029: for (it=0; it<NDIM; it++){
12030: p[it+1]=gsl_vector_get(sfm->x,it);
12031: fprintf(ficrespow," %.12lf", p[it]);
12032: }
12033: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
12034: #endif
12035: #ifdef POWELL
12036: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
12037: #endif
1.126 brouard 12038: fclose(ficrespow);
12039:
1.203 brouard 12040: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 12041:
12042: for(i=1; i <=NDIM; i++)
12043: for(j=i+1;j<=NDIM;j++)
1.220 brouard 12044: matcov[i][j]=matcov[j][i];
1.126 brouard 12045:
12046: printf("\nCovariance matrix\n ");
1.203 brouard 12047: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 12048: for(i=1; i <=NDIM; i++) {
12049: for(j=1;j<=NDIM;j++){
1.220 brouard 12050: printf("%f ",matcov[i][j]);
12051: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 12052: }
1.203 brouard 12053: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 12054: }
12055:
12056: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 12057: for (i=1;i<=NDIM;i++) {
1.126 brouard 12058: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 12059: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
12060: }
1.302 brouard 12061: lsurv=vector(agegomp,AGESUP);
12062: lpop=vector(agegomp,AGESUP);
12063: tpop=vector(agegomp,AGESUP);
1.126 brouard 12064: lsurv[agegomp]=100000;
12065:
12066: for (k=agegomp;k<=AGESUP;k++) {
12067: agemortsup=k;
12068: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
12069: }
12070:
12071: for (k=agegomp;k<agemortsup;k++)
12072: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
12073:
12074: for (k=agegomp;k<agemortsup;k++){
12075: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
12076: sumlpop=sumlpop+lpop[k];
12077: }
12078:
12079: tpop[agegomp]=sumlpop;
12080: for (k=agegomp;k<(agemortsup-3);k++){
12081: /* tpop[k+1]=2;*/
12082: tpop[k+1]=tpop[k]-lpop[k];
12083: }
12084:
12085:
12086: printf("\nAge lx qx dx Lx Tx e(x)\n");
12087: for (k=agegomp;k<(agemortsup-2);k++)
12088: 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]);
12089:
12090:
12091: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 12092: ageminpar=50;
12093: agemaxpar=100;
1.194 brouard 12094: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
12095: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
12096: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12097: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
12098: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
12099: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12100: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 12101: }else{
12102: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
12103: 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 12104: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 12105: }
1.201 brouard 12106: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 12107: stepm, weightopt,\
12108: model,imx,p,matcov,agemortsup);
12109:
1.302 brouard 12110: free_vector(lsurv,agegomp,AGESUP);
12111: free_vector(lpop,agegomp,AGESUP);
12112: free_vector(tpop,agegomp,AGESUP);
1.220 brouard 12113: free_matrix(ximort,1,NDIM,1,NDIM);
1.290 brouard 12114: free_ivector(dcwave,firstobs,lastobs);
12115: free_vector(agecens,firstobs,lastobs);
12116: free_vector(ageexmed,firstobs,lastobs);
12117: free_ivector(cens,firstobs,lastobs);
1.220 brouard 12118: #ifdef GSL
1.136 brouard 12119: #endif
1.186 brouard 12120: } /* Endof if mle==-3 mortality only */
1.205 brouard 12121: /* Standard */
12122: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
12123: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
12124: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 12125: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 12126: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
12127: for (k=1; k<=npar;k++)
12128: printf(" %d %8.5f",k,p[k]);
12129: printf("\n");
1.205 brouard 12130: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
12131: /* mlikeli uses func not funcone */
1.247 brouard 12132: /* for(i=1;i<nlstate;i++){ */
12133: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
12134: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
12135: /* } */
1.205 brouard 12136: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
12137: }
12138: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
12139: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
12140: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
12141: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
12142: }
12143: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 12144: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
12145: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
12146: for (k=1; k<=npar;k++)
12147: printf(" %d %8.5f",k,p[k]);
12148: printf("\n");
12149:
12150: /*--------- results files --------------*/
1.283 brouard 12151: /* 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 12152:
12153:
12154: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
12155: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
12156: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
12157: for(i=1,jk=1; i <=nlstate; i++){
12158: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 12159: if (k != i) {
12160: printf("%d%d ",i,k);
12161: fprintf(ficlog,"%d%d ",i,k);
12162: fprintf(ficres,"%1d%1d ",i,k);
12163: for(j=1; j <=ncovmodel; j++){
12164: printf("%12.7f ",p[jk]);
12165: fprintf(ficlog,"%12.7f ",p[jk]);
12166: fprintf(ficres,"%12.7f ",p[jk]);
12167: jk++;
12168: }
12169: printf("\n");
12170: fprintf(ficlog,"\n");
12171: fprintf(ficres,"\n");
12172: }
1.126 brouard 12173: }
12174: }
1.203 brouard 12175: if(mle != 0){
12176: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 12177: ftolhess=ftol; /* Usually correct */
1.203 brouard 12178: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
12179: 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");
12180: 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");
12181: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 12182: for(k=1; k <=(nlstate+ndeath); k++){
12183: if (k != i) {
12184: printf("%d%d ",i,k);
12185: fprintf(ficlog,"%d%d ",i,k);
12186: for(j=1; j <=ncovmodel; j++){
12187: 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]));
12188: 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]));
12189: jk++;
12190: }
12191: printf("\n");
12192: fprintf(ficlog,"\n");
12193: }
12194: }
1.193 brouard 12195: }
1.203 brouard 12196: } /* end of hesscov and Wald tests */
1.225 brouard 12197:
1.203 brouard 12198: /* */
1.126 brouard 12199: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
12200: printf("# Scales (for hessian or gradient estimation)\n");
12201: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
12202: for(i=1,jk=1; i <=nlstate; i++){
12203: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 12204: if (j!=i) {
12205: fprintf(ficres,"%1d%1d",i,j);
12206: printf("%1d%1d",i,j);
12207: fprintf(ficlog,"%1d%1d",i,j);
12208: for(k=1; k<=ncovmodel;k++){
12209: printf(" %.5e",delti[jk]);
12210: fprintf(ficlog," %.5e",delti[jk]);
12211: fprintf(ficres," %.5e",delti[jk]);
12212: jk++;
12213: }
12214: printf("\n");
12215: fprintf(ficlog,"\n");
12216: fprintf(ficres,"\n");
12217: }
1.126 brouard 12218: }
12219: }
12220:
12221: 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 12222: if(mle >= 1) /* To big for the screen */
1.126 brouard 12223: 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");
12224: 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");
12225: /* # 121 Var(a12)\n\ */
12226: /* # 122 Cov(b12,a12) Var(b12)\n\ */
12227: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
12228: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
12229: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
12230: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
12231: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
12232: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
12233:
12234:
12235: /* Just to have a covariance matrix which will be more understandable
12236: even is we still don't want to manage dictionary of variables
12237: */
12238: for(itimes=1;itimes<=2;itimes++){
12239: jj=0;
12240: for(i=1; i <=nlstate; i++){
1.225 brouard 12241: for(j=1; j <=nlstate+ndeath; j++){
12242: if(j==i) continue;
12243: for(k=1; k<=ncovmodel;k++){
12244: jj++;
12245: ca[0]= k+'a'-1;ca[1]='\0';
12246: if(itimes==1){
12247: if(mle>=1)
12248: printf("#%1d%1d%d",i,j,k);
12249: fprintf(ficlog,"#%1d%1d%d",i,j,k);
12250: fprintf(ficres,"#%1d%1d%d",i,j,k);
12251: }else{
12252: if(mle>=1)
12253: printf("%1d%1d%d",i,j,k);
12254: fprintf(ficlog,"%1d%1d%d",i,j,k);
12255: fprintf(ficres,"%1d%1d%d",i,j,k);
12256: }
12257: ll=0;
12258: for(li=1;li <=nlstate; li++){
12259: for(lj=1;lj <=nlstate+ndeath; lj++){
12260: if(lj==li) continue;
12261: for(lk=1;lk<=ncovmodel;lk++){
12262: ll++;
12263: if(ll<=jj){
12264: cb[0]= lk +'a'-1;cb[1]='\0';
12265: if(ll<jj){
12266: if(itimes==1){
12267: if(mle>=1)
12268: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12269: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12270: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12271: }else{
12272: if(mle>=1)
12273: printf(" %.5e",matcov[jj][ll]);
12274: fprintf(ficlog," %.5e",matcov[jj][ll]);
12275: fprintf(ficres," %.5e",matcov[jj][ll]);
12276: }
12277: }else{
12278: if(itimes==1){
12279: if(mle>=1)
12280: printf(" Var(%s%1d%1d)",ca,i,j);
12281: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
12282: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
12283: }else{
12284: if(mle>=1)
12285: printf(" %.7e",matcov[jj][ll]);
12286: fprintf(ficlog," %.7e",matcov[jj][ll]);
12287: fprintf(ficres," %.7e",matcov[jj][ll]);
12288: }
12289: }
12290: }
12291: } /* end lk */
12292: } /* end lj */
12293: } /* end li */
12294: if(mle>=1)
12295: printf("\n");
12296: fprintf(ficlog,"\n");
12297: fprintf(ficres,"\n");
12298: numlinepar++;
12299: } /* end k*/
12300: } /*end j */
1.126 brouard 12301: } /* end i */
12302: } /* end itimes */
12303:
12304: fflush(ficlog);
12305: fflush(ficres);
1.225 brouard 12306: while(fgets(line, MAXLINE, ficpar)) {
12307: /* If line starts with a # it is a comment */
12308: if (line[0] == '#') {
12309: numlinepar++;
12310: fputs(line,stdout);
12311: fputs(line,ficparo);
12312: fputs(line,ficlog);
1.299 brouard 12313: fputs(line,ficres);
1.225 brouard 12314: continue;
12315: }else
12316: break;
12317: }
12318:
1.209 brouard 12319: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
12320: /* ungetc(c,ficpar); */
12321: /* fgets(line, MAXLINE, ficpar); */
12322: /* fputs(line,stdout); */
12323: /* fputs(line,ficparo); */
12324: /* } */
12325: /* ungetc(c,ficpar); */
1.126 brouard 12326:
12327: estepm=0;
1.209 brouard 12328: 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 12329:
12330: if (num_filled != 6) {
12331: 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);
12332: 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);
12333: goto end;
12334: }
12335: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
12336: }
12337: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
12338: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
12339:
1.209 brouard 12340: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 12341: if (estepm==0 || estepm < stepm) estepm=stepm;
12342: if (fage <= 2) {
12343: bage = ageminpar;
12344: fage = agemaxpar;
12345: }
12346:
12347: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 12348: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
12349: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 12350:
1.186 brouard 12351: /* Other stuffs, more or less useful */
1.254 brouard 12352: while(fgets(line, MAXLINE, ficpar)) {
12353: /* If line starts with a # it is a comment */
12354: if (line[0] == '#') {
12355: numlinepar++;
12356: fputs(line,stdout);
12357: fputs(line,ficparo);
12358: fputs(line,ficlog);
1.299 brouard 12359: fputs(line,ficres);
1.254 brouard 12360: continue;
12361: }else
12362: break;
12363: }
12364:
12365: 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){
12366:
12367: if (num_filled != 7) {
12368: 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);
12369: 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);
12370: goto end;
12371: }
12372: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
12373: 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);
12374: 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);
12375: 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 12376: }
1.254 brouard 12377:
12378: while(fgets(line, MAXLINE, ficpar)) {
12379: /* If line starts with a # it is a comment */
12380: if (line[0] == '#') {
12381: numlinepar++;
12382: fputs(line,stdout);
12383: fputs(line,ficparo);
12384: fputs(line,ficlog);
1.299 brouard 12385: fputs(line,ficres);
1.254 brouard 12386: continue;
12387: }else
12388: break;
1.126 brouard 12389: }
12390:
12391:
12392: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
12393: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
12394:
1.254 brouard 12395: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
12396: if (num_filled != 1) {
12397: 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);
12398: 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);
12399: goto end;
12400: }
12401: printf("pop_based=%d\n",popbased);
12402: fprintf(ficlog,"pop_based=%d\n",popbased);
12403: fprintf(ficparo,"pop_based=%d\n",popbased);
12404: fprintf(ficres,"pop_based=%d\n",popbased);
12405: }
12406:
1.258 brouard 12407: /* Results */
12408: nresult=0;
12409: do{
12410: if(!fgets(line, MAXLINE, ficpar)){
12411: endishere=1;
12412: parameterline=14;
12413: }else if (line[0] == '#') {
12414: /* If line starts with a # it is a comment */
1.254 brouard 12415: numlinepar++;
12416: fputs(line,stdout);
12417: fputs(line,ficparo);
12418: fputs(line,ficlog);
1.299 brouard 12419: fputs(line,ficres);
1.254 brouard 12420: continue;
1.258 brouard 12421: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
12422: parameterline=11;
1.296 brouard 12423: else if(sscanf(line,"prevbackcast=%[^\n]\n",modeltemp))
1.258 brouard 12424: parameterline=12;
12425: else if(sscanf(line,"result:%[^\n]\n",modeltemp))
12426: parameterline=13;
12427: else{
12428: parameterline=14;
1.254 brouard 12429: }
1.258 brouard 12430: switch (parameterline){
12431: case 11:
1.296 brouard 12432: 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 && (num_filled == 8)){
12433: 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);
1.258 brouard 12434: 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);
12435: 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);
12436: 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);
12437: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 12438: dateproj1=anproj1+(mproj1-1)/12.+(jproj1-1)/365.;
12439: dateproj2=anproj2+(mproj2-1)/12.+(jproj2-1)/365.;
1.296 brouard 12440: prvforecast = 1;
12441: }
12442: else if((num_filled=sscanf(line,"prevforecast=%d yearsfproj=%lf mobil_average=%d\n",&prevfcast,&yrfproj,&mobilavproj)) !=EOF){/* && (num_filled == 3))*/
1.302 brouard 12443: printf("prevforecast=%d yearsfproj=%lf.2 mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
12444: fprintf(ficlog,"prevforecast=%d yearsfproj=%lf.2 mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
12445: fprintf(ficres,"prevforecast=%d yearsfproj=%lf.2 mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
1.296 brouard 12446: prvforecast = 2;
12447: }
12448: else {
12449: 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\nnor 3 (data)parameters, for example:prevforecast=1 yearsfproj=10 mobil_average=0. Your line=%s . You are running probably an older format.\n, ",num_filled,line);
12450: 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 mobil_average=0\nnor 3 (data)parameters, for example:prevforecast=1 yearproj=10 mobil_average=0. Your line=%s . You are running probably an older format.\n, ",num_filled,line);
12451: goto end;
1.258 brouard 12452: }
1.254 brouard 12453: break;
1.258 brouard 12454: case 12:
1.296 brouard 12455: if((num_filled=sscanf(line,"prevbackcast=%d starting-back-date=%lf/%lf/%lf final-back-date=%lf/%lf/%lf mobil_average=%d\n",&prevbcast,&jback1,&mback1,&anback1,&jback2,&mback2,&anback2,&mobilavproj)) !=EOF && (num_filled == 8)){
12456: fprintf(ficparo,"prevbackcast=%d starting-back-date=%.lf/%.lf/%.lf final-back-date=%.lf/%.lf/%.lf mobil_average=%d\n",prevbcast,jback1,mback1,anback1,jback2,mback2,anback2,mobilavproj);
12457: printf("prevbackcast=%d starting-back-date=%.lf/%.lf/%.lf final-back-date=%.lf/%.lf/%.lf mobil_average=%d\n",prevbcast,jback1,mback1,anback1,jback2,mback2,anback2,mobilavproj);
12458: fprintf(ficlog,"prevbackcast=%d starting-back-date=%.lf/%.lf/%.lf final-back-date=%.lf/%.lf/%.lf mobil_average=%d\n",prevbcast,jback1,mback1,anback1,jback2,mback2,anback2,mobilavproj);
12459: fprintf(ficres,"prevbackcast=%d starting-back-date=%.lf/%.lf/%.lf final-back-date=%.lf/%.lf/%.lf mobil_average=%d\n",prevbcast,jback1,mback1,anback1,jback2,mback2,anback2,mobilavproj);
12460: /* day and month of back2 are not used but only year anback2.*/
1.273 brouard 12461: dateback1=anback1+(mback1-1)/12.+(jback1-1)/365.;
12462: dateback2=anback2+(mback2-1)/12.+(jback2-1)/365.;
1.296 brouard 12463: prvbackcast = 1;
12464: }
12465: else if((num_filled=sscanf(line,"prevbackcast=%d yearsbproj=%lf mobil_average=%d\n",&prevbcast,&yrbproj,&mobilavproj)) ==3){/* && (num_filled == 3))*/
1.302 brouard 12466: printf("prevbackcast=%d yearsbproj=%lf.2 mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
12467: fprintf(ficlog,"prevbackcast=%d yearsbproj=%lf.2 mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
12468: fprintf(ficres,"prevbackcast=%d yearsbproj=%lf.2 mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
1.296 brouard 12469: prvbackcast = 2;
12470: }
12471: else {
12472: printf("Error: Not 8 (data)parameters in line but %d, for example:prevbackcast=1 starting-back-date=1/1/1990 final-back-date=1/1/2000 mobil_average=0\nnor 3 (data)parameters, for example:prevbackcast=1 yearsbproj=10 mobil_average=0. Your line=%s . You are running probably an older format.\n, ",num_filled,line);
12473: fprintf(ficlog,"Error: Not 8 (data)parameters in line but %d, for example:prevbackcast=1 starting-back-date=1/1/1990 final-back-date=1/1/2000 mobil_average=0\nnor 3 (data)parameters, for example:prevbackcast=1 yearbproj=10 mobil_average=0. Your line=%s . You are running probably an older format.\n, ",num_filled,line);
12474: goto end;
1.258 brouard 12475: }
1.230 brouard 12476: break;
1.258 brouard 12477: case 13:
12478: if((num_filled=sscanf(line,"result:%[^\n]\n",resultline)) !=EOF){
12479: if (num_filled == 0){
12480: resultline[0]='\0';
12481: printf("Warning %d: no result line! It should be at minimum 'result: V2=0 V1=1 or result:.\n%s\n", num_filled, line);
12482: 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);
12483: break;
12484: } else if (num_filled != 1){
12485: printf("ERROR %d: result line! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",num_filled, line);
12486: fprintf(ficlog,"ERROR %d: result line! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",num_filled, line);
12487: }
12488: nresult++; /* Sum of resultlines */
12489: printf("Result %d: result=%s\n",nresult, resultline);
12490: if(nresult > MAXRESULTLINES){
12491: printf("ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\n",MAXRESULTLINES,nresult);
12492: fprintf(ficlog,"ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\n",MAXRESULTLINES,nresult);
12493: goto end;
12494: }
12495: decoderesult(resultline, nresult); /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
12496: fprintf(ficparo,"result: %s\n",resultline);
12497: fprintf(ficres,"result: %s\n",resultline);
12498: fprintf(ficlog,"result: %s\n",resultline);
1.230 brouard 12499: break;
1.303 brouard 12500: case 14:
12501: printf("Error: Unknown command '%s'\n",line);
12502: fprintf(ficlog,"Error: Unknown command '%s'\n",line);
12503: if(ncovmodel >=2 && nresult==0 ){
1.259 brouard 12504: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.303 brouard 12505: fprintf(ficlog,"ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 12506: }
1.303 brouard 12507: goto end;
1.259 brouard 12508: break;
1.258 brouard 12509: default:
12510: nresult=1;
12511: decoderesult(".",nresult ); /* No covariate */
12512: }
12513: } /* End switch parameterline */
12514: }while(endishere==0); /* End do */
1.126 brouard 12515:
1.230 brouard 12516: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 12517: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 12518:
12519: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 12520: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 12521: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 12522: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12523: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 12524: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 12525: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12526: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 12527: }else{
1.270 brouard 12528: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
1.296 brouard 12529: /* It seems that anprojd which is computed from the mean year at interview which is known yet because of freqsummary */
12530: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */ /* Done in freqsummary */
12531: if(prvforecast==1){
12532: dateprojd=(jproj1+12*mproj1+365*anproj1)/365;
12533: jprojd=jproj1;
12534: mprojd=mproj1;
12535: anprojd=anproj1;
12536: dateprojf=(jproj2+12*mproj2+365*anproj2)/365;
12537: jprojf=jproj2;
12538: mprojf=mproj2;
12539: anprojf=anproj2;
12540: } else if(prvforecast == 2){
12541: dateprojd=dateintmean;
12542: date2dmy(dateprojd,&jprojd, &mprojd, &anprojd);
12543: dateprojf=dateintmean+yrfproj;
12544: date2dmy(dateprojf,&jprojf, &mprojf, &anprojf);
12545: }
12546: if(prvbackcast==1){
12547: datebackd=(jback1+12*mback1+365*anback1)/365;
12548: jbackd=jback1;
12549: mbackd=mback1;
12550: anbackd=anback1;
12551: datebackf=(jback2+12*mback2+365*anback2)/365;
12552: jbackf=jback2;
12553: mbackf=mback2;
12554: anbackf=anback2;
12555: } else if(prvbackcast == 2){
12556: datebackd=dateintmean;
12557: date2dmy(datebackd,&jbackd, &mbackd, &anbackd);
12558: datebackf=dateintmean-yrbproj;
12559: date2dmy(datebackf,&jbackf, &mbackf, &anbackf);
12560: }
12561:
12562: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, prevbcast, pathc,p, (int)anprojd-bage, (int)anbackd-fage);
1.220 brouard 12563: }
12564: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.296 brouard 12565: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,prevbcast, estepm, \
12566: jprev1,mprev1,anprev1,dateprev1, dateprojd, datebackd,jprev2,mprev2,anprev2,dateprev2,dateprojf, datebackf);
1.220 brouard 12567:
1.225 brouard 12568: /*------------ free_vector -------------*/
12569: /* chdir(path); */
1.220 brouard 12570:
1.215 brouard 12571: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
12572: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
12573: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
12574: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.290 brouard 12575: free_lvector(num,firstobs,lastobs);
12576: free_vector(agedc,firstobs,lastobs);
1.126 brouard 12577: /*free_matrix(covar,0,NCOVMAX,1,n);*/
12578: /*free_matrix(covar,1,NCOVMAX,1,n);*/
12579: fclose(ficparo);
12580: fclose(ficres);
1.220 brouard 12581:
12582:
1.186 brouard 12583: /* Other results (useful)*/
1.220 brouard 12584:
12585:
1.126 brouard 12586: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 12587: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
12588: prlim=matrix(1,nlstate,1,nlstate);
1.209 brouard 12589: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 12590: fclose(ficrespl);
12591:
12592: /*------------- h Pij x at various ages ------------*/
1.180 brouard 12593: /*#include "hpijx.h"*/
12594: hPijx(p, bage, fage);
1.145 brouard 12595: fclose(ficrespij);
1.227 brouard 12596:
1.220 brouard 12597: /* ncovcombmax= pow(2,cptcoveff); */
1.219 brouard 12598: /*-------------- Variance of one-step probabilities---*/
1.145 brouard 12599: k=1;
1.126 brouard 12600: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 12601:
1.269 brouard 12602: /* Prevalence for each covariate combination in probs[age][status][cov] */
12603: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
12604: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 12605: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 12606: for(k=1;k<=ncovcombmax;k++)
12607: probs[i][j][k]=0.;
1.269 brouard 12608: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
12609: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 12610: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 12611: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
12612: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 12613: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 12614: for(k=1;k<=ncovcombmax;k++)
12615: mobaverages[i][j][k]=0.;
1.219 brouard 12616: mobaverage=mobaverages;
12617: if (mobilav!=0) {
1.235 brouard 12618: printf("Movingaveraging observed prevalence\n");
1.258 brouard 12619: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 12620: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
12621: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
12622: printf(" Error in movingaverage mobilav=%d\n",mobilav);
12623: }
1.269 brouard 12624: } else if (mobilavproj !=0) {
1.235 brouard 12625: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 12626: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 12627: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
12628: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
12629: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
12630: }
1.269 brouard 12631: }else{
12632: printf("Internal error moving average\n");
12633: fflush(stdout);
12634: exit(1);
1.219 brouard 12635: }
12636: }/* end if moving average */
1.227 brouard 12637:
1.126 brouard 12638: /*---------- Forecasting ------------------*/
1.296 brouard 12639: if(prevfcast==1){
12640: /* /\* if(stepm ==1){*\/ */
12641: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
12642: /*This done previously after freqsummary.*/
12643: /* dateprojd=(jproj1+12*mproj1+365*anproj1)/365; */
12644: /* dateprojf=(jproj2+12*mproj2+365*anproj2)/365; */
12645:
12646: /* } else if (prvforecast==2){ */
12647: /* /\* if(stepm ==1){*\/ */
12648: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
12649: /* } */
12650: /*prevforecast(fileresu, dateintmean, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);*/
12651: prevforecast(fileresu,dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, p, cptcoveff);
1.126 brouard 12652: }
1.269 brouard 12653:
1.296 brouard 12654: /* Prevbcasting */
12655: if(prevbcast==1){
1.219 brouard 12656: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12657: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12658: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12659:
12660: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
12661:
12662: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 12663:
1.219 brouard 12664: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
12665: fclose(ficresplb);
12666:
1.222 brouard 12667: hBijx(p, bage, fage, mobaverage);
12668: fclose(ficrespijb);
1.219 brouard 12669:
1.296 brouard 12670: /* /\* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, *\/ */
12671: /* /\* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); *\/ */
12672: /* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, */
12673: /* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); */
12674: prevbackforecast(fileresu, mobaverage, dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2,
12675: mobilavproj, bage, fage, firstpass, lastpass, p, cptcoveff);
12676:
12677:
1.269 brouard 12678: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 12679:
12680:
1.269 brouard 12681: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 12682: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
12683: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
12684: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.296 brouard 12685: } /* end Prevbcasting */
1.268 brouard 12686:
1.186 brouard 12687:
12688: /* ------ Other prevalence ratios------------ */
1.126 brouard 12689:
1.215 brouard 12690: free_ivector(wav,1,imx);
12691: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
12692: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
12693: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 12694:
12695:
1.127 brouard 12696: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 12697:
1.201 brouard 12698: strcpy(filerese,"E_");
12699: strcat(filerese,fileresu);
1.126 brouard 12700: if((ficreseij=fopen(filerese,"w"))==NULL) {
12701: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
12702: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
12703: }
1.208 brouard 12704: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
12705: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 12706:
12707: pstamp(ficreseij);
1.219 brouard 12708:
1.235 brouard 12709: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
12710: if (cptcovn < 1){i1=1;}
12711:
12712: for(nres=1; nres <= nresult; nres++) /* For each resultline */
12713: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 12714: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 12715: continue;
1.219 brouard 12716: fprintf(ficreseij,"\n#****** ");
1.235 brouard 12717: printf("\n#****** ");
1.225 brouard 12718: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 12719: fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 12720: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12721: }
12722: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12723: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12724: fprintf(ficreseij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
1.219 brouard 12725: }
12726: fprintf(ficreseij,"******\n");
1.235 brouard 12727: printf("******\n");
1.219 brouard 12728:
12729: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12730: oldm=oldms;savm=savms;
1.235 brouard 12731: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 12732:
1.219 brouard 12733: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 12734: }
12735: fclose(ficreseij);
1.208 brouard 12736: printf("done evsij\n");fflush(stdout);
12737: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 12738:
1.218 brouard 12739:
1.227 brouard 12740: /*---------- State-specific expectancies and variances ------------*/
1.218 brouard 12741:
1.201 brouard 12742: strcpy(filerest,"T_");
12743: strcat(filerest,fileresu);
1.127 brouard 12744: if((ficrest=fopen(filerest,"w"))==NULL) {
12745: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
12746: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
12747: }
1.208 brouard 12748: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
12749: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 12750: strcpy(fileresstde,"STDE_");
12751: strcat(fileresstde,fileresu);
1.126 brouard 12752: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 12753: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
12754: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 12755: }
1.227 brouard 12756: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
12757: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 12758:
1.201 brouard 12759: strcpy(filerescve,"CVE_");
12760: strcat(filerescve,fileresu);
1.126 brouard 12761: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 12762: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
12763: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 12764: }
1.227 brouard 12765: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
12766: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 12767:
1.201 brouard 12768: strcpy(fileresv,"V_");
12769: strcat(fileresv,fileresu);
1.126 brouard 12770: if((ficresvij=fopen(fileresv,"w"))==NULL) {
12771: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
12772: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
12773: }
1.227 brouard 12774: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
12775: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 12776:
1.235 brouard 12777: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
12778: if (cptcovn < 1){i1=1;}
12779:
12780: for(nres=1; nres <= nresult; nres++) /* For each resultline */
12781: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 12782: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 12783: continue;
1.242 brouard 12784: printf("\n#****** Result for:");
12785: fprintf(ficrest,"\n#****** Result for:");
12786: fprintf(ficlog,"\n#****** Result for:");
1.227 brouard 12787: for(j=1;j<=cptcoveff;j++){
12788: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12789: fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12790: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12791: }
1.235 brouard 12792: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12793: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12794: fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12795: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12796: }
1.208 brouard 12797: fprintf(ficrest,"******\n");
1.227 brouard 12798: fprintf(ficlog,"******\n");
12799: printf("******\n");
1.208 brouard 12800:
12801: fprintf(ficresstdeij,"\n#****** ");
12802: fprintf(ficrescveij,"\n#****** ");
1.225 brouard 12803: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 12804: fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12805: fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.208 brouard 12806: }
1.235 brouard 12807: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12808: fprintf(ficresstdeij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12809: fprintf(ficrescveij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12810: }
1.208 brouard 12811: fprintf(ficresstdeij,"******\n");
12812: fprintf(ficrescveij,"******\n");
12813:
12814: fprintf(ficresvij,"\n#****** ");
1.238 brouard 12815: /* pstamp(ficresvij); */
1.225 brouard 12816: for(j=1;j<=cptcoveff;j++)
1.227 brouard 12817: fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 12818: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12819: fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12820: }
1.208 brouard 12821: fprintf(ficresvij,"******\n");
12822:
12823: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12824: oldm=oldms;savm=savms;
1.235 brouard 12825: printf(" cvevsij ");
12826: fprintf(ficlog, " cvevsij ");
12827: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 12828: printf(" end cvevsij \n ");
12829: fprintf(ficlog, " end cvevsij \n ");
12830:
12831: /*
12832: */
12833: /* goto endfree; */
12834:
12835: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12836: pstamp(ficrest);
12837:
1.269 brouard 12838: epj=vector(1,nlstate+1);
1.208 brouard 12839: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 12840: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
12841: cptcod= 0; /* To be deleted */
12842: printf("varevsij vpopbased=%d \n",vpopbased);
12843: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 12844: 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 12845: 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 ");
12846: if(vpopbased==1)
12847: 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);
12848: else
1.288 brouard 12849: fprintf(ficrest,"the age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 12850: fprintf(ficrest,"# Age popbased mobilav e.. (std) ");
12851: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
12852: fprintf(ficrest,"\n");
12853: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
1.288 brouard 12854: printf("Computing age specific forward period (stable) prevalences in each health state \n");
12855: fprintf(ficlog,"Computing age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 12856: for(age=bage; age <=fage ;age++){
1.235 brouard 12857: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 12858: if (vpopbased==1) {
12859: if(mobilav ==0){
12860: for(i=1; i<=nlstate;i++)
12861: prlim[i][i]=probs[(int)age][i][k];
12862: }else{ /* mobilav */
12863: for(i=1; i<=nlstate;i++)
12864: prlim[i][i]=mobaverage[(int)age][i][k];
12865: }
12866: }
1.219 brouard 12867:
1.227 brouard 12868: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
12869: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
12870: /* printf(" age %4.0f ",age); */
12871: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
12872: for(i=1, epj[j]=0.;i <=nlstate;i++) {
12873: epj[j] += prlim[i][i]*eij[i][j][(int)age];
12874: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
12875: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
12876: }
12877: epj[nlstate+1] +=epj[j];
12878: }
12879: /* printf(" age %4.0f \n",age); */
1.219 brouard 12880:
1.227 brouard 12881: for(i=1, vepp=0.;i <=nlstate;i++)
12882: for(j=1;j <=nlstate;j++)
12883: vepp += vareij[i][j][(int)age];
12884: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
12885: for(j=1;j <=nlstate;j++){
12886: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
12887: }
12888: fprintf(ficrest,"\n");
12889: }
1.208 brouard 12890: } /* End vpopbased */
1.269 brouard 12891: free_vector(epj,1,nlstate+1);
1.208 brouard 12892: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
12893: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 12894: printf("done selection\n");fflush(stdout);
12895: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 12896:
1.235 brouard 12897: } /* End k selection */
1.227 brouard 12898:
12899: printf("done State-specific expectancies\n");fflush(stdout);
12900: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
12901:
1.288 brouard 12902: /* variance-covariance of forward period prevalence*/
1.269 brouard 12903: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 12904:
1.227 brouard 12905:
1.290 brouard 12906: free_vector(weight,firstobs,lastobs);
1.227 brouard 12907: free_imatrix(Tvard,1,NCOVMAX,1,2);
1.290 brouard 12908: free_imatrix(s,1,maxwav+1,firstobs,lastobs);
12909: free_matrix(anint,1,maxwav,firstobs,lastobs);
12910: free_matrix(mint,1,maxwav,firstobs,lastobs);
12911: free_ivector(cod,firstobs,lastobs);
1.227 brouard 12912: free_ivector(tab,1,NCOVMAX);
12913: fclose(ficresstdeij);
12914: fclose(ficrescveij);
12915: fclose(ficresvij);
12916: fclose(ficrest);
12917: fclose(ficpar);
12918:
12919:
1.126 brouard 12920: /*---------- End : free ----------------*/
1.219 brouard 12921: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 12922: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
12923: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 12924: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
12925: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 12926: } /* mle==-3 arrives here for freeing */
1.227 brouard 12927: /* endfree:*/
12928: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
12929: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
12930: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.290 brouard 12931: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,firstobs,lastobs);
12932: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,firstobs,lastobs);
12933: if(nqv>=1)free_matrix(coqvar,1,nqv,firstobs,lastobs);
12934: free_matrix(covar,0,NCOVMAX,firstobs,lastobs);
1.227 brouard 12935: free_matrix(matcov,1,npar,1,npar);
12936: free_matrix(hess,1,npar,1,npar);
12937: /*free_vector(delti,1,npar);*/
12938: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
12939: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 12940: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 12941: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
12942:
12943: free_ivector(ncodemax,1,NCOVMAX);
12944: free_ivector(ncodemaxwundef,1,NCOVMAX);
12945: free_ivector(Dummy,-1,NCOVMAX);
12946: free_ivector(Fixed,-1,NCOVMAX);
1.238 brouard 12947: free_ivector(DummyV,1,NCOVMAX);
12948: free_ivector(FixedV,1,NCOVMAX);
1.227 brouard 12949: free_ivector(Typevar,-1,NCOVMAX);
12950: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 12951: free_ivector(TvarsQ,1,NCOVMAX);
12952: free_ivector(TvarsQind,1,NCOVMAX);
12953: free_ivector(TvarsD,1,NCOVMAX);
12954: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 12955: free_ivector(TvarFD,1,NCOVMAX);
12956: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 12957: free_ivector(TvarF,1,NCOVMAX);
12958: free_ivector(TvarFind,1,NCOVMAX);
12959: free_ivector(TvarV,1,NCOVMAX);
12960: free_ivector(TvarVind,1,NCOVMAX);
12961: free_ivector(TvarA,1,NCOVMAX);
12962: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 12963: free_ivector(TvarFQ,1,NCOVMAX);
12964: free_ivector(TvarFQind,1,NCOVMAX);
12965: free_ivector(TvarVD,1,NCOVMAX);
12966: free_ivector(TvarVDind,1,NCOVMAX);
12967: free_ivector(TvarVQ,1,NCOVMAX);
12968: free_ivector(TvarVQind,1,NCOVMAX);
1.230 brouard 12969: free_ivector(Tvarsel,1,NCOVMAX);
12970: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 12971: free_ivector(Tposprod,1,NCOVMAX);
12972: free_ivector(Tprod,1,NCOVMAX);
12973: free_ivector(Tvaraff,1,NCOVMAX);
12974: free_ivector(invalidvarcomb,1,ncovcombmax);
12975: free_ivector(Tage,1,NCOVMAX);
12976: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 12977: free_ivector(TmodelInvind,1,NCOVMAX);
12978: free_ivector(TmodelInvQind,1,NCOVMAX);
1.227 brouard 12979:
12980: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
12981: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 12982: fflush(fichtm);
12983: fflush(ficgp);
12984:
1.227 brouard 12985:
1.126 brouard 12986: if((nberr >0) || (nbwarn>0)){
1.216 brouard 12987: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
12988: 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 12989: }else{
12990: printf("End of Imach\n");
12991: fprintf(ficlog,"End of Imach\n");
12992: }
12993: printf("See log file on %s\n",filelog);
12994: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 12995: /*(void) gettimeofday(&end_time,&tzp);*/
12996: rend_time = time(NULL);
12997: end_time = *localtime(&rend_time);
12998: /* tml = *localtime(&end_time.tm_sec); */
12999: strcpy(strtend,asctime(&end_time));
1.126 brouard 13000: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
13001: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 13002: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 13003:
1.157 brouard 13004: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
13005: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
13006: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 13007: /* printf("Total time was %d uSec.\n", total_usecs);*/
13008: /* if(fileappend(fichtm,optionfilehtm)){ */
13009: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
13010: fclose(fichtm);
13011: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
13012: fclose(fichtmcov);
13013: fclose(ficgp);
13014: fclose(ficlog);
13015: /*------ End -----------*/
1.227 brouard 13016:
1.281 brouard 13017:
13018: /* Executes gnuplot */
1.227 brouard 13019:
13020: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 13021: #ifdef WIN32
1.227 brouard 13022: if (_chdir(pathcd) != 0)
13023: printf("Can't move to directory %s!\n",path);
13024: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 13025: #else
1.227 brouard 13026: if(chdir(pathcd) != 0)
13027: printf("Can't move to directory %s!\n", path);
13028: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 13029: #endif
1.126 brouard 13030: printf("Current directory %s!\n",pathcd);
13031: /*strcat(plotcmd,CHARSEPARATOR);*/
13032: sprintf(plotcmd,"gnuplot");
1.157 brouard 13033: #ifdef _WIN32
1.126 brouard 13034: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
13035: #endif
13036: if(!stat(plotcmd,&info)){
1.158 brouard 13037: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 13038: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 13039: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 13040: }else
13041: strcpy(pplotcmd,plotcmd);
1.157 brouard 13042: #ifdef __unix
1.126 brouard 13043: strcpy(plotcmd,GNUPLOTPROGRAM);
13044: if(!stat(plotcmd,&info)){
1.158 brouard 13045: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 13046: }else
13047: strcpy(pplotcmd,plotcmd);
13048: #endif
13049: }else
13050: strcpy(pplotcmd,plotcmd);
13051:
13052: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 13053: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.292 brouard 13054: strcpy(pplotcmd,plotcmd);
1.227 brouard 13055:
1.126 brouard 13056: if((outcmd=system(plotcmd)) != 0){
1.292 brouard 13057: printf("Error in gnuplot, command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 13058: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 13059: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.292 brouard 13060: if((outcmd=system(plotcmd)) != 0){
1.153 brouard 13061: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.292 brouard 13062: strcpy(plotcmd,pplotcmd);
13063: }
1.126 brouard 13064: }
1.158 brouard 13065: printf(" Successful, please wait...");
1.126 brouard 13066: while (z[0] != 'q') {
13067: /* chdir(path); */
1.154 brouard 13068: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 13069: scanf("%s",z);
13070: /* if (z[0] == 'c') system("./imach"); */
13071: if (z[0] == 'e') {
1.158 brouard 13072: #ifdef __APPLE__
1.152 brouard 13073: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 13074: #elif __linux
13075: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 13076: #else
1.152 brouard 13077: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 13078: #endif
13079: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
13080: system(pplotcmd);
1.126 brouard 13081: }
13082: else if (z[0] == 'g') system(plotcmd);
13083: else if (z[0] == 'q') exit(0);
13084: }
1.227 brouard 13085: end:
1.126 brouard 13086: while (z[0] != 'q') {
1.195 brouard 13087: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 13088: scanf("%s",z);
13089: }
1.283 brouard 13090: printf("End\n");
1.282 brouard 13091: exit(0);
1.126 brouard 13092: }
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