Annotation of imach/src/imach.c, revision 1.300
1.300 ! brouard 1: /* $Id: imach.c,v 1.299 2019/05/22 18:37:08 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.300 ! brouard 4: Revision 1.299 2019/05/22 18:37:08 brouard
! 5: Summary: Cleaned 0.99r19
! 6:
1.299 brouard 7: Revision 1.298 2019/05/22 18:19:56 brouard
8: *** empty log message ***
9:
1.298 brouard 10: Revision 1.297 2019/05/22 17:56:10 brouard
11: Summary: Fix bug by moving date2dmy and nhstepm which gaefin=-1
12:
1.297 brouard 13: Revision 1.296 2019/05/20 13:03:18 brouard
14: Summary: Projection syntax simplified
15:
16:
17: We can now start projections, forward or backward, from the mean date
18: of inteviews up to or down to a number of years of projection:
19: prevforecast=1 yearsfproj=15.3 mobil_average=0
20: or
21: prevforecast=1 starting-proj-date=1/1/2007 final-proj-date=12/31/2017 mobil_average=0
22: or
23: prevbackcast=1 yearsbproj=12.3 mobil_average=1
24: or
25: prevbackcast=1 starting-back-date=1/10/1999 final-back-date=1/1/1985 mobil_average=1
26:
1.296 brouard 27: Revision 1.295 2019/05/18 09:52:50 brouard
28: Summary: doxygen tex bug
29:
1.295 brouard 30: Revision 1.294 2019/05/16 14:54:33 brouard
31: Summary: There was some wrong lines added
32:
1.294 brouard 33: Revision 1.293 2019/05/09 15:17:34 brouard
34: *** empty log message ***
35:
1.293 brouard 36: Revision 1.292 2019/05/09 14:17:20 brouard
37: Summary: Some updates
38:
1.292 brouard 39: Revision 1.291 2019/05/09 13:44:18 brouard
40: Summary: Before ncovmax
41:
1.291 brouard 42: Revision 1.290 2019/05/09 13:39:37 brouard
43: Summary: 0.99r18 unlimited number of individuals
44:
45: 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.
46:
1.290 brouard 47: Revision 1.289 2018/12/13 09:16:26 brouard
48: Summary: Bug for young ages (<-30) will be in r17
49:
1.289 brouard 50: Revision 1.288 2018/05/02 20:58:27 brouard
51: Summary: Some bugs fixed
52:
1.288 brouard 53: Revision 1.287 2018/05/01 17:57:25 brouard
54: Summary: Bug fixed by providing frequencies only for non missing covariates
55:
1.287 brouard 56: Revision 1.286 2018/04/27 14:27:04 brouard
57: Summary: some minor bugs
58:
1.286 brouard 59: Revision 1.285 2018/04/21 21:02:16 brouard
60: Summary: Some bugs fixed, valgrind tested
61:
1.285 brouard 62: Revision 1.284 2018/04/20 05:22:13 brouard
63: Summary: Computing mean and stdeviation of fixed quantitative variables
64:
1.284 brouard 65: Revision 1.283 2018/04/19 14:49:16 brouard
66: Summary: Some minor bugs fixed
67:
1.283 brouard 68: Revision 1.282 2018/02/27 22:50:02 brouard
69: *** empty log message ***
70:
1.282 brouard 71: Revision 1.281 2018/02/27 19:25:23 brouard
72: Summary: Adding second argument for quitting
73:
1.281 brouard 74: Revision 1.280 2018/02/21 07:58:13 brouard
75: Summary: 0.99r15
76:
77: New Makefile with recent VirtualBox 5.26. Bug in sqrt negatve in imach.c
78:
1.280 brouard 79: Revision 1.279 2017/07/20 13:35:01 brouard
80: Summary: temporary working
81:
1.279 brouard 82: Revision 1.278 2017/07/19 14:09:02 brouard
83: Summary: Bug for mobil_average=0 and prevforecast fixed(?)
84:
1.278 brouard 85: Revision 1.277 2017/07/17 08:53:49 brouard
86: Summary: BOM files can be read now
87:
1.277 brouard 88: Revision 1.276 2017/06/30 15:48:31 brouard
89: Summary: Graphs improvements
90:
1.276 brouard 91: Revision 1.275 2017/06/30 13:39:33 brouard
92: Summary: Saito's color
93:
1.275 brouard 94: Revision 1.274 2017/06/29 09:47:08 brouard
95: Summary: Version 0.99r14
96:
1.274 brouard 97: Revision 1.273 2017/06/27 11:06:02 brouard
98: Summary: More documentation on projections
99:
1.273 brouard 100: Revision 1.272 2017/06/27 10:22:40 brouard
101: Summary: Color of backprojection changed from 6 to 5(yellow)
102:
1.272 brouard 103: Revision 1.271 2017/06/27 10:17:50 brouard
104: Summary: Some bug with rint
105:
1.271 brouard 106: Revision 1.270 2017/05/24 05:45:29 brouard
107: *** empty log message ***
108:
1.270 brouard 109: Revision 1.269 2017/05/23 08:39:25 brouard
110: Summary: Code into subroutine, cleanings
111:
1.269 brouard 112: Revision 1.268 2017/05/18 20:09:32 brouard
113: Summary: backprojection and confidence intervals of backprevalence
114:
1.268 brouard 115: Revision 1.267 2017/05/13 10:25:05 brouard
116: Summary: temporary save for backprojection
117:
1.267 brouard 118: Revision 1.266 2017/05/13 07:26:12 brouard
119: Summary: Version 0.99r13 (improvements and bugs fixed)
120:
1.266 brouard 121: Revision 1.265 2017/04/26 16:22:11 brouard
122: Summary: imach 0.99r13 Some bugs fixed
123:
1.265 brouard 124: Revision 1.264 2017/04/26 06:01:29 brouard
125: Summary: Labels in graphs
126:
1.264 brouard 127: Revision 1.263 2017/04/24 15:23:15 brouard
128: Summary: to save
129:
1.263 brouard 130: Revision 1.262 2017/04/18 16:48:12 brouard
131: *** empty log message ***
132:
1.262 brouard 133: Revision 1.261 2017/04/05 10:14:09 brouard
134: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
135:
1.261 brouard 136: Revision 1.260 2017/04/04 17:46:59 brouard
137: Summary: Gnuplot indexations fixed (humm)
138:
1.260 brouard 139: Revision 1.259 2017/04/04 13:01:16 brouard
140: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
141:
1.259 brouard 142: Revision 1.258 2017/04/03 10:17:47 brouard
143: Summary: Version 0.99r12
144:
145: Some cleanings, conformed with updated documentation.
146:
1.258 brouard 147: Revision 1.257 2017/03/29 16:53:30 brouard
148: Summary: Temp
149:
1.257 brouard 150: Revision 1.256 2017/03/27 05:50:23 brouard
151: Summary: Temporary
152:
1.256 brouard 153: Revision 1.255 2017/03/08 16:02:28 brouard
154: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
155:
1.255 brouard 156: Revision 1.254 2017/03/08 07:13:00 brouard
157: Summary: Fixing data parameter line
158:
1.254 brouard 159: Revision 1.253 2016/12/15 11:59:41 brouard
160: Summary: 0.99 in progress
161:
1.253 brouard 162: Revision 1.252 2016/09/15 21:15:37 brouard
163: *** empty log message ***
164:
1.252 brouard 165: Revision 1.251 2016/09/15 15:01:13 brouard
166: Summary: not working
167:
1.251 brouard 168: Revision 1.250 2016/09/08 16:07:27 brouard
169: Summary: continue
170:
1.250 brouard 171: Revision 1.249 2016/09/07 17:14:18 brouard
172: Summary: Starting values from frequencies
173:
1.249 brouard 174: Revision 1.248 2016/09/07 14:10:18 brouard
175: *** empty log message ***
176:
1.248 brouard 177: Revision 1.247 2016/09/02 11:11:21 brouard
178: *** empty log message ***
179:
1.247 brouard 180: Revision 1.246 2016/09/02 08:49:22 brouard
181: *** empty log message ***
182:
1.246 brouard 183: Revision 1.245 2016/09/02 07:25:01 brouard
184: *** empty log message ***
185:
1.245 brouard 186: Revision 1.244 2016/09/02 07:17:34 brouard
187: *** empty log message ***
188:
1.244 brouard 189: Revision 1.243 2016/09/02 06:45:35 brouard
190: *** empty log message ***
191:
1.243 brouard 192: Revision 1.242 2016/08/30 15:01:20 brouard
193: Summary: Fixing a lots
194:
1.242 brouard 195: Revision 1.241 2016/08/29 17:17:25 brouard
196: Summary: gnuplot problem in Back projection to fix
197:
1.241 brouard 198: Revision 1.240 2016/08/29 07:53:18 brouard
199: Summary: Better
200:
1.240 brouard 201: Revision 1.239 2016/08/26 15:51:03 brouard
202: Summary: Improvement in Powell output in order to copy and paste
203:
204: Author:
205:
1.239 brouard 206: Revision 1.238 2016/08/26 14:23:35 brouard
207: Summary: Starting tests of 0.99
208:
1.238 brouard 209: Revision 1.237 2016/08/26 09:20:19 brouard
210: Summary: to valgrind
211:
1.237 brouard 212: Revision 1.236 2016/08/25 10:50:18 brouard
213: *** empty log message ***
214:
1.236 brouard 215: Revision 1.235 2016/08/25 06:59:23 brouard
216: *** empty log message ***
217:
1.235 brouard 218: Revision 1.234 2016/08/23 16:51:20 brouard
219: *** empty log message ***
220:
1.234 brouard 221: Revision 1.233 2016/08/23 07:40:50 brouard
222: Summary: not working
223:
1.233 brouard 224: Revision 1.232 2016/08/22 14:20:21 brouard
225: Summary: not working
226:
1.232 brouard 227: Revision 1.231 2016/08/22 07:17:15 brouard
228: Summary: not working
229:
1.231 brouard 230: Revision 1.230 2016/08/22 06:55:53 brouard
231: Summary: Not working
232:
1.230 brouard 233: Revision 1.229 2016/07/23 09:45:53 brouard
234: Summary: Completing for func too
235:
1.229 brouard 236: Revision 1.228 2016/07/22 17:45:30 brouard
237: Summary: Fixing some arrays, still debugging
238:
1.227 brouard 239: Revision 1.226 2016/07/12 18:42:34 brouard
240: Summary: temp
241:
1.226 brouard 242: Revision 1.225 2016/07/12 08:40:03 brouard
243: Summary: saving but not running
244:
1.225 brouard 245: Revision 1.224 2016/07/01 13:16:01 brouard
246: Summary: Fixes
247:
1.224 brouard 248: Revision 1.223 2016/02/19 09:23:35 brouard
249: Summary: temporary
250:
1.223 brouard 251: Revision 1.222 2016/02/17 08:14:50 brouard
252: Summary: Probably last 0.98 stable version 0.98r6
253:
1.222 brouard 254: Revision 1.221 2016/02/15 23:35:36 brouard
255: Summary: minor bug
256:
1.220 brouard 257: Revision 1.219 2016/02/15 00:48:12 brouard
258: *** empty log message ***
259:
1.219 brouard 260: Revision 1.218 2016/02/12 11:29:23 brouard
261: Summary: 0.99 Back projections
262:
1.218 brouard 263: Revision 1.217 2015/12/23 17:18:31 brouard
264: Summary: Experimental backcast
265:
1.217 brouard 266: Revision 1.216 2015/12/18 17:32:11 brouard
267: Summary: 0.98r4 Warning and status=-2
268:
269: Version 0.98r4 is now:
270: - displaying an error when status is -1, date of interview unknown and date of death known;
271: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
272: Older changes concerning s=-2, dating from 2005 have been supersed.
273:
1.216 brouard 274: Revision 1.215 2015/12/16 08:52:24 brouard
275: Summary: 0.98r4 working
276:
1.215 brouard 277: Revision 1.214 2015/12/16 06:57:54 brouard
278: Summary: temporary not working
279:
1.214 brouard 280: Revision 1.213 2015/12/11 18:22:17 brouard
281: Summary: 0.98r4
282:
1.213 brouard 283: Revision 1.212 2015/11/21 12:47:24 brouard
284: Summary: minor typo
285:
1.212 brouard 286: Revision 1.211 2015/11/21 12:41:11 brouard
287: Summary: 0.98r3 with some graph of projected cross-sectional
288:
289: Author: Nicolas Brouard
290:
1.211 brouard 291: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 292: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 293: Summary: Adding ftolpl parameter
294: Author: N Brouard
295:
296: We had difficulties to get smoothed confidence intervals. It was due
297: to the period prevalence which wasn't computed accurately. The inner
298: parameter ftolpl is now an outer parameter of the .imach parameter
299: file after estepm. If ftolpl is small 1.e-4 and estepm too,
300: computation are long.
301:
1.209 brouard 302: Revision 1.208 2015/11/17 14:31:57 brouard
303: Summary: temporary
304:
1.208 brouard 305: Revision 1.207 2015/10/27 17:36:57 brouard
306: *** empty log message ***
307:
1.207 brouard 308: Revision 1.206 2015/10/24 07:14:11 brouard
309: *** empty log message ***
310:
1.206 brouard 311: Revision 1.205 2015/10/23 15:50:53 brouard
312: Summary: 0.98r3 some clarification for graphs on likelihood contributions
313:
1.205 brouard 314: Revision 1.204 2015/10/01 16:20:26 brouard
315: Summary: Some new graphs of contribution to likelihood
316:
1.204 brouard 317: Revision 1.203 2015/09/30 17:45:14 brouard
318: Summary: looking at better estimation of the hessian
319:
320: Also a better criteria for convergence to the period prevalence And
321: therefore adding the number of years needed to converge. (The
322: prevalence in any alive state shold sum to one
323:
1.203 brouard 324: Revision 1.202 2015/09/22 19:45:16 brouard
325: Summary: Adding some overall graph on contribution to likelihood. Might change
326:
1.202 brouard 327: Revision 1.201 2015/09/15 17:34:58 brouard
328: Summary: 0.98r0
329:
330: - Some new graphs like suvival functions
331: - Some bugs fixed like model=1+age+V2.
332:
1.201 brouard 333: Revision 1.200 2015/09/09 16:53:55 brouard
334: Summary: Big bug thanks to Flavia
335:
336: Even model=1+age+V2. did not work anymore
337:
1.200 brouard 338: Revision 1.199 2015/09/07 14:09:23 brouard
339: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
340:
1.199 brouard 341: Revision 1.198 2015/09/03 07:14:39 brouard
342: Summary: 0.98q5 Flavia
343:
1.198 brouard 344: Revision 1.197 2015/09/01 18:24:39 brouard
345: *** empty log message ***
346:
1.197 brouard 347: Revision 1.196 2015/08/18 23:17:52 brouard
348: Summary: 0.98q5
349:
1.196 brouard 350: Revision 1.195 2015/08/18 16:28:39 brouard
351: Summary: Adding a hack for testing purpose
352:
353: After reading the title, ftol and model lines, if the comment line has
354: a q, starting with #q, the answer at the end of the run is quit. It
355: permits to run test files in batch with ctest. The former workaround was
356: $ echo q | imach foo.imach
357:
1.195 brouard 358: Revision 1.194 2015/08/18 13:32:00 brouard
359: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
360:
1.194 brouard 361: Revision 1.193 2015/08/04 07:17:42 brouard
362: Summary: 0.98q4
363:
1.193 brouard 364: Revision 1.192 2015/07/16 16:49:02 brouard
365: Summary: Fixing some outputs
366:
1.192 brouard 367: Revision 1.191 2015/07/14 10:00:33 brouard
368: Summary: Some fixes
369:
1.191 brouard 370: Revision 1.190 2015/05/05 08:51:13 brouard
371: Summary: Adding digits in output parameters (7 digits instead of 6)
372:
373: Fix 1+age+.
374:
1.190 brouard 375: Revision 1.189 2015/04/30 14:45:16 brouard
376: Summary: 0.98q2
377:
1.189 brouard 378: Revision 1.188 2015/04/30 08:27:53 brouard
379: *** empty log message ***
380:
1.188 brouard 381: Revision 1.187 2015/04/29 09:11:15 brouard
382: *** empty log message ***
383:
1.187 brouard 384: Revision 1.186 2015/04/23 12:01:52 brouard
385: Summary: V1*age is working now, version 0.98q1
386:
387: Some codes had been disabled in order to simplify and Vn*age was
388: working in the optimization phase, ie, giving correct MLE parameters,
389: but, as usual, outputs were not correct and program core dumped.
390:
1.186 brouard 391: Revision 1.185 2015/03/11 13:26:42 brouard
392: Summary: Inclusion of compile and links command line for Intel Compiler
393:
1.185 brouard 394: Revision 1.184 2015/03/11 11:52:39 brouard
395: Summary: Back from Windows 8. Intel Compiler
396:
1.184 brouard 397: Revision 1.183 2015/03/10 20:34:32 brouard
398: Summary: 0.98q0, trying with directest, mnbrak fixed
399:
400: We use directest instead of original Powell test; probably no
401: incidence on the results, but better justifications;
402: We fixed Numerical Recipes mnbrak routine which was wrong and gave
403: wrong results.
404:
1.183 brouard 405: Revision 1.182 2015/02/12 08:19:57 brouard
406: Summary: Trying to keep directest which seems simpler and more general
407: Author: Nicolas Brouard
408:
1.182 brouard 409: Revision 1.181 2015/02/11 23:22:24 brouard
410: Summary: Comments on Powell added
411:
412: Author:
413:
1.181 brouard 414: Revision 1.180 2015/02/11 17:33:45 brouard
415: Summary: Finishing move from main to function (hpijx and prevalence_limit)
416:
1.180 brouard 417: Revision 1.179 2015/01/04 09:57:06 brouard
418: Summary: back to OS/X
419:
1.179 brouard 420: Revision 1.178 2015/01/04 09:35:48 brouard
421: *** empty log message ***
422:
1.178 brouard 423: Revision 1.177 2015/01/03 18:40:56 brouard
424: Summary: Still testing ilc32 on OSX
425:
1.177 brouard 426: Revision 1.176 2015/01/03 16:45:04 brouard
427: *** empty log message ***
428:
1.176 brouard 429: Revision 1.175 2015/01/03 16:33:42 brouard
430: *** empty log message ***
431:
1.175 brouard 432: Revision 1.174 2015/01/03 16:15:49 brouard
433: Summary: Still in cross-compilation
434:
1.174 brouard 435: Revision 1.173 2015/01/03 12:06:26 brouard
436: Summary: trying to detect cross-compilation
437:
1.173 brouard 438: Revision 1.172 2014/12/27 12:07:47 brouard
439: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
440:
1.172 brouard 441: Revision 1.171 2014/12/23 13:26:59 brouard
442: Summary: Back from Visual C
443:
444: Still problem with utsname.h on Windows
445:
1.171 brouard 446: Revision 1.170 2014/12/23 11:17:12 brouard
447: Summary: Cleaning some \%% back to %%
448:
449: The escape was mandatory for a specific compiler (which one?), but too many warnings.
450:
1.170 brouard 451: Revision 1.169 2014/12/22 23:08:31 brouard
452: Summary: 0.98p
453:
454: Outputs some informations on compiler used, OS etc. Testing on different platforms.
455:
1.169 brouard 456: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 457: Summary: update
1.169 brouard 458:
1.168 brouard 459: Revision 1.167 2014/12/22 13:50:56 brouard
460: Summary: Testing uname and compiler version and if compiled 32 or 64
461:
462: Testing on Linux 64
463:
1.167 brouard 464: Revision 1.166 2014/12/22 11:40:47 brouard
465: *** empty log message ***
466:
1.166 brouard 467: Revision 1.165 2014/12/16 11:20:36 brouard
468: Summary: After compiling on Visual C
469:
470: * imach.c (Module): Merging 1.61 to 1.162
471:
1.165 brouard 472: Revision 1.164 2014/12/16 10:52:11 brouard
473: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
474:
475: * imach.c (Module): Merging 1.61 to 1.162
476:
1.164 brouard 477: Revision 1.163 2014/12/16 10:30:11 brouard
478: * imach.c (Module): Merging 1.61 to 1.162
479:
1.163 brouard 480: Revision 1.162 2014/09/25 11:43:39 brouard
481: Summary: temporary backup 0.99!
482:
1.162 brouard 483: Revision 1.1 2014/09/16 11:06:58 brouard
484: Summary: With some code (wrong) for nlopt
485:
486: Author:
487:
488: Revision 1.161 2014/09/15 20:41:41 brouard
489: Summary: Problem with macro SQR on Intel compiler
490:
1.161 brouard 491: Revision 1.160 2014/09/02 09:24:05 brouard
492: *** empty log message ***
493:
1.160 brouard 494: Revision 1.159 2014/09/01 10:34:10 brouard
495: Summary: WIN32
496: Author: Brouard
497:
1.159 brouard 498: Revision 1.158 2014/08/27 17:11:51 brouard
499: *** empty log message ***
500:
1.158 brouard 501: Revision 1.157 2014/08/27 16:26:55 brouard
502: Summary: Preparing windows Visual studio version
503: Author: Brouard
504:
505: In order to compile on Visual studio, time.h is now correct and time_t
506: and tm struct should be used. difftime should be used but sometimes I
507: just make the differences in raw time format (time(&now).
508: Trying to suppress #ifdef LINUX
509: Add xdg-open for __linux in order to open default browser.
510:
1.157 brouard 511: Revision 1.156 2014/08/25 20:10:10 brouard
512: *** empty log message ***
513:
1.156 brouard 514: Revision 1.155 2014/08/25 18:32:34 brouard
515: Summary: New compile, minor changes
516: Author: Brouard
517:
1.155 brouard 518: Revision 1.154 2014/06/20 17:32:08 brouard
519: Summary: Outputs now all graphs of convergence to period prevalence
520:
1.154 brouard 521: Revision 1.153 2014/06/20 16:45:46 brouard
522: Summary: If 3 live state, convergence to period prevalence on same graph
523: Author: Brouard
524:
1.153 brouard 525: Revision 1.152 2014/06/18 17:54:09 brouard
526: Summary: open browser, use gnuplot on same dir than imach if not found in the path
527:
1.152 brouard 528: Revision 1.151 2014/06/18 16:43:30 brouard
529: *** empty log message ***
530:
1.151 brouard 531: Revision 1.150 2014/06/18 16:42:35 brouard
532: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
533: Author: brouard
534:
1.150 brouard 535: Revision 1.149 2014/06/18 15:51:14 brouard
536: Summary: Some fixes in parameter files errors
537: Author: Nicolas Brouard
538:
1.149 brouard 539: Revision 1.148 2014/06/17 17:38:48 brouard
540: Summary: Nothing new
541: Author: Brouard
542:
543: Just a new packaging for OS/X version 0.98nS
544:
1.148 brouard 545: Revision 1.147 2014/06/16 10:33:11 brouard
546: *** empty log message ***
547:
1.147 brouard 548: Revision 1.146 2014/06/16 10:20:28 brouard
549: Summary: Merge
550: Author: Brouard
551:
552: Merge, before building revised version.
553:
1.146 brouard 554: Revision 1.145 2014/06/10 21:23:15 brouard
555: Summary: Debugging with valgrind
556: Author: Nicolas Brouard
557:
558: Lot of changes in order to output the results with some covariates
559: After the Edimburgh REVES conference 2014, it seems mandatory to
560: improve the code.
561: No more memory valgrind error but a lot has to be done in order to
562: continue the work of splitting the code into subroutines.
563: Also, decodemodel has been improved. Tricode is still not
564: optimal. nbcode should be improved. Documentation has been added in
565: the source code.
566:
1.144 brouard 567: Revision 1.143 2014/01/26 09:45:38 brouard
568: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
569:
570: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
571: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
572:
1.143 brouard 573: Revision 1.142 2014/01/26 03:57:36 brouard
574: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
575:
576: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
577:
1.142 brouard 578: Revision 1.141 2014/01/26 02:42:01 brouard
579: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
580:
1.141 brouard 581: Revision 1.140 2011/09/02 10:37:54 brouard
582: Summary: times.h is ok with mingw32 now.
583:
1.140 brouard 584: Revision 1.139 2010/06/14 07:50:17 brouard
585: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
586: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
587:
1.139 brouard 588: Revision 1.138 2010/04/30 18:19:40 brouard
589: *** empty log message ***
590:
1.138 brouard 591: Revision 1.137 2010/04/29 18:11:38 brouard
592: (Module): Checking covariates for more complex models
593: than V1+V2. A lot of change to be done. Unstable.
594:
1.137 brouard 595: Revision 1.136 2010/04/26 20:30:53 brouard
596: (Module): merging some libgsl code. Fixing computation
597: of likelione (using inter/intrapolation if mle = 0) in order to
598: get same likelihood as if mle=1.
599: Some cleaning of code and comments added.
600:
1.136 brouard 601: Revision 1.135 2009/10/29 15:33:14 brouard
602: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
603:
1.135 brouard 604: Revision 1.134 2009/10/29 13:18:53 brouard
605: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
606:
1.134 brouard 607: Revision 1.133 2009/07/06 10:21:25 brouard
608: just nforces
609:
1.133 brouard 610: Revision 1.132 2009/07/06 08:22:05 brouard
611: Many tings
612:
1.132 brouard 613: Revision 1.131 2009/06/20 16:22:47 brouard
614: Some dimensions resccaled
615:
1.131 brouard 616: Revision 1.130 2009/05/26 06:44:34 brouard
617: (Module): Max Covariate is now set to 20 instead of 8. A
618: lot of cleaning with variables initialized to 0. Trying to make
619: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
620:
1.130 brouard 621: Revision 1.129 2007/08/31 13:49:27 lievre
622: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
623:
1.129 lievre 624: Revision 1.128 2006/06/30 13:02:05 brouard
625: (Module): Clarifications on computing e.j
626:
1.128 brouard 627: Revision 1.127 2006/04/28 18:11:50 brouard
628: (Module): Yes the sum of survivors was wrong since
629: imach-114 because nhstepm was no more computed in the age
630: loop. Now we define nhstepma in the age loop.
631: (Module): In order to speed up (in case of numerous covariates) we
632: compute health expectancies (without variances) in a first step
633: and then all the health expectancies with variances or standard
634: deviation (needs data from the Hessian matrices) which slows the
635: computation.
636: In the future we should be able to stop the program is only health
637: expectancies and graph are needed without standard deviations.
638:
1.127 brouard 639: Revision 1.126 2006/04/28 17:23:28 brouard
640: (Module): Yes the sum of survivors was wrong since
641: imach-114 because nhstepm was no more computed in the age
642: loop. Now we define nhstepma in the age loop.
643: Version 0.98h
644:
1.126 brouard 645: Revision 1.125 2006/04/04 15:20:31 lievre
646: Errors in calculation of health expectancies. Age was not initialized.
647: Forecasting file added.
648:
649: Revision 1.124 2006/03/22 17:13:53 lievre
650: Parameters are printed with %lf instead of %f (more numbers after the comma).
651: The log-likelihood is printed in the log file
652:
653: Revision 1.123 2006/03/20 10:52:43 brouard
654: * imach.c (Module): <title> changed, corresponds to .htm file
655: name. <head> headers where missing.
656:
657: * imach.c (Module): Weights can have a decimal point as for
658: English (a comma might work with a correct LC_NUMERIC environment,
659: otherwise the weight is truncated).
660: Modification of warning when the covariates values are not 0 or
661: 1.
662: Version 0.98g
663:
664: Revision 1.122 2006/03/20 09:45:41 brouard
665: (Module): Weights can have a decimal point as for
666: English (a comma might work with a correct LC_NUMERIC environment,
667: otherwise the weight is truncated).
668: Modification of warning when the covariates values are not 0 or
669: 1.
670: Version 0.98g
671:
672: Revision 1.121 2006/03/16 17:45:01 lievre
673: * imach.c (Module): Comments concerning covariates added
674:
675: * imach.c (Module): refinements in the computation of lli if
676: status=-2 in order to have more reliable computation if stepm is
677: not 1 month. Version 0.98f
678:
679: Revision 1.120 2006/03/16 15:10:38 lievre
680: (Module): refinements in the computation of lli if
681: status=-2 in order to have more reliable computation if stepm is
682: not 1 month. Version 0.98f
683:
684: Revision 1.119 2006/03/15 17:42:26 brouard
685: (Module): Bug if status = -2, the loglikelihood was
686: computed as likelihood omitting the logarithm. Version O.98e
687:
688: Revision 1.118 2006/03/14 18:20:07 brouard
689: (Module): varevsij Comments added explaining the second
690: table of variances if popbased=1 .
691: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
692: (Module): Function pstamp added
693: (Module): Version 0.98d
694:
695: Revision 1.117 2006/03/14 17:16:22 brouard
696: (Module): varevsij Comments added explaining the second
697: table of variances if popbased=1 .
698: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
699: (Module): Function pstamp added
700: (Module): Version 0.98d
701:
702: Revision 1.116 2006/03/06 10:29:27 brouard
703: (Module): Variance-covariance wrong links and
704: varian-covariance of ej. is needed (Saito).
705:
706: Revision 1.115 2006/02/27 12:17:45 brouard
707: (Module): One freematrix added in mlikeli! 0.98c
708:
709: Revision 1.114 2006/02/26 12:57:58 brouard
710: (Module): Some improvements in processing parameter
711: filename with strsep.
712:
713: Revision 1.113 2006/02/24 14:20:24 brouard
714: (Module): Memory leaks checks with valgrind and:
715: datafile was not closed, some imatrix were not freed and on matrix
716: allocation too.
717:
718: Revision 1.112 2006/01/30 09:55:26 brouard
719: (Module): Back to gnuplot.exe instead of wgnuplot.exe
720:
721: Revision 1.111 2006/01/25 20:38:18 brouard
722: (Module): Lots of cleaning and bugs added (Gompertz)
723: (Module): Comments can be added in data file. Missing date values
724: can be a simple dot '.'.
725:
726: Revision 1.110 2006/01/25 00:51:50 brouard
727: (Module): Lots of cleaning and bugs added (Gompertz)
728:
729: Revision 1.109 2006/01/24 19:37:15 brouard
730: (Module): Comments (lines starting with a #) are allowed in data.
731:
732: Revision 1.108 2006/01/19 18:05:42 lievre
733: Gnuplot problem appeared...
734: To be fixed
735:
736: Revision 1.107 2006/01/19 16:20:37 brouard
737: Test existence of gnuplot in imach path
738:
739: Revision 1.106 2006/01/19 13:24:36 brouard
740: Some cleaning and links added in html output
741:
742: Revision 1.105 2006/01/05 20:23:19 lievre
743: *** empty log message ***
744:
745: Revision 1.104 2005/09/30 16:11:43 lievre
746: (Module): sump fixed, loop imx fixed, and simplifications.
747: (Module): If the status is missing at the last wave but we know
748: that the person is alive, then we can code his/her status as -2
749: (instead of missing=-1 in earlier versions) and his/her
750: contributions to the likelihood is 1 - Prob of dying from last
751: health status (= 1-p13= p11+p12 in the easiest case of somebody in
752: the healthy state at last known wave). Version is 0.98
753:
754: Revision 1.103 2005/09/30 15:54:49 lievre
755: (Module): sump fixed, loop imx fixed, and simplifications.
756:
757: Revision 1.102 2004/09/15 17:31:30 brouard
758: Add the possibility to read data file including tab characters.
759:
760: Revision 1.101 2004/09/15 10:38:38 brouard
761: Fix on curr_time
762:
763: Revision 1.100 2004/07/12 18:29:06 brouard
764: Add version for Mac OS X. Just define UNIX in Makefile
765:
766: Revision 1.99 2004/06/05 08:57:40 brouard
767: *** empty log message ***
768:
769: Revision 1.98 2004/05/16 15:05:56 brouard
770: New version 0.97 . First attempt to estimate force of mortality
771: directly from the data i.e. without the need of knowing the health
772: state at each age, but using a Gompertz model: log u =a + b*age .
773: This is the basic analysis of mortality and should be done before any
774: other analysis, in order to test if the mortality estimated from the
775: cross-longitudinal survey is different from the mortality estimated
776: from other sources like vital statistic data.
777:
778: The same imach parameter file can be used but the option for mle should be -3.
779:
1.133 brouard 780: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 781: former routines in order to include the new code within the former code.
782:
783: The output is very simple: only an estimate of the intercept and of
784: the slope with 95% confident intervals.
785:
786: Current limitations:
787: A) Even if you enter covariates, i.e. with the
788: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
789: B) There is no computation of Life Expectancy nor Life Table.
790:
791: Revision 1.97 2004/02/20 13:25:42 lievre
792: Version 0.96d. Population forecasting command line is (temporarily)
793: suppressed.
794:
795: Revision 1.96 2003/07/15 15:38:55 brouard
796: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
797: rewritten within the same printf. Workaround: many printfs.
798:
799: Revision 1.95 2003/07/08 07:54:34 brouard
800: * imach.c (Repository):
801: (Repository): Using imachwizard code to output a more meaningful covariance
802: matrix (cov(a12,c31) instead of numbers.
803:
804: Revision 1.94 2003/06/27 13:00:02 brouard
805: Just cleaning
806:
807: Revision 1.93 2003/06/25 16:33:55 brouard
808: (Module): On windows (cygwin) function asctime_r doesn't
809: exist so I changed back to asctime which exists.
810: (Module): Version 0.96b
811:
812: Revision 1.92 2003/06/25 16:30:45 brouard
813: (Module): On windows (cygwin) function asctime_r doesn't
814: exist so I changed back to asctime which exists.
815:
816: Revision 1.91 2003/06/25 15:30:29 brouard
817: * imach.c (Repository): Duplicated warning errors corrected.
818: (Repository): Elapsed time after each iteration is now output. It
819: helps to forecast when convergence will be reached. Elapsed time
820: is stamped in powell. We created a new html file for the graphs
821: concerning matrix of covariance. It has extension -cov.htm.
822:
823: Revision 1.90 2003/06/24 12:34:15 brouard
824: (Module): Some bugs corrected for windows. Also, when
825: mle=-1 a template is output in file "or"mypar.txt with the design
826: of the covariance matrix to be input.
827:
828: Revision 1.89 2003/06/24 12:30:52 brouard
829: (Module): Some bugs corrected for windows. Also, when
830: mle=-1 a template is output in file "or"mypar.txt with the design
831: of the covariance matrix to be input.
832:
833: Revision 1.88 2003/06/23 17:54:56 brouard
834: * 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.
835:
836: Revision 1.87 2003/06/18 12:26:01 brouard
837: Version 0.96
838:
839: Revision 1.86 2003/06/17 20:04:08 brouard
840: (Module): Change position of html and gnuplot routines and added
841: routine fileappend.
842:
843: Revision 1.85 2003/06/17 13:12:43 brouard
844: * imach.c (Repository): Check when date of death was earlier that
845: current date of interview. It may happen when the death was just
846: prior to the death. In this case, dh was negative and likelihood
847: was wrong (infinity). We still send an "Error" but patch by
848: assuming that the date of death was just one stepm after the
849: interview.
850: (Repository): Because some people have very long ID (first column)
851: we changed int to long in num[] and we added a new lvector for
852: memory allocation. But we also truncated to 8 characters (left
853: truncation)
854: (Repository): No more line truncation errors.
855:
856: Revision 1.84 2003/06/13 21:44:43 brouard
857: * imach.c (Repository): Replace "freqsummary" at a correct
858: place. It differs from routine "prevalence" which may be called
859: many times. Probs is memory consuming and must be used with
860: parcimony.
861: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
862:
863: Revision 1.83 2003/06/10 13:39:11 lievre
864: *** empty log message ***
865:
866: Revision 1.82 2003/06/05 15:57:20 brouard
867: Add log in imach.c and fullversion number is now printed.
868:
869: */
870: /*
871: Interpolated Markov Chain
872:
873: Short summary of the programme:
874:
1.227 brouard 875: This program computes Healthy Life Expectancies or State-specific
876: (if states aren't health statuses) Expectancies from
877: cross-longitudinal data. Cross-longitudinal data consist in:
878:
879: -1- a first survey ("cross") where individuals from different ages
880: are interviewed on their health status or degree of disability (in
881: the case of a health survey which is our main interest)
882:
883: -2- at least a second wave of interviews ("longitudinal") which
884: measure each change (if any) in individual health status. Health
885: expectancies are computed from the time spent in each health state
886: according to a model. More health states you consider, more time is
887: necessary to reach the Maximum Likelihood of the parameters involved
888: in the model. The simplest model is the multinomial logistic model
889: where pij is the probability to be observed in state j at the second
890: wave conditional to be observed in state i at the first
891: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
892: etc , where 'age' is age and 'sex' is a covariate. If you want to
893: have a more complex model than "constant and age", you should modify
894: the program where the markup *Covariates have to be included here
895: again* invites you to do it. More covariates you add, slower the
1.126 brouard 896: convergence.
897:
898: The advantage of this computer programme, compared to a simple
899: multinomial logistic model, is clear when the delay between waves is not
900: identical for each individual. Also, if a individual missed an
901: intermediate interview, the information is lost, but taken into
902: account using an interpolation or extrapolation.
903:
904: hPijx is the probability to be observed in state i at age x+h
905: conditional to the observed state i at age x. The delay 'h' can be
906: split into an exact number (nh*stepm) of unobserved intermediate
907: states. This elementary transition (by month, quarter,
908: semester or year) is modelled as a multinomial logistic. The hPx
909: matrix is simply the matrix product of nh*stepm elementary matrices
910: and the contribution of each individual to the likelihood is simply
911: hPijx.
912:
913: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 914: of the life expectancies. It also computes the period (stable) prevalence.
915:
916: Back prevalence and projections:
1.227 brouard 917:
918: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
919: double agemaxpar, double ftolpl, int *ncvyearp, double
920: dateprev1,double dateprev2, int firstpass, int lastpass, int
921: mobilavproj)
922:
923: Computes the back prevalence limit for any combination of
924: covariate values k at any age between ageminpar and agemaxpar and
925: returns it in **bprlim. In the loops,
926:
927: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
928: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
929:
930: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 931: Computes for any combination of covariates k and any age between bage and fage
932: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
933: oldm=oldms;savm=savms;
1.227 brouard 934:
1.267 brouard 935: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 936: Computes the transition matrix starting at age 'age' over
937: 'nhstepm*hstepm*stepm' months (i.e. until
938: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 939: nhstepm*hstepm matrices.
940:
941: Returns p3mat[i][j][h] after calling
942: p3mat[i][j][h]=matprod2(newm,
943: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
944: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
945: oldm);
1.226 brouard 946:
947: Important routines
948:
949: - func (or funcone), computes logit (pij) distinguishing
950: o fixed variables (single or product dummies or quantitative);
951: o varying variables by:
952: (1) wave (single, product dummies, quantitative),
953: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
954: % fixed dummy (treated) or quantitative (not done because time-consuming);
955: % varying dummy (not done) or quantitative (not done);
956: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
957: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
958: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
959: o There are 2*cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
960: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 961:
1.226 brouard 962:
963:
1.133 brouard 964: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
965: Institut national d'études démographiques, Paris.
1.126 brouard 966: This software have been partly granted by Euro-REVES, a concerted action
967: from the European Union.
968: It is copyrighted identically to a GNU software product, ie programme and
969: software can be distributed freely for non commercial use. Latest version
970: can be accessed at http://euroreves.ined.fr/imach .
971:
972: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
973: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
974:
975: **********************************************************************/
976: /*
977: main
978: read parameterfile
979: read datafile
980: concatwav
981: freqsummary
982: if (mle >= 1)
983: mlikeli
984: print results files
985: if mle==1
986: computes hessian
987: read end of parameter file: agemin, agemax, bage, fage, estepm
988: begin-prev-date,...
989: open gnuplot file
990: open html file
1.145 brouard 991: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
992: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
993: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
994: freexexit2 possible for memory heap.
995:
996: h Pij x | pij_nom ficrestpij
997: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
998: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
999: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
1000:
1001: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
1002: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
1003: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
1004: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
1005: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
1006:
1.126 brouard 1007: forecasting if prevfcast==1 prevforecast call prevalence()
1008: health expectancies
1009: Variance-covariance of DFLE
1010: prevalence()
1011: movingaverage()
1012: varevsij()
1013: if popbased==1 varevsij(,popbased)
1014: total life expectancies
1015: Variance of period (stable) prevalence
1016: end
1017: */
1018:
1.187 brouard 1019: /* #define DEBUG */
1020: /* #define DEBUGBRENT */
1.203 brouard 1021: /* #define DEBUGLINMIN */
1022: /* #define DEBUGHESS */
1023: #define DEBUGHESSIJ
1.224 brouard 1024: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 1025: #define POWELL /* Instead of NLOPT */
1.224 brouard 1026: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 1027: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
1028: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.126 brouard 1029:
1030: #include <math.h>
1031: #include <stdio.h>
1032: #include <stdlib.h>
1033: #include <string.h>
1.226 brouard 1034: #include <ctype.h>
1.159 brouard 1035:
1036: #ifdef _WIN32
1037: #include <io.h>
1.172 brouard 1038: #include <windows.h>
1039: #include <tchar.h>
1.159 brouard 1040: #else
1.126 brouard 1041: #include <unistd.h>
1.159 brouard 1042: #endif
1.126 brouard 1043:
1044: #include <limits.h>
1045: #include <sys/types.h>
1.171 brouard 1046:
1047: #if defined(__GNUC__)
1048: #include <sys/utsname.h> /* Doesn't work on Windows */
1049: #endif
1050:
1.126 brouard 1051: #include <sys/stat.h>
1052: #include <errno.h>
1.159 brouard 1053: /* extern int errno; */
1.126 brouard 1054:
1.157 brouard 1055: /* #ifdef LINUX */
1056: /* #include <time.h> */
1057: /* #include "timeval.h" */
1058: /* #else */
1059: /* #include <sys/time.h> */
1060: /* #endif */
1061:
1.126 brouard 1062: #include <time.h>
1063:
1.136 brouard 1064: #ifdef GSL
1065: #include <gsl/gsl_errno.h>
1066: #include <gsl/gsl_multimin.h>
1067: #endif
1068:
1.167 brouard 1069:
1.162 brouard 1070: #ifdef NLOPT
1071: #include <nlopt.h>
1072: typedef struct {
1073: double (* function)(double [] );
1074: } myfunc_data ;
1075: #endif
1076:
1.126 brouard 1077: /* #include <libintl.h> */
1078: /* #define _(String) gettext (String) */
1079:
1.251 brouard 1080: #define MAXLINE 2048 /* Was 256 and 1024. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 1081:
1082: #define GNUPLOTPROGRAM "gnuplot"
1083: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
1084: #define FILENAMELENGTH 132
1085:
1086: #define GLOCK_ERROR_NOPATH -1 /* empty path */
1087: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
1088:
1.144 brouard 1089: #define MAXPARM 128 /**< Maximum number of parameters for the optimization */
1090: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 1091:
1092: #define NINTERVMAX 8
1.144 brouard 1093: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
1094: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
1.291 brouard 1095: #define NCOVMAX 20 /**< Maximum number of covariates, including generated covariates V1*V2 */
1.197 brouard 1096: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 1097: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
1098: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.290 brouard 1099: /*#define MAXN 20000 */ /* Should by replaced by nobs, real number of observations and unlimited */
1.144 brouard 1100: #define YEARM 12. /**< Number of months per year */
1.218 brouard 1101: /* #define AGESUP 130 */
1.288 brouard 1102: /* #define AGESUP 150 */
1103: #define AGESUP 200
1.268 brouard 1104: #define AGEINF 0
1.218 brouard 1105: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1106: #define AGEBASE 40
1.194 brouard 1107: #define AGEOVERFLOW 1.e20
1.164 brouard 1108: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1109: #ifdef _WIN32
1110: #define DIRSEPARATOR '\\'
1111: #define CHARSEPARATOR "\\"
1112: #define ODIRSEPARATOR '/'
1113: #else
1.126 brouard 1114: #define DIRSEPARATOR '/'
1115: #define CHARSEPARATOR "/"
1116: #define ODIRSEPARATOR '\\'
1117: #endif
1118:
1.300 ! brouard 1119: /* $Id: imach.c,v 1.299 2019/05/22 18:37:08 brouard Exp $ */
1.126 brouard 1120: /* $State: Exp $ */
1.196 brouard 1121: #include "version.h"
1122: char version[]=__IMACH_VERSION__;
1.300 ! brouard 1123: 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";
! 1124: char fullversion[]="$Revision: 1.299 $ $Date: 2019/05/22 18:37:08 $";
1.126 brouard 1125: char strstart[80];
1126: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1127: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.187 brouard 1128: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.145 brouard 1129: /* Number of covariates model=V2+V1+ V3*age+V2*V4 */
1130: int cptcovn=0; /**< cptcovn number of covariates added in the model (excepting constant and age and age*product) */
1131: int cptcovt=0; /**< cptcovt number of covariates added in the model (excepting constant and age) */
1.225 brouard 1132: int cptcovs=0; /**< cptcovs number of simple covariates in the model V2+V1 =2 */
1133: int cptcovsnq=0; /**< cptcovsnq number of simple covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1134: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1135: int cptcovprodnoage=0; /**< Number of covariate products without age */
1136: int cptcoveff=0; /* Total number of covariates to vary for printing results */
1.233 brouard 1137: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1138: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.232 brouard 1139: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (dummy of quantitative) in the model */
1.234 brouard 1140: int nsd=0; /**< Total number of single dummy variables (output) */
1141: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1142: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1143: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1144: int ntveff=0; /**< ntveff number of effective time varying variables */
1145: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1146: int cptcov=0; /* Working variable */
1.290 brouard 1147: int nobs=10; /* Number of observations in the data lastobs-firstobs */
1.218 brouard 1148: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.126 brouard 1149: int npar=NPARMAX;
1150: int nlstate=2; /* Number of live states */
1151: int ndeath=1; /* Number of dead states */
1.130 brouard 1152: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.223 brouard 1153: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable */
1.126 brouard 1154: int popbased=0;
1155:
1156: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1157: int maxwav=0; /* Maxim number of waves */
1158: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1159: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1160: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 1161: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1162: int mle=1, weightopt=0;
1.126 brouard 1163: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1164: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1165: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1166: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1167: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1168: int selected(int kvar); /* Is covariate kvar selected for printing results */
1169:
1.130 brouard 1170: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1171: double **matprod2(); /* test */
1.126 brouard 1172: double **oldm, **newm, **savm; /* Working pointers to matrices */
1173: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1174: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1175:
1.136 brouard 1176: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1177: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1178: FILE *ficlog, *ficrespow;
1.130 brouard 1179: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1180: double fretone; /* Only one call to likelihood */
1.130 brouard 1181: long ipmx=0; /* Number of contributions */
1.126 brouard 1182: double sw; /* Sum of weights */
1183: char filerespow[FILENAMELENGTH];
1184: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1185: FILE *ficresilk;
1186: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1187: FILE *ficresprobmorprev;
1188: FILE *fichtm, *fichtmcov; /* Html File */
1189: FILE *ficreseij;
1190: char filerese[FILENAMELENGTH];
1191: FILE *ficresstdeij;
1192: char fileresstde[FILENAMELENGTH];
1193: FILE *ficrescveij;
1194: char filerescve[FILENAMELENGTH];
1195: FILE *ficresvij;
1196: char fileresv[FILENAMELENGTH];
1.269 brouard 1197:
1.126 brouard 1198: char title[MAXLINE];
1.234 brouard 1199: char model[MAXLINE]; /**< The model line */
1.217 brouard 1200: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1201: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1202: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1203: char command[FILENAMELENGTH];
1204: int outcmd=0;
1205:
1.217 brouard 1206: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1207: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1208: char filelog[FILENAMELENGTH]; /* Log file */
1209: char filerest[FILENAMELENGTH];
1210: char fileregp[FILENAMELENGTH];
1211: char popfile[FILENAMELENGTH];
1212:
1213: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1214:
1.157 brouard 1215: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1216: /* struct timezone tzp; */
1217: /* extern int gettimeofday(); */
1218: struct tm tml, *gmtime(), *localtime();
1219:
1220: extern time_t time();
1221:
1222: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1223: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1224: struct tm tm;
1225:
1.126 brouard 1226: char strcurr[80], strfor[80];
1227:
1228: char *endptr;
1229: long lval;
1230: double dval;
1231:
1232: #define NR_END 1
1233: #define FREE_ARG char*
1234: #define FTOL 1.0e-10
1235:
1236: #define NRANSI
1.240 brouard 1237: #define ITMAX 200
1238: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1239:
1240: #define TOL 2.0e-4
1241:
1242: #define CGOLD 0.3819660
1243: #define ZEPS 1.0e-10
1244: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1245:
1246: #define GOLD 1.618034
1247: #define GLIMIT 100.0
1248: #define TINY 1.0e-20
1249:
1250: static double maxarg1,maxarg2;
1251: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1252: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1253:
1254: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1255: #define rint(a) floor(a+0.5)
1.166 brouard 1256: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1257: #define mytinydouble 1.0e-16
1.166 brouard 1258: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1259: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1260: /* static double dsqrarg; */
1261: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1262: static double sqrarg;
1263: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1264: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1265: int agegomp= AGEGOMP;
1266:
1267: int imx;
1268: int stepm=1;
1269: /* Stepm, step in month: minimum step interpolation*/
1270:
1271: int estepm;
1272: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1273:
1274: int m,nb;
1275: long *num;
1.197 brouard 1276: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1277: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1278: covariate for which somebody answered excluding
1279: undefined. Usually 2: 0 and 1. */
1280: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1281: covariate for which somebody answered including
1282: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1283: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1284: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1285: double ***mobaverage, ***mobaverages; /* New global variable */
1.126 brouard 1286: double *ageexmed,*agecens;
1287: double dateintmean=0;
1.296 brouard 1288: double anprojd, mprojd, jprojd; /* For eventual projections */
1289: double anprojf, mprojf, jprojf;
1.126 brouard 1290:
1.296 brouard 1291: double anbackd, mbackd, jbackd; /* For eventual backprojections */
1292: double anbackf, mbackf, jbackf;
1293: double jintmean,mintmean,aintmean;
1.126 brouard 1294: double *weight;
1295: int **s; /* Status */
1.141 brouard 1296: double *agedc;
1.145 brouard 1297: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1298: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1299: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1300: double **coqvar; /* Fixed quantitative covariate nqv */
1301: double ***cotvar; /* Time varying covariate ntv */
1.225 brouard 1302: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1303: double idx;
1304: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.234 brouard 1305: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1306: /*k 1 2 3 4 5 6 7 8 9 */
1307: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 */
1308: /* Tndvar[k] 1 2 3 4 5 */
1309: /*TDvar 4 3 6 7 1 */ /* For outputs only; combination of dummies fixed or varying */
1310: /* Tns[k] 1 2 2 4 5 */ /* Number of single cova */
1311: /* TvarsD[k] 1 2 3 */ /* Number of single dummy cova */
1312: /* TvarsDind 2 3 9 */ /* position K of single dummy cova */
1313: /* TvarsQ[k] 1 2 */ /* Number of single quantitative cova */
1314: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1315: /* Tprod[i]=k 4 7 */
1316: /* Tage[i]=k 5 8 */
1317: /* */
1318: /* Type */
1319: /* V 1 2 3 4 5 */
1320: /* F F V V V */
1321: /* D Q D D Q */
1322: /* */
1323: int *TvarsD;
1324: int *TvarsDind;
1325: int *TvarsQ;
1326: int *TvarsQind;
1327:
1.235 brouard 1328: #define MAXRESULTLINES 10
1329: int nresult=0;
1.258 brouard 1330: int parameterline=0; /* # of the parameter (type) line */
1.235 brouard 1331: int TKresult[MAXRESULTLINES];
1.237 brouard 1332: int Tresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */
1333: int Tinvresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */
1.235 brouard 1334: int Tvresult[MAXRESULTLINES][NCOVMAX]; /* For dummy variable , variable # (output) */
1335: double Tqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */
1.237 brouard 1336: double Tqinvresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */
1.235 brouard 1337: int Tvqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , variable # (output) */
1338:
1.234 brouard 1339: /* 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 1340: 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 */
1341: 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 */
1342: 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 */
1343: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1344: 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 */
1345: 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 1346: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1347: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1348: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1349: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1350: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1351: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1352: 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 */
1353: 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 */
1354:
1.230 brouard 1355: int *Tvarsel; /**< Selected covariates for output */
1356: double *Tvalsel; /**< Selected modality value of covariate for output */
1.226 brouard 1357: int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.227 brouard 1358: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1359: 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 1360: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1361: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1362: int *Tage;
1.227 brouard 1363: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1364: 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 1365: 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*/
1366: 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 1367: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1368: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1369: int **Tvard;
1370: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1371: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1372: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1373: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1374: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1375: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1376: double *lsurv, *lpop, *tpop;
1377:
1.231 brouard 1378: #define FD 1; /* Fixed dummy covariate */
1379: #define FQ 2; /* Fixed quantitative covariate */
1380: #define FP 3; /* Fixed product covariate */
1381: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1382: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1383: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1384: #define VD 10; /* Varying dummy covariate */
1385: #define VQ 11; /* Varying quantitative covariate */
1386: #define VP 12; /* Varying product covariate */
1387: #define VPDD 13; /* Varying product dummy*dummy covariate */
1388: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1389: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1390: #define APFD 16; /* Age product * fixed dummy covariate */
1391: #define APFQ 17; /* Age product * fixed quantitative covariate */
1392: #define APVD 18; /* Age product * varying dummy covariate */
1393: #define APVQ 19; /* Age product * varying quantitative covariate */
1394:
1395: #define FTYPE 1; /* Fixed covariate */
1396: #define VTYPE 2; /* Varying covariate (loop in wave) */
1397: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1398:
1399: struct kmodel{
1400: int maintype; /* main type */
1401: int subtype; /* subtype */
1402: };
1403: struct kmodel modell[NCOVMAX];
1404:
1.143 brouard 1405: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1406: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1407:
1408: /**************** split *************************/
1409: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1410: {
1411: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1412: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1413: */
1414: char *ss; /* pointer */
1.186 brouard 1415: int l1=0, l2=0; /* length counters */
1.126 brouard 1416:
1417: l1 = strlen(path ); /* length of path */
1418: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1419: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1420: if ( ss == NULL ) { /* no directory, so determine current directory */
1421: strcpy( name, path ); /* we got the fullname name because no directory */
1422: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1423: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1424: /* get current working directory */
1425: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1426: #ifdef WIN32
1427: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1428: #else
1429: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1430: #endif
1.126 brouard 1431: return( GLOCK_ERROR_GETCWD );
1432: }
1433: /* got dirc from getcwd*/
1434: printf(" DIRC = %s \n",dirc);
1.205 brouard 1435: } else { /* strip directory from path */
1.126 brouard 1436: ss++; /* after this, the filename */
1437: l2 = strlen( ss ); /* length of filename */
1438: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1439: strcpy( name, ss ); /* save file name */
1440: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1441: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1442: printf(" DIRC2 = %s \n",dirc);
1443: }
1444: /* We add a separator at the end of dirc if not exists */
1445: l1 = strlen( dirc ); /* length of directory */
1446: if( dirc[l1-1] != DIRSEPARATOR ){
1447: dirc[l1] = DIRSEPARATOR;
1448: dirc[l1+1] = 0;
1449: printf(" DIRC3 = %s \n",dirc);
1450: }
1451: ss = strrchr( name, '.' ); /* find last / */
1452: if (ss >0){
1453: ss++;
1454: strcpy(ext,ss); /* save extension */
1455: l1= strlen( name);
1456: l2= strlen(ss)+1;
1457: strncpy( finame, name, l1-l2);
1458: finame[l1-l2]= 0;
1459: }
1460:
1461: return( 0 ); /* we're done */
1462: }
1463:
1464:
1465: /******************************************/
1466:
1467: void replace_back_to_slash(char *s, char*t)
1468: {
1469: int i;
1470: int lg=0;
1471: i=0;
1472: lg=strlen(t);
1473: for(i=0; i<= lg; i++) {
1474: (s[i] = t[i]);
1475: if (t[i]== '\\') s[i]='/';
1476: }
1477: }
1478:
1.132 brouard 1479: char *trimbb(char *out, char *in)
1.137 brouard 1480: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1481: char *s;
1482: s=out;
1483: while (*in != '\0'){
1.137 brouard 1484: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1485: in++;
1486: }
1487: *out++ = *in++;
1488: }
1489: *out='\0';
1490: return s;
1491: }
1492:
1.187 brouard 1493: /* char *substrchaine(char *out, char *in, char *chain) */
1494: /* { */
1495: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1496: /* char *s, *t; */
1497: /* t=in;s=out; */
1498: /* while ((*in != *chain) && (*in != '\0')){ */
1499: /* *out++ = *in++; */
1500: /* } */
1501:
1502: /* /\* *in matches *chain *\/ */
1503: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1504: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1505: /* } */
1506: /* in--; chain--; */
1507: /* while ( (*in != '\0')){ */
1508: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1509: /* *out++ = *in++; */
1510: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1511: /* } */
1512: /* *out='\0'; */
1513: /* out=s; */
1514: /* return out; */
1515: /* } */
1516: char *substrchaine(char *out, char *in, char *chain)
1517: {
1518: /* Substract chain 'chain' from 'in', return and output 'out' */
1519: /* in="V1+V1*age+age*age+V2", chain="age*age" */
1520:
1521: char *strloc;
1522:
1523: strcpy (out, in);
1524: strloc = strstr(out, chain); /* strloc points to out at age*age+V2 */
1525: printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out);
1526: if(strloc != NULL){
1527: /* will affect out */ /* strloc+strlenc(chain)=+V2 */ /* Will also work in Unicode */
1528: memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1);
1529: /* strcpy (strloc, strloc +strlen(chain));*/
1530: }
1531: printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out);
1532: return out;
1533: }
1534:
1535:
1.145 brouard 1536: char *cutl(char *blocc, char *alocc, char *in, char occ)
1537: {
1.187 brouard 1538: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.145 brouard 1539: and alocc starts after first occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1.187 brouard 1540: gives blocc="abcdef" and alocc="ghi2j".
1.145 brouard 1541: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1542: */
1.160 brouard 1543: char *s, *t;
1.145 brouard 1544: t=in;s=in;
1545: while ((*in != occ) && (*in != '\0')){
1546: *alocc++ = *in++;
1547: }
1548: if( *in == occ){
1549: *(alocc)='\0';
1550: s=++in;
1551: }
1552:
1553: if (s == t) {/* occ not found */
1554: *(alocc-(in-s))='\0';
1555: in=s;
1556: }
1557: while ( *in != '\0'){
1558: *blocc++ = *in++;
1559: }
1560:
1561: *blocc='\0';
1562: return t;
1563: }
1.137 brouard 1564: char *cutv(char *blocc, char *alocc, char *in, char occ)
1565: {
1.187 brouard 1566: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1567: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1568: gives blocc="abcdef2ghi" and alocc="j".
1569: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1570: */
1571: char *s, *t;
1572: t=in;s=in;
1573: while (*in != '\0'){
1574: while( *in == occ){
1575: *blocc++ = *in++;
1576: s=in;
1577: }
1578: *blocc++ = *in++;
1579: }
1580: if (s == t) /* occ not found */
1581: *(blocc-(in-s))='\0';
1582: else
1583: *(blocc-(in-s)-1)='\0';
1584: in=s;
1585: while ( *in != '\0'){
1586: *alocc++ = *in++;
1587: }
1588:
1589: *alocc='\0';
1590: return s;
1591: }
1592:
1.126 brouard 1593: int nbocc(char *s, char occ)
1594: {
1595: int i,j=0;
1596: int lg=20;
1597: i=0;
1598: lg=strlen(s);
1599: for(i=0; i<= lg; i++) {
1.234 brouard 1600: if (s[i] == occ ) j++;
1.126 brouard 1601: }
1602: return j;
1603: }
1604:
1.137 brouard 1605: /* void cutv(char *u,char *v, char*t, char occ) */
1606: /* { */
1607: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1608: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1609: /* gives u="abcdef2ghi" and v="j" *\/ */
1610: /* int i,lg,j,p=0; */
1611: /* i=0; */
1612: /* lg=strlen(t); */
1613: /* for(j=0; j<=lg-1; j++) { */
1614: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1615: /* } */
1.126 brouard 1616:
1.137 brouard 1617: /* for(j=0; j<p; j++) { */
1618: /* (u[j] = t[j]); */
1619: /* } */
1620: /* u[p]='\0'; */
1.126 brouard 1621:
1.137 brouard 1622: /* for(j=0; j<= lg; j++) { */
1623: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1624: /* } */
1625: /* } */
1.126 brouard 1626:
1.160 brouard 1627: #ifdef _WIN32
1628: char * strsep(char **pp, const char *delim)
1629: {
1630: char *p, *q;
1631:
1632: if ((p = *pp) == NULL)
1633: return 0;
1634: if ((q = strpbrk (p, delim)) != NULL)
1635: {
1636: *pp = q + 1;
1637: *q = '\0';
1638: }
1639: else
1640: *pp = 0;
1641: return p;
1642: }
1643: #endif
1644:
1.126 brouard 1645: /********************** nrerror ********************/
1646:
1647: void nrerror(char error_text[])
1648: {
1649: fprintf(stderr,"ERREUR ...\n");
1650: fprintf(stderr,"%s\n",error_text);
1651: exit(EXIT_FAILURE);
1652: }
1653: /*********************** vector *******************/
1654: double *vector(int nl, int nh)
1655: {
1656: double *v;
1657: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
1658: if (!v) nrerror("allocation failure in vector");
1659: return v-nl+NR_END;
1660: }
1661:
1662: /************************ free vector ******************/
1663: void free_vector(double*v, int nl, int nh)
1664: {
1665: free((FREE_ARG)(v+nl-NR_END));
1666: }
1667:
1668: /************************ivector *******************************/
1669: int *ivector(long nl,long nh)
1670: {
1671: int *v;
1672: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
1673: if (!v) nrerror("allocation failure in ivector");
1674: return v-nl+NR_END;
1675: }
1676:
1677: /******************free ivector **************************/
1678: void free_ivector(int *v, long nl, long nh)
1679: {
1680: free((FREE_ARG)(v+nl-NR_END));
1681: }
1682:
1683: /************************lvector *******************************/
1684: long *lvector(long nl,long nh)
1685: {
1686: long *v;
1687: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
1688: if (!v) nrerror("allocation failure in ivector");
1689: return v-nl+NR_END;
1690: }
1691:
1692: /******************free lvector **************************/
1693: void free_lvector(long *v, long nl, long nh)
1694: {
1695: free((FREE_ARG)(v+nl-NR_END));
1696: }
1697:
1698: /******************* imatrix *******************************/
1699: int **imatrix(long nrl, long nrh, long ncl, long nch)
1700: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
1701: {
1702: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
1703: int **m;
1704:
1705: /* allocate pointers to rows */
1706: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
1707: if (!m) nrerror("allocation failure 1 in matrix()");
1708: m += NR_END;
1709: m -= nrl;
1710:
1711:
1712: /* allocate rows and set pointers to them */
1713: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
1714: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1715: m[nrl] += NR_END;
1716: m[nrl] -= ncl;
1717:
1718: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
1719:
1720: /* return pointer to array of pointers to rows */
1721: return m;
1722: }
1723:
1724: /****************** free_imatrix *************************/
1725: void free_imatrix(m,nrl,nrh,ncl,nch)
1726: int **m;
1727: long nch,ncl,nrh,nrl;
1728: /* free an int matrix allocated by imatrix() */
1729: {
1730: free((FREE_ARG) (m[nrl]+ncl-NR_END));
1731: free((FREE_ARG) (m+nrl-NR_END));
1732: }
1733:
1734: /******************* matrix *******************************/
1735: double **matrix(long nrl, long nrh, long ncl, long nch)
1736: {
1737: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
1738: double **m;
1739:
1740: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1741: if (!m) nrerror("allocation failure 1 in matrix()");
1742: m += NR_END;
1743: m -= nrl;
1744:
1745: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1746: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1747: m[nrl] += NR_END;
1748: m[nrl] -= ncl;
1749:
1750: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1751: return m;
1.145 brouard 1752: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
1753: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
1754: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 1755: */
1756: }
1757:
1758: /*************************free matrix ************************/
1759: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
1760: {
1761: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1762: free((FREE_ARG)(m+nrl-NR_END));
1763: }
1764:
1765: /******************* ma3x *******************************/
1766: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
1767: {
1768: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
1769: double ***m;
1770:
1771: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1772: if (!m) nrerror("allocation failure 1 in matrix()");
1773: m += NR_END;
1774: m -= nrl;
1775:
1776: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1777: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1778: m[nrl] += NR_END;
1779: m[nrl] -= ncl;
1780:
1781: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1782:
1783: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
1784: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
1785: m[nrl][ncl] += NR_END;
1786: m[nrl][ncl] -= nll;
1787: for (j=ncl+1; j<=nch; j++)
1788: m[nrl][j]=m[nrl][j-1]+nlay;
1789:
1790: for (i=nrl+1; i<=nrh; i++) {
1791: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
1792: for (j=ncl+1; j<=nch; j++)
1793: m[i][j]=m[i][j-1]+nlay;
1794: }
1795: return m;
1796: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
1797: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
1798: */
1799: }
1800:
1801: /*************************free ma3x ************************/
1802: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
1803: {
1804: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
1805: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1806: free((FREE_ARG)(m+nrl-NR_END));
1807: }
1808:
1809: /*************** function subdirf ***********/
1810: char *subdirf(char fileres[])
1811: {
1812: /* Caution optionfilefiname is hidden */
1813: strcpy(tmpout,optionfilefiname);
1814: strcat(tmpout,"/"); /* Add to the right */
1815: strcat(tmpout,fileres);
1816: return tmpout;
1817: }
1818:
1819: /*************** function subdirf2 ***********/
1820: char *subdirf2(char fileres[], char *preop)
1821: {
1822:
1823: /* Caution optionfilefiname is hidden */
1824: strcpy(tmpout,optionfilefiname);
1825: strcat(tmpout,"/");
1826: strcat(tmpout,preop);
1827: strcat(tmpout,fileres);
1828: return tmpout;
1829: }
1830:
1831: /*************** function subdirf3 ***********/
1832: char *subdirf3(char fileres[], char *preop, char *preop2)
1833: {
1834:
1835: /* Caution optionfilefiname is hidden */
1836: strcpy(tmpout,optionfilefiname);
1837: strcat(tmpout,"/");
1838: strcat(tmpout,preop);
1839: strcat(tmpout,preop2);
1840: strcat(tmpout,fileres);
1841: return tmpout;
1842: }
1.213 brouard 1843:
1844: /*************** function subdirfext ***********/
1845: char *subdirfext(char fileres[], char *preop, char *postop)
1846: {
1847:
1848: strcpy(tmpout,preop);
1849: strcat(tmpout,fileres);
1850: strcat(tmpout,postop);
1851: return tmpout;
1852: }
1.126 brouard 1853:
1.213 brouard 1854: /*************** function subdirfext3 ***********/
1855: char *subdirfext3(char fileres[], char *preop, char *postop)
1856: {
1857:
1858: /* Caution optionfilefiname is hidden */
1859: strcpy(tmpout,optionfilefiname);
1860: strcat(tmpout,"/");
1861: strcat(tmpout,preop);
1862: strcat(tmpout,fileres);
1863: strcat(tmpout,postop);
1864: return tmpout;
1865: }
1866:
1.162 brouard 1867: char *asc_diff_time(long time_sec, char ascdiff[])
1868: {
1869: long sec_left, days, hours, minutes;
1870: days = (time_sec) / (60*60*24);
1871: sec_left = (time_sec) % (60*60*24);
1872: hours = (sec_left) / (60*60) ;
1873: sec_left = (sec_left) %(60*60);
1874: minutes = (sec_left) /60;
1875: sec_left = (sec_left) % (60);
1876: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
1877: return ascdiff;
1878: }
1879:
1.126 brouard 1880: /***************** f1dim *************************/
1881: extern int ncom;
1882: extern double *pcom,*xicom;
1883: extern double (*nrfunc)(double []);
1884:
1885: double f1dim(double x)
1886: {
1887: int j;
1888: double f;
1889: double *xt;
1890:
1891: xt=vector(1,ncom);
1892: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
1893: f=(*nrfunc)(xt);
1894: free_vector(xt,1,ncom);
1895: return f;
1896: }
1897:
1898: /*****************brent *************************/
1899: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 1900: {
1901: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
1902: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
1903: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
1904: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
1905: * returned function value.
1906: */
1.126 brouard 1907: int iter;
1908: double a,b,d,etemp;
1.159 brouard 1909: double fu=0,fv,fw,fx;
1.164 brouard 1910: double ftemp=0.;
1.126 brouard 1911: double p,q,r,tol1,tol2,u,v,w,x,xm;
1912: double e=0.0;
1913:
1914: a=(ax < cx ? ax : cx);
1915: b=(ax > cx ? ax : cx);
1916: x=w=v=bx;
1917: fw=fv=fx=(*f)(x);
1918: for (iter=1;iter<=ITMAX;iter++) {
1919: xm=0.5*(a+b);
1920: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
1921: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
1922: printf(".");fflush(stdout);
1923: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 1924: #ifdef DEBUGBRENT
1.126 brouard 1925: 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);
1926: 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);
1927: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
1928: #endif
1929: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
1930: *xmin=x;
1931: return fx;
1932: }
1933: ftemp=fu;
1934: if (fabs(e) > tol1) {
1935: r=(x-w)*(fx-fv);
1936: q=(x-v)*(fx-fw);
1937: p=(x-v)*q-(x-w)*r;
1938: q=2.0*(q-r);
1939: if (q > 0.0) p = -p;
1940: q=fabs(q);
1941: etemp=e;
1942: e=d;
1943: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 1944: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 1945: else {
1.224 brouard 1946: d=p/q;
1947: u=x+d;
1948: if (u-a < tol2 || b-u < tol2)
1949: d=SIGN(tol1,xm-x);
1.126 brouard 1950: }
1951: } else {
1952: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1953: }
1954: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
1955: fu=(*f)(u);
1956: if (fu <= fx) {
1957: if (u >= x) a=x; else b=x;
1958: SHFT(v,w,x,u)
1.183 brouard 1959: SHFT(fv,fw,fx,fu)
1960: } else {
1961: if (u < x) a=u; else b=u;
1962: if (fu <= fw || w == x) {
1.224 brouard 1963: v=w;
1964: w=u;
1965: fv=fw;
1966: fw=fu;
1.183 brouard 1967: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 1968: v=u;
1969: fv=fu;
1.183 brouard 1970: }
1971: }
1.126 brouard 1972: }
1973: nrerror("Too many iterations in brent");
1974: *xmin=x;
1975: return fx;
1976: }
1977:
1978: /****************** mnbrak ***********************/
1979:
1980: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
1981: double (*func)(double))
1.183 brouard 1982: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
1983: the downhill direction (defined by the function as evaluated at the initial points) and returns
1984: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
1985: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
1986: */
1.126 brouard 1987: double ulim,u,r,q, dum;
1988: double fu;
1.187 brouard 1989:
1990: double scale=10.;
1991: int iterscale=0;
1992:
1993: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
1994: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
1995:
1996:
1997: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
1998: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
1999: /* *bx = *ax - (*ax - *bx)/scale; */
2000: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
2001: /* } */
2002:
1.126 brouard 2003: if (*fb > *fa) {
2004: SHFT(dum,*ax,*bx,dum)
1.183 brouard 2005: SHFT(dum,*fb,*fa,dum)
2006: }
1.126 brouard 2007: *cx=(*bx)+GOLD*(*bx-*ax);
2008: *fc=(*func)(*cx);
1.183 brouard 2009: #ifdef DEBUG
1.224 brouard 2010: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
2011: 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 2012: #endif
1.224 brouard 2013: 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 2014: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 2015: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 2016: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 2017: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
2018: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
2019: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 2020: fu=(*func)(u);
1.163 brouard 2021: #ifdef DEBUG
2022: /* f(x)=A(x-u)**2+f(u) */
2023: double A, fparabu;
2024: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2025: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 2026: 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);
2027: 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 2028: /* And thus,it can be that fu > *fc even if fparabu < *fc */
2029: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
2030: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
2031: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 2032: #endif
1.184 brouard 2033: #ifdef MNBRAKORIGINAL
1.183 brouard 2034: #else
1.191 brouard 2035: /* if (fu > *fc) { */
2036: /* #ifdef DEBUG */
2037: /* printf("mnbrak4 fu > fc \n"); */
2038: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
2039: /* #endif */
2040: /* /\* 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 *\\/ *\/ */
2041: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
2042: /* dum=u; /\* Shifting c and u *\/ */
2043: /* u = *cx; */
2044: /* *cx = dum; */
2045: /* dum = fu; */
2046: /* fu = *fc; */
2047: /* *fc =dum; */
2048: /* } else { /\* end *\/ */
2049: /* #ifdef DEBUG */
2050: /* printf("mnbrak3 fu < fc \n"); */
2051: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
2052: /* #endif */
2053: /* dum=u; /\* Shifting c and u *\/ */
2054: /* u = *cx; */
2055: /* *cx = dum; */
2056: /* dum = fu; */
2057: /* fu = *fc; */
2058: /* *fc =dum; */
2059: /* } */
1.224 brouard 2060: #ifdef DEBUGMNBRAK
2061: double A, fparabu;
2062: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2063: fparabu= *fa - A*(*ax-u)*(*ax-u);
2064: 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);
2065: 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 2066: #endif
1.191 brouard 2067: dum=u; /* Shifting c and u */
2068: u = *cx;
2069: *cx = dum;
2070: dum = fu;
2071: fu = *fc;
2072: *fc =dum;
1.183 brouard 2073: #endif
1.162 brouard 2074: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 2075: #ifdef DEBUG
1.224 brouard 2076: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
2077: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 2078: #endif
1.126 brouard 2079: fu=(*func)(u);
2080: if (fu < *fc) {
1.183 brouard 2081: #ifdef DEBUG
1.224 brouard 2082: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2083: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2084: #endif
2085: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
2086: SHFT(*fb,*fc,fu,(*func)(u))
2087: #ifdef DEBUG
2088: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 2089: #endif
2090: }
1.162 brouard 2091: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 2092: #ifdef DEBUG
1.224 brouard 2093: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
2094: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 2095: #endif
1.126 brouard 2096: u=ulim;
2097: fu=(*func)(u);
1.183 brouard 2098: } else { /* u could be left to b (if r > q parabola has a maximum) */
2099: #ifdef DEBUG
1.224 brouard 2100: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
2101: 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 2102: #endif
1.126 brouard 2103: u=(*cx)+GOLD*(*cx-*bx);
2104: fu=(*func)(u);
1.224 brouard 2105: #ifdef DEBUG
2106: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2107: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2108: #endif
1.183 brouard 2109: } /* end tests */
1.126 brouard 2110: SHFT(*ax,*bx,*cx,u)
1.183 brouard 2111: SHFT(*fa,*fb,*fc,fu)
2112: #ifdef DEBUG
1.224 brouard 2113: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2114: 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 2115: #endif
2116: } /* 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 2117: }
2118:
2119: /*************** linmin ************************/
1.162 brouard 2120: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2121: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2122: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2123: the value of func at the returned location p . This is actually all accomplished by calling the
2124: routines mnbrak and brent .*/
1.126 brouard 2125: int ncom;
2126: double *pcom,*xicom;
2127: double (*nrfunc)(double []);
2128:
1.224 brouard 2129: #ifdef LINMINORIGINAL
1.126 brouard 2130: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2131: #else
2132: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2133: #endif
1.126 brouard 2134: {
2135: double brent(double ax, double bx, double cx,
2136: double (*f)(double), double tol, double *xmin);
2137: double f1dim(double x);
2138: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2139: double *fc, double (*func)(double));
2140: int j;
2141: double xx,xmin,bx,ax;
2142: double fx,fb,fa;
1.187 brouard 2143:
1.203 brouard 2144: #ifdef LINMINORIGINAL
2145: #else
2146: double scale=10., axs, xxs; /* Scale added for infinity */
2147: #endif
2148:
1.126 brouard 2149: ncom=n;
2150: pcom=vector(1,n);
2151: xicom=vector(1,n);
2152: nrfunc=func;
2153: for (j=1;j<=n;j++) {
2154: pcom[j]=p[j];
1.202 brouard 2155: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2156: }
1.187 brouard 2157:
1.203 brouard 2158: #ifdef LINMINORIGINAL
2159: xx=1.;
2160: #else
2161: axs=0.0;
2162: xxs=1.;
2163: do{
2164: xx= xxs;
2165: #endif
1.187 brouard 2166: ax=0.;
2167: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2168: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2169: /* 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)) */
2170: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2171: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2172: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2173: /* 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 2174: #ifdef LINMINORIGINAL
2175: #else
2176: if (fx != fx){
1.224 brouard 2177: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2178: printf("|");
2179: fprintf(ficlog,"|");
1.203 brouard 2180: #ifdef DEBUGLINMIN
1.224 brouard 2181: 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 2182: #endif
2183: }
1.224 brouard 2184: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2185: #endif
2186:
1.191 brouard 2187: #ifdef DEBUGLINMIN
2188: 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 2189: 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 2190: #endif
1.224 brouard 2191: #ifdef LINMINORIGINAL
2192: #else
2193: if(fb == fx){ /* Flat function in the direction */
2194: xmin=xx;
2195: *flat=1;
2196: }else{
2197: *flat=0;
2198: #endif
2199: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2200: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2201: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2202: /* fmin = f(p[j] + xmin * xi[j]) */
2203: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2204: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2205: #ifdef DEBUG
1.224 brouard 2206: 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);
2207: 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);
2208: #endif
2209: #ifdef LINMINORIGINAL
2210: #else
2211: }
1.126 brouard 2212: #endif
1.191 brouard 2213: #ifdef DEBUGLINMIN
2214: printf("linmin end ");
1.202 brouard 2215: fprintf(ficlog,"linmin end ");
1.191 brouard 2216: #endif
1.126 brouard 2217: for (j=1;j<=n;j++) {
1.203 brouard 2218: #ifdef LINMINORIGINAL
2219: xi[j] *= xmin;
2220: #else
2221: #ifdef DEBUGLINMIN
2222: if(xxs <1.0)
2223: printf(" before xi[%d]=%12.8f", j,xi[j]);
2224: #endif
2225: 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) */
2226: #ifdef DEBUGLINMIN
2227: if(xxs <1.0)
2228: 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 );
2229: #endif
2230: #endif
1.187 brouard 2231: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2232: }
1.191 brouard 2233: #ifdef DEBUGLINMIN
1.203 brouard 2234: printf("\n");
1.191 brouard 2235: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2236: 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 2237: for (j=1;j<=n;j++) {
1.202 brouard 2238: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2239: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2240: if(j % ncovmodel == 0){
1.191 brouard 2241: printf("\n");
1.202 brouard 2242: fprintf(ficlog,"\n");
2243: }
1.191 brouard 2244: }
1.203 brouard 2245: #else
1.191 brouard 2246: #endif
1.126 brouard 2247: free_vector(xicom,1,n);
2248: free_vector(pcom,1,n);
2249: }
2250:
2251:
2252: /*************** powell ************************/
1.162 brouard 2253: /*
2254: Minimization of a function func of n variables. Input consists of an initial starting point
2255: p[1..n] ; an initial matrix xi[1..n][1..n] , whose columns contain the initial set of di-
2256: rections (usually the n unit vectors); and ftol , the fractional tolerance in the function value
2257: such that failure to decrease by more than this amount on one iteration signals doneness. On
2258: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2259: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2260: */
1.224 brouard 2261: #ifdef LINMINORIGINAL
2262: #else
2263: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2264: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2265: #endif
1.126 brouard 2266: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2267: double (*func)(double []))
2268: {
1.224 brouard 2269: #ifdef LINMINORIGINAL
2270: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2271: double (*func)(double []));
1.224 brouard 2272: #else
1.241 brouard 2273: void linmin(double p[], double xi[], int n, double *fret,
2274: double (*func)(double []),int *flat);
1.224 brouard 2275: #endif
1.239 brouard 2276: int i,ibig,j,jk,k;
1.126 brouard 2277: double del,t,*pt,*ptt,*xit;
1.181 brouard 2278: double directest;
1.126 brouard 2279: double fp,fptt;
2280: double *xits;
2281: int niterf, itmp;
1.224 brouard 2282: #ifdef LINMINORIGINAL
2283: #else
2284:
2285: flatdir=ivector(1,n);
2286: for (j=1;j<=n;j++) flatdir[j]=0;
2287: #endif
1.126 brouard 2288:
2289: pt=vector(1,n);
2290: ptt=vector(1,n);
2291: xit=vector(1,n);
2292: xits=vector(1,n);
2293: *fret=(*func)(p);
2294: for (j=1;j<=n;j++) pt[j]=p[j];
1.202 brouard 2295: rcurr_time = time(NULL);
1.126 brouard 2296: for (*iter=1;;++(*iter)) {
1.187 brouard 2297: fp=(*fret); /* From former iteration or initial value */
1.126 brouard 2298: ibig=0;
2299: del=0.0;
1.157 brouard 2300: rlast_time=rcurr_time;
2301: /* (void) gettimeofday(&curr_time,&tzp); */
2302: rcurr_time = time(NULL);
2303: curr_time = *localtime(&rcurr_time);
2304: printf("\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout);
2305: fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog);
2306: /* fprintf(ficrespow,"%d %.12f %ld",*iter,*fret,curr_time.tm_sec-start_time.tm_sec); */
1.192 brouard 2307: for (i=1;i<=n;i++) {
1.126 brouard 2308: fprintf(ficrespow," %.12lf", p[i]);
2309: }
1.239 brouard 2310: fprintf(ficrespow,"\n");fflush(ficrespow);
2311: printf("\n#model= 1 + age ");
2312: fprintf(ficlog,"\n#model= 1 + age ");
2313: if(nagesqr==1){
1.241 brouard 2314: printf(" + age*age ");
2315: fprintf(ficlog," + age*age ");
1.239 brouard 2316: }
2317: for(j=1;j <=ncovmodel-2;j++){
2318: if(Typevar[j]==0) {
2319: printf(" + V%d ",Tvar[j]);
2320: fprintf(ficlog," + V%d ",Tvar[j]);
2321: }else if(Typevar[j]==1) {
2322: printf(" + V%d*age ",Tvar[j]);
2323: fprintf(ficlog," + V%d*age ",Tvar[j]);
2324: }else if(Typevar[j]==2) {
2325: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2326: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2327: }
2328: }
1.126 brouard 2329: printf("\n");
1.239 brouard 2330: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2331: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2332: fprintf(ficlog,"\n");
1.239 brouard 2333: for(i=1,jk=1; i <=nlstate; i++){
2334: for(k=1; k <=(nlstate+ndeath); k++){
2335: if (k != i) {
2336: printf("%d%d ",i,k);
2337: fprintf(ficlog,"%d%d ",i,k);
2338: for(j=1; j <=ncovmodel; j++){
2339: printf("%12.7f ",p[jk]);
2340: fprintf(ficlog,"%12.7f ",p[jk]);
2341: jk++;
2342: }
2343: printf("\n");
2344: fprintf(ficlog,"\n");
2345: }
2346: }
2347: }
1.241 brouard 2348: if(*iter <=3 && *iter >1){
1.157 brouard 2349: tml = *localtime(&rcurr_time);
2350: strcpy(strcurr,asctime(&tml));
2351: rforecast_time=rcurr_time;
1.126 brouard 2352: itmp = strlen(strcurr);
2353: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2354: strcurr[itmp-1]='\0';
1.162 brouard 2355: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2356: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.126 brouard 2357: for(niterf=10;niterf<=30;niterf+=10){
1.241 brouard 2358: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2359: forecast_time = *localtime(&rforecast_time);
2360: strcpy(strfor,asctime(&forecast_time));
2361: itmp = strlen(strfor);
2362: if(strfor[itmp-1]=='\n')
2363: strfor[itmp-1]='\0';
2364: 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);
2365: 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 2366: }
2367: }
1.187 brouard 2368: for (i=1;i<=n;i++) { /* For each direction i */
2369: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2370: fptt=(*fret);
2371: #ifdef DEBUG
1.203 brouard 2372: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2373: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2374: #endif
1.203 brouard 2375: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2376: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2377: #ifdef LINMINORIGINAL
1.188 brouard 2378: linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.224 brouard 2379: #else
2380: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2381: flatdir[i]=flat; /* Function is vanishing in that direction i */
2382: #endif
2383: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2384: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2385: /* because that direction will be replaced unless the gain del is small */
2386: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2387: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2388: /* with the new direction. */
2389: del=fabs(fptt-(*fret));
2390: ibig=i;
1.126 brouard 2391: }
2392: #ifdef DEBUG
2393: printf("%d %.12e",i,(*fret));
2394: fprintf(ficlog,"%d %.12e",i,(*fret));
2395: for (j=1;j<=n;j++) {
1.224 brouard 2396: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2397: printf(" x(%d)=%.12e",j,xit[j]);
2398: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2399: }
2400: for(j=1;j<=n;j++) {
1.225 brouard 2401: printf(" p(%d)=%.12e",j,p[j]);
2402: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2403: }
2404: printf("\n");
2405: fprintf(ficlog,"\n");
2406: #endif
1.187 brouard 2407: } /* end loop on each direction i */
2408: /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
1.188 brouard 2409: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.187 brouard 2410: /* New value of last point Pn is not computed, P(n-1) */
1.224 brouard 2411: for(j=1;j<=n;j++) {
1.225 brouard 2412: if(flatdir[j] >0){
2413: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2414: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2415: }
2416: /* printf("\n"); */
2417: /* fprintf(ficlog,"\n"); */
2418: }
1.243 brouard 2419: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
2420: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2421: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2422: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2423: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2424: /* decreased of more than 3.84 */
2425: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2426: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2427: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2428:
1.188 brouard 2429: /* Starting the program with initial values given by a former maximization will simply change */
2430: /* the scales of the directions and the directions, because the are reset to canonical directions */
2431: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2432: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2433: #ifdef DEBUG
2434: int k[2],l;
2435: k[0]=1;
2436: k[1]=-1;
2437: printf("Max: %.12e",(*func)(p));
2438: fprintf(ficlog,"Max: %.12e",(*func)(p));
2439: for (j=1;j<=n;j++) {
2440: printf(" %.12e",p[j]);
2441: fprintf(ficlog," %.12e",p[j]);
2442: }
2443: printf("\n");
2444: fprintf(ficlog,"\n");
2445: for(l=0;l<=1;l++) {
2446: for (j=1;j<=n;j++) {
2447: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2448: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2449: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2450: }
2451: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2452: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2453: }
2454: #endif
2455:
1.224 brouard 2456: #ifdef LINMINORIGINAL
2457: #else
2458: free_ivector(flatdir,1,n);
2459: #endif
1.126 brouard 2460: free_vector(xit,1,n);
2461: free_vector(xits,1,n);
2462: free_vector(ptt,1,n);
2463: free_vector(pt,1,n);
2464: return;
1.192 brouard 2465: } /* enough precision */
1.240 brouard 2466: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2467: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2468: ptt[j]=2.0*p[j]-pt[j];
2469: xit[j]=p[j]-pt[j];
2470: pt[j]=p[j];
2471: }
1.181 brouard 2472: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2473: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2474: if (*iter <=4) {
1.225 brouard 2475: #else
2476: #endif
1.224 brouard 2477: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2478: #else
1.161 brouard 2479: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2480: #endif
1.162 brouard 2481: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2482: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2483: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2484: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2485: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2486: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2487: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2488: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2489: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2490: /* Even if f3 <f1, directest can be negative and t >0 */
2491: /* mu² and del² are equal when f3=f1 */
2492: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2493: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2494: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2495: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2496: #ifdef NRCORIGINAL
2497: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2498: #else
2499: 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 2500: t= t- del*SQR(fp-fptt);
1.183 brouard 2501: #endif
1.202 brouard 2502: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2503: #ifdef DEBUG
1.181 brouard 2504: 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);
2505: 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 2506: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2507: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2508: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2509: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2510: 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);
2511: 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);
2512: #endif
1.183 brouard 2513: #ifdef POWELLORIGINAL
2514: if (t < 0.0) { /* Then we use it for new direction */
2515: #else
1.182 brouard 2516: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2517: 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 2518: 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 2519: 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 2520: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2521: }
1.181 brouard 2522: if (directest < 0.0) { /* Then we use it for new direction */
2523: #endif
1.191 brouard 2524: #ifdef DEBUGLINMIN
1.234 brouard 2525: printf("Before linmin in direction P%d-P0\n",n);
2526: for (j=1;j<=n;j++) {
2527: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2528: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2529: if(j % ncovmodel == 0){
2530: printf("\n");
2531: fprintf(ficlog,"\n");
2532: }
2533: }
1.224 brouard 2534: #endif
2535: #ifdef LINMINORIGINAL
1.234 brouard 2536: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2537: #else
1.234 brouard 2538: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2539: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2540: #endif
1.234 brouard 2541:
1.191 brouard 2542: #ifdef DEBUGLINMIN
1.234 brouard 2543: for (j=1;j<=n;j++) {
2544: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2545: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2546: if(j % ncovmodel == 0){
2547: printf("\n");
2548: fprintf(ficlog,"\n");
2549: }
2550: }
1.224 brouard 2551: #endif
1.234 brouard 2552: for (j=1;j<=n;j++) {
2553: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2554: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2555: }
1.224 brouard 2556: #ifdef LINMINORIGINAL
2557: #else
1.234 brouard 2558: for (j=1, flatd=0;j<=n;j++) {
2559: if(flatdir[j]>0)
2560: flatd++;
2561: }
2562: if(flatd >0){
1.255 brouard 2563: printf("%d flat directions: ",flatd);
2564: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 2565: for (j=1;j<=n;j++) {
2566: if(flatdir[j]>0){
2567: printf("%d ",j);
2568: fprintf(ficlog,"%d ",j);
2569: }
2570: }
2571: printf("\n");
2572: fprintf(ficlog,"\n");
2573: }
1.191 brouard 2574: #endif
1.234 brouard 2575: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2576: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2577:
1.126 brouard 2578: #ifdef DEBUG
1.234 brouard 2579: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2580: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2581: for(j=1;j<=n;j++){
2582: printf(" %lf",xit[j]);
2583: fprintf(ficlog," %lf",xit[j]);
2584: }
2585: printf("\n");
2586: fprintf(ficlog,"\n");
1.126 brouard 2587: #endif
1.192 brouard 2588: } /* end of t or directest negative */
1.224 brouard 2589: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2590: #else
1.234 brouard 2591: } /* end if (fptt < fp) */
1.192 brouard 2592: #endif
1.225 brouard 2593: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2594: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2595: #else
1.224 brouard 2596: #endif
1.234 brouard 2597: } /* loop iteration */
1.126 brouard 2598: }
1.234 brouard 2599:
1.126 brouard 2600: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 2601:
1.235 brouard 2602: 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 2603: {
1.279 brouard 2604: /**< Computes the prevalence limit in each live state at age x and for covariate combination ij
2605: * (and selected quantitative values in nres)
2606: * by left multiplying the unit
2607: * matrix by transitions matrix until convergence is reached with precision ftolpl
2608: * Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I
2609: * Wx is row vector: population in state 1, population in state 2, population dead
2610: * or prevalence in state 1, prevalence in state 2, 0
2611: * newm is the matrix after multiplications, its rows are identical at a factor.
2612: * Inputs are the parameter, age, a tolerance for the prevalence limit ftolpl.
2613: * Output is prlim.
2614: * Initial matrix pimij
2615: */
1.206 brouard 2616: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2617: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2618: /* 0, 0 , 1} */
2619: /*
2620: * and after some iteration: */
2621: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2622: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2623: /* 0, 0 , 1} */
2624: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2625: /* {0.51571254859325999, 0.4842874514067399, */
2626: /* 0.51326036147820708, 0.48673963852179264} */
2627: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 2628:
1.126 brouard 2629: int i, ii,j,k;
1.209 brouard 2630: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 2631: /* double **matprod2(); */ /* test */
1.218 brouard 2632: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 2633: double **newm;
1.209 brouard 2634: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 2635: int ncvloop=0;
1.288 brouard 2636: int first=0;
1.169 brouard 2637:
1.209 brouard 2638: min=vector(1,nlstate);
2639: max=vector(1,nlstate);
2640: meandiff=vector(1,nlstate);
2641:
1.218 brouard 2642: /* Starting with matrix unity */
1.126 brouard 2643: for (ii=1;ii<=nlstate+ndeath;ii++)
2644: for (j=1;j<=nlstate+ndeath;j++){
2645: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2646: }
1.169 brouard 2647:
2648: cov[1]=1.;
2649:
2650: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 2651: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 2652: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 2653: ncvloop++;
1.126 brouard 2654: newm=savm;
2655: /* Covariates have to be included here again */
1.138 brouard 2656: cov[2]=agefin;
1.187 brouard 2657: if(nagesqr==1)
2658: cov[3]= agefin*agefin;;
1.234 brouard 2659: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2660: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2661: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.235 brouard 2662: /* 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 2663: }
2664: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2665: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
1.235 brouard 2666: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2667: /* 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 2668: }
1.237 brouard 2669: for (k=1; k<=cptcovage;k++){ /* For product with age */
1.234 brouard 2670: if(Dummy[Tvar[Tage[k]]]){
2671: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
2672: } else{
1.235 brouard 2673: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
1.234 brouard 2674: }
1.235 brouard 2675: /* 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 2676: }
1.237 brouard 2677: for (k=1; k<=cptcovprod;k++){ /* For product without age */
1.235 brouard 2678: /* 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 2679: if(Dummy[Tvard[k][1]==0]){
2680: if(Dummy[Tvard[k][2]==0]){
2681: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2682: }else{
2683: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2684: }
2685: }else{
2686: if(Dummy[Tvard[k][2]==0]){
2687: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2688: }else{
2689: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2690: }
2691: }
1.234 brouard 2692: }
1.138 brouard 2693: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2694: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2695: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 2696: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2697: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2698: /* age and covariate values of ij are in 'cov' */
1.142 brouard 2699: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 2700:
1.126 brouard 2701: savm=oldm;
2702: oldm=newm;
1.209 brouard 2703:
2704: for(j=1; j<=nlstate; j++){
2705: max[j]=0.;
2706: min[j]=1.;
2707: }
2708: for(i=1;i<=nlstate;i++){
2709: sumnew=0;
2710: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
2711: for(j=1; j<=nlstate; j++){
2712: prlim[i][j]= newm[i][j]/(1-sumnew);
2713: max[j]=FMAX(max[j],prlim[i][j]);
2714: min[j]=FMIN(min[j],prlim[i][j]);
2715: }
2716: }
2717:
1.126 brouard 2718: maxmax=0.;
1.209 brouard 2719: for(j=1; j<=nlstate; j++){
2720: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
2721: maxmax=FMAX(maxmax,meandiff[j]);
2722: /* 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 2723: } /* j loop */
1.203 brouard 2724: *ncvyear= (int)age- (int)agefin;
1.208 brouard 2725: /* 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 2726: if(maxmax < ftolpl){
1.209 brouard 2727: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
2728: free_vector(min,1,nlstate);
2729: free_vector(max,1,nlstate);
2730: free_vector(meandiff,1,nlstate);
1.126 brouard 2731: return prlim;
2732: }
1.288 brouard 2733: } /* agefin loop */
1.208 brouard 2734: /* After some age loop it doesn't converge */
1.288 brouard 2735: if(!first){
2736: first=1;
2737: 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);
2738: }
2739: 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);
2740:
1.209 brouard 2741: /* 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); */
2742: free_vector(min,1,nlstate);
2743: free_vector(max,1,nlstate);
2744: free_vector(meandiff,1,nlstate);
1.208 brouard 2745:
1.169 brouard 2746: return prlim; /* should not reach here */
1.126 brouard 2747: }
2748:
1.217 brouard 2749:
2750: /**** Back Prevalence limit (stable or period prevalence) ****************/
2751:
1.218 brouard 2752: /* 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) */
2753: /* 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 2754: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 2755: {
1.264 brouard 2756: /* 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 2757: matrix by transitions matrix until convergence is reached with precision ftolpl */
2758: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
2759: /* Wx is row vector: population in state 1, population in state 2, population dead */
2760: /* or prevalence in state 1, prevalence in state 2, 0 */
2761: /* newm is the matrix after multiplications, its rows are identical at a factor */
2762: /* Initial matrix pimij */
2763: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2764: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2765: /* 0, 0 , 1} */
2766: /*
2767: * and after some iteration: */
2768: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2769: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2770: /* 0, 0 , 1} */
2771: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2772: /* {0.51571254859325999, 0.4842874514067399, */
2773: /* 0.51326036147820708, 0.48673963852179264} */
2774: /* If we start from prlim again, prlim tends to a constant matrix */
2775:
2776: int i, ii,j,k;
1.247 brouard 2777: int first=0;
1.217 brouard 2778: double *min, *max, *meandiff, maxmax,sumnew=0.;
2779: /* double **matprod2(); */ /* test */
2780: double **out, cov[NCOVMAX+1], **bmij();
2781: double **newm;
1.218 brouard 2782: double **dnewm, **doldm, **dsavm; /* for use */
2783: double **oldm, **savm; /* for use */
2784:
1.217 brouard 2785: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
2786: int ncvloop=0;
2787:
2788: min=vector(1,nlstate);
2789: max=vector(1,nlstate);
2790: meandiff=vector(1,nlstate);
2791:
1.266 brouard 2792: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
2793: oldm=oldms; savm=savms;
2794:
2795: /* Starting with matrix unity */
2796: for (ii=1;ii<=nlstate+ndeath;ii++)
2797: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 2798: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2799: }
2800:
2801: cov[1]=1.;
2802:
2803: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
2804: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 2805: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
1.288 brouard 2806: /* for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
2807: for(agefin=age; agefin<FMIN(AGESUP,age+delaymax); agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 2808: ncvloop++;
1.218 brouard 2809: newm=savm; /* oldm should be kept from previous iteration or unity at start */
2810: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 2811: /* Covariates have to be included here again */
2812: cov[2]=agefin;
2813: if(nagesqr==1)
2814: cov[3]= agefin*agefin;;
1.242 brouard 2815: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2816: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2817: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.264 brouard 2818: /* 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 2819: }
2820: /* for (k=1; k<=cptcovn;k++) { */
2821: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
2822: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
2823: /* /\* 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])]); *\/ */
2824: /* } */
2825: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2826: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
2827: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2828: /* 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]); */
2829: }
2830: /* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; */
2831: /* for (k=1; k<=cptcovprod;k++) /\* Useless *\/ */
2832: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\/ */
2833: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */
2834: for (k=1; k<=cptcovage;k++){ /* For product with age */
2835: if(Dummy[Tvar[Tage[k]]]){
2836: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
2837: } else{
2838: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
2839: }
2840: /* 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]); */
2841: }
2842: for (k=1; k<=cptcovprod;k++){ /* For product without age */
2843: /* 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]); */
2844: if(Dummy[Tvard[k][1]==0]){
2845: if(Dummy[Tvard[k][2]==0]){
2846: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2847: }else{
2848: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2849: }
2850: }else{
2851: if(Dummy[Tvard[k][2]==0]){
2852: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2853: }else{
2854: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2855: }
2856: }
1.217 brouard 2857: }
2858:
2859: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2860: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2861: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
2862: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2863: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2864: /* ij should be linked to the correct index of cov */
2865: /* age and covariate values ij are in 'cov', but we need to pass
2866: * ij for the observed prevalence at age and status and covariate
2867: * number: prevacurrent[(int)agefin][ii][ij]
2868: */
2869: /* 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 *\/ */
2870: /* 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 *\/ */
2871: 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 2872: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 2873: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
2874: /* for(i=1; i<=nlstate+ndeath; i++) { */
2875: /* printf("%d newm= ",i); */
2876: /* for(j=1;j<=nlstate+ndeath;j++) { */
2877: /* printf("%f ",newm[i][j]); */
2878: /* } */
2879: /* printf("oldm * "); */
2880: /* for(j=1;j<=nlstate+ndeath;j++) { */
2881: /* printf("%f ",oldm[i][j]); */
2882: /* } */
1.268 brouard 2883: /* printf(" bmmij "); */
1.266 brouard 2884: /* for(j=1;j<=nlstate+ndeath;j++) { */
2885: /* printf("%f ",pmmij[i][j]); */
2886: /* } */
2887: /* printf("\n"); */
2888: /* } */
2889: /* } */
1.217 brouard 2890: savm=oldm;
2891: oldm=newm;
1.266 brouard 2892:
1.217 brouard 2893: for(j=1; j<=nlstate; j++){
2894: max[j]=0.;
2895: min[j]=1.;
2896: }
2897: for(j=1; j<=nlstate; j++){
2898: for(i=1;i<=nlstate;i++){
1.234 brouard 2899: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
2900: bprlim[i][j]= newm[i][j];
2901: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
2902: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 2903: }
2904: }
1.218 brouard 2905:
1.217 brouard 2906: maxmax=0.;
2907: for(i=1; i<=nlstate; i++){
2908: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column */
2909: maxmax=FMAX(maxmax,meandiff[i]);
2910: /* 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 2911: } /* i loop */
1.217 brouard 2912: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 2913: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 2914: if(maxmax < ftolpl){
1.220 brouard 2915: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 2916: free_vector(min,1,nlstate);
2917: free_vector(max,1,nlstate);
2918: free_vector(meandiff,1,nlstate);
2919: return bprlim;
2920: }
1.288 brouard 2921: } /* agefin loop */
1.217 brouard 2922: /* After some age loop it doesn't converge */
1.288 brouard 2923: if(!first){
1.247 brouard 2924: first=1;
2925: 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\
2926: 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);
2927: }
2928: 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 2929: 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);
2930: /* 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); */
2931: free_vector(min,1,nlstate);
2932: free_vector(max,1,nlstate);
2933: free_vector(meandiff,1,nlstate);
2934:
2935: return bprlim; /* should not reach here */
2936: }
2937:
1.126 brouard 2938: /*************** transition probabilities ***************/
2939:
2940: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
2941: {
1.138 brouard 2942: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 2943: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 2944: model to the ncovmodel covariates (including constant and age).
2945: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
2946: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
2947: ncth covariate in the global vector x is given by the formula:
2948: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
2949: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
2950: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
2951: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 2952: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 2953: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 2954: Sum on j ps[i][j] should equal to 1.
1.138 brouard 2955: */
2956: double s1, lnpijopii;
1.126 brouard 2957: /*double t34;*/
1.164 brouard 2958: int i,j, nc, ii, jj;
1.126 brouard 2959:
1.223 brouard 2960: for(i=1; i<= nlstate; i++){
2961: for(j=1; j<i;j++){
2962: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2963: /*lnpijopii += param[i][j][nc]*cov[nc];*/
2964: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
2965: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2966: }
2967: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2968: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2969: }
2970: for(j=i+1; j<=nlstate+ndeath;j++){
2971: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2972: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
2973: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
2974: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
2975: }
2976: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2977: }
2978: }
1.218 brouard 2979:
1.223 brouard 2980: for(i=1; i<= nlstate; i++){
2981: s1=0;
2982: for(j=1; j<i; j++){
2983: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2984: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2985: }
2986: for(j=i+1; j<=nlstate+ndeath; j++){
2987: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2988: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2989: }
2990: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
2991: ps[i][i]=1./(s1+1.);
2992: /* Computing other pijs */
2993: for(j=1; j<i; j++)
2994: ps[i][j]= exp(ps[i][j])*ps[i][i];
2995: for(j=i+1; j<=nlstate+ndeath; j++)
2996: ps[i][j]= exp(ps[i][j])*ps[i][i];
2997: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
2998: } /* end i */
1.218 brouard 2999:
1.223 brouard 3000: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3001: for(jj=1; jj<= nlstate+ndeath; jj++){
3002: ps[ii][jj]=0;
3003: ps[ii][ii]=1;
3004: }
3005: }
1.294 brouard 3006:
3007:
1.223 brouard 3008: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3009: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3010: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3011: /* } */
3012: /* printf("\n "); */
3013: /* } */
3014: /* printf("\n ");printf("%lf ",cov[2]);*/
3015: /*
3016: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 3017: goto end;*/
1.266 brouard 3018: return ps; /* Pointer is unchanged since its call */
1.126 brouard 3019: }
3020:
1.218 brouard 3021: /*************** backward transition probabilities ***************/
3022:
3023: /* 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 ) */
3024: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
3025: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
3026: {
1.266 brouard 3027: /* Computes the backward probability at age agefin and covariate combination ij. In fact cov is already filled and x too.
3028: * 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 3029: */
1.218 brouard 3030: int i, ii, j,k;
1.222 brouard 3031:
3032: double **out, **pmij();
3033: double sumnew=0.;
1.218 brouard 3034: double agefin;
1.292 brouard 3035: 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 3036: double **dnewm, **dsavm, **doldm;
3037: double **bbmij;
3038:
1.218 brouard 3039: doldm=ddoldms; /* global pointers */
1.222 brouard 3040: dnewm=ddnewms;
3041: dsavm=ddsavms;
3042:
3043: agefin=cov[2];
1.268 brouard 3044: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 3045: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 3046: the observed prevalence (with this covariate ij) at beginning of transition */
3047: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 3048:
3049: /* P_x */
1.266 brouard 3050: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm */
1.268 brouard 3051: /* outputs pmmij which is a stochastic matrix in row */
3052:
3053: /* Diag(w_x) */
1.292 brouard 3054: /* Rescaling the cross-sectional prevalence: Problem with prevacurrent which can be zero */
1.268 brouard 3055: sumnew=0.;
1.269 brouard 3056: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 3057: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.297 brouard 3058: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 3059: sumnew+=prevacurrent[(int)agefin][ii][ij];
3060: }
3061: if(sumnew >0.01){ /* At least some value in the prevalence */
3062: for (ii=1;ii<=nlstate+ndeath;ii++){
3063: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 3064: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 3065: }
3066: }else{
3067: for (ii=1;ii<=nlstate+ndeath;ii++){
3068: for (j=1;j<=nlstate+ndeath;j++)
3069: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
3070: }
3071: /* if(sumnew <0.9){ */
3072: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
3073: /* } */
3074: }
3075: k3=0.0; /* We put the last diagonal to 0 */
3076: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
3077: doldm[ii][ii]= k3;
3078: }
3079: /* End doldm, At the end doldm is diag[(w_i)] */
3080:
1.292 brouard 3081: /* Left product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm): diag[(w_i)*Px */
3082: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* was a Bug Valgrind */
1.268 brouard 3083:
1.292 brouard 3084: /* Diag(Sum_i w^i_x p^ij_x, should be the prevalence at age x+stepm */
1.268 brouard 3085: /* 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 3086: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 3087: sumnew=0.;
1.222 brouard 3088: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 3089: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 3090: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 3091: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 3092: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 3093: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 3094: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3095: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 3096: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3097: /* }else */
1.268 brouard 3098: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
3099: } /*End ii */
3100: } /* 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 */
3101:
1.292 brouard 3102: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* was a Bug Valgrind */
1.268 brouard 3103: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 3104: /* end bmij */
1.266 brouard 3105: return ps; /*pointer is unchanged */
1.218 brouard 3106: }
1.217 brouard 3107: /*************** transition probabilities ***************/
3108:
1.218 brouard 3109: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 3110: {
3111: /* According to parameters values stored in x and the covariate's values stored in cov,
3112: computes the probability to be observed in state j being in state i by appying the
3113: model to the ncovmodel covariates (including constant and age).
3114: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3115: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3116: ncth covariate in the global vector x is given by the formula:
3117: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3118: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3119: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3120: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
3121: Outputs ps[i][j] the probability to be observed in j being in j according to
3122: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
3123: */
3124: double s1, lnpijopii;
3125: /*double t34;*/
3126: int i,j, nc, ii, jj;
3127:
1.234 brouard 3128: for(i=1; i<= nlstate; i++){
3129: for(j=1; j<i;j++){
3130: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3131: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3132: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3133: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3134: }
3135: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3136: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3137: }
3138: for(j=i+1; j<=nlstate+ndeath;j++){
3139: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3140: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3141: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3142: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3143: }
3144: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3145: }
3146: }
3147:
3148: for(i=1; i<= nlstate; i++){
3149: s1=0;
3150: for(j=1; j<i; j++){
3151: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3152: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3153: }
3154: for(j=i+1; j<=nlstate+ndeath; j++){
3155: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3156: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3157: }
3158: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3159: ps[i][i]=1./(s1+1.);
3160: /* Computing other pijs */
3161: for(j=1; j<i; j++)
3162: ps[i][j]= exp(ps[i][j])*ps[i][i];
3163: for(j=i+1; j<=nlstate+ndeath; j++)
3164: ps[i][j]= exp(ps[i][j])*ps[i][i];
3165: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3166: } /* end i */
3167:
3168: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3169: for(jj=1; jj<= nlstate+ndeath; jj++){
3170: ps[ii][jj]=0;
3171: ps[ii][ii]=1;
3172: }
3173: }
1.296 brouard 3174: /* Added for prevbcast */ /* Transposed matrix too */
1.234 brouard 3175: for(jj=1; jj<= nlstate+ndeath; jj++){
3176: s1=0.;
3177: for(ii=1; ii<= nlstate+ndeath; ii++){
3178: s1+=ps[ii][jj];
3179: }
3180: for(ii=1; ii<= nlstate; ii++){
3181: ps[ii][jj]=ps[ii][jj]/s1;
3182: }
3183: }
3184: /* Transposition */
3185: for(jj=1; jj<= nlstate+ndeath; jj++){
3186: for(ii=jj; ii<= nlstate+ndeath; ii++){
3187: s1=ps[ii][jj];
3188: ps[ii][jj]=ps[jj][ii];
3189: ps[jj][ii]=s1;
3190: }
3191: }
3192: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3193: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3194: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3195: /* } */
3196: /* printf("\n "); */
3197: /* } */
3198: /* printf("\n ");printf("%lf ",cov[2]);*/
3199: /*
3200: for(i=1; i<= npar; i++) printf("%f ",x[i]);
3201: goto end;*/
3202: return ps;
1.217 brouard 3203: }
3204:
3205:
1.126 brouard 3206: /**************** Product of 2 matrices ******************/
3207:
1.145 brouard 3208: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 3209: {
3210: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
3211: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
3212: /* in, b, out are matrice of pointers which should have been initialized
3213: before: only the contents of out is modified. The function returns
3214: a pointer to pointers identical to out */
1.145 brouard 3215: int i, j, k;
1.126 brouard 3216: for(i=nrl; i<= nrh; i++)
1.145 brouard 3217: for(k=ncolol; k<=ncoloh; k++){
3218: out[i][k]=0.;
3219: for(j=ncl; j<=nch; j++)
3220: out[i][k] +=in[i][j]*b[j][k];
3221: }
1.126 brouard 3222: return out;
3223: }
3224:
3225:
3226: /************* Higher Matrix Product ***************/
3227:
1.235 brouard 3228: 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 3229: {
1.218 brouard 3230: /* Computes the transition matrix starting at age 'age' and combination of covariate values corresponding to ij over
1.126 brouard 3231: 'nhstepm*hstepm*stepm' months (i.e. until
3232: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3233: nhstepm*hstepm matrices.
3234: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3235: (typically every 2 years instead of every month which is too big
3236: for the memory).
3237: Model is determined by parameters x and covariates have to be
3238: included manually here.
3239:
3240: */
3241:
3242: int i, j, d, h, k;
1.131 brouard 3243: double **out, cov[NCOVMAX+1];
1.126 brouard 3244: double **newm;
1.187 brouard 3245: double agexact;
1.214 brouard 3246: double agebegin, ageend;
1.126 brouard 3247:
3248: /* Hstepm could be zero and should return the unit matrix */
3249: for (i=1;i<=nlstate+ndeath;i++)
3250: for (j=1;j<=nlstate+ndeath;j++){
3251: oldm[i][j]=(i==j ? 1.0 : 0.0);
3252: po[i][j][0]=(i==j ? 1.0 : 0.0);
3253: }
3254: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3255: for(h=1; h <=nhstepm; h++){
3256: for(d=1; d <=hstepm; d++){
3257: newm=savm;
3258: /* Covariates have to be included here again */
3259: cov[1]=1.;
1.214 brouard 3260: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3261: cov[2]=agexact;
3262: if(nagesqr==1)
1.227 brouard 3263: cov[3]= agexact*agexact;
1.235 brouard 3264: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
3265: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
3266: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3267: /* 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)); */
3268: }
3269: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3270: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3271: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3272: /* 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]); */
3273: }
3274: for (k=1; k<=cptcovage;k++){
3275: if(Dummy[Tvar[Tage[k]]]){
3276: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
3277: } else{
3278: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3279: }
3280: /* 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]); */
3281: }
3282: for (k=1; k<=cptcovprod;k++){ /* */
3283: /* 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]); */
3284: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
3285: }
3286: /* for (k=1; k<=cptcovn;k++) */
3287: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3288: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3289: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3290: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3291: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3292:
3293:
1.126 brouard 3294: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3295: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.218 brouard 3296: /* right multiplication of oldm by the current matrix */
1.126 brouard 3297: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3298: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3299: /* if((int)age == 70){ */
3300: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3301: /* for(i=1; i<=nlstate+ndeath; i++) { */
3302: /* printf("%d pmmij ",i); */
3303: /* for(j=1;j<=nlstate+ndeath;j++) { */
3304: /* printf("%f ",pmmij[i][j]); */
3305: /* } */
3306: /* printf(" oldm "); */
3307: /* for(j=1;j<=nlstate+ndeath;j++) { */
3308: /* printf("%f ",oldm[i][j]); */
3309: /* } */
3310: /* printf("\n"); */
3311: /* } */
3312: /* } */
1.126 brouard 3313: savm=oldm;
3314: oldm=newm;
3315: }
3316: for(i=1; i<=nlstate+ndeath; i++)
3317: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 3318: po[i][j][h]=newm[i][j];
3319: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3320: }
1.128 brouard 3321: /*printf("h=%d ",h);*/
1.126 brouard 3322: } /* end h */
1.267 brouard 3323: /* printf("\n H=%d \n",h); */
1.126 brouard 3324: return po;
3325: }
3326:
1.217 brouard 3327: /************* Higher Back Matrix Product ***************/
1.218 brouard 3328: /* 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 3329: 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 3330: {
1.266 brouard 3331: /* For a combination of dummy covariate ij, computes the transition matrix starting at age 'age' over
1.217 brouard 3332: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3333: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3334: nhstepm*hstepm matrices.
3335: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3336: (typically every 2 years instead of every month which is too big
1.217 brouard 3337: for the memory).
1.218 brouard 3338: Model is determined by parameters x and covariates have to be
1.266 brouard 3339: included manually here. Then we use a call to bmij(x and cov)
3340: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 3341: */
1.217 brouard 3342:
3343: int i, j, d, h, k;
1.266 brouard 3344: double **out, cov[NCOVMAX+1], **bmij();
3345: double **newm, ***newmm;
1.217 brouard 3346: double agexact;
3347: double agebegin, ageend;
1.222 brouard 3348: double **oldm, **savm;
1.217 brouard 3349:
1.266 brouard 3350: newmm=po; /* To be saved */
3351: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 3352: /* Hstepm could be zero and should return the unit matrix */
3353: for (i=1;i<=nlstate+ndeath;i++)
3354: for (j=1;j<=nlstate+ndeath;j++){
3355: oldm[i][j]=(i==j ? 1.0 : 0.0);
3356: po[i][j][0]=(i==j ? 1.0 : 0.0);
3357: }
3358: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3359: for(h=1; h <=nhstepm; h++){
3360: for(d=1; d <=hstepm; d++){
3361: newm=savm;
3362: /* Covariates have to be included here again */
3363: cov[1]=1.;
1.271 brouard 3364: agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 3365: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
3366: cov[2]=agexact;
3367: if(nagesqr==1)
1.222 brouard 3368: cov[3]= agexact*agexact;
1.266 brouard 3369: for (k=1; k<=cptcovn;k++){
3370: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3371: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
3372: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3373: /* 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)); */
3374: }
1.267 brouard 3375: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3376: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3377: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3378: /* 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]); */
3379: }
3380: for (k=1; k<=cptcovage;k++){ /* Should start at cptcovn+1 */
3381: if(Dummy[Tvar[Tage[k]]]){
3382: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
3383: } else{
3384: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3385: }
3386: /* 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]); */
3387: }
3388: for (k=1; k<=cptcovprod;k++){ /* Useless because included in cptcovn */
1.222 brouard 3389: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.267 brouard 3390: }
1.217 brouard 3391: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3392: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.267 brouard 3393:
1.218 brouard 3394: /* Careful transposed matrix */
1.266 brouard 3395: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 3396: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3397: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3398: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.222 brouard 3399: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);
1.217 brouard 3400: /* if((int)age == 70){ */
3401: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3402: /* for(i=1; i<=nlstate+ndeath; i++) { */
3403: /* printf("%d pmmij ",i); */
3404: /* for(j=1;j<=nlstate+ndeath;j++) { */
3405: /* printf("%f ",pmmij[i][j]); */
3406: /* } */
3407: /* printf(" oldm "); */
3408: /* for(j=1;j<=nlstate+ndeath;j++) { */
3409: /* printf("%f ",oldm[i][j]); */
3410: /* } */
3411: /* printf("\n"); */
3412: /* } */
3413: /* } */
3414: savm=oldm;
3415: oldm=newm;
3416: }
3417: for(i=1; i<=nlstate+ndeath; i++)
3418: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 3419: po[i][j][h]=newm[i][j];
1.268 brouard 3420: /* if(h==nhstepm) */
3421: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 3422: }
1.268 brouard 3423: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 3424: } /* end h */
1.268 brouard 3425: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 3426: return po;
3427: }
3428:
3429:
1.162 brouard 3430: #ifdef NLOPT
3431: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
3432: double fret;
3433: double *xt;
3434: int j;
3435: myfunc_data *d2 = (myfunc_data *) pd;
3436: /* xt = (p1-1); */
3437: xt=vector(1,n);
3438: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
3439:
3440: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
3441: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
3442: printf("Function = %.12lf ",fret);
3443: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
3444: printf("\n");
3445: free_vector(xt,1,n);
3446: return fret;
3447: }
3448: #endif
1.126 brouard 3449:
3450: /*************** log-likelihood *************/
3451: double func( double *x)
3452: {
1.226 brouard 3453: int i, ii, j, k, mi, d, kk;
3454: int ioffset=0;
3455: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
3456: double **out;
3457: double lli; /* Individual log likelihood */
3458: int s1, s2;
1.228 brouard 3459: 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 3460: double bbh, survp;
3461: long ipmx;
3462: double agexact;
3463: /*extern weight */
3464: /* We are differentiating ll according to initial status */
3465: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3466: /*for(i=1;i<imx;i++)
3467: printf(" %d\n",s[4][i]);
3468: */
1.162 brouard 3469:
1.226 brouard 3470: ++countcallfunc;
1.162 brouard 3471:
1.226 brouard 3472: cov[1]=1.;
1.126 brouard 3473:
1.226 brouard 3474: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3475: ioffset=0;
1.226 brouard 3476: if(mle==1){
3477: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3478: /* Computes the values of the ncovmodel covariates of the model
3479: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
3480: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
3481: to be observed in j being in i according to the model.
3482: */
1.243 brouard 3483: ioffset=2+nagesqr ;
1.233 brouard 3484: /* Fixed */
1.234 brouard 3485: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */
3486: 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)*/
3487: }
1.226 brouard 3488: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
3489: is 6, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]
3490: has been calculated etc */
3491: /* For an individual i, wav[i] gives the number of effective waves */
3492: /* We compute the contribution to Likelihood of each effective transition
3493: mw[mi][i] is real wave of the mi th effectve wave */
3494: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
3495: s2=s[mw[mi+1][i]][i];
3496: And the iv th varying covariate is the cotvar[mw[mi+1][i]][iv][i]
3497: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
3498: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
3499: */
3500: for(mi=1; mi<= wav[i]-1; mi++){
1.234 brouard 3501: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 3502: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
3503: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
1.234 brouard 3504: }
3505: for (ii=1;ii<=nlstate+ndeath;ii++)
3506: for (j=1;j<=nlstate+ndeath;j++){
3507: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3508: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3509: }
3510: for(d=0; d<dh[mi][i]; d++){
3511: newm=savm;
3512: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3513: cov[2]=agexact;
3514: if(nagesqr==1)
3515: cov[3]= agexact*agexact; /* Should be changed here */
3516: for (kk=1; kk<=cptcovage;kk++) {
1.242 brouard 3517: if(!FixedV[Tvar[Tage[kk]]])
1.234 brouard 3518: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
1.242 brouard 3519: else
3520: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
1.234 brouard 3521: }
3522: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3523: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3524: savm=oldm;
3525: oldm=newm;
3526: } /* end mult */
3527:
3528: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
3529: /* But now since version 0.9 we anticipate for bias at large stepm.
3530: * If stepm is larger than one month (smallest stepm) and if the exact delay
3531: * (in months) between two waves is not a multiple of stepm, we rounded to
3532: * the nearest (and in case of equal distance, to the lowest) interval but now
3533: * we keep into memory the bias bh[mi][i] and also the previous matrix product
3534: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
3535: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 3536: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
3537: * -stepm/2 to stepm/2 .
3538: * For stepm=1 the results are the same as for previous versions of Imach.
3539: * For stepm > 1 the results are less biased than in previous versions.
3540: */
1.234 brouard 3541: s1=s[mw[mi][i]][i];
3542: s2=s[mw[mi+1][i]][i];
3543: bbh=(double)bh[mi][i]/(double)stepm;
3544: /* bias bh is positive if real duration
3545: * is higher than the multiple of stepm and negative otherwise.
3546: */
3547: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
3548: if( s2 > nlstate){
3549: /* i.e. if s2 is a death state and if the date of death is known
3550: then the contribution to the likelihood is the probability to
3551: die between last step unit time and current step unit time,
3552: which is also equal to probability to die before dh
3553: minus probability to die before dh-stepm .
3554: In version up to 0.92 likelihood was computed
3555: as if date of death was unknown. Death was treated as any other
3556: health state: the date of the interview describes the actual state
3557: and not the date of a change in health state. The former idea was
3558: to consider that at each interview the state was recorded
3559: (healthy, disable or death) and IMaCh was corrected; but when we
3560: introduced the exact date of death then we should have modified
3561: the contribution of an exact death to the likelihood. This new
3562: contribution is smaller and very dependent of the step unit
3563: stepm. It is no more the probability to die between last interview
3564: and month of death but the probability to survive from last
3565: interview up to one month before death multiplied by the
3566: probability to die within a month. Thanks to Chris
3567: Jackson for correcting this bug. Former versions increased
3568: mortality artificially. The bad side is that we add another loop
3569: which slows down the processing. The difference can be up to 10%
3570: lower mortality.
3571: */
3572: /* If, at the beginning of the maximization mostly, the
3573: cumulative probability or probability to be dead is
3574: constant (ie = 1) over time d, the difference is equal to
3575: 0. out[s1][3] = savm[s1][3]: probability, being at state
3576: s1 at precedent wave, to be dead a month before current
3577: wave is equal to probability, being at state s1 at
3578: precedent wave, to be dead at mont of the current
3579: wave. Then the observed probability (that this person died)
3580: is null according to current estimated parameter. In fact,
3581: it should be very low but not zero otherwise the log go to
3582: infinity.
3583: */
1.183 brouard 3584: /* #ifdef INFINITYORIGINAL */
3585: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3586: /* #else */
3587: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
3588: /* lli=log(mytinydouble); */
3589: /* else */
3590: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3591: /* #endif */
1.226 brouard 3592: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3593:
1.226 brouard 3594: } else if ( s2==-1 ) { /* alive */
3595: for (j=1,survp=0. ; j<=nlstate; j++)
3596: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3597: /*survp += out[s1][j]; */
3598: lli= log(survp);
3599: }
3600: else if (s2==-4) {
3601: for (j=3,survp=0. ; j<=nlstate; j++)
3602: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3603: lli= log(survp);
3604: }
3605: else if (s2==-5) {
3606: for (j=1,survp=0. ; j<=2; j++)
3607: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3608: lli= log(survp);
3609: }
3610: else{
3611: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3612: /* 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 */
3613: }
3614: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
3615: /*if(lli ==000.0)*/
3616: /*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); */
3617: ipmx +=1;
3618: sw += weight[i];
3619: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3620: /* if (lli < log(mytinydouble)){ */
3621: /* 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); */
3622: /* 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]); */
3623: /* } */
3624: } /* end of wave */
3625: } /* end of individual */
3626: } else if(mle==2){
3627: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3628: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3629: for(mi=1; mi<= wav[i]-1; mi++){
3630: for (ii=1;ii<=nlstate+ndeath;ii++)
3631: for (j=1;j<=nlstate+ndeath;j++){
3632: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3633: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3634: }
3635: for(d=0; d<=dh[mi][i]; d++){
3636: newm=savm;
3637: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3638: cov[2]=agexact;
3639: if(nagesqr==1)
3640: cov[3]= agexact*agexact;
3641: for (kk=1; kk<=cptcovage;kk++) {
3642: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3643: }
3644: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3645: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3646: savm=oldm;
3647: oldm=newm;
3648: } /* end mult */
3649:
3650: s1=s[mw[mi][i]][i];
3651: s2=s[mw[mi+1][i]][i];
3652: bbh=(double)bh[mi][i]/(double)stepm;
3653: 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 */
3654: ipmx +=1;
3655: sw += weight[i];
3656: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3657: } /* end of wave */
3658: } /* end of individual */
3659: } else if(mle==3){ /* exponential inter-extrapolation */
3660: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3661: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3662: for(mi=1; mi<= wav[i]-1; mi++){
3663: for (ii=1;ii<=nlstate+ndeath;ii++)
3664: for (j=1;j<=nlstate+ndeath;j++){
3665: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3666: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3667: }
3668: for(d=0; d<dh[mi][i]; d++){
3669: newm=savm;
3670: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3671: cov[2]=agexact;
3672: if(nagesqr==1)
3673: cov[3]= agexact*agexact;
3674: for (kk=1; kk<=cptcovage;kk++) {
3675: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3676: }
3677: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3678: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3679: savm=oldm;
3680: oldm=newm;
3681: } /* end mult */
3682:
3683: s1=s[mw[mi][i]][i];
3684: s2=s[mw[mi+1][i]][i];
3685: bbh=(double)bh[mi][i]/(double)stepm;
3686: 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 */
3687: ipmx +=1;
3688: sw += weight[i];
3689: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3690: } /* end of wave */
3691: } /* end of individual */
3692: }else if (mle==4){ /* ml=4 no inter-extrapolation */
3693: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3694: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3695: for(mi=1; mi<= wav[i]-1; mi++){
3696: for (ii=1;ii<=nlstate+ndeath;ii++)
3697: for (j=1;j<=nlstate+ndeath;j++){
3698: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3699: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3700: }
3701: for(d=0; d<dh[mi][i]; d++){
3702: newm=savm;
3703: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3704: cov[2]=agexact;
3705: if(nagesqr==1)
3706: cov[3]= agexact*agexact;
3707: for (kk=1; kk<=cptcovage;kk++) {
3708: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3709: }
1.126 brouard 3710:
1.226 brouard 3711: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3712: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3713: savm=oldm;
3714: oldm=newm;
3715: } /* end mult */
3716:
3717: s1=s[mw[mi][i]][i];
3718: s2=s[mw[mi+1][i]][i];
3719: if( s2 > nlstate){
3720: lli=log(out[s1][s2] - savm[s1][s2]);
3721: } else if ( s2==-1 ) { /* alive */
3722: for (j=1,survp=0. ; j<=nlstate; j++)
3723: survp += out[s1][j];
3724: lli= log(survp);
3725: }else{
3726: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3727: }
3728: ipmx +=1;
3729: sw += weight[i];
3730: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.126 brouard 3731: /* printf("i=%6d s1=%1d s2=%1d mi=%1d mw=%1d dh=%3d prob=%10.6f w=%6.4f out=%10.6f sav=%10.6f\n",i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],out[s1][s2],savm[s1][s2]); */
1.226 brouard 3732: } /* end of wave */
3733: } /* end of individual */
3734: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
3735: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3736: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3737: for(mi=1; mi<= wav[i]-1; mi++){
3738: for (ii=1;ii<=nlstate+ndeath;ii++)
3739: for (j=1;j<=nlstate+ndeath;j++){
3740: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3741: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3742: }
3743: for(d=0; d<dh[mi][i]; d++){
3744: newm=savm;
3745: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3746: cov[2]=agexact;
3747: if(nagesqr==1)
3748: cov[3]= agexact*agexact;
3749: for (kk=1; kk<=cptcovage;kk++) {
3750: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3751: }
1.126 brouard 3752:
1.226 brouard 3753: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3754: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3755: savm=oldm;
3756: oldm=newm;
3757: } /* end mult */
3758:
3759: s1=s[mw[mi][i]][i];
3760: s2=s[mw[mi+1][i]][i];
3761: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3762: ipmx +=1;
3763: sw += weight[i];
3764: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3765: /*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]);*/
3766: } /* end of wave */
3767: } /* end of individual */
3768: } /* End of if */
3769: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3770: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3771: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3772: return -l;
1.126 brouard 3773: }
3774:
3775: /*************** log-likelihood *************/
3776: double funcone( double *x)
3777: {
1.228 brouard 3778: /* Same as func but slower because of a lot of printf and if */
1.126 brouard 3779: int i, ii, j, k, mi, d, kk;
1.228 brouard 3780: int ioffset=0;
1.131 brouard 3781: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 3782: double **out;
3783: double lli; /* Individual log likelihood */
3784: double llt;
3785: int s1, s2;
1.228 brouard 3786: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
3787:
1.126 brouard 3788: double bbh, survp;
1.187 brouard 3789: double agexact;
1.214 brouard 3790: double agebegin, ageend;
1.126 brouard 3791: /*extern weight */
3792: /* We are differentiating ll according to initial status */
3793: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3794: /*for(i=1;i<imx;i++)
3795: printf(" %d\n",s[4][i]);
3796: */
3797: cov[1]=1.;
3798:
3799: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3800: ioffset=0;
3801: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.243 brouard 3802: /* ioffset=2+nagesqr+cptcovage; */
3803: ioffset=2+nagesqr;
1.232 brouard 3804: /* Fixed */
1.224 brouard 3805: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 3806: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
3807: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */
3808: 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)*/
3809: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
3810: /* cov[2+6]=covar[Tvar[6]][i]; */
3811: /* cov[2+6]=covar[2][i]; V2 */
3812: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
3813: /* cov[2+7]=covar[Tvar[7]][i]; */
3814: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
3815: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
3816: /* cov[2+9]=covar[Tvar[9]][i]; */
3817: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 3818: }
1.232 brouard 3819: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
3820: /* 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?)*\/ */
3821: /* } */
1.231 brouard 3822: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
3823: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
3824: /* } */
1.225 brouard 3825:
1.233 brouard 3826:
3827: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.232 brouard 3828: /* Wave varying (but not age varying) */
3829: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 3830: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
3831: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
3832: }
1.232 brouard 3833: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates (single??)*\/ */
1.242 brouard 3834: /* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3835: /* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; */
3836: /* k=ioffset-2-nagesqr-cptcovage+itv; /\* position in simple model *\/ */
3837: /* cov[ioffset+itv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; */
3838: /* 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 3839: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 3840: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3841: /* /\* 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]); *\/ */
3842: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 3843: /* } */
1.126 brouard 3844: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 3845: for (j=1;j<=nlstate+ndeath;j++){
3846: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3847: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3848: }
1.214 brouard 3849:
3850: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
3851: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
3852: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 3853: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 3854: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
3855: and mw[mi+1][i]. dh depends on stepm.*/
3856: newm=savm;
1.247 brouard 3857: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 3858: cov[2]=agexact;
3859: if(nagesqr==1)
3860: cov[3]= agexact*agexact;
3861: for (kk=1; kk<=cptcovage;kk++) {
3862: if(!FixedV[Tvar[Tage[kk]]])
3863: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3864: else
3865: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
3866: }
3867: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
3868: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3869: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3870: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3871: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
3872: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
3873: savm=oldm;
3874: oldm=newm;
1.126 brouard 3875: } /* end mult */
3876:
3877: s1=s[mw[mi][i]][i];
3878: s2=s[mw[mi+1][i]][i];
1.217 brouard 3879: /* if(s2==-1){ */
1.268 brouard 3880: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 3881: /* /\* exit(1); *\/ */
3882: /* } */
1.126 brouard 3883: bbh=(double)bh[mi][i]/(double)stepm;
3884: /* bias is positive if real duration
3885: * is higher than the multiple of stepm and negative otherwise.
3886: */
3887: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 3888: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3889: } else if ( s2==-1 ) { /* alive */
1.242 brouard 3890: for (j=1,survp=0. ; j<=nlstate; j++)
3891: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3892: lli= log(survp);
1.126 brouard 3893: }else if (mle==1){
1.242 brouard 3894: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 3895: } else if(mle==2){
1.242 brouard 3896: 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 3897: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 3898: 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 3899: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 3900: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 3901: } else{ /* mle=0 back to 1 */
1.242 brouard 3902: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3903: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 3904: } /* End of if */
3905: ipmx +=1;
3906: sw += weight[i];
3907: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.132 brouard 3908: /*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 3909: if(globpr){
1.246 brouard 3910: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 3911: %11.6f %11.6f %11.6f ", \
1.242 brouard 3912: 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 3913: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.242 brouard 3914: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
3915: llt +=ll[k]*gipmx/gsw;
3916: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
3917: }
3918: fprintf(ficresilk," %10.6f\n", -llt);
1.126 brouard 3919: }
1.232 brouard 3920: } /* end of wave */
3921: } /* end of individual */
3922: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3923: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3924: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3925: if(globpr==0){ /* First time we count the contributions and weights */
3926: gipmx=ipmx;
3927: gsw=sw;
3928: }
3929: return -l;
1.126 brouard 3930: }
3931:
3932:
3933: /*************** function likelione ***********/
1.292 brouard 3934: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*func)(double []))
1.126 brouard 3935: {
3936: /* This routine should help understanding what is done with
3937: the selection of individuals/waves and
3938: to check the exact contribution to the likelihood.
3939: Plotting could be done.
3940: */
3941: int k;
3942:
3943: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 3944: strcpy(fileresilk,"ILK_");
1.202 brouard 3945: strcat(fileresilk,fileresu);
1.126 brouard 3946: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
3947: printf("Problem with resultfile: %s\n", fileresilk);
3948: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
3949: }
1.214 brouard 3950: 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");
3951: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 3952: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
3953: for(k=1; k<=nlstate; k++)
3954: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
3955: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total)\n");
3956: }
3957:
1.292 brouard 3958: *fretone=(*func)(p);
1.126 brouard 3959: if(*globpri !=0){
3960: fclose(ficresilk);
1.205 brouard 3961: if (mle ==0)
3962: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
3963: else if(mle >=1)
3964: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
3965: 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 3966: fprintf(fichtm,"\n<br>Equation of the model: <b>model=1+age+%s</b><br>\n",model);
1.208 brouard 3967:
3968: for (k=1; k<= nlstate ; k++) {
1.211 brouard 3969: 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 3970: <img src=\"%s-p%dj.png\">",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
3971: }
1.207 brouard 3972: 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 3973: <img src=\"%s-ori.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 3974: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.204 brouard 3975: <img src=\"%s-dest.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 3976: fflush(fichtm);
1.205 brouard 3977: }
1.126 brouard 3978: return;
3979: }
3980:
3981:
3982: /*********** Maximum Likelihood Estimation ***************/
3983:
3984: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
3985: {
1.165 brouard 3986: int i,j, iter=0;
1.126 brouard 3987: double **xi;
3988: double fret;
3989: double fretone; /* Only one call to likelihood */
3990: /* char filerespow[FILENAMELENGTH];*/
1.162 brouard 3991:
3992: #ifdef NLOPT
3993: int creturn;
3994: nlopt_opt opt;
3995: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
3996: double *lb;
3997: double minf; /* the minimum objective value, upon return */
3998: double * p1; /* Shifted parameters from 0 instead of 1 */
3999: myfunc_data dinst, *d = &dinst;
4000: #endif
4001:
4002:
1.126 brouard 4003: xi=matrix(1,npar,1,npar);
4004: for (i=1;i<=npar;i++)
4005: for (j=1;j<=npar;j++)
4006: xi[i][j]=(i==j ? 1.0 : 0.0);
4007: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 4008: strcpy(filerespow,"POW_");
1.126 brouard 4009: strcat(filerespow,fileres);
4010: if((ficrespow=fopen(filerespow,"w"))==NULL) {
4011: printf("Problem with resultfile: %s\n", filerespow);
4012: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
4013: }
4014: fprintf(ficrespow,"# Powell\n# iter -2*LL");
4015: for (i=1;i<=nlstate;i++)
4016: for(j=1;j<=nlstate+ndeath;j++)
4017: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
4018: fprintf(ficrespow,"\n");
1.162 brouard 4019: #ifdef POWELL
1.126 brouard 4020: powell(p,xi,npar,ftol,&iter,&fret,func);
1.162 brouard 4021: #endif
1.126 brouard 4022:
1.162 brouard 4023: #ifdef NLOPT
4024: #ifdef NEWUOA
4025: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
4026: #else
4027: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
4028: #endif
4029: lb=vector(0,npar-1);
4030: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
4031: nlopt_set_lower_bounds(opt, lb);
4032: nlopt_set_initial_step1(opt, 0.1);
4033:
4034: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
4035: d->function = func;
4036: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
4037: nlopt_set_min_objective(opt, myfunc, d);
4038: nlopt_set_xtol_rel(opt, ftol);
4039: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
4040: printf("nlopt failed! %d\n",creturn);
4041: }
4042: else {
4043: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
4044: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
4045: iter=1; /* not equal */
4046: }
4047: nlopt_destroy(opt);
4048: #endif
1.126 brouard 4049: free_matrix(xi,1,npar,1,npar);
4050: fclose(ficrespow);
1.203 brouard 4051: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
4052: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 4053: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 4054:
4055: }
4056:
4057: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 4058: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 4059: {
4060: double **a,**y,*x,pd;
1.203 brouard 4061: /* double **hess; */
1.164 brouard 4062: int i, j;
1.126 brouard 4063: int *indx;
4064:
4065: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 4066: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 4067: void lubksb(double **a, int npar, int *indx, double b[]) ;
4068: void ludcmp(double **a, int npar, int *indx, double *d) ;
4069: double gompertz(double p[]);
1.203 brouard 4070: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 4071:
4072: printf("\nCalculation of the hessian matrix. Wait...\n");
4073: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
4074: for (i=1;i<=npar;i++){
1.203 brouard 4075: printf("%d-",i);fflush(stdout);
4076: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 4077:
4078: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
4079:
4080: /* printf(" %f ",p[i]);
4081: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
4082: }
4083:
4084: for (i=1;i<=npar;i++) {
4085: for (j=1;j<=npar;j++) {
4086: if (j>i) {
1.203 brouard 4087: printf(".%d-%d",i,j);fflush(stdout);
4088: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
4089: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 4090:
4091: hess[j][i]=hess[i][j];
4092: /*printf(" %lf ",hess[i][j]);*/
4093: }
4094: }
4095: }
4096: printf("\n");
4097: fprintf(ficlog,"\n");
4098:
4099: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
4100: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
4101:
4102: a=matrix(1,npar,1,npar);
4103: y=matrix(1,npar,1,npar);
4104: x=vector(1,npar);
4105: indx=ivector(1,npar);
4106: for (i=1;i<=npar;i++)
4107: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
4108: ludcmp(a,npar,indx,&pd);
4109:
4110: for (j=1;j<=npar;j++) {
4111: for (i=1;i<=npar;i++) x[i]=0;
4112: x[j]=1;
4113: lubksb(a,npar,indx,x);
4114: for (i=1;i<=npar;i++){
4115: matcov[i][j]=x[i];
4116: }
4117: }
4118:
4119: printf("\n#Hessian matrix#\n");
4120: fprintf(ficlog,"\n#Hessian matrix#\n");
4121: for (i=1;i<=npar;i++) {
4122: for (j=1;j<=npar;j++) {
1.203 brouard 4123: printf("%.6e ",hess[i][j]);
4124: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 4125: }
4126: printf("\n");
4127: fprintf(ficlog,"\n");
4128: }
4129:
1.203 brouard 4130: /* printf("\n#Covariance matrix#\n"); */
4131: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
4132: /* for (i=1;i<=npar;i++) { */
4133: /* for (j=1;j<=npar;j++) { */
4134: /* printf("%.6e ",matcov[i][j]); */
4135: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
4136: /* } */
4137: /* printf("\n"); */
4138: /* fprintf(ficlog,"\n"); */
4139: /* } */
4140:
1.126 brouard 4141: /* Recompute Inverse */
1.203 brouard 4142: /* for (i=1;i<=npar;i++) */
4143: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
4144: /* ludcmp(a,npar,indx,&pd); */
4145:
4146: /* printf("\n#Hessian matrix recomputed#\n"); */
4147:
4148: /* for (j=1;j<=npar;j++) { */
4149: /* for (i=1;i<=npar;i++) x[i]=0; */
4150: /* x[j]=1; */
4151: /* lubksb(a,npar,indx,x); */
4152: /* for (i=1;i<=npar;i++){ */
4153: /* y[i][j]=x[i]; */
4154: /* printf("%.3e ",y[i][j]); */
4155: /* fprintf(ficlog,"%.3e ",y[i][j]); */
4156: /* } */
4157: /* printf("\n"); */
4158: /* fprintf(ficlog,"\n"); */
4159: /* } */
4160:
4161: /* Verifying the inverse matrix */
4162: #ifdef DEBUGHESS
4163: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 4164:
1.203 brouard 4165: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
4166: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 4167:
4168: for (j=1;j<=npar;j++) {
4169: for (i=1;i<=npar;i++){
1.203 brouard 4170: printf("%.2f ",y[i][j]);
4171: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 4172: }
4173: printf("\n");
4174: fprintf(ficlog,"\n");
4175: }
1.203 brouard 4176: #endif
1.126 brouard 4177:
4178: free_matrix(a,1,npar,1,npar);
4179: free_matrix(y,1,npar,1,npar);
4180: free_vector(x,1,npar);
4181: free_ivector(indx,1,npar);
1.203 brouard 4182: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 4183:
4184:
4185: }
4186:
4187: /*************** hessian matrix ****************/
4188: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 4189: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 4190: int i;
4191: int l=1, lmax=20;
1.203 brouard 4192: double k1,k2, res, fx;
1.132 brouard 4193: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 4194: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
4195: int k=0,kmax=10;
4196: double l1;
4197:
4198: fx=func(x);
4199: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 4200: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 4201: l1=pow(10,l);
4202: delts=delt;
4203: for(k=1 ; k <kmax; k=k+1){
4204: delt = delta*(l1*k);
4205: p2[theta]=x[theta] +delt;
1.145 brouard 4206: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 4207: p2[theta]=x[theta]-delt;
4208: k2=func(p2)-fx;
4209: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 4210: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 4211:
1.203 brouard 4212: #ifdef DEBUGHESSII
1.126 brouard 4213: 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);
4214: 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);
4215: #endif
4216: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
4217: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
4218: k=kmax;
4219: }
4220: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 4221: k=kmax; l=lmax*10;
1.126 brouard 4222: }
4223: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
4224: delts=delt;
4225: }
1.203 brouard 4226: } /* End loop k */
1.126 brouard 4227: }
4228: delti[theta]=delts;
4229: return res;
4230:
4231: }
4232:
1.203 brouard 4233: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 4234: {
4235: int i;
1.164 brouard 4236: int l=1, lmax=20;
1.126 brouard 4237: double k1,k2,k3,k4,res,fx;
1.132 brouard 4238: double p2[MAXPARM+1];
1.203 brouard 4239: int k, kmax=1;
4240: double v1, v2, cv12, lc1, lc2;
1.208 brouard 4241:
4242: int firstime=0;
1.203 brouard 4243:
1.126 brouard 4244: fx=func(x);
1.203 brouard 4245: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 4246: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 4247: p2[thetai]=x[thetai]+delti[thetai]*k;
4248: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4249: k1=func(p2)-fx;
4250:
1.203 brouard 4251: p2[thetai]=x[thetai]+delti[thetai]*k;
4252: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4253: k2=func(p2)-fx;
4254:
1.203 brouard 4255: p2[thetai]=x[thetai]-delti[thetai]*k;
4256: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4257: k3=func(p2)-fx;
4258:
1.203 brouard 4259: p2[thetai]=x[thetai]-delti[thetai]*k;
4260: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4261: k4=func(p2)-fx;
1.203 brouard 4262: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
4263: if(k1*k2*k3*k4 <0.){
1.208 brouard 4264: firstime=1;
1.203 brouard 4265: kmax=kmax+10;
1.208 brouard 4266: }
4267: if(kmax >=10 || firstime ==1){
1.246 brouard 4268: 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);
4269: 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 4270: 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);
4271: 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);
4272: }
4273: #ifdef DEBUGHESSIJ
4274: v1=hess[thetai][thetai];
4275: v2=hess[thetaj][thetaj];
4276: cv12=res;
4277: /* Computing eigen value of Hessian matrix */
4278: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4279: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4280: if ((lc2 <0) || (lc1 <0) ){
4281: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4282: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
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: }
1.126 brouard 4286: #endif
4287: }
4288: return res;
4289: }
4290:
1.203 brouard 4291: /* Not done yet: Was supposed to fix if not exactly at the maximum */
4292: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
4293: /* { */
4294: /* int i; */
4295: /* int l=1, lmax=20; */
4296: /* double k1,k2,k3,k4,res,fx; */
4297: /* double p2[MAXPARM+1]; */
4298: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
4299: /* int k=0,kmax=10; */
4300: /* double l1; */
4301:
4302: /* fx=func(x); */
4303: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
4304: /* l1=pow(10,l); */
4305: /* delts=delt; */
4306: /* for(k=1 ; k <kmax; k=k+1){ */
4307: /* delt = delti*(l1*k); */
4308: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
4309: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4310: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4311: /* k1=func(p2)-fx; */
4312:
4313: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4314: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4315: /* k2=func(p2)-fx; */
4316:
4317: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4318: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4319: /* k3=func(p2)-fx; */
4320:
4321: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4322: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4323: /* k4=func(p2)-fx; */
4324: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
4325: /* #ifdef DEBUGHESSIJ */
4326: /* 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); */
4327: /* 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); */
4328: /* #endif */
4329: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
4330: /* k=kmax; */
4331: /* } */
4332: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
4333: /* k=kmax; l=lmax*10; */
4334: /* } */
4335: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
4336: /* delts=delt; */
4337: /* } */
4338: /* } /\* End loop k *\/ */
4339: /* } */
4340: /* delti[theta]=delts; */
4341: /* return res; */
4342: /* } */
4343:
4344:
1.126 brouard 4345: /************** Inverse of matrix **************/
4346: void ludcmp(double **a, int n, int *indx, double *d)
4347: {
4348: int i,imax,j,k;
4349: double big,dum,sum,temp;
4350: double *vv;
4351:
4352: vv=vector(1,n);
4353: *d=1.0;
4354: for (i=1;i<=n;i++) {
4355: big=0.0;
4356: for (j=1;j<=n;j++)
4357: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 4358: if (big == 0.0){
4359: printf(" Singular Hessian matrix at row %d:\n",i);
4360: for (j=1;j<=n;j++) {
4361: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
4362: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
4363: }
4364: fflush(ficlog);
4365: fclose(ficlog);
4366: nrerror("Singular matrix in routine ludcmp");
4367: }
1.126 brouard 4368: vv[i]=1.0/big;
4369: }
4370: for (j=1;j<=n;j++) {
4371: for (i=1;i<j;i++) {
4372: sum=a[i][j];
4373: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
4374: a[i][j]=sum;
4375: }
4376: big=0.0;
4377: for (i=j;i<=n;i++) {
4378: sum=a[i][j];
4379: for (k=1;k<j;k++)
4380: sum -= a[i][k]*a[k][j];
4381: a[i][j]=sum;
4382: if ( (dum=vv[i]*fabs(sum)) >= big) {
4383: big=dum;
4384: imax=i;
4385: }
4386: }
4387: if (j != imax) {
4388: for (k=1;k<=n;k++) {
4389: dum=a[imax][k];
4390: a[imax][k]=a[j][k];
4391: a[j][k]=dum;
4392: }
4393: *d = -(*d);
4394: vv[imax]=vv[j];
4395: }
4396: indx[j]=imax;
4397: if (a[j][j] == 0.0) a[j][j]=TINY;
4398: if (j != n) {
4399: dum=1.0/(a[j][j]);
4400: for (i=j+1;i<=n;i++) a[i][j] *= dum;
4401: }
4402: }
4403: free_vector(vv,1,n); /* Doesn't work */
4404: ;
4405: }
4406:
4407: void lubksb(double **a, int n, int *indx, double b[])
4408: {
4409: int i,ii=0,ip,j;
4410: double sum;
4411:
4412: for (i=1;i<=n;i++) {
4413: ip=indx[i];
4414: sum=b[ip];
4415: b[ip]=b[i];
4416: if (ii)
4417: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
4418: else if (sum) ii=i;
4419: b[i]=sum;
4420: }
4421: for (i=n;i>=1;i--) {
4422: sum=b[i];
4423: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
4424: b[i]=sum/a[i][i];
4425: }
4426: }
4427:
4428: void pstamp(FILE *fichier)
4429: {
1.196 brouard 4430: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 4431: }
4432:
1.297 brouard 4433: void date2dmy(double date,double *day, double *month, double *year){
4434: double yp=0., yp1=0., yp2=0.;
4435:
4436: yp1=modf(date,&yp);/* extracts integral of date in yp and
4437: fractional in yp1 */
4438: *year=yp;
4439: yp2=modf((yp1*12),&yp);
4440: *month=yp;
4441: yp1=modf((yp2*30.5),&yp);
4442: *day=yp;
4443: if(*day==0) *day=1;
4444: if(*month==0) *month=1;
4445: }
4446:
1.253 brouard 4447:
4448:
1.126 brouard 4449: /************ Frequencies ********************/
1.251 brouard 4450: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 4451: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
4452: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 4453: { /* Some frequencies as well as proposing some starting values */
1.226 brouard 4454:
1.265 brouard 4455: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 4456: int iind=0, iage=0;
4457: int mi; /* Effective wave */
4458: int first;
4459: double ***freq; /* Frequencies */
1.268 brouard 4460: 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 */
4461: 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 4462: double *meanq, *stdq, *idq;
1.226 brouard 4463: double **meanqt;
4464: double *pp, **prop, *posprop, *pospropt;
4465: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
4466: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
4467: double agebegin, ageend;
4468:
4469: pp=vector(1,nlstate);
1.251 brouard 4470: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4471: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
4472: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
4473: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
4474: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.284 brouard 4475: stdq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.283 brouard 4476: idq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.226 brouard 4477: meanqt=matrix(1,lastpass,1,nqtveff);
4478: strcpy(fileresp,"P_");
4479: strcat(fileresp,fileresu);
4480: /*strcat(fileresphtm,fileresu);*/
4481: if((ficresp=fopen(fileresp,"w"))==NULL) {
4482: printf("Problem with prevalence resultfile: %s\n", fileresp);
4483: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
4484: exit(0);
4485: }
1.240 brouard 4486:
1.226 brouard 4487: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
4488: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
4489: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4490: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4491: fflush(ficlog);
4492: exit(70);
4493: }
4494: else{
4495: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 4496: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4497: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4498: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4499: }
1.237 brouard 4500: 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 4501:
1.226 brouard 4502: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
4503: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
4504: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4505: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4506: fflush(ficlog);
4507: exit(70);
1.240 brouard 4508: } else{
1.226 brouard 4509: 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 4510: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4511: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4512: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4513: }
1.240 brouard 4514: 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);
4515:
1.253 brouard 4516: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
4517: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 4518: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4519: j1=0;
1.126 brouard 4520:
1.227 brouard 4521: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
4522: j=cptcoveff; /* Only dummy covariates of the model */
1.226 brouard 4523: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 4524:
4525:
1.226 brouard 4526: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
4527: reference=low_education V1=0,V2=0
4528: med_educ V1=1 V2=0,
4529: high_educ V1=0 V2=1
4530: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcoveff
4531: */
1.249 brouard 4532: dateintsum=0;
4533: k2cpt=0;
4534:
1.253 brouard 4535: if(cptcoveff == 0 )
1.265 brouard 4536: nl=1; /* Constant and age model only */
1.253 brouard 4537: else
4538: nl=2;
1.265 brouard 4539:
4540: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
4541: /* Loop on nj=1 or 2 if dummy covariates j!=0
4542: * Loop on j1(1 to 2**cptcoveff) covariate combination
4543: * freq[s1][s2][iage] =0.
4544: * Loop on iind
4545: * ++freq[s1][s2][iage] weighted
4546: * end iind
4547: * if covariate and j!0
4548: * headers Variable on one line
4549: * endif cov j!=0
4550: * header of frequency table by age
4551: * Loop on age
4552: * pp[s1]+=freq[s1][s2][iage] weighted
4553: * pos+=freq[s1][s2][iage] weighted
4554: * Loop on s1 initial state
4555: * fprintf(ficresp
4556: * end s1
4557: * end age
4558: * if j!=0 computes starting values
4559: * end compute starting values
4560: * end j1
4561: * end nl
4562: */
1.253 brouard 4563: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
4564: if(nj==1)
4565: j=0; /* First pass for the constant */
1.265 brouard 4566: else{
1.253 brouard 4567: j=cptcoveff; /* Other passes for the covariate values */
1.265 brouard 4568: }
1.251 brouard 4569: first=1;
1.265 brouard 4570: 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 4571: posproptt=0.;
4572: /*printf("cptcoveff=%d Tvaraff=%d", cptcoveff,Tvaraff[1]);
4573: scanf("%d", i);*/
4574: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 4575: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 4576: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 4577: freq[i][s2][m]=0;
1.251 brouard 4578:
4579: for (i=1; i<=nlstate; i++) {
1.240 brouard 4580: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 4581: prop[i][m]=0;
4582: posprop[i]=0;
4583: pospropt[i]=0;
4584: }
1.283 brouard 4585: for (z1=1; z1<= nqfveff; z1++) { /* zeroing for each combination j1 as well as for the total */
1.284 brouard 4586: idq[z1]=0.;
4587: meanq[z1]=0.;
4588: stdq[z1]=0.;
1.283 brouard 4589: }
4590: /* for (z1=1; z1<= nqtveff; z1++) { */
1.251 brouard 4591: /* for(m=1;m<=lastpass;m++){ */
1.283 brouard 4592: /* meanqt[m][z1]=0.; */
4593: /* } */
4594: /* } */
1.251 brouard 4595: /* dateintsum=0; */
4596: /* k2cpt=0; */
4597:
1.265 brouard 4598: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 4599: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
4600: bool=1;
4601: if(j !=0){
4602: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
4603: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
4604: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
4605: /* if(Tvaraff[z1] ==-20){ */
4606: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
4607: /* }else if(Tvaraff[z1] ==-10){ */
4608: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
4609: /* }else */
4610: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]){ /* for combination j1 of covariates */
1.265 brouard 4611: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 4612: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
4613: /* 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",
4614: bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),
4615: j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
4616: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
4617: } /* Onlyf fixed */
4618: } /* end z1 */
4619: } /* cptcovn > 0 */
4620: } /* end any */
4621: }/* end j==0 */
1.265 brouard 4622: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 4623: /* for(m=firstpass; m<=lastpass; m++){ */
1.284 brouard 4624: for(mi=1; mi<wav[iind];mi++){ /* For each wave */
1.251 brouard 4625: m=mw[mi][iind];
4626: if(j!=0){
4627: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
4628: for (z1=1; z1<=cptcoveff; z1++) {
4629: if( Fixed[Tmodelind[z1]]==1){
4630: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
4631: if (cotvar[m][iv][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality. If covariate's
4632: value is -1, we don't select. It differs from the
4633: constant and age model which counts them. */
4634: bool=0; /* not selected */
4635: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
4636: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
4637: bool=0;
4638: }
4639: }
4640: }
4641: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
4642: } /* end j==0 */
4643: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
1.284 brouard 4644: if(bool==1){ /*Selected */
1.251 brouard 4645: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
4646: and mw[mi+1][iind]. dh depends on stepm. */
4647: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
4648: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
4649: if(m >=firstpass && m <=lastpass){
4650: k2=anint[m][iind]+(mint[m][iind]/12.);
4651: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
4652: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
4653: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
4654: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
4655: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
4656: if (m<lastpass) {
4657: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
4658: /* 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]); */
4659: if(s[m][iind]==-1)
4660: 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.));
4661: 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 4662: for (z1=1; z1<= nqfveff; z1++) { /* Quantitative variables, calculating mean */
4663: idq[z1]=idq[z1]+weight[iind];
4664: meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /* Computes mean of quantitative with selected filter */
4665: stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /* *weight[iind];*/ /* Computes mean of quantitative with selected filter */
4666: }
1.251 brouard 4667: /* if((int)agev[m][iind] == 55) */
4668: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
4669: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
4670: 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 4671: }
1.251 brouard 4672: } /* end if between passes */
4673: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
4674: dateintsum=dateintsum+k2; /* on all covariates ?*/
4675: k2cpt++;
4676: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 4677: }
1.251 brouard 4678: }else{
4679: bool=1;
4680: }/* end bool 2 */
4681: } /* end m */
1.284 brouard 4682: /* for (z1=1; z1<= nqfveff; z1++) { /\* Quantitative variables, calculating mean *\/ */
4683: /* idq[z1]=idq[z1]+weight[iind]; */
4684: /* meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /\* Computes mean of quantitative with selected filter *\/ */
4685: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /\* *weight[iind];*\/ /\* Computes mean of quantitative with selected filter *\/ */
4686: /* } */
1.251 brouard 4687: } /* end bool */
4688: } /* end iind = 1 to imx */
4689: /* prop[s][age] is feeded for any initial and valid live state as well as
4690: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
4691:
4692:
4693: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.265 brouard 4694: if(cptcoveff==0 && nj==1) /* no covariate and first pass */
4695: pstamp(ficresp);
1.251 brouard 4696: if (cptcoveff>0 && j!=0){
1.265 brouard 4697: pstamp(ficresp);
1.251 brouard 4698: printf( "\n#********** Variable ");
4699: fprintf(ficresp, "\n#********** Variable ");
4700: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
4701: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
4702: fprintf(ficlog, "\n#********** Variable ");
4703: for (z1=1; z1<=cptcoveff; z1++){
4704: if(!FixedV[Tvaraff[z1]]){
4705: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4706: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4707: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4708: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4709: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.250 brouard 4710: }else{
1.251 brouard 4711: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4712: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4713: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4714: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4715: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4716: }
4717: }
4718: printf( "**********\n#");
4719: fprintf(ficresp, "**********\n#");
4720: fprintf(ficresphtm, "**********</h3>\n");
4721: fprintf(ficresphtmfr, "**********</h3>\n");
4722: fprintf(ficlog, "**********\n");
4723: }
1.284 brouard 4724: /*
4725: Printing means of quantitative variables if any
4726: */
4727: for (z1=1; z1<= nqfveff; z1++) {
1.285 brouard 4728: fprintf(ficlog,"Mean of fixed quantitative variable V%d on %.0f individuals sum=%f", ncovcol+z1, idq[z1], meanq[z1]);
1.284 brouard 4729: fprintf(ficlog,", mean=%.3g\n",meanq[z1]/idq[z1]);
4730: if(weightopt==1){
4731: printf(" Weighted mean and standard deviation of");
4732: fprintf(ficlog," Weighted mean and standard deviation of");
4733: fprintf(ficresphtmfr," Weighted mean and standard deviation of");
4734: }
1.285 brouard 4735: 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]));
4736: 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]));
4737: 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 4738: }
4739: /* for (z1=1; z1<= nqtveff; z1++) { */
4740: /* for(m=1;m<=lastpass;m++){ */
4741: /* fprintf(ficresphtmfr,"V quantitative id %d, pass id=%d, mean=%f<p>\n", z1, m, meanqt[m][z1]); */
4742: /* } */
4743: /* } */
1.283 brouard 4744:
1.251 brouard 4745: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.265 brouard 4746: if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
4747: fprintf(ficresp, " Age");
4748: 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 4749: for(i=1; i<=nlstate;i++) {
1.265 brouard 4750: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 4751: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
4752: }
1.265 brouard 4753: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 4754: fprintf(ficresphtm, "\n");
4755:
4756: /* Header of frequency table by age */
4757: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
4758: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 4759: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 4760: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 4761: if(s2!=0 && m!=0)
4762: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 4763: }
1.226 brouard 4764: }
1.251 brouard 4765: fprintf(ficresphtmfr, "\n");
4766:
4767: /* For each age */
4768: for(iage=iagemin; iage <= iagemax+3; iage++){
4769: fprintf(ficresphtm,"<tr>");
4770: if(iage==iagemax+1){
4771: fprintf(ficlog,"1");
4772: fprintf(ficresphtmfr,"<tr><th>0</th> ");
4773: }else if(iage==iagemax+2){
4774: fprintf(ficlog,"0");
4775: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
4776: }else if(iage==iagemax+3){
4777: fprintf(ficlog,"Total");
4778: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
4779: }else{
1.240 brouard 4780: if(first==1){
1.251 brouard 4781: first=0;
4782: printf("See log file for details...\n");
4783: }
4784: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
4785: fprintf(ficlog,"Age %d", iage);
4786: }
1.265 brouard 4787: for(s1=1; s1 <=nlstate ; s1++){
4788: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
4789: pp[s1] += freq[s1][m][iage];
1.251 brouard 4790: }
1.265 brouard 4791: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 4792: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 4793: pos += freq[s1][m][iage];
4794: if(pp[s1]>=1.e-10){
1.251 brouard 4795: if(first==1){
1.265 brouard 4796: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 4797: }
1.265 brouard 4798: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 4799: }else{
4800: if(first==1)
1.265 brouard 4801: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
4802: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 4803: }
4804: }
4805:
1.265 brouard 4806: for(s1=1; s1 <=nlstate ; s1++){
4807: /* posprop[s1]=0; */
4808: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
4809: pp[s1] += freq[s1][m][iage];
4810: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
4811:
4812: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
4813: pos += pp[s1]; /* pos is the total number of transitions until this age */
4814: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
4815: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
4816: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
4817: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
4818: }
4819:
4820: /* Writing ficresp */
4821: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
4822: if( iage <= iagemax){
4823: fprintf(ficresp," %d",iage);
4824: }
4825: }else if( nj==2){
4826: if( iage <= iagemax){
4827: fprintf(ficresp," %d",iage);
4828: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4829: }
1.240 brouard 4830: }
1.265 brouard 4831: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 4832: if(pos>=1.e-5){
1.251 brouard 4833: if(first==1)
1.265 brouard 4834: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
4835: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 4836: }else{
4837: if(first==1)
1.265 brouard 4838: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
4839: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 4840: }
4841: if( iage <= iagemax){
4842: if(pos>=1.e-5){
1.265 brouard 4843: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
4844: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4845: }else if( nj==2){
4846: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4847: }
4848: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4849: /*probs[iage][s1][j1]= pp[s1]/pos;*/
4850: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
4851: } else{
4852: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
4853: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 4854: }
1.240 brouard 4855: }
1.265 brouard 4856: pospropt[s1] +=posprop[s1];
4857: } /* end loop s1 */
1.251 brouard 4858: /* pospropt=0.; */
1.265 brouard 4859: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 4860: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 4861: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 4862: if(first==1){
1.265 brouard 4863: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 4864: }
1.265 brouard 4865: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
4866: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 4867: }
1.265 brouard 4868: if(s1!=0 && m!=0)
4869: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 4870: }
1.265 brouard 4871: } /* end loop s1 */
1.251 brouard 4872: posproptt=0.;
1.265 brouard 4873: for(s1=1; s1 <=nlstate; s1++){
4874: posproptt += pospropt[s1];
1.251 brouard 4875: }
4876: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 4877: fprintf(ficresphtm,"</tr>\n");
4878: if((cptcoveff==0 && nj==1)|| nj==2 ) {
4879: if(iage <= iagemax)
4880: fprintf(ficresp,"\n");
1.240 brouard 4881: }
1.251 brouard 4882: if(first==1)
4883: printf("Others in log...\n");
4884: fprintf(ficlog,"\n");
4885: } /* end loop age iage */
1.265 brouard 4886:
1.251 brouard 4887: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 4888: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 4889: if(posproptt < 1.e-5){
1.265 brouard 4890: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 4891: }else{
1.265 brouard 4892: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 4893: }
1.226 brouard 4894: }
1.251 brouard 4895: fprintf(ficresphtm,"</tr>\n");
4896: fprintf(ficresphtm,"</table>\n");
4897: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 4898: if(posproptt < 1.e-5){
1.251 brouard 4899: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
4900: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 4901: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
4902: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 4903: invalidvarcomb[j1]=1;
1.226 brouard 4904: }else{
1.251 brouard 4905: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced.</p>",j1);
4906: invalidvarcomb[j1]=0;
1.226 brouard 4907: }
1.251 brouard 4908: fprintf(ficresphtmfr,"</table>\n");
4909: fprintf(ficlog,"\n");
4910: if(j!=0){
4911: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 4912: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 4913: for(k=1; k <=(nlstate+ndeath); k++){
4914: if (k != i) {
1.265 brouard 4915: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 4916: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 4917: if(j1==1){ /* All dummy covariates to zero */
4918: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
4919: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 4920: printf("%d%d ",i,k);
4921: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 4922: 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]));
4923: 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]));
4924: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 4925: }
1.253 brouard 4926: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
4927: for(iage=iagemin; iage <= iagemax+3; iage++){
4928: x[iage]= (double)iage;
4929: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 4930: /* 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 4931: }
1.268 brouard 4932: /* Some are not finite, but linreg will ignore these ages */
4933: no=0;
1.253 brouard 4934: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 4935: pstart[s1]=b;
4936: pstart[s1-1]=a;
1.252 brouard 4937: }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 */
4938: 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]);
4939: 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 4940: 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 4941: printf("%d%d ",i,k);
4942: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 4943: 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 4944: }else{ /* Other cases, like quantitative fixed or varying covariates */
4945: ;
4946: }
4947: /* printf("%12.7f )", param[i][jj][k]); */
4948: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 4949: s1++;
1.251 brouard 4950: } /* end jj */
4951: } /* end k!= i */
4952: } /* end k */
1.265 brouard 4953: } /* end i, s1 */
1.251 brouard 4954: } /* end j !=0 */
4955: } /* end selected combination of covariate j1 */
4956: if(j==0){ /* We can estimate starting values from the occurences in each case */
4957: printf("#Freqsummary: Starting values for the constants:\n");
4958: fprintf(ficlog,"\n");
1.265 brouard 4959: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 4960: for(k=1; k <=(nlstate+ndeath); k++){
4961: if (k != i) {
4962: printf("%d%d ",i,k);
4963: fprintf(ficlog,"%d%d ",i,k);
4964: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 4965: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 4966: if(jj==1){ /* Age has to be done */
1.265 brouard 4967: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
4968: 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]));
4969: 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 4970: }
4971: /* printf("%12.7f )", param[i][jj][k]); */
4972: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 4973: s1++;
1.250 brouard 4974: }
1.251 brouard 4975: printf("\n");
4976: fprintf(ficlog,"\n");
1.250 brouard 4977: }
4978: }
1.284 brouard 4979: } /* end of state i */
1.251 brouard 4980: printf("#Freqsummary\n");
4981: fprintf(ficlog,"\n");
1.265 brouard 4982: for(s1=-1; s1 <=nlstate+ndeath; s1++){
4983: for(s2=-1; s2 <=nlstate+ndeath; s2++){
4984: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
4985: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
4986: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
4987: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
4988: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
4989: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 4990: /* } */
4991: }
1.265 brouard 4992: } /* end loop s1 */
1.251 brouard 4993:
4994: printf("\n");
4995: fprintf(ficlog,"\n");
4996: } /* end j=0 */
1.249 brouard 4997: } /* end j */
1.252 brouard 4998:
1.253 brouard 4999: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 5000: for(i=1, jk=1; i <=nlstate; i++){
5001: for(j=1; j <=nlstate+ndeath; j++){
5002: if(j!=i){
5003: /*ca[0]= k+'a'-1;ca[1]='\0';*/
5004: printf("%1d%1d",i,j);
5005: fprintf(ficparo,"%1d%1d",i,j);
5006: for(k=1; k<=ncovmodel;k++){
5007: /* printf(" %lf",param[i][j][k]); */
5008: /* fprintf(ficparo," %lf",param[i][j][k]); */
5009: p[jk]=pstart[jk];
5010: printf(" %f ",pstart[jk]);
5011: fprintf(ficparo," %f ",pstart[jk]);
5012: jk++;
5013: }
5014: printf("\n");
5015: fprintf(ficparo,"\n");
5016: }
5017: }
5018: }
5019: } /* end mle=-2 */
1.226 brouard 5020: dateintmean=dateintsum/k2cpt;
1.296 brouard 5021: date2dmy(dateintmean,&jintmean,&mintmean,&aintmean);
1.240 brouard 5022:
1.226 brouard 5023: fclose(ficresp);
5024: fclose(ficresphtm);
5025: fclose(ficresphtmfr);
1.283 brouard 5026: free_vector(idq,1,nqfveff);
1.226 brouard 5027: free_vector(meanq,1,nqfveff);
1.284 brouard 5028: free_vector(stdq,1,nqfveff);
1.226 brouard 5029: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 5030: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
5031: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 5032: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 5033: free_vector(pospropt,1,nlstate);
5034: free_vector(posprop,1,nlstate);
1.251 brouard 5035: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 5036: free_vector(pp,1,nlstate);
5037: /* End of freqsummary */
5038: }
1.126 brouard 5039:
1.268 brouard 5040: /* Simple linear regression */
5041: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
5042:
5043: /* y=a+bx regression */
5044: double sumx = 0.0; /* sum of x */
5045: double sumx2 = 0.0; /* sum of x**2 */
5046: double sumxy = 0.0; /* sum of x * y */
5047: double sumy = 0.0; /* sum of y */
5048: double sumy2 = 0.0; /* sum of y**2 */
5049: double sume2 = 0.0; /* sum of square or residuals */
5050: double yhat;
5051:
5052: double denom=0;
5053: int i;
5054: int ne=*no;
5055:
5056: for ( i=ifi, ne=0;i<=ila;i++) {
5057: if(!isfinite(x[i]) || !isfinite(y[i])){
5058: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5059: continue;
5060: }
5061: ne=ne+1;
5062: sumx += x[i];
5063: sumx2 += x[i]*x[i];
5064: sumxy += x[i] * y[i];
5065: sumy += y[i];
5066: sumy2 += y[i]*y[i];
5067: denom = (ne * sumx2 - sumx*sumx);
5068: /* 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); */
5069: }
5070:
5071: denom = (ne * sumx2 - sumx*sumx);
5072: if (denom == 0) {
5073: // vertical, slope m is infinity
5074: *b = INFINITY;
5075: *a = 0;
5076: if (r) *r = 0;
5077: return 1;
5078: }
5079:
5080: *b = (ne * sumxy - sumx * sumy) / denom;
5081: *a = (sumy * sumx2 - sumx * sumxy) / denom;
5082: if (r!=NULL) {
5083: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
5084: sqrt((sumx2 - sumx*sumx/ne) *
5085: (sumy2 - sumy*sumy/ne));
5086: }
5087: *no=ne;
5088: for ( i=ifi, ne=0;i<=ila;i++) {
5089: if(!isfinite(x[i]) || !isfinite(y[i])){
5090: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5091: continue;
5092: }
5093: ne=ne+1;
5094: yhat = y[i] - *a -*b* x[i];
5095: sume2 += yhat * yhat ;
5096:
5097: denom = (ne * sumx2 - sumx*sumx);
5098: /* 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); */
5099: }
5100: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
5101: *sa= *sb * sqrt(sumx2/ne);
5102:
5103: return 0;
5104: }
5105:
1.126 brouard 5106: /************ Prevalence ********************/
1.227 brouard 5107: 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)
5108: {
5109: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
5110: in each health status at the date of interview (if between dateprev1 and dateprev2).
5111: We still use firstpass and lastpass as another selection.
5112: */
1.126 brouard 5113:
1.227 brouard 5114: int i, m, jk, j1, bool, z1,j, iv;
5115: int mi; /* Effective wave */
5116: int iage;
5117: double agebegin, ageend;
5118:
5119: double **prop;
5120: double posprop;
5121: double y2; /* in fractional years */
5122: int iagemin, iagemax;
5123: int first; /** to stop verbosity which is redirected to log file */
5124:
5125: iagemin= (int) agemin;
5126: iagemax= (int) agemax;
5127: /*pp=vector(1,nlstate);*/
1.251 brouard 5128: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5129: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
5130: j1=0;
1.222 brouard 5131:
1.227 brouard 5132: /*j=cptcoveff;*/
5133: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 5134:
1.288 brouard 5135: first=0;
1.227 brouard 5136: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of covariate */
5137: for (i=1; i<=nlstate; i++)
1.251 brouard 5138: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 5139: prop[i][iage]=0.0;
5140: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
5141: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
5142: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
5143:
5144: for (i=1; i<=imx; i++) { /* Each individual */
5145: bool=1;
5146: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
5147: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
5148: m=mw[mi][i];
5149: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
5150: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
5151: for (z1=1; z1<=cptcoveff; z1++){
5152: if( Fixed[Tmodelind[z1]]==1){
5153: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
5154: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality */
5155: bool=0;
5156: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
5157: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
5158: bool=0;
5159: }
5160: }
5161: if(bool==1){ /* Otherwise we skip that wave/person */
5162: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
5163: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
5164: if(m >=firstpass && m <=lastpass){
5165: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
5166: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
5167: if(agev[m][i]==0) agev[m][i]=iagemax+1;
5168: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 5169: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 5170: 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);
5171: exit(1);
5172: }
5173: if (s[m][i]>0 && s[m][i]<=nlstate) {
5174: /*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]]);*/
5175: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
5176: prop[s[m][i]][iagemax+3] += weight[i];
5177: } /* end valid statuses */
5178: } /* end selection of dates */
5179: } /* end selection of waves */
5180: } /* end bool */
5181: } /* end wave */
5182: } /* end individual */
5183: for(i=iagemin; i <= iagemax+3; i++){
5184: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
5185: posprop += prop[jk][i];
5186: }
5187:
5188: for(jk=1; jk <=nlstate ; jk++){
5189: if( i <= iagemax){
5190: if(posprop>=1.e-5){
5191: probs[i][jk][j1]= prop[jk][i]/posprop;
5192: } else{
1.288 brouard 5193: if(!first){
5194: first=1;
1.266 brouard 5195: 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]);
5196: }else{
1.288 brouard 5197: 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 5198: }
5199: }
5200: }
5201: }/* end jk */
5202: }/* end i */
1.222 brouard 5203: /*} *//* end i1 */
1.227 brouard 5204: } /* end j1 */
1.222 brouard 5205:
1.227 brouard 5206: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
5207: /*free_vector(pp,1,nlstate);*/
1.251 brouard 5208: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5209: } /* End of prevalence */
1.126 brouard 5210:
5211: /************* Waves Concatenation ***************/
5212:
5213: 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)
5214: {
1.298 brouard 5215: /* 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 5216: Death is a valid wave (if date is known).
5217: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
5218: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
1.298 brouard 5219: and mw[mi+1][i]. dh depends on stepm. s[m][i] exists for any wave from firstpass to lastpass
1.227 brouard 5220: */
1.126 brouard 5221:
1.224 brouard 5222: int i=0, mi=0, m=0, mli=0;
1.126 brouard 5223: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
5224: double sum=0., jmean=0.;*/
1.224 brouard 5225: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 5226: int j, k=0,jk, ju, jl;
5227: double sum=0.;
5228: first=0;
1.214 brouard 5229: firstwo=0;
1.217 brouard 5230: firsthree=0;
1.218 brouard 5231: firstfour=0;
1.164 brouard 5232: jmin=100000;
1.126 brouard 5233: jmax=-1;
5234: jmean=0.;
1.224 brouard 5235:
5236: /* Treating live states */
1.214 brouard 5237: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 5238: mi=0; /* First valid wave */
1.227 brouard 5239: mli=0; /* Last valid wave */
1.126 brouard 5240: m=firstpass;
1.214 brouard 5241: while(s[m][i] <= nlstate){ /* a live state */
1.227 brouard 5242: 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 */
5243: mli=m-1;/* mw[++mi][i]=m-1; */
5244: }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 */
5245: mw[++mi][i]=m;
5246: mli=m;
1.224 brouard 5247: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
5248: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 5249: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 5250: }
1.227 brouard 5251: else{ /* m >= lastpass, eventual special issue with warning */
1.224 brouard 5252: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 5253: break;
1.224 brouard 5254: #else
1.227 brouard 5255: if(s[m][i]==-1 && (int) andc[i] == 9999 && (int)anint[m][i] != 9999){
5256: if(firsthree == 0){
1.262 brouard 5257: 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 5258: firsthree=1;
5259: }
1.262 brouard 5260: 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 5261: mw[++mi][i]=m;
5262: mli=m;
5263: }
5264: if(s[m][i]==-2){ /* Vital status is really unknown */
5265: nbwarn++;
5266: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified? */
5267: 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);
5268: 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);
5269: }
5270: break;
5271: }
5272: break;
1.224 brouard 5273: #endif
1.227 brouard 5274: }/* End m >= lastpass */
1.126 brouard 5275: }/* end while */
1.224 brouard 5276:
1.227 brouard 5277: /* 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 5278: /* After last pass */
1.224 brouard 5279: /* Treating death states */
1.214 brouard 5280: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 5281: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
5282: /* } */
1.126 brouard 5283: mi++; /* Death is another wave */
5284: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 5285: /* Only death is a correct wave */
1.126 brouard 5286: mw[mi][i]=m;
1.257 brouard 5287: } /* else not in a death state */
1.224 brouard 5288: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 5289: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 5290: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.227 brouard 5291: 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 */
5292: nbwarn++;
5293: if(firstfiv==0){
5294: 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 );
5295: firstfiv=1;
5296: }else{
5297: 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 );
5298: }
5299: }else{ /* Death occured afer last wave potential bias */
5300: nberr++;
5301: if(firstwo==0){
1.257 brouard 5302: 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 5303: firstwo=1;
5304: }
1.257 brouard 5305: 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 5306: }
1.257 brouard 5307: }else{ /* if date of interview is unknown */
1.227 brouard 5308: /* death is known but not confirmed by death status at any wave */
5309: if(firstfour==0){
5310: 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 );
5311: firstfour=1;
5312: }
5313: 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 5314: }
1.224 brouard 5315: } /* end if date of death is known */
5316: #endif
5317: wav[i]=mi; /* mi should be the last effective wave (or mli) */
5318: /* wav[i]=mw[mi][i]; */
1.126 brouard 5319: if(mi==0){
5320: nbwarn++;
5321: if(first==0){
1.227 brouard 5322: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
5323: first=1;
1.126 brouard 5324: }
5325: if(first==1){
1.227 brouard 5326: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 5327: }
5328: } /* end mi==0 */
5329: } /* End individuals */
1.214 brouard 5330: /* wav and mw are no more changed */
1.223 brouard 5331:
1.214 brouard 5332:
1.126 brouard 5333: for(i=1; i<=imx; i++){
5334: for(mi=1; mi<wav[i];mi++){
5335: if (stepm <=0)
1.227 brouard 5336: dh[mi][i]=1;
1.126 brouard 5337: else{
1.260 brouard 5338: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 5339: if (agedc[i] < 2*AGESUP) {
5340: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
5341: if(j==0) j=1; /* Survives at least one month after exam */
5342: else if(j<0){
5343: nberr++;
5344: 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]);
5345: j=1; /* Temporary Dangerous patch */
5346: 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);
5347: 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]);
5348: 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);
5349: }
5350: k=k+1;
5351: if (j >= jmax){
5352: jmax=j;
5353: ijmax=i;
5354: }
5355: if (j <= jmin){
5356: jmin=j;
5357: ijmin=i;
5358: }
5359: sum=sum+j;
5360: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
5361: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
5362: }
5363: }
5364: else{
5365: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 5366: /* 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 5367:
1.227 brouard 5368: k=k+1;
5369: if (j >= jmax) {
5370: jmax=j;
5371: ijmax=i;
5372: }
5373: else if (j <= jmin){
5374: jmin=j;
5375: ijmin=i;
5376: }
5377: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
5378: /*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]);*/
5379: if(j<0){
5380: nberr++;
5381: 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]);
5382: 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]);
5383: }
5384: sum=sum+j;
5385: }
5386: jk= j/stepm;
5387: jl= j -jk*stepm;
5388: ju= j -(jk+1)*stepm;
5389: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
5390: if(jl==0){
5391: dh[mi][i]=jk;
5392: bh[mi][i]=0;
5393: }else{ /* We want a negative bias in order to only have interpolation ie
5394: * to avoid the price of an extra matrix product in likelihood */
5395: dh[mi][i]=jk+1;
5396: bh[mi][i]=ju;
5397: }
5398: }else{
5399: if(jl <= -ju){
5400: dh[mi][i]=jk;
5401: bh[mi][i]=jl; /* bias is positive if real duration
5402: * is higher than the multiple of stepm and negative otherwise.
5403: */
5404: }
5405: else{
5406: dh[mi][i]=jk+1;
5407: bh[mi][i]=ju;
5408: }
5409: if(dh[mi][i]==0){
5410: dh[mi][i]=1; /* At least one step */
5411: bh[mi][i]=ju; /* At least one step */
5412: /* 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);*/
5413: }
5414: } /* end if mle */
1.126 brouard 5415: }
5416: } /* end wave */
5417: }
5418: jmean=sum/k;
5419: 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 5420: 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 5421: }
1.126 brouard 5422:
5423: /*********** Tricode ****************************/
1.220 brouard 5424: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 5425: {
5426: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
5427: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
5428: * Boring subroutine which should only output nbcode[Tvar[j]][k]
5429: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
5430: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
5431: */
1.130 brouard 5432:
1.242 brouard 5433: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
5434: int modmaxcovj=0; /* Modality max of covariates j */
5435: int cptcode=0; /* Modality max of covariates j */
5436: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 5437:
5438:
1.242 brouard 5439: /* cptcoveff=0; */
5440: /* *cptcov=0; */
1.126 brouard 5441:
1.242 brouard 5442: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.285 brouard 5443: for (k=1; k <= maxncov; k++)
5444: for(j=1; j<=2; j++)
5445: nbcode[k][j]=0; /* Valgrind */
1.126 brouard 5446:
1.242 brouard 5447: /* Loop on covariates without age and products and no quantitative variable */
5448: for (k=1; k<=cptcovt; k++) { /* From model V1 + V2*age + V3 + V3*V4 keeps V1 + V3 = 2 only */
5449: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
5450: if(Dummy[k]==0 && Typevar[k] !=1){ /* Dummy covariate and not age product */
5451: switch(Fixed[k]) {
5452: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
5453: 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*/
5454: ij=(int)(covar[Tvar[k]][i]);
5455: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
5456: * If product of Vn*Vm, still boolean *:
5457: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
5458: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
5459: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
5460: modality of the nth covariate of individual i. */
5461: if (ij > modmaxcovj)
5462: modmaxcovj=ij;
5463: else if (ij < modmincovj)
5464: modmincovj=ij;
1.287 brouard 5465: if (ij <0 || ij >1 ){
5466: printf("Information, IMaCh doesn't treat covariate with missing values (-1), individual %d will be skipped.\n",i);
5467: fprintf(ficlog,"Information, currently IMaCh doesn't treat covariate with missing values (-1), individual %d will be skipped.\n",i);
5468: }
5469: if ((ij < -1) || (ij > NCOVMAX)){
1.242 brouard 5470: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
5471: exit(1);
5472: }else
5473: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
5474: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
5475: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
5476: /* getting the maximum value of the modality of the covariate
5477: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
5478: female ies 1, then modmaxcovj=1.
5479: */
5480: } /* end for loop on individuals i */
5481: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5482: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5483: cptcode=modmaxcovj;
5484: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
5485: /*for (i=0; i<=cptcode; i++) {*/
5486: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
5487: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5488: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5489: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
5490: if( j != -1){
5491: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
5492: covariate for which somebody answered excluding
5493: undefined. Usually 2: 0 and 1. */
5494: }
5495: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
5496: covariate for which somebody answered including
5497: undefined. Usually 3: -1, 0 and 1. */
5498: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
5499: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
5500: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 5501:
1.242 brouard 5502: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
5503: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
5504: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
5505: /* modmincovj=3; modmaxcovj = 7; */
5506: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
5507: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
5508: /* defining two dummy variables: variables V1_1 and V1_2.*/
5509: /* nbcode[Tvar[j]][ij]=k; */
5510: /* nbcode[Tvar[j]][1]=0; */
5511: /* nbcode[Tvar[j]][2]=1; */
5512: /* nbcode[Tvar[j]][3]=2; */
5513: /* To be continued (not working yet). */
5514: ij=0; /* ij is similar to i but can jump over null modalities */
1.287 brouard 5515:
5516: /* 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*/
5517: /* Skipping the case of missing values by reducing nbcode to 0 and 1 and not -1, 0, 1 */
5518: /* model=V1+V2+V3, if V2=-1, 0 or 1, then nbcode[2][1]=0 and nbcode[2][2]=1 instead of
5519: * nbcode[2][1]=-1, nbcode[2][2]=0 and nbcode[2][3]=1 */
5520: /*, could be restored in the future */
5521: 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 5522: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
5523: break;
5524: }
5525: ij++;
1.287 brouard 5526: 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 5527: cptcode = ij; /* New max modality for covar j */
5528: } /* end of loop on modality i=-1 to 1 or more */
5529: break;
5530: case 1: /* Testing on varying covariate, could be simple and
5531: * should look at waves or product of fixed *
5532: * varying. No time to test -1, assuming 0 and 1 only */
5533: ij=0;
5534: for(i=0; i<=1;i++){
5535: nbcode[Tvar[k]][++ij]=i;
5536: }
5537: break;
5538: default:
5539: break;
5540: } /* end switch */
5541: } /* end dummy test */
1.287 brouard 5542: } /* 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 5543:
5544: for (k=-1; k< maxncov; k++) Ndum[k]=0;
5545: /* Look at fixed dummy (single or product) covariates to check empty modalities */
5546: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
5547: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
5548: 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 */
5549: 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 */
5550: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
5551: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
5552:
5553: ij=0;
5554: /* for (i=0; i<= maxncov-1; i++) { /\* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) *\/ */
5555: for (k=1; k<= cptcovt; k++) { /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
5556: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
5557: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
5558: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy and non empty in the model */
5559: /* If product not in single variable we don't print results */
5560: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
5561: ++ij;/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, */
5562: 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*/
5563: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
5564: 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 */
5565: if(Fixed[k]!=0)
5566: anyvaryingduminmodel=1;
5567: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
5568: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
5569: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
5570: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
5571: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
5572: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
5573: }
5574: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
5575: /* ij--; */
5576: /* cptcoveff=ij; /\*Number of total covariates*\/ */
5577: *cptcov=ij; /*Number of total real effective covariates: effective
5578: * because they can be excluded from the model and real
5579: * if in the model but excluded because missing values, but how to get k from ij?*/
5580: for(j=ij+1; j<= cptcovt; j++){
5581: Tvaraff[j]=0;
5582: Tmodelind[j]=0;
5583: }
5584: for(j=ntveff+1; j<= cptcovt; j++){
5585: TmodelInvind[j]=0;
5586: }
5587: /* To be sorted */
5588: ;
5589: }
1.126 brouard 5590:
1.145 brouard 5591:
1.126 brouard 5592: /*********** Health Expectancies ****************/
5593:
1.235 brouard 5594: 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 5595:
5596: {
5597: /* Health expectancies, no variances */
1.164 brouard 5598: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 5599: int nhstepma, nstepma; /* Decreasing with age */
5600: double age, agelim, hf;
5601: double ***p3mat;
5602: double eip;
5603:
1.238 brouard 5604: /* pstamp(ficreseij); */
1.126 brouard 5605: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
5606: fprintf(ficreseij,"# Age");
5607: for(i=1; i<=nlstate;i++){
5608: for(j=1; j<=nlstate;j++){
5609: fprintf(ficreseij," e%1d%1d ",i,j);
5610: }
5611: fprintf(ficreseij," e%1d. ",i);
5612: }
5613: fprintf(ficreseij,"\n");
5614:
5615:
5616: if(estepm < stepm){
5617: printf ("Problem %d lower than %d\n",estepm, stepm);
5618: }
5619: else hstepm=estepm;
5620: /* We compute the life expectancy from trapezoids spaced every estepm months
5621: * This is mainly to measure the difference between two models: for example
5622: * if stepm=24 months pijx are given only every 2 years and by summing them
5623: * we are calculating an estimate of the Life Expectancy assuming a linear
5624: * progression in between and thus overestimating or underestimating according
5625: * to the curvature of the survival function. If, for the same date, we
5626: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5627: * to compare the new estimate of Life expectancy with the same linear
5628: * hypothesis. A more precise result, taking into account a more precise
5629: * curvature will be obtained if estepm is as small as stepm. */
5630:
5631: /* For example we decided to compute the life expectancy with the smallest unit */
5632: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5633: nhstepm is the number of hstepm from age to agelim
5634: nstepm is the number of stepm from age to agelin.
1.270 brouard 5635: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 5636: and note for a fixed period like estepm months */
5637: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5638: survival function given by stepm (the optimization length). Unfortunately it
5639: means that if the survival funtion is printed only each two years of age and if
5640: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5641: results. So we changed our mind and took the option of the best precision.
5642: */
5643: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5644:
5645: agelim=AGESUP;
5646: /* If stepm=6 months */
5647: /* Computed by stepm unit matrices, product of hstepm matrices, stored
5648: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
5649:
5650: /* nhstepm age range expressed in number of stepm */
5651: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5652: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5653: /* if (stepm >= YEARM) hstepm=1;*/
5654: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5655: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5656:
5657: for (age=bage; age<=fage; age ++){
5658: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5659: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5660: /* if (stepm >= YEARM) hstepm=1;*/
5661: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
5662:
5663: /* If stepm=6 months */
5664: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5665: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5666:
1.235 brouard 5667: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 5668:
5669: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
5670:
5671: printf("%d|",(int)age);fflush(stdout);
5672: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5673:
5674: /* Computing expectancies */
5675: for(i=1; i<=nlstate;i++)
5676: for(j=1; j<=nlstate;j++)
5677: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5678: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
5679:
5680: /* 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]);*/
5681:
5682: }
5683:
5684: fprintf(ficreseij,"%3.0f",age );
5685: for(i=1; i<=nlstate;i++){
5686: eip=0;
5687: for(j=1; j<=nlstate;j++){
5688: eip +=eij[i][j][(int)age];
5689: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
5690: }
5691: fprintf(ficreseij,"%9.4f", eip );
5692: }
5693: fprintf(ficreseij,"\n");
5694:
5695: }
5696: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5697: printf("\n");
5698: fprintf(ficlog,"\n");
5699:
5700: }
5701:
1.235 brouard 5702: 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 5703:
5704: {
5705: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 5706: to initial status i, ei. .
1.126 brouard 5707: */
5708: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
5709: int nhstepma, nstepma; /* Decreasing with age */
5710: double age, agelim, hf;
5711: double ***p3matp, ***p3matm, ***varhe;
5712: double **dnewm,**doldm;
5713: double *xp, *xm;
5714: double **gp, **gm;
5715: double ***gradg, ***trgradg;
5716: int theta;
5717:
5718: double eip, vip;
5719:
5720: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
5721: xp=vector(1,npar);
5722: xm=vector(1,npar);
5723: dnewm=matrix(1,nlstate*nlstate,1,npar);
5724: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
5725:
5726: pstamp(ficresstdeij);
5727: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
5728: fprintf(ficresstdeij,"# Age");
5729: for(i=1; i<=nlstate;i++){
5730: for(j=1; j<=nlstate;j++)
5731: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
5732: fprintf(ficresstdeij," e%1d. ",i);
5733: }
5734: fprintf(ficresstdeij,"\n");
5735:
5736: pstamp(ficrescveij);
5737: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
5738: fprintf(ficrescveij,"# Age");
5739: for(i=1; i<=nlstate;i++)
5740: for(j=1; j<=nlstate;j++){
5741: cptj= (j-1)*nlstate+i;
5742: for(i2=1; i2<=nlstate;i2++)
5743: for(j2=1; j2<=nlstate;j2++){
5744: cptj2= (j2-1)*nlstate+i2;
5745: if(cptj2 <= cptj)
5746: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
5747: }
5748: }
5749: fprintf(ficrescveij,"\n");
5750:
5751: if(estepm < stepm){
5752: printf ("Problem %d lower than %d\n",estepm, stepm);
5753: }
5754: else hstepm=estepm;
5755: /* We compute the life expectancy from trapezoids spaced every estepm months
5756: * This is mainly to measure the difference between two models: for example
5757: * if stepm=24 months pijx are given only every 2 years and by summing them
5758: * we are calculating an estimate of the Life Expectancy assuming a linear
5759: * progression in between and thus overestimating or underestimating according
5760: * to the curvature of the survival function. If, for the same date, we
5761: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5762: * to compare the new estimate of Life expectancy with the same linear
5763: * hypothesis. A more precise result, taking into account a more precise
5764: * curvature will be obtained if estepm is as small as stepm. */
5765:
5766: /* For example we decided to compute the life expectancy with the smallest unit */
5767: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5768: nhstepm is the number of hstepm from age to agelim
5769: nstepm is the number of stepm from age to agelin.
5770: Look at hpijx to understand the reason of that which relies in memory size
5771: and note for a fixed period like estepm months */
5772: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5773: survival function given by stepm (the optimization length). Unfortunately it
5774: means that if the survival funtion is printed only each two years of age and if
5775: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5776: results. So we changed our mind and took the option of the best precision.
5777: */
5778: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5779:
5780: /* If stepm=6 months */
5781: /* nhstepm age range expressed in number of stepm */
5782: agelim=AGESUP;
5783: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
5784: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5785: /* if (stepm >= YEARM) hstepm=1;*/
5786: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5787:
5788: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5789: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5790: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
5791: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
5792: gp=matrix(0,nhstepm,1,nlstate*nlstate);
5793: gm=matrix(0,nhstepm,1,nlstate*nlstate);
5794:
5795: for (age=bage; age<=fage; age ++){
5796: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5797: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5798: /* if (stepm >= YEARM) hstepm=1;*/
5799: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 5800:
1.126 brouard 5801: /* If stepm=6 months */
5802: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5803: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5804:
5805: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 5806:
1.126 brouard 5807: /* Computing Variances of health expectancies */
5808: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
5809: decrease memory allocation */
5810: for(theta=1; theta <=npar; theta++){
5811: for(i=1; i<=npar; i++){
1.222 brouard 5812: xp[i] = x[i] + (i==theta ?delti[theta]:0);
5813: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 5814: }
1.235 brouard 5815: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
5816: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 5817:
1.126 brouard 5818: for(j=1; j<= nlstate; j++){
1.222 brouard 5819: for(i=1; i<=nlstate; i++){
5820: for(h=0; h<=nhstepm-1; h++){
5821: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
5822: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
5823: }
5824: }
1.126 brouard 5825: }
1.218 brouard 5826:
1.126 brouard 5827: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 5828: for(h=0; h<=nhstepm-1; h++){
5829: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
5830: }
1.126 brouard 5831: }/* End theta */
5832:
5833:
5834: for(h=0; h<=nhstepm-1; h++)
5835: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 5836: for(theta=1; theta <=npar; theta++)
5837: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 5838:
1.218 brouard 5839:
1.222 brouard 5840: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 5841: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 5842: varhe[ij][ji][(int)age] =0.;
1.218 brouard 5843:
1.222 brouard 5844: printf("%d|",(int)age);fflush(stdout);
5845: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5846: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 5847: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 5848: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
5849: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
5850: for(ij=1;ij<=nlstate*nlstate;ij++)
5851: for(ji=1;ji<=nlstate*nlstate;ji++)
5852: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 5853: }
5854: }
1.218 brouard 5855:
1.126 brouard 5856: /* Computing expectancies */
1.235 brouard 5857: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 5858: for(i=1; i<=nlstate;i++)
5859: for(j=1; j<=nlstate;j++)
1.222 brouard 5860: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5861: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 5862:
1.222 brouard 5863: /* 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 5864:
1.222 brouard 5865: }
1.269 brouard 5866:
5867: /* Standard deviation of expectancies ij */
1.126 brouard 5868: fprintf(ficresstdeij,"%3.0f",age );
5869: for(i=1; i<=nlstate;i++){
5870: eip=0.;
5871: vip=0.;
5872: for(j=1; j<=nlstate;j++){
1.222 brouard 5873: eip += eij[i][j][(int)age];
5874: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
5875: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
5876: 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 5877: }
5878: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
5879: }
5880: fprintf(ficresstdeij,"\n");
1.218 brouard 5881:
1.269 brouard 5882: /* Variance of expectancies ij */
1.126 brouard 5883: fprintf(ficrescveij,"%3.0f",age );
5884: for(i=1; i<=nlstate;i++)
5885: for(j=1; j<=nlstate;j++){
1.222 brouard 5886: cptj= (j-1)*nlstate+i;
5887: for(i2=1; i2<=nlstate;i2++)
5888: for(j2=1; j2<=nlstate;j2++){
5889: cptj2= (j2-1)*nlstate+i2;
5890: if(cptj2 <= cptj)
5891: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
5892: }
1.126 brouard 5893: }
5894: fprintf(ficrescveij,"\n");
1.218 brouard 5895:
1.126 brouard 5896: }
5897: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
5898: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
5899: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
5900: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
5901: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5902: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5903: printf("\n");
5904: fprintf(ficlog,"\n");
1.218 brouard 5905:
1.126 brouard 5906: free_vector(xm,1,npar);
5907: free_vector(xp,1,npar);
5908: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
5909: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
5910: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
5911: }
1.218 brouard 5912:
1.126 brouard 5913: /************ Variance ******************/
1.235 brouard 5914: 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 5915: {
1.279 brouard 5916: /** Variance of health expectancies
5917: * double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);
5918: * double **newm;
5919: * int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)
5920: */
1.218 brouard 5921:
5922: /* int movingaverage(); */
5923: double **dnewm,**doldm;
5924: double **dnewmp,**doldmp;
5925: int i, j, nhstepm, hstepm, h, nstepm ;
1.288 brouard 5926: int first=0;
1.218 brouard 5927: int k;
5928: double *xp;
1.279 brouard 5929: double **gp, **gm; /**< for var eij */
5930: double ***gradg, ***trgradg; /**< for var eij */
5931: double **gradgp, **trgradgp; /**< for var p point j */
5932: double *gpp, *gmp; /**< for var p point j */
5933: double **varppt; /**< for var p point j nlstate to nlstate+ndeath */
1.218 brouard 5934: double ***p3mat;
5935: double age,agelim, hf;
5936: /* double ***mobaverage; */
5937: int theta;
5938: char digit[4];
5939: char digitp[25];
5940:
5941: char fileresprobmorprev[FILENAMELENGTH];
5942:
5943: if(popbased==1){
5944: if(mobilav!=0)
5945: strcpy(digitp,"-POPULBASED-MOBILAV_");
5946: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
5947: }
5948: else
5949: strcpy(digitp,"-STABLBASED_");
1.126 brouard 5950:
1.218 brouard 5951: /* if (mobilav!=0) { */
5952: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
5953: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
5954: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
5955: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
5956: /* } */
5957: /* } */
5958:
5959: strcpy(fileresprobmorprev,"PRMORPREV-");
5960: sprintf(digit,"%-d",ij);
5961: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
5962: strcat(fileresprobmorprev,digit); /* Tvar to be done */
5963: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
5964: strcat(fileresprobmorprev,fileresu);
5965: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
5966: printf("Problem with resultfile: %s\n", fileresprobmorprev);
5967: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
5968: }
5969: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
5970: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
5971: pstamp(ficresprobmorprev);
5972: 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 5973: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
5974: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
5975: fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
5976: }
5977: for(j=1;j<=cptcoveff;j++)
5978: fprintf(ficresprobmorprev,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,j)]);
5979: fprintf(ficresprobmorprev,"\n");
5980:
1.218 brouard 5981: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
5982: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
5983: fprintf(ficresprobmorprev," p.%-d SE",j);
5984: for(i=1; i<=nlstate;i++)
5985: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
5986: }
5987: fprintf(ficresprobmorprev,"\n");
5988:
5989: fprintf(ficgp,"\n# Routine varevsij");
5990: fprintf(ficgp,"\nunset title \n");
5991: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
5992: 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");
5993: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
1.279 brouard 5994:
1.218 brouard 5995: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
5996: pstamp(ficresvij);
5997: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
5998: if(popbased==1)
5999: 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);
6000: else
6001: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
6002: fprintf(ficresvij,"# Age");
6003: for(i=1; i<=nlstate;i++)
6004: for(j=1; j<=nlstate;j++)
6005: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
6006: fprintf(ficresvij,"\n");
6007:
6008: xp=vector(1,npar);
6009: dnewm=matrix(1,nlstate,1,npar);
6010: doldm=matrix(1,nlstate,1,nlstate);
6011: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
6012: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6013:
6014: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
6015: gpp=vector(nlstate+1,nlstate+ndeath);
6016: gmp=vector(nlstate+1,nlstate+ndeath);
6017: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 6018:
1.218 brouard 6019: if(estepm < stepm){
6020: printf ("Problem %d lower than %d\n",estepm, stepm);
6021: }
6022: else hstepm=estepm;
6023: /* For example we decided to compute the life expectancy with the smallest unit */
6024: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6025: nhstepm is the number of hstepm from age to agelim
6026: nstepm is the number of stepm from age to agelim.
6027: Look at function hpijx to understand why because of memory size limitations,
6028: we decided (b) to get a life expectancy respecting the most precise curvature of the
6029: survival function given by stepm (the optimization length). Unfortunately it
6030: means that if the survival funtion is printed every two years of age and if
6031: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6032: results. So we changed our mind and took the option of the best precision.
6033: */
6034: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6035: agelim = AGESUP;
6036: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6037: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6038: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6039: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6040: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
6041: gp=matrix(0,nhstepm,1,nlstate);
6042: gm=matrix(0,nhstepm,1,nlstate);
6043:
6044:
6045: for(theta=1; theta <=npar; theta++){
6046: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
6047: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6048: }
1.279 brouard 6049: /**< Computes the prevalence limit with parameter theta shifted of delta up to ftolpl precision and
6050: * returns into prlim .
1.288 brouard 6051: */
1.242 brouard 6052: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.279 brouard 6053:
6054: /* If popbased = 1 we use crossection prevalences. Previous step is useless but prlim is created */
1.218 brouard 6055: if (popbased==1) {
6056: if(mobilav ==0){
6057: for(i=1; i<=nlstate;i++)
6058: prlim[i][i]=probs[(int)age][i][ij];
6059: }else{ /* mobilav */
6060: for(i=1; i<=nlstate;i++)
6061: prlim[i][i]=mobaverage[(int)age][i][ij];
6062: }
6063: }
1.295 brouard 6064: /**< Computes the shifted transition matrix \f$ {}{h}_p^{ij}x\f$ at horizon h.
1.279 brouard 6065: */
6066: 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 6067: /**< 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 6068: * at horizon h in state j including mortality.
6069: */
1.218 brouard 6070: for(j=1; j<= nlstate; j++){
6071: for(h=0; h<=nhstepm; h++){
6072: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
6073: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
6074: }
6075: }
1.279 brouard 6076: /* Next for computing shifted+ probability of death (h=1 means
1.218 brouard 6077: computed over hstepm matrices product = hstepm*stepm months)
1.279 brouard 6078: as a weighted average of prlim(i) * p(i,j) p.3=w1*p13 + w2*p23 .
1.218 brouard 6079: */
6080: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6081: for(i=1,gpp[j]=0.; i<= nlstate; i++)
6082: gpp[j] += prlim[i][i]*p3mat[i][j][1];
1.279 brouard 6083: }
6084:
6085: /* Again with minus shift */
1.218 brouard 6086:
6087: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
6088: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 6089:
1.242 brouard 6090: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 6091:
6092: if (popbased==1) {
6093: if(mobilav ==0){
6094: for(i=1; i<=nlstate;i++)
6095: prlim[i][i]=probs[(int)age][i][ij];
6096: }else{ /* mobilav */
6097: for(i=1; i<=nlstate;i++)
6098: prlim[i][i]=mobaverage[(int)age][i][ij];
6099: }
6100: }
6101:
1.235 brouard 6102: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 6103:
6104: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
6105: for(h=0; h<=nhstepm; h++){
6106: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
6107: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
6108: }
6109: }
6110: /* This for computing probability of death (h=1 means
6111: computed over hstepm matrices product = hstepm*stepm months)
6112: as a weighted average of prlim.
6113: */
6114: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6115: for(i=1,gmp[j]=0.; i<= nlstate; i++)
6116: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6117: }
1.279 brouard 6118: /* end shifting computations */
6119:
6120: /**< Computing gradient matrix at horizon h
6121: */
1.218 brouard 6122: for(j=1; j<= nlstate; j++) /* vareij */
6123: for(h=0; h<=nhstepm; h++){
6124: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
6125: }
1.279 brouard 6126: /**< Gradient of overall mortality p.3 (or p.j)
6127: */
6128: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu mortality from j */
1.218 brouard 6129: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
6130: }
6131:
6132: } /* End theta */
1.279 brouard 6133:
6134: /* We got the gradient matrix for each theta and state j */
1.218 brouard 6135: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
6136:
6137: for(h=0; h<=nhstepm; h++) /* veij */
6138: for(j=1; j<=nlstate;j++)
6139: for(theta=1; theta <=npar; theta++)
6140: trgradg[h][j][theta]=gradg[h][theta][j];
6141:
6142: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
6143: for(theta=1; theta <=npar; theta++)
6144: trgradgp[j][theta]=gradgp[theta][j];
1.279 brouard 6145: /**< as well as its transposed matrix
6146: */
1.218 brouard 6147:
6148: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6149: for(i=1;i<=nlstate;i++)
6150: for(j=1;j<=nlstate;j++)
6151: vareij[i][j][(int)age] =0.;
1.279 brouard 6152:
6153: /* Computing trgradg by matcov by gradg at age and summing over h
6154: * and k (nhstepm) formula 15 of article
6155: * Lievre-Brouard-Heathcote
6156: */
6157:
1.218 brouard 6158: for(h=0;h<=nhstepm;h++){
6159: for(k=0;k<=nhstepm;k++){
6160: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
6161: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
6162: for(i=1;i<=nlstate;i++)
6163: for(j=1;j<=nlstate;j++)
6164: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
6165: }
6166: }
6167:
1.279 brouard 6168: /* pptj is p.3 or p.j = trgradgp by cov by gradgp, variance of
6169: * p.j overall mortality formula 49 but computed directly because
6170: * we compute the grad (wix pijx) instead of grad (pijx),even if
6171: * wix is independent of theta.
6172: */
1.218 brouard 6173: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
6174: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
6175: for(j=nlstate+1;j<=nlstate+ndeath;j++)
6176: for(i=nlstate+1;i<=nlstate+ndeath;i++)
6177: varppt[j][i]=doldmp[j][i];
6178: /* end ppptj */
6179: /* x centered again */
6180:
1.242 brouard 6181: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 6182:
6183: if (popbased==1) {
6184: if(mobilav ==0){
6185: for(i=1; i<=nlstate;i++)
6186: prlim[i][i]=probs[(int)age][i][ij];
6187: }else{ /* mobilav */
6188: for(i=1; i<=nlstate;i++)
6189: prlim[i][i]=mobaverage[(int)age][i][ij];
6190: }
6191: }
6192:
6193: /* This for computing probability of death (h=1 means
6194: computed over hstepm (estepm) matrices product = hstepm*stepm months)
6195: as a weighted average of prlim.
6196: */
1.235 brouard 6197: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 6198: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6199: for(i=1,gmp[j]=0.;i<= nlstate; i++)
6200: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6201: }
6202: /* end probability of death */
6203:
6204: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
6205: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6206: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
6207: for(i=1; i<=nlstate;i++){
6208: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
6209: }
6210: }
6211: fprintf(ficresprobmorprev,"\n");
6212:
6213: fprintf(ficresvij,"%.0f ",age );
6214: for(i=1; i<=nlstate;i++)
6215: for(j=1; j<=nlstate;j++){
6216: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
6217: }
6218: fprintf(ficresvij,"\n");
6219: free_matrix(gp,0,nhstepm,1,nlstate);
6220: free_matrix(gm,0,nhstepm,1,nlstate);
6221: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
6222: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
6223: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6224: } /* End age */
6225: free_vector(gpp,nlstate+1,nlstate+ndeath);
6226: free_vector(gmp,nlstate+1,nlstate+ndeath);
6227: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
6228: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
6229: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
6230: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
6231: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
6232: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
6233: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
6234: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
6235: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
6236: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
6237: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
6238: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
6239: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
6240: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
6241: 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);
6242: /* 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 6243: */
1.218 brouard 6244: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
6245: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 6246:
1.218 brouard 6247: free_vector(xp,1,npar);
6248: free_matrix(doldm,1,nlstate,1,nlstate);
6249: free_matrix(dnewm,1,nlstate,1,npar);
6250: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6251: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
6252: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6253: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6254: fclose(ficresprobmorprev);
6255: fflush(ficgp);
6256: fflush(fichtm);
6257: } /* end varevsij */
1.126 brouard 6258:
6259: /************ Variance of prevlim ******************/
1.269 brouard 6260: 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 6261: {
1.205 brouard 6262: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 6263: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 6264:
1.268 brouard 6265: double **dnewmpar,**doldm;
1.126 brouard 6266: int i, j, nhstepm, hstepm;
6267: double *xp;
6268: double *gp, *gm;
6269: double **gradg, **trgradg;
1.208 brouard 6270: double **mgm, **mgp;
1.126 brouard 6271: double age,agelim;
6272: int theta;
6273:
6274: pstamp(ficresvpl);
1.288 brouard 6275: fprintf(ficresvpl,"# Standard deviation of period (forward stable) prevalences \n");
1.241 brouard 6276: fprintf(ficresvpl,"# Age ");
6277: if(nresult >=1)
6278: fprintf(ficresvpl," Result# ");
1.126 brouard 6279: for(i=1; i<=nlstate;i++)
6280: fprintf(ficresvpl," %1d-%1d",i,i);
6281: fprintf(ficresvpl,"\n");
6282:
6283: xp=vector(1,npar);
1.268 brouard 6284: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 6285: doldm=matrix(1,nlstate,1,nlstate);
6286:
6287: hstepm=1*YEARM; /* Every year of age */
6288: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6289: agelim = AGESUP;
6290: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6291: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6292: if (stepm >= YEARM) hstepm=1;
6293: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6294: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 6295: mgp=matrix(1,npar,1,nlstate);
6296: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 6297: gp=vector(1,nlstate);
6298: gm=vector(1,nlstate);
6299:
6300: for(theta=1; theta <=npar; theta++){
6301: for(i=1; i<=npar; i++){ /* Computes gradient */
6302: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6303: }
1.288 brouard 6304: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
6305: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
6306: /* else */
6307: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6308: for(i=1;i<=nlstate;i++){
1.126 brouard 6309: gp[i] = prlim[i][i];
1.208 brouard 6310: mgp[theta][i] = prlim[i][i];
6311: }
1.126 brouard 6312: for(i=1; i<=npar; i++) /* Computes gradient */
6313: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 6314: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
6315: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
6316: /* else */
6317: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6318: for(i=1;i<=nlstate;i++){
1.126 brouard 6319: gm[i] = prlim[i][i];
1.208 brouard 6320: mgm[theta][i] = prlim[i][i];
6321: }
1.126 brouard 6322: for(i=1;i<=nlstate;i++)
6323: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 6324: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 6325: } /* End theta */
6326:
6327: trgradg =matrix(1,nlstate,1,npar);
6328:
6329: for(j=1; j<=nlstate;j++)
6330: for(theta=1; theta <=npar; theta++)
6331: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 6332: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6333: /* printf("\nmgm mgp %d ",(int)age); */
6334: /* for(j=1; j<=nlstate;j++){ */
6335: /* printf(" %d ",j); */
6336: /* for(theta=1; theta <=npar; theta++) */
6337: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6338: /* printf("\n "); */
6339: /* } */
6340: /* } */
6341: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6342: /* printf("\n gradg %d ",(int)age); */
6343: /* for(j=1; j<=nlstate;j++){ */
6344: /* printf("%d ",j); */
6345: /* for(theta=1; theta <=npar; theta++) */
6346: /* printf("%d %lf ",theta,gradg[theta][j]); */
6347: /* printf("\n "); */
6348: /* } */
6349: /* } */
1.126 brouard 6350:
6351: for(i=1;i<=nlstate;i++)
6352: varpl[i][(int)age] =0.;
1.209 brouard 6353: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 brouard 6354: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6355: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6356: }else{
1.268 brouard 6357: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6358: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6359: }
1.126 brouard 6360: for(i=1;i<=nlstate;i++)
6361: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6362:
6363: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 6364: if(nresult >=1)
6365: fprintf(ficresvpl,"%d ",nres );
1.288 brouard 6366: for(i=1; i<=nlstate;i++){
1.126 brouard 6367: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
1.288 brouard 6368: /* for(j=1;j<=nlstate;j++) */
6369: /* fprintf(ficresvpl," %d %.5f ",j,prlim[j][i]); */
6370: }
1.126 brouard 6371: fprintf(ficresvpl,"\n");
6372: free_vector(gp,1,nlstate);
6373: free_vector(gm,1,nlstate);
1.208 brouard 6374: free_matrix(mgm,1,npar,1,nlstate);
6375: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 6376: free_matrix(gradg,1,npar,1,nlstate);
6377: free_matrix(trgradg,1,nlstate,1,npar);
6378: } /* End age */
6379:
6380: free_vector(xp,1,npar);
6381: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 6382: free_matrix(dnewmpar,1,nlstate,1,nlstate);
6383:
6384: }
6385:
6386:
6387: /************ Variance of backprevalence limit ******************/
1.269 brouard 6388: 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 6389: {
6390: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
6391: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
6392:
6393: double **dnewmpar,**doldm;
6394: int i, j, nhstepm, hstepm;
6395: double *xp;
6396: double *gp, *gm;
6397: double **gradg, **trgradg;
6398: double **mgm, **mgp;
6399: double age,agelim;
6400: int theta;
6401:
6402: pstamp(ficresvbl);
6403: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
6404: fprintf(ficresvbl,"# Age ");
6405: if(nresult >=1)
6406: fprintf(ficresvbl," Result# ");
6407: for(i=1; i<=nlstate;i++)
6408: fprintf(ficresvbl," %1d-%1d",i,i);
6409: fprintf(ficresvbl,"\n");
6410:
6411: xp=vector(1,npar);
6412: dnewmpar=matrix(1,nlstate,1,npar);
6413: doldm=matrix(1,nlstate,1,nlstate);
6414:
6415: hstepm=1*YEARM; /* Every year of age */
6416: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6417: agelim = AGEINF;
6418: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
6419: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6420: if (stepm >= YEARM) hstepm=1;
6421: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6422: gradg=matrix(1,npar,1,nlstate);
6423: mgp=matrix(1,npar,1,nlstate);
6424: mgm=matrix(1,npar,1,nlstate);
6425: gp=vector(1,nlstate);
6426: gm=vector(1,nlstate);
6427:
6428: for(theta=1; theta <=npar; theta++){
6429: for(i=1; i<=npar; i++){ /* Computes gradient */
6430: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6431: }
6432: if(mobilavproj > 0 )
6433: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6434: else
6435: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6436: for(i=1;i<=nlstate;i++){
6437: gp[i] = bprlim[i][i];
6438: mgp[theta][i] = bprlim[i][i];
6439: }
6440: for(i=1; i<=npar; i++) /* Computes gradient */
6441: xp[i] = x[i] - (i==theta ?delti[theta]:0);
6442: if(mobilavproj > 0 )
6443: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6444: else
6445: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6446: for(i=1;i<=nlstate;i++){
6447: gm[i] = bprlim[i][i];
6448: mgm[theta][i] = bprlim[i][i];
6449: }
6450: for(i=1;i<=nlstate;i++)
6451: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
6452: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
6453: } /* End theta */
6454:
6455: trgradg =matrix(1,nlstate,1,npar);
6456:
6457: for(j=1; j<=nlstate;j++)
6458: for(theta=1; theta <=npar; theta++)
6459: trgradg[j][theta]=gradg[theta][j];
6460: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6461: /* printf("\nmgm mgp %d ",(int)age); */
6462: /* for(j=1; j<=nlstate;j++){ */
6463: /* printf(" %d ",j); */
6464: /* for(theta=1; theta <=npar; theta++) */
6465: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6466: /* printf("\n "); */
6467: /* } */
6468: /* } */
6469: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6470: /* printf("\n gradg %d ",(int)age); */
6471: /* for(j=1; j<=nlstate;j++){ */
6472: /* printf("%d ",j); */
6473: /* for(theta=1; theta <=npar; theta++) */
6474: /* printf("%d %lf ",theta,gradg[theta][j]); */
6475: /* printf("\n "); */
6476: /* } */
6477: /* } */
6478:
6479: for(i=1;i<=nlstate;i++)
6480: varbpl[i][(int)age] =0.;
6481: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
6482: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6483: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6484: }else{
6485: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6486: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6487: }
6488: for(i=1;i<=nlstate;i++)
6489: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6490:
6491: fprintf(ficresvbl,"%.0f ",age );
6492: if(nresult >=1)
6493: fprintf(ficresvbl,"%d ",nres );
6494: for(i=1; i<=nlstate;i++)
6495: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
6496: fprintf(ficresvbl,"\n");
6497: free_vector(gp,1,nlstate);
6498: free_vector(gm,1,nlstate);
6499: free_matrix(mgm,1,npar,1,nlstate);
6500: free_matrix(mgp,1,npar,1,nlstate);
6501: free_matrix(gradg,1,npar,1,nlstate);
6502: free_matrix(trgradg,1,nlstate,1,npar);
6503: } /* End age */
6504:
6505: free_vector(xp,1,npar);
6506: free_matrix(doldm,1,nlstate,1,npar);
6507: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 6508:
6509: }
6510:
6511: /************ Variance of one-step probabilities ******************/
6512: 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 6513: {
6514: int i, j=0, k1, l1, tj;
6515: int k2, l2, j1, z1;
6516: int k=0, l;
6517: int first=1, first1, first2;
6518: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
6519: double **dnewm,**doldm;
6520: double *xp;
6521: double *gp, *gm;
6522: double **gradg, **trgradg;
6523: double **mu;
6524: double age, cov[NCOVMAX+1];
6525: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
6526: int theta;
6527: char fileresprob[FILENAMELENGTH];
6528: char fileresprobcov[FILENAMELENGTH];
6529: char fileresprobcor[FILENAMELENGTH];
6530: double ***varpij;
6531:
6532: strcpy(fileresprob,"PROB_");
6533: strcat(fileresprob,fileres);
6534: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
6535: printf("Problem with resultfile: %s\n", fileresprob);
6536: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
6537: }
6538: strcpy(fileresprobcov,"PROBCOV_");
6539: strcat(fileresprobcov,fileresu);
6540: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
6541: printf("Problem with resultfile: %s\n", fileresprobcov);
6542: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
6543: }
6544: strcpy(fileresprobcor,"PROBCOR_");
6545: strcat(fileresprobcor,fileresu);
6546: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
6547: printf("Problem with resultfile: %s\n", fileresprobcor);
6548: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
6549: }
6550: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6551: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6552: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6553: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6554: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6555: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6556: pstamp(ficresprob);
6557: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
6558: fprintf(ficresprob,"# Age");
6559: pstamp(ficresprobcov);
6560: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
6561: fprintf(ficresprobcov,"# Age");
6562: pstamp(ficresprobcor);
6563: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
6564: fprintf(ficresprobcor,"# Age");
1.126 brouard 6565:
6566:
1.222 brouard 6567: for(i=1; i<=nlstate;i++)
6568: for(j=1; j<=(nlstate+ndeath);j++){
6569: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
6570: fprintf(ficresprobcov," p%1d-%1d ",i,j);
6571: fprintf(ficresprobcor," p%1d-%1d ",i,j);
6572: }
6573: /* fprintf(ficresprob,"\n");
6574: fprintf(ficresprobcov,"\n");
6575: fprintf(ficresprobcor,"\n");
6576: */
6577: xp=vector(1,npar);
6578: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6579: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6580: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
6581: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
6582: first=1;
6583: fprintf(ficgp,"\n# Routine varprob");
6584: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
6585: fprintf(fichtm,"\n");
6586:
1.288 brouard 6587: 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 6588: 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);
6589: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 6590: and drawn. It helps understanding how is the covariance between two incidences.\
6591: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 6592: 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 6593: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
6594: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
6595: standard deviations wide on each axis. <br>\
6596: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
6597: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
6598: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
6599:
1.222 brouard 6600: cov[1]=1;
6601: /* tj=cptcoveff; */
1.225 brouard 6602: tj = (int) pow(2,cptcoveff);
1.222 brouard 6603: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
6604: j1=0;
1.224 brouard 6605: for(j1=1; j1<=tj;j1++){ /* For each valid combination of covariates or only once*/
1.222 brouard 6606: if (cptcovn>0) {
6607: fprintf(ficresprob, "\n#********** Variable ");
1.225 brouard 6608: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6609: fprintf(ficresprob, "**********\n#\n");
6610: fprintf(ficresprobcov, "\n#********** Variable ");
1.225 brouard 6611: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcov, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6612: fprintf(ficresprobcov, "**********\n#\n");
1.220 brouard 6613:
1.222 brouard 6614: fprintf(ficgp, "\n#********** Variable ");
1.225 brouard 6615: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficgp, " V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6616: fprintf(ficgp, "**********\n#\n");
1.220 brouard 6617:
6618:
1.222 brouard 6619: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
1.225 brouard 6620: for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtm, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6621: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 6622:
1.222 brouard 6623: fprintf(ficresprobcor, "\n#********** Variable ");
1.225 brouard 6624: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcor, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6625: fprintf(ficresprobcor, "**********\n#");
6626: if(invalidvarcomb[j1]){
6627: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
6628: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
6629: continue;
6630: }
6631: }
6632: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
6633: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6634: gp=vector(1,(nlstate)*(nlstate+ndeath));
6635: gm=vector(1,(nlstate)*(nlstate+ndeath));
6636: for (age=bage; age<=fage; age ++){
6637: cov[2]=age;
6638: if(nagesqr==1)
6639: cov[3]= age*age;
6640: for (k=1; k<=cptcovn;k++) {
6641: cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)];
6642: /*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*//* j1 1 2 3 4
6643: * 1 1 1 1 1
6644: * 2 2 1 1 1
6645: * 3 1 2 1 1
6646: */
6647: /* nbcode[1][1]=0 nbcode[1][2]=1;*/
6648: }
6649: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; */
6650: for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
6651: for (k=1; k<=cptcovprod;k++)
6652: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.220 brouard 6653:
6654:
1.222 brouard 6655: for(theta=1; theta <=npar; theta++){
6656: for(i=1; i<=npar; i++)
6657: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 6658:
1.222 brouard 6659: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 6660:
1.222 brouard 6661: k=0;
6662: for(i=1; i<= (nlstate); i++){
6663: for(j=1; j<=(nlstate+ndeath);j++){
6664: k=k+1;
6665: gp[k]=pmmij[i][j];
6666: }
6667: }
1.220 brouard 6668:
1.222 brouard 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);
6673: k=0;
6674: for(i=1; i<=(nlstate); i++){
6675: for(j=1; j<=(nlstate+ndeath);j++){
6676: k=k+1;
6677: gm[k]=pmmij[i][j];
6678: }
6679: }
1.220 brouard 6680:
1.222 brouard 6681: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
6682: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
6683: }
1.126 brouard 6684:
1.222 brouard 6685: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
6686: for(theta=1; theta <=npar; theta++)
6687: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 6688:
1.222 brouard 6689: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
6690: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 6691:
1.222 brouard 6692: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 6693:
1.222 brouard 6694: k=0;
6695: for(i=1; i<=(nlstate); i++){
6696: for(j=1; j<=(nlstate+ndeath);j++){
6697: k=k+1;
6698: mu[k][(int) age]=pmmij[i][j];
6699: }
6700: }
6701: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
6702: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
6703: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 6704:
1.222 brouard 6705: /*printf("\n%d ",(int)age);
6706: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6707: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6708: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6709: }*/
1.220 brouard 6710:
1.222 brouard 6711: fprintf(ficresprob,"\n%d ",(int)age);
6712: fprintf(ficresprobcov,"\n%d ",(int)age);
6713: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 6714:
1.222 brouard 6715: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
6716: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
6717: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6718: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
6719: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
6720: }
6721: i=0;
6722: for (k=1; k<=(nlstate);k++){
6723: for (l=1; l<=(nlstate+ndeath);l++){
6724: i++;
6725: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
6726: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
6727: for (j=1; j<=i;j++){
6728: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
6729: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
6730: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
6731: }
6732: }
6733: }/* end of loop for state */
6734: } /* end of loop for age */
6735: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
6736: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
6737: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
6738: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
6739:
6740: /* Confidence intervalle of pij */
6741: /*
6742: fprintf(ficgp,"\nunset parametric;unset label");
6743: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
6744: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
6745: 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);
6746: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
6747: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
6748: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
6749: */
6750:
6751: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
6752: first1=1;first2=2;
6753: for (k2=1; k2<=(nlstate);k2++){
6754: for (l2=1; l2<=(nlstate+ndeath);l2++){
6755: if(l2==k2) continue;
6756: j=(k2-1)*(nlstate+ndeath)+l2;
6757: for (k1=1; k1<=(nlstate);k1++){
6758: for (l1=1; l1<=(nlstate+ndeath);l1++){
6759: if(l1==k1) continue;
6760: i=(k1-1)*(nlstate+ndeath)+l1;
6761: if(i<=j) continue;
6762: for (age=bage; age<=fage; age ++){
6763: if ((int)age %5==0){
6764: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
6765: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
6766: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
6767: mu1=mu[i][(int) age]/stepm*YEARM ;
6768: mu2=mu[j][(int) age]/stepm*YEARM;
6769: c12=cv12/sqrt(v1*v2);
6770: /* Computing eigen value of matrix of covariance */
6771: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6772: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6773: if ((lc2 <0) || (lc1 <0) ){
6774: if(first2==1){
6775: first1=0;
6776: 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);
6777: }
6778: 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);
6779: /* lc1=fabs(lc1); */ /* If we want to have them positive */
6780: /* lc2=fabs(lc2); */
6781: }
1.220 brouard 6782:
1.222 brouard 6783: /* Eigen vectors */
1.280 brouard 6784: if(1+(v1-lc1)*(v1-lc1)/cv12/cv12 <1.e-5){
6785: printf(" Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
6786: fprintf(ficlog," Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
6787: v11=(1./sqrt(fabs(1+(v1-lc1)*(v1-lc1)/cv12/cv12)));
6788: }else
6789: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
1.222 brouard 6790: /*v21=sqrt(1.-v11*v11); *//* error */
6791: v21=(lc1-v1)/cv12*v11;
6792: v12=-v21;
6793: v22=v11;
6794: tnalp=v21/v11;
6795: if(first1==1){
6796: first1=0;
6797: 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);
6798: }
6799: 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);
6800: /*printf(fignu*/
6801: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
6802: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
6803: if(first==1){
6804: first=0;
6805: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
6806: fprintf(ficgp,"\nset parametric;unset label");
6807: 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);
6808: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 6809: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 6810: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 6811: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 6812: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
6813: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6814: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6815: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
6816: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6817: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
6818: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
6819: 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 6820: mu1,std,v11,sqrt(fabs(lc1)),v12,sqrt(fabs(lc2)), \
6821: mu2,std,v21,sqrt(fabs(lc1)),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 6822: }else{
6823: first=0;
6824: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
6825: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
6826: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
6827: 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 6828: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
6829: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 6830: }/* if first */
6831: } /* age mod 5 */
6832: } /* end loop age */
6833: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6834: first=1;
6835: } /*l12 */
6836: } /* k12 */
6837: } /*l1 */
6838: }/* k1 */
6839: } /* loop on combination of covariates j1 */
6840: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
6841: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
6842: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6843: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
6844: free_vector(xp,1,npar);
6845: fclose(ficresprob);
6846: fclose(ficresprobcov);
6847: fclose(ficresprobcor);
6848: fflush(ficgp);
6849: fflush(fichtmcov);
6850: }
1.126 brouard 6851:
6852:
6853: /******************* Printing html file ***********/
1.201 brouard 6854: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 6855: int lastpass, int stepm, int weightopt, char model[],\
6856: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.296 brouard 6857: int popforecast, int mobilav, int prevfcast, int mobilavproj, int prevbcast, int estepm , \
6858: double jprev1, double mprev1,double anprev1, double dateprev1, double dateprojd, double dateback1, \
6859: double jprev2, double mprev2,double anprev2, double dateprev2, double dateprojf, double dateback2){
1.237 brouard 6860: int jj1, k1, i1, cpt, k4, nres;
1.126 brouard 6861:
6862: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
6863: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
6864: </ul>");
1.237 brouard 6865: fprintf(fichtm,"<ul><li> model=1+age+%s\n \
6866: </ul>", model);
1.214 brouard 6867: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
6868: 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",
6869: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
6870: 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 6871: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
6872: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 6873: fprintf(fichtm,"\
6874: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 6875: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 6876: fprintf(fichtm,"\
1.217 brouard 6877: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
6878: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
6879: fprintf(fichtm,"\
1.288 brouard 6880: - Period (forward) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 6881: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 6882: fprintf(fichtm,"\
1.288 brouard 6883: - Backward prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.217 brouard 6884: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
6885: fprintf(fichtm,"\
1.211 brouard 6886: - (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 6887: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 6888: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 6889: if(prevfcast==1){
6890: fprintf(fichtm,"\
6891: - Prevalence projections by age and states: \
1.201 brouard 6892: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 6893: }
1.126 brouard 6894:
6895:
1.225 brouard 6896: m=pow(2,cptcoveff);
1.222 brouard 6897: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 6898:
1.264 brouard 6899: fprintf(fichtm," \n<ul><li><b>Graphs</b></li><p>");
6900:
6901: jj1=0;
6902:
6903: fprintf(fichtm," \n<ul>");
6904: for(nres=1; nres <= nresult; nres++) /* For each resultline */
6905: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
6906: if(m != 1 && TKresult[nres]!= k1)
6907: continue;
6908: jj1++;
6909: if (cptcovn > 0) {
6910: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
6911: for (cpt=1; cpt<=cptcoveff;cpt++){
6912: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6913: }
6914: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6915: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
6916: }
6917: fprintf(fichtm,"\">");
6918:
6919: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
6920: fprintf(fichtm,"************ Results for covariates");
6921: for (cpt=1; cpt<=cptcoveff;cpt++){
6922: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6923: }
6924: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6925: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6926: }
6927: if(invalidvarcomb[k1]){
6928: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
6929: continue;
6930: }
6931: fprintf(fichtm,"</a></li>");
6932: } /* cptcovn >0 */
6933: }
6934: fprintf(fichtm," \n</ul>");
6935:
1.222 brouard 6936: jj1=0;
1.237 brouard 6937:
6938: for(nres=1; nres <= nresult; nres++) /* For each resultline */
1.241 brouard 6939: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
1.253 brouard 6940: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 6941: continue;
1.220 brouard 6942:
1.222 brouard 6943: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
6944: jj1++;
6945: if (cptcovn > 0) {
1.264 brouard 6946: fprintf(fichtm,"\n<p><a name=\"rescov");
6947: for (cpt=1; cpt<=cptcoveff;cpt++){
6948: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6949: }
6950: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6951: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
6952: }
6953: fprintf(fichtm,"\"</a>");
6954:
1.222 brouard 6955: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 6956: for (cpt=1; cpt<=cptcoveff;cpt++){
1.237 brouard 6957: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6958: printf(" V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);fflush(stdout);
6959: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
6960: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 6961: }
1.237 brouard 6962: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6963: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6964: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);fflush(stdout);
6965: }
6966:
1.230 brouard 6967: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.222 brouard 6968: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
6969: if(invalidvarcomb[k1]){
6970: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
6971: printf("\nCombination (%d) ignored because no cases \n",k1);
6972: continue;
6973: }
6974: }
6975: /* aij, bij */
1.259 brouard 6976: 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 6977: <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 6978: /* Pij */
1.241 brouard 6979: 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> \
6980: <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 6981: /* Quasi-incidences */
6982: 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 6983: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 6984: 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 6985: 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> \
6986: <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 6987: /* Survival functions (period) in state j */
6988: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 6989: 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 6990: <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 6991: }
6992: /* State specific survival functions (period) */
6993: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 6994: fprintf(fichtm,"<br>\n- Survival functions in state %d and in any other live state (total).\
6995: And probability to be observed in various states (up to %d) being in state %d at different ages. \
1.283 brouard 6996: <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 6997: }
1.288 brouard 6998: /* Period (forward stable) prevalence in each health state */
1.222 brouard 6999: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 7000: 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> \
7001: <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 7002: }
1.296 brouard 7003: if(prevbcast==1){
1.288 brouard 7004: /* Backward prevalence in each health state */
1.222 brouard 7005: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 7006: 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 7007: <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 7008: }
1.217 brouard 7009: }
1.222 brouard 7010: if(prevfcast==1){
1.288 brouard 7011: /* Projection of prevalence up to period (forward stable) prevalence in each health state */
1.222 brouard 7012: for(cpt=1; cpt<=nlstate;cpt++){
1.288 brouard 7013: 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 7014: <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 7015: }
7016: }
1.296 brouard 7017: if(prevbcast==1){
1.268 brouard 7018: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
7019: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 7020: fprintf(fichtm,"<br>\n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), \
7021: 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 \
7022: 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) \
7023: with weights corresponding to observed prevalence at different ages. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br> \
7024: <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 7025: }
7026: }
1.220 brouard 7027:
1.222 brouard 7028: for(cpt=1; cpt<=nlstate;cpt++) {
1.241 brouard 7029: 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> \
7030: <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 7031: }
7032: /* } /\* end i1 *\/ */
7033: }/* End k1 */
7034: fprintf(fichtm,"</ul>");
1.126 brouard 7035:
1.222 brouard 7036: fprintf(fichtm,"\
1.126 brouard 7037: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 7038: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 7039: - 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 7040: But because parameters are usually highly correlated (a higher incidence of disability \
7041: and a higher incidence of recovery can give very close observed transition) it might \
7042: be very useful to look not only at linear confidence intervals estimated from the \
7043: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
7044: (parameters) of the logistic regression, it might be more meaningful to visualize the \
7045: covariance matrix of the one-step probabilities. \
7046: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 7047:
1.222 brouard 7048: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
7049: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
7050: fprintf(fichtm,"\
1.126 brouard 7051: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 7052: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 7053:
1.222 brouard 7054: fprintf(fichtm,"\
1.126 brouard 7055: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 7056: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
7057: fprintf(fichtm,"\
1.126 brouard 7058: - 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): \
7059: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 7060: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 7061: fprintf(fichtm,"\
1.126 brouard 7062: - (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): \
7063: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 7064: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 7065: fprintf(fichtm,"\
1.288 brouard 7066: - 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 7067: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
7068: fprintf(fichtm,"\
1.128 brouard 7069: - 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 7070: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
7071: fprintf(fichtm,"\
1.288 brouard 7072: - Standard deviation of forward (period) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 7073: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 7074:
7075: /* if(popforecast==1) fprintf(fichtm,"\n */
7076: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
7077: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
7078: /* <br>",fileres,fileres,fileres,fileres); */
7079: /* else */
7080: /* 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 7081: fflush(fichtm);
7082: fprintf(fichtm," <ul><li><b>Graphs</b></li><p>");
1.126 brouard 7083:
1.225 brouard 7084: m=pow(2,cptcoveff);
1.222 brouard 7085: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 7086:
1.222 brouard 7087: jj1=0;
1.237 brouard 7088:
1.241 brouard 7089: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.222 brouard 7090: for(k1=1; k1<=m;k1++){
1.253 brouard 7091: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7092: continue;
1.222 brouard 7093: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
7094: jj1++;
1.126 brouard 7095: if (cptcovn > 0) {
7096: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 7097: for (cpt=1; cpt<=cptcoveff;cpt++) /**< cptcoveff number of variables */
1.237 brouard 7098: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);
7099: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
7100: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7101: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7102: }
7103:
1.126 brouard 7104: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 7105:
1.222 brouard 7106: if(invalidvarcomb[k1]){
7107: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
7108: continue;
7109: }
1.126 brouard 7110: }
7111: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 7112: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.241 brouard 7113: 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 7114: <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 7115: }
7116: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.128 brouard 7117: health expectancies in states (1) and (2). If popbased=1 the smooth (due to the model) \
7118: true period expectancies (those weighted with period prevalences are also\
7119: drawn in addition to the population based expectancies computed using\
1.241 brouard 7120: observed and cahotic prevalences: <a href=\"%s_%d-%d.svg\">%s_%d-%d.svg</a>\n<br>\
7121: <img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 7122: /* } /\* end i1 *\/ */
7123: }/* End k1 */
1.241 brouard 7124: }/* End nres */
1.222 brouard 7125: fprintf(fichtm,"</ul>");
7126: fflush(fichtm);
1.126 brouard 7127: }
7128:
7129: /******************* Gnuplot file **************/
1.296 brouard 7130: 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 7131:
7132: char dirfileres[132],optfileres[132];
1.264 brouard 7133: char gplotcondition[132], gplotlabel[132];
1.237 brouard 7134: 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 7135: int lv=0, vlv=0, kl=0;
1.130 brouard 7136: int ng=0;
1.201 brouard 7137: int vpopbased;
1.223 brouard 7138: int ioffset; /* variable offset for columns */
1.270 brouard 7139: int iyearc=1; /* variable column for year of projection */
7140: int iagec=1; /* variable column for age of projection */
1.235 brouard 7141: int nres=0; /* Index of resultline */
1.266 brouard 7142: int istart=1; /* For starting graphs in projections */
1.219 brouard 7143:
1.126 brouard 7144: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
7145: /* printf("Problem with file %s",optionfilegnuplot); */
7146: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
7147: /* } */
7148:
7149: /*#ifdef windows */
7150: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 7151: /*#endif */
1.225 brouard 7152: m=pow(2,cptcoveff);
1.126 brouard 7153:
1.274 brouard 7154: /* diagram of the model */
7155: fprintf(ficgp,"\n#Diagram of the model \n");
7156: fprintf(ficgp,"\ndelta=0.03;delta2=0.07;unset arrow;\n");
7157: fprintf(ficgp,"yoff=(%d > 2? 0:1);\n",nlstate);
7158: 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);
7159:
7160: 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);
7161: fprintf(ficgp,"\n#show arrow\nunset label\n");
7162: 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);
7163: fprintf(ficgp,"\nset label %d+1 sprintf(\"State %%d\",%d+1) center at 0.,0. font \"helvetica, 16\" tc rgbcolor \"red\"\n",nlstate,nlstate);
7164: fprintf(ficgp,"\n#show label\nunset border;unset xtics; unset ytics;\n");
7165: fprintf(ficgp,"\n\nset ter svg size 640, 480;set out \"%s_.svg\" \n",subdirf2(optionfilefiname,"D_"));
7166: fprintf(ficgp,"unset log y; plot [-1.2:1.2][yoff-1.2:1.2] 1/0 not; set out;reset;\n");
7167:
1.202 brouard 7168: /* Contribution to likelihood */
7169: /* Plot the probability implied in the likelihood */
1.223 brouard 7170: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
7171: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
7172: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
7173: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 7174: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 7175: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
7176: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 7177: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
7178: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
7179: 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));
7180: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
7181: 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));
7182: for (i=1; i<= nlstate ; i ++) {
7183: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
7184: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
7185: 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);
7186: for (j=2; j<= nlstate+ndeath ; j ++) {
7187: 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);
7188: }
7189: fprintf(ficgp,";\nset out; unset ylabel;\n");
7190: }
7191: /* 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 */
7192: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
7193: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
7194: fprintf(ficgp,"\nset out;unset log\n");
7195: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 7196:
1.126 brouard 7197: strcpy(dirfileres,optionfilefiname);
7198: strcpy(optfileres,"vpl");
1.223 brouard 7199: /* 1eme*/
1.238 brouard 7200: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
7201: for (k1=1; k1<= m ; k1 ++){ /* For each valid combination of covariate */
1.236 brouard 7202: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.238 brouard 7203: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.253 brouard 7204: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7205: continue;
7206: /* We are interested in selected combination by the resultline */
1.246 brouard 7207: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.288 brouard 7208: fprintf(ficgp,"\n# 1st: Forward (stable period) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 7209: strcpy(gplotlabel,"(");
1.238 brouard 7210: for (k=1; k<=cptcoveff; k++){ /* For each covariate k get corresponding value lv for combination k1 */
7211: lv= decodtabm(k1,k,cptcoveff); /* Should be the value of the covariate corresponding to k1 combination */
7212: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7213: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7214: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7215: vlv= nbcode[Tvaraff[k]][lv]; /* vlv is the value of the covariate lv, 0 or 1 */
7216: /* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv */
1.246 brouard 7217: /* printf(" V%d=%d ",Tvaraff[k],vlv); */
1.238 brouard 7218: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7219: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7220: }
7221: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.246 brouard 7222: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 7223: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7224: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7225: }
7226: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 7227: /* printf("\n#\n"); */
1.238 brouard 7228: fprintf(ficgp,"\n#\n");
7229: if(invalidvarcomb[k1]){
1.260 brouard 7230: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 7231: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7232: continue;
7233: }
1.235 brouard 7234:
1.241 brouard 7235: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
7236: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.276 brouard 7237: /* fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel); */
7238: fprintf(ficgp,"set title \"Alive state %d %s\" font \"Helvetica,12\"\n",cpt,gplotlabel);
1.260 brouard 7239: 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);
7240: /* 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); */
7241: /* k1-1 error should be nres-1*/
1.238 brouard 7242: for (i=1; i<= nlstate ; i ++) {
7243: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7244: else fprintf(ficgp," %%*lf (%%*lf)");
7245: }
1.288 brouard 7246: 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 7247: for (i=1; i<= nlstate ; i ++) {
7248: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7249: else fprintf(ficgp," %%*lf (%%*lf)");
7250: }
1.260 brouard 7251: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 7252: for (i=1; i<= nlstate ; i ++) {
7253: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7254: else fprintf(ficgp," %%*lf (%%*lf)");
7255: }
1.265 brouard 7256: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
7257:
7258: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
7259: if(cptcoveff ==0){
1.271 brouard 7260: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+3*(cpt-1), cpt );
1.265 brouard 7261: }else{
7262: kl=0;
7263: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7264: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7265: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7266: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7267: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7268: vlv= nbcode[Tvaraff[k]][lv];
7269: kl++;
7270: /* 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 *\/ */
7271: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7272: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7273: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7274: if(k==cptcoveff){
7275: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
7276: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
7277: }else{
7278: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7279: kl++;
7280: }
7281: } /* end covariate */
7282: } /* end if no covariate */
7283:
1.296 brouard 7284: if(prevbcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
1.238 brouard 7285: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 7286: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 7287: if(cptcoveff ==0){
1.245 brouard 7288: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 7289: }else{
7290: kl=0;
7291: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7292: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7293: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7294: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7295: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7296: vlv= nbcode[Tvaraff[k]][lv];
1.223 brouard 7297: kl++;
1.238 brouard 7298: /* 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 *\/ */
7299: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7300: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7301: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7302: if(k==cptcoveff){
1.245 brouard 7303: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 7304: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 7305: }else{
7306: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7307: kl++;
7308: }
7309: } /* end covariate */
7310: } /* end if no covariate */
1.296 brouard 7311: if(prevbcast == 1){
1.268 brouard 7312: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
7313: /* k1-1 error should be nres-1*/
7314: for (i=1; i<= nlstate ; i ++) {
7315: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7316: else fprintf(ficgp," %%*lf (%%*lf)");
7317: }
1.271 brouard 7318: 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 7319: for (i=1; i<= nlstate ; i ++) {
7320: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7321: else fprintf(ficgp," %%*lf (%%*lf)");
7322: }
1.276 brouard 7323: 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 7324: for (i=1; i<= nlstate ; i ++) {
7325: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7326: else fprintf(ficgp," %%*lf (%%*lf)");
7327: }
1.274 brouard 7328: fprintf(ficgp,"\" t\"\" w l lt 4");
1.268 brouard 7329: } /* end if backprojcast */
1.296 brouard 7330: } /* end if prevbcast */
1.276 brouard 7331: /* fprintf(ficgp,"\nset out ;unset label;\n"); */
7332: fprintf(ficgp,"\nset out ;unset title;\n");
1.238 brouard 7333: } /* nres */
1.201 brouard 7334: } /* k1 */
7335: } /* cpt */
1.235 brouard 7336:
7337:
1.126 brouard 7338: /*2 eme*/
1.238 brouard 7339: for (k1=1; k1<= m ; k1 ++){
7340: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7341: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7342: continue;
7343: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 7344: strcpy(gplotlabel,"(");
1.238 brouard 7345: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.225 brouard 7346: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
1.223 brouard 7347: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7348: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7349: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7350: vlv= nbcode[Tvaraff[k]][lv];
7351: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7352: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7353: }
1.237 brouard 7354: /* for(k=1; k <= ncovds; k++){ */
1.236 brouard 7355: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 7356: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.236 brouard 7357: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7358: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7359: }
1.264 brouard 7360: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7361: fprintf(ficgp,"\n#\n");
1.223 brouard 7362: if(invalidvarcomb[k1]){
7363: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7364: continue;
7365: }
1.219 brouard 7366:
1.241 brouard 7367: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 7368: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 7369: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
7370: if(vpopbased==0){
1.238 brouard 7371: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 7372: }else
1.238 brouard 7373: fprintf(ficgp,"\nreplot ");
7374: for (i=1; i<= nlstate+1 ; i ++) {
7375: k=2*i;
1.261 brouard 7376: 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 7377: for (j=1; j<= nlstate+1 ; j ++) {
7378: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7379: else fprintf(ficgp," %%*lf (%%*lf)");
7380: }
7381: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
7382: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
1.261 brouard 7383: 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 7384: for (j=1; j<= nlstate+1 ; j ++) {
7385: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7386: else fprintf(ficgp," %%*lf (%%*lf)");
7387: }
7388: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 7389: 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 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== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
7395: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
7396: } /* state */
7397: } /* vpopbased */
1.264 brouard 7398: 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 7399: } /* end nres */
7400: } /* k1 end 2 eme*/
7401:
7402:
7403: /*3eme*/
7404: for (k1=1; k1<= m ; k1 ++){
7405: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7406: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7407: continue;
7408:
7409: for (cpt=1; cpt<= nlstate ; cpt ++) {
1.261 brouard 7410: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 7411: strcpy(gplotlabel,"(");
1.238 brouard 7412: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7413: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7414: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7415: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7416: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7417: vlv= nbcode[Tvaraff[k]][lv];
7418: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7419: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7420: }
7421: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7422: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7423: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7424: }
1.264 brouard 7425: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7426: fprintf(ficgp,"\n#\n");
7427: if(invalidvarcomb[k1]){
7428: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7429: continue;
7430: }
7431:
7432: /* k=2+nlstate*(2*cpt-2); */
7433: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 7434: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 7435: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 7436: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 7437: 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 7438: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7439: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7440: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
7441: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7442: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7443: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 7444:
1.238 brouard 7445: */
7446: for (i=1; i< nlstate ; i ++) {
1.261 brouard 7447: 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 7448: /* 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 7449:
1.238 brouard 7450: }
1.261 brouard 7451: 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 7452: }
1.264 brouard 7453: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 7454: } /* end nres */
7455: } /* end kl 3eme */
1.126 brouard 7456:
1.223 brouard 7457: /* 4eme */
1.201 brouard 7458: /* Survival functions (period) from state i in state j by initial state i */
1.238 brouard 7459: for (k1=1; k1<=m; k1++){ /* For each covariate and each value */
7460: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7461: if(m != 1 && TKresult[nres]!= k1)
1.223 brouard 7462: continue;
1.238 brouard 7463: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 7464: strcpy(gplotlabel,"(");
1.238 brouard 7465: fprintf(ficgp,"\n#\n#\n# Survival functions in state j : 'LIJ_' files, cov=%d state=%d",k1, cpt);
7466: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7467: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7468: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7469: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7470: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7471: vlv= nbcode[Tvaraff[k]][lv];
7472: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7473: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7474: }
7475: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7476: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7477: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7478: }
1.264 brouard 7479: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7480: fprintf(ficgp,"\n#\n");
7481: if(invalidvarcomb[k1]){
7482: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7483: continue;
1.223 brouard 7484: }
1.238 brouard 7485:
1.241 brouard 7486: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 7487: 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 7488: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7489: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7490: k=3;
7491: for (i=1; i<= nlstate ; i ++){
7492: if(i==1){
7493: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7494: }else{
7495: fprintf(ficgp,", '' ");
7496: }
7497: l=(nlstate+ndeath)*(i-1)+1;
7498: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7499: for (j=2; j<= nlstate+ndeath ; j ++)
7500: fprintf(ficgp,"+$%d",k+l+j-1);
7501: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
7502: } /* nlstate */
1.264 brouard 7503: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7504: } /* end cpt state*/
7505: } /* end nres */
7506: } /* end covariate k1 */
7507:
1.220 brouard 7508: /* 5eme */
1.201 brouard 7509: /* Survival functions (period) from state i in state j by final state j */
1.238 brouard 7510: for (k1=1; k1<= m ; k1++){ /* For each covariate combination if any */
7511: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7512: if(m != 1 && TKresult[nres]!= k1)
1.227 brouard 7513: continue;
1.238 brouard 7514: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 7515: strcpy(gplotlabel,"(");
1.238 brouard 7516: 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);
7517: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7518: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7519: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7520: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7521: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7522: vlv= nbcode[Tvaraff[k]][lv];
7523: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7524: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7525: }
7526: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7527: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7528: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7529: }
1.264 brouard 7530: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7531: fprintf(ficgp,"\n#\n");
7532: if(invalidvarcomb[k1]){
7533: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7534: continue;
7535: }
1.227 brouard 7536:
1.241 brouard 7537: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 7538: 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 7539: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7540: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7541: k=3;
7542: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7543: if(j==1)
7544: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7545: else
7546: fprintf(ficgp,", '' ");
7547: l=(nlstate+ndeath)*(cpt-1) +j;
7548: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
7549: /* for (i=2; i<= nlstate+ndeath ; i ++) */
7550: /* fprintf(ficgp,"+$%d",k+l+i-1); */
7551: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
7552: } /* nlstate */
7553: fprintf(ficgp,", '' ");
7554: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
7555: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7556: l=(nlstate+ndeath)*(cpt-1) +j;
7557: if(j < nlstate)
7558: fprintf(ficgp,"$%d +",k+l);
7559: else
7560: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
7561: }
1.264 brouard 7562: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7563: } /* end cpt state*/
7564: } /* end covariate */
7565: } /* end nres */
1.227 brouard 7566:
1.220 brouard 7567: /* 6eme */
1.202 brouard 7568: /* CV preval stable (period) for each covariate */
1.237 brouard 7569: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7570: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7571: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7572: continue;
1.255 brouard 7573: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 7574: strcpy(gplotlabel,"(");
1.288 brouard 7575: fprintf(ficgp,"\n#\n#\n#CV preval stable (forward): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.225 brouard 7576: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.227 brouard 7577: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7578: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7579: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7580: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7581: vlv= nbcode[Tvaraff[k]][lv];
7582: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7583: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7584: }
1.237 brouard 7585: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7586: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7587: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7588: }
1.264 brouard 7589: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7590: fprintf(ficgp,"\n#\n");
1.223 brouard 7591: if(invalidvarcomb[k1]){
1.227 brouard 7592: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7593: continue;
1.223 brouard 7594: }
1.227 brouard 7595:
1.241 brouard 7596: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 7597: 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 7598: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7599: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 7600: k=3; /* Offset */
1.255 brouard 7601: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 7602: if(i==1)
7603: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7604: else
7605: fprintf(ficgp,", '' ");
1.255 brouard 7606: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7607: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7608: for (j=2; j<= nlstate ; j ++)
7609: fprintf(ficgp,"+$%d",k+l+j-1);
7610: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 7611: } /* nlstate */
1.264 brouard 7612: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 7613: } /* end cpt state*/
7614: } /* end covariate */
1.227 brouard 7615:
7616:
1.220 brouard 7617: /* 7eme */
1.296 brouard 7618: if(prevbcast == 1){
1.288 brouard 7619: /* CV backward prevalence for each covariate */
1.237 brouard 7620: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7621: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7622: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7623: continue;
1.268 brouard 7624: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 7625: strcpy(gplotlabel,"(");
1.288 brouard 7626: fprintf(ficgp,"\n#\n#\n#CV Backward stable prevalence: 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 7627: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7628: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7629: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7630: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
1.223 brouard 7631: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.227 brouard 7632: vlv= nbcode[Tvaraff[k]][lv];
7633: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7634: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 7635: }
1.237 brouard 7636: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7637: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7638: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7639: }
1.264 brouard 7640: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 7641: fprintf(ficgp,"\n#\n");
7642: if(invalidvarcomb[k1]){
7643: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7644: continue;
7645: }
7646:
1.241 brouard 7647: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 7648: 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 7649: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7650: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 7651: k=3; /* Offset */
1.268 brouard 7652: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 7653: if(i==1)
7654: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
7655: else
7656: fprintf(ficgp,", '' ");
7657: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 7658: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7659: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
7660: /* 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 7661: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 7662: /* for (j=2; j<= nlstate ; j ++) */
7663: /* fprintf(ficgp,"+$%d",k+l+j-1); */
7664: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 7665: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 7666: } /* nlstate */
1.264 brouard 7667: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 7668: } /* end cpt state*/
7669: } /* end covariate */
1.296 brouard 7670: } /* End if prevbcast */
1.218 brouard 7671:
1.223 brouard 7672: /* 8eme */
1.218 brouard 7673: if(prevfcast==1){
1.288 brouard 7674: /* Projection from cross-sectional to forward stable (period) prevalence for each covariate */
1.218 brouard 7675:
1.237 brouard 7676: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7677: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7678: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7679: continue;
1.211 brouard 7680: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 7681: strcpy(gplotlabel,"(");
1.288 brouard 7682: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to forward stable prevalence (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 7683: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7684: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7685: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7686: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7687: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7688: vlv= nbcode[Tvaraff[k]][lv];
7689: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7690: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 7691: }
1.237 brouard 7692: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7693: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7694: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7695: }
1.264 brouard 7696: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 7697: fprintf(ficgp,"\n#\n");
7698: if(invalidvarcomb[k1]){
7699: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7700: continue;
7701: }
7702:
7703: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 7704: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 7705: 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 7706: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 7707: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 7708:
7709: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
7710: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
7711: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
7712: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 7713: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7714: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7715: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7716: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 7717: if(i==istart){
1.227 brouard 7718: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
7719: }else{
7720: fprintf(ficgp,",\\\n '' ");
7721: }
7722: if(cptcoveff ==0){ /* No covariate */
7723: ioffset=2; /* Age is in 2 */
7724: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7725: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7726: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7727: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7728: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 7729: if(i==nlstate+1){
1.270 brouard 7730: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 7731: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
7732: fprintf(ficgp,",\\\n '' ");
7733: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 7734: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 7735: offyear, \
1.268 brouard 7736: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 7737: }else
1.227 brouard 7738: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
7739: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
7740: }else{ /* more than 2 covariates */
1.270 brouard 7741: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
7742: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7743: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7744: iyearc=ioffset-1;
7745: iagec=ioffset;
1.227 brouard 7746: fprintf(ficgp," u %d:(",ioffset);
7747: kl=0;
7748: strcpy(gplotcondition,"(");
7749: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
7750: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
7751: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7752: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7753: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7754: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
7755: kl++;
7756: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
7757: kl++;
7758: if(k <cptcoveff && cptcoveff>1)
7759: sprintf(gplotcondition+strlen(gplotcondition)," && ");
7760: }
7761: strcpy(gplotcondition+strlen(gplotcondition),")");
7762: /* 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 *\/ */
7763: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7764: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7765: /* '' 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*/
7766: if(i==nlstate+1){
1.270 brouard 7767: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
7768: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 7769: fprintf(ficgp,",\\\n '' ");
1.270 brouard 7770: fprintf(ficgp," u %d:(",iagec);
7771: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
7772: iyearc, iagec, offyear, \
7773: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 7774: /* '' 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 7775: }else{
7776: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
7777: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
7778: }
7779: } /* end if covariate */
7780: } /* nlstate */
1.264 brouard 7781: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 7782: } /* end cpt state*/
7783: } /* end covariate */
7784: } /* End if prevfcast */
1.227 brouard 7785:
1.296 brouard 7786: if(prevbcast==1){
1.268 brouard 7787: /* Back projection from cross-sectional to stable (mixed) for each covariate */
7788:
7789: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7790: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
7791: if(m != 1 && TKresult[nres]!= k1)
7792: continue;
7793: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
7794: strcpy(gplotlabel,"(");
7795: fprintf(ficgp,"\n#\n#\n#Back projection of prevalence to stable (mixed) back prevalence: 'BPROJ_' files, covariatecombination#=%d originstate=%d",k1, cpt);
7796: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7797: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7798: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7799: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7800: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7801: vlv= nbcode[Tvaraff[k]][lv];
7802: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
7803: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
7804: }
7805: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7806: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7807: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7808: }
7809: strcpy(gplotlabel+strlen(gplotlabel),")");
7810: fprintf(ficgp,"\n#\n");
7811: if(invalidvarcomb[k1]){
7812: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7813: continue;
7814: }
7815:
7816: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
7817: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
7818: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
7819: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
7820: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7821:
7822: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
7823: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
7824: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
7825: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
7826: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7827: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7828: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7829: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7830: if(i==istart){
7831: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
7832: }else{
7833: fprintf(ficgp,",\\\n '' ");
7834: }
7835: if(cptcoveff ==0){ /* No covariate */
7836: ioffset=2; /* Age is in 2 */
7837: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7838: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7839: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7840: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7841: fprintf(ficgp," u %d:(", ioffset);
7842: if(i==nlstate+1){
1.270 brouard 7843: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 7844: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
7845: fprintf(ficgp,",\\\n '' ");
7846: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 7847: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 7848: offbyear, \
7849: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
7850: }else
7851: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
7852: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
7853: }else{ /* more than 2 covariates */
1.270 brouard 7854: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
7855: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7856: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7857: iyearc=ioffset-1;
7858: iagec=ioffset;
1.268 brouard 7859: fprintf(ficgp," u %d:(",ioffset);
7860: kl=0;
7861: strcpy(gplotcondition,"(");
7862: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
7863: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
7864: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7865: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7866: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7867: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
7868: kl++;
7869: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
7870: kl++;
7871: if(k <cptcoveff && cptcoveff>1)
7872: sprintf(gplotcondition+strlen(gplotcondition)," && ");
7873: }
7874: strcpy(gplotcondition+strlen(gplotcondition),")");
7875: /* 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 *\/ */
7876: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7877: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7878: /* '' 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*/
7879: if(i==nlstate+1){
1.270 brouard 7880: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
7881: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 7882: fprintf(ficgp,",\\\n '' ");
1.270 brouard 7883: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 7884: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 brouard 7885: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
7886: iyearc,iagec,offbyear, \
7887: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 7888: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
7889: }else{
7890: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
7891: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
7892: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
7893: }
7894: } /* end if covariate */
7895: } /* nlstate */
7896: fprintf(ficgp,"\nset out; unset label;\n");
7897: } /* end cpt state*/
7898: } /* end covariate */
1.296 brouard 7899: } /* End if prevbcast */
1.268 brouard 7900:
1.227 brouard 7901:
1.238 brouard 7902: /* 9eme writing MLE parameters */
7903: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 7904: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 7905: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 7906: for(k=1; k <=(nlstate+ndeath); k++){
7907: if (k != i) {
1.227 brouard 7908: fprintf(ficgp,"# current state %d\n",k);
7909: for(j=1; j <=ncovmodel; j++){
7910: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
7911: jk++;
7912: }
7913: fprintf(ficgp,"\n");
1.126 brouard 7914: }
7915: }
1.223 brouard 7916: }
1.187 brouard 7917: fprintf(ficgp,"##############\n#\n");
1.227 brouard 7918:
1.145 brouard 7919: /*goto avoid;*/
1.238 brouard 7920: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
7921: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 7922: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
7923: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
7924: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
7925: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
7926: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7927: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
7928: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7929: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
7930: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
7931: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7932: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
7933: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
7934: fprintf(ficgp,"#\n");
1.223 brouard 7935: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 7936: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.237 brouard 7937: fprintf(ficgp,"#model=%s \n",model);
1.238 brouard 7938: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.264 brouard 7939: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/* to be checked */
7940: for(k1=1; k1 <=m; k1++) /* For each combination of covariate */
1.237 brouard 7941: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.264 brouard 7942: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7943: continue;
1.264 brouard 7944: fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1);
7945: strcpy(gplotlabel,"(");
1.276 brouard 7946: /*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*/
1.264 brouard 7947: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7948: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7949: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7950: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7951: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7952: vlv= nbcode[Tvaraff[k]][lv];
7953: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
7954: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
7955: }
1.237 brouard 7956: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7957: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7958: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7959: }
1.264 brouard 7960: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 7961: fprintf(ficgp,"\n#\n");
1.264 brouard 7962: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
1.276 brouard 7963: fprintf(ficgp,"\nset key outside ");
7964: /* fprintf(ficgp,"\nset label \"%s\" at graph 1.2,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel); */
7965: fprintf(ficgp,"\nset title \"%s\" font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 7966: fprintf(ficgp,"\nset ter svg size 640, 480 ");
7967: if (ng==1){
7968: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
7969: fprintf(ficgp,"\nunset log y");
7970: }else if (ng==2){
7971: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
7972: fprintf(ficgp,"\nset log y");
7973: }else if (ng==3){
7974: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
7975: fprintf(ficgp,"\nset log y");
7976: }else
7977: fprintf(ficgp,"\nunset title ");
7978: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
7979: i=1;
7980: for(k2=1; k2<=nlstate; k2++) {
7981: k3=i;
7982: for(k=1; k<=(nlstate+ndeath); k++) {
7983: if (k != k2){
7984: switch( ng) {
7985: case 1:
7986: if(nagesqr==0)
7987: fprintf(ficgp," p%d+p%d*x",i,i+1);
7988: else /* nagesqr =1 */
7989: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
7990: break;
7991: case 2: /* ng=2 */
7992: if(nagesqr==0)
7993: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
7994: else /* nagesqr =1 */
7995: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
7996: break;
7997: case 3:
7998: if(nagesqr==0)
7999: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
8000: else /* nagesqr =1 */
8001: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
8002: break;
8003: }
8004: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 8005: ijp=1; /* product no age */
8006: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
8007: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 8008: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.268 brouard 8009: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
8010: if(j==Tage[ij]) { /* Product by age To be looked at!!*/
8011: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
8012: if(DummyV[j]==0){
8013: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
8014: }else{ /* quantitative */
8015: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
8016: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
8017: }
8018: ij++;
1.237 brouard 8019: }
1.268 brouard 8020: }
8021: }else if(cptcovprod >0){
8022: if(j==Tprod[ijp]) { /* */
8023: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
8024: if(ijp <=cptcovprod) { /* Product */
8025: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
8026: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
8027: /* 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)]); */
8028: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
8029: }else{ /* Vn is dummy and Vm is quanti */
8030: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
8031: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
8032: }
8033: }else{ /* Vn*Vm Vn is quanti */
8034: if(DummyV[Tvard[ijp][2]]==0){
8035: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
8036: }else{ /* Both quanti */
8037: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
8038: }
1.237 brouard 8039: }
1.268 brouard 8040: ijp++;
1.237 brouard 8041: }
1.268 brouard 8042: } /* end Tprod */
1.237 brouard 8043: } else{ /* simple covariate */
1.264 brouard 8044: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 8045: if(Dummy[j]==0){
8046: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
8047: }else{ /* quantitative */
8048: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 8049: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 8050: }
1.237 brouard 8051: } /* end simple */
8052: } /* end j */
1.223 brouard 8053: }else{
8054: i=i-ncovmodel;
8055: if(ng !=1 ) /* For logit formula of log p11 is more difficult to get */
8056: fprintf(ficgp," (1.");
8057: }
1.227 brouard 8058:
1.223 brouard 8059: if(ng != 1){
8060: fprintf(ficgp,")/(1");
1.227 brouard 8061:
1.264 brouard 8062: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 8063: if(nagesqr==0)
1.264 brouard 8064: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 8065: else /* nagesqr =1 */
1.264 brouard 8066: 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 8067:
1.223 brouard 8068: ij=1;
8069: for(j=3; j <=ncovmodel-nagesqr; j++){
1.268 brouard 8070: if(cptcovage >0){
8071: if((j-2)==Tage[ij]) { /* Bug valgrind */
8072: if(ij <=cptcovage) { /* Bug valgrind */
8073: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);
8074: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
8075: ij++;
8076: }
8077: }
8078: }else
8079: 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 8080: }
8081: fprintf(ficgp,")");
8082: }
8083: fprintf(ficgp,")");
8084: if(ng ==2)
1.276 brouard 8085: 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 8086: else /* ng= 3 */
1.276 brouard 8087: 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 8088: }else{ /* end ng <> 1 */
8089: if( k !=k2) /* logit p11 is hard to draw */
1.276 brouard 8090: 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 8091: }
8092: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
8093: fprintf(ficgp,",");
8094: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
8095: fprintf(ficgp,",");
8096: i=i+ncovmodel;
8097: } /* end k */
8098: } /* end k2 */
1.276 brouard 8099: /* fprintf(ficgp,"\n set out; unset label;set key default;\n"); */
8100: fprintf(ficgp,"\n set out; unset title;set key default;\n");
1.264 brouard 8101: } /* end k1 */
1.223 brouard 8102: } /* end ng */
8103: /* avoid: */
8104: fflush(ficgp);
1.126 brouard 8105: } /* end gnuplot */
8106:
8107:
8108: /*************** Moving average **************/
1.219 brouard 8109: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 8110: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 8111:
1.222 brouard 8112: int i, cpt, cptcod;
8113: int modcovmax =1;
8114: int mobilavrange, mob;
8115: int iage=0;
1.288 brouard 8116: int firstA1=0, firstA2=0;
1.222 brouard 8117:
1.266 brouard 8118: double sum=0., sumr=0.;
1.222 brouard 8119: double age;
1.266 brouard 8120: double *sumnewp, *sumnewm, *sumnewmr;
8121: double *agemingood, *agemaxgood;
8122: double *agemingoodr, *agemaxgoodr;
1.222 brouard 8123:
8124:
1.278 brouard 8125: /* modcovmax=2*cptcoveff; Max number of modalities. We suppose */
8126: /* a covariate has 2 modalities, should be equal to ncovcombmax */
1.222 brouard 8127:
8128: sumnewp = vector(1,ncovcombmax);
8129: sumnewm = vector(1,ncovcombmax);
1.266 brouard 8130: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 8131: agemingood = vector(1,ncovcombmax);
1.266 brouard 8132: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 8133: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 8134: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 8135:
8136: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 8137: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 8138: sumnewp[cptcod]=0.;
1.266 brouard 8139: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
8140: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 8141: }
8142: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
8143:
1.266 brouard 8144: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
8145: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 8146: else mobilavrange=mobilav;
8147: for (age=bage; age<=fage; age++)
8148: for (i=1; i<=nlstate;i++)
8149: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
8150: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8151: /* We keep the original values on the extreme ages bage, fage and for
8152: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
8153: we use a 5 terms etc. until the borders are no more concerned.
8154: */
8155: for (mob=3;mob <=mobilavrange;mob=mob+2){
8156: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 8157: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
8158: sumnewm[cptcod]=0.;
8159: for (i=1; i<=nlstate;i++){
1.222 brouard 8160: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
8161: for (cpt=1;cpt<=(mob-1)/2;cpt++){
8162: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
8163: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
8164: }
8165: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 8166: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8167: } /* end i */
8168: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
8169: } /* end cptcod */
1.222 brouard 8170: }/* end age */
8171: }/* end mob */
1.266 brouard 8172: }else{
8173: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 8174: return -1;
1.266 brouard 8175: }
8176:
8177: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 8178: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
8179: if(invalidvarcomb[cptcod]){
8180: printf("\nCombination (%d) ignored because no cases \n",cptcod);
8181: continue;
8182: }
1.219 brouard 8183:
1.266 brouard 8184: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
8185: sumnewm[cptcod]=0.;
8186: sumnewmr[cptcod]=0.;
8187: for (i=1; i<=nlstate;i++){
8188: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8189: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8190: }
8191: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8192: agemingoodr[cptcod]=age;
8193: }
8194: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8195: agemingood[cptcod]=age;
8196: }
8197: } /* age */
8198: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 8199: sumnewm[cptcod]=0.;
1.266 brouard 8200: sumnewmr[cptcod]=0.;
1.222 brouard 8201: for (i=1; i<=nlstate;i++){
8202: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8203: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8204: }
8205: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8206: agemaxgoodr[cptcod]=age;
1.222 brouard 8207: }
8208: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 8209: agemaxgood[cptcod]=age;
8210: }
8211: } /* age */
8212: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
8213: /* but they will change */
1.288 brouard 8214: firstA1=0;firstA2=0;
1.266 brouard 8215: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
8216: sumnewm[cptcod]=0.;
8217: sumnewmr[cptcod]=0.;
8218: for (i=1; i<=nlstate;i++){
8219: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8220: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8221: }
8222: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8223: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8224: agemaxgoodr[cptcod]=age; /* age min */
8225: for (i=1; i<=nlstate;i++)
8226: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8227: }else{ /* bad we change the value with the values of good ages */
8228: for (i=1; i<=nlstate;i++){
8229: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
8230: } /* i */
8231: } /* end bad */
8232: }else{
8233: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8234: agemaxgood[cptcod]=age;
8235: }else{ /* bad we change the value with the values of good ages */
8236: for (i=1; i<=nlstate;i++){
8237: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
8238: } /* i */
8239: } /* end bad */
8240: }/* end else */
8241: sum=0.;sumr=0.;
8242: for (i=1; i<=nlstate;i++){
8243: sum+=mobaverage[(int)age][i][cptcod];
8244: sumr+=probs[(int)age][i][cptcod];
8245: }
8246: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.288 brouard 8247: if(!firstA1){
8248: firstA1=1;
8249: 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);
8250: }
8251: 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 8252: } /* end bad */
8253: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8254: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.288 brouard 8255: if(!firstA2){
8256: firstA2=1;
8257: 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);
8258: }
8259: 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 8260: } /* end bad */
8261: }/* age */
1.266 brouard 8262:
8263: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 8264: sumnewm[cptcod]=0.;
1.266 brouard 8265: sumnewmr[cptcod]=0.;
1.222 brouard 8266: for (i=1; i<=nlstate;i++){
8267: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8268: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8269: }
8270: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8271: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
8272: agemingoodr[cptcod]=age;
8273: for (i=1; i<=nlstate;i++)
8274: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8275: }else{ /* bad we change the value with the values of good ages */
8276: for (i=1; i<=nlstate;i++){
8277: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
8278: } /* i */
8279: } /* end bad */
8280: }else{
8281: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8282: agemingood[cptcod]=age;
8283: }else{ /* bad */
8284: for (i=1; i<=nlstate;i++){
8285: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
8286: } /* i */
8287: } /* end bad */
8288: }/* end else */
8289: sum=0.;sumr=0.;
8290: for (i=1; i<=nlstate;i++){
8291: sum+=mobaverage[(int)age][i][cptcod];
8292: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 8293: }
1.266 brouard 8294: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 8295: 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 8296: } /* end bad */
8297: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8298: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 8299: 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 8300: } /* end bad */
8301: }/* age */
1.266 brouard 8302:
1.222 brouard 8303:
8304: for (age=bage; age<=fage; age++){
1.235 brouard 8305: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 8306: sumnewp[cptcod]=0.;
8307: sumnewm[cptcod]=0.;
8308: for (i=1; i<=nlstate;i++){
8309: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
8310: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8311: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
8312: }
8313: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
8314: }
8315: /* printf("\n"); */
8316: /* } */
1.266 brouard 8317:
1.222 brouard 8318: /* brutal averaging */
1.266 brouard 8319: /* for (i=1; i<=nlstate;i++){ */
8320: /* for (age=1; age<=bage; age++){ */
8321: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
8322: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8323: /* } */
8324: /* for (age=fage; age<=AGESUP; age++){ */
8325: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
8326: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8327: /* } */
8328: /* } /\* end i status *\/ */
8329: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
8330: /* for (age=1; age<=AGESUP; age++){ */
8331: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
8332: /* mobaverage[(int)age][i][cptcod]=0.; */
8333: /* } */
8334: /* } */
1.222 brouard 8335: }/* end cptcod */
1.266 brouard 8336: free_vector(agemaxgoodr,1, ncovcombmax);
8337: free_vector(agemaxgood,1, ncovcombmax);
8338: free_vector(agemingood,1, ncovcombmax);
8339: free_vector(agemingoodr,1, ncovcombmax);
8340: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 8341: free_vector(sumnewm,1, ncovcombmax);
8342: free_vector(sumnewp,1, ncovcombmax);
8343: return 0;
8344: }/* End movingaverage */
1.218 brouard 8345:
1.126 brouard 8346:
1.296 brouard 8347:
1.126 brouard 8348: /************** Forecasting ******************/
1.296 brouard 8349: /* 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)*/
8350: 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){
8351: /* dateintemean, mean date of interviews
8352: dateprojd, year, month, day of starting projection
8353: dateprojf date of end of projection;year of end of projection (same day and month as proj1).
1.126 brouard 8354: agemin, agemax range of age
8355: dateprev1 dateprev2 range of dates during which prevalence is computed
8356: */
1.296 brouard 8357: /* double anprojd, mprojd, jprojd; */
8358: /* double anprojf, mprojf, jprojf; */
1.267 brouard 8359: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 8360: double agec; /* generic age */
1.296 brouard 8361: double agelim, ppij, yp,yp1,yp2;
1.126 brouard 8362: double *popeffectif,*popcount;
8363: double ***p3mat;
1.218 brouard 8364: /* double ***mobaverage; */
1.126 brouard 8365: char fileresf[FILENAMELENGTH];
8366:
8367: agelim=AGESUP;
1.211 brouard 8368: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8369: in each health status at the date of interview (if between dateprev1 and dateprev2).
8370: We still use firstpass and lastpass as another selection.
8371: */
1.214 brouard 8372: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8373: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 8374:
1.201 brouard 8375: strcpy(fileresf,"F_");
8376: strcat(fileresf,fileresu);
1.126 brouard 8377: if((ficresf=fopen(fileresf,"w"))==NULL) {
8378: printf("Problem with forecast resultfile: %s\n", fileresf);
8379: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
8380: }
1.235 brouard 8381: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
8382: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 8383:
1.225 brouard 8384: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 8385:
8386:
8387: stepsize=(int) (stepm+YEARM-1)/YEARM;
8388: if (stepm<=12) stepsize=1;
8389: if(estepm < stepm){
8390: printf ("Problem %d lower than %d\n",estepm, stepm);
8391: }
1.270 brouard 8392: else{
8393: hstepm=estepm;
8394: }
8395: if(estepm > stepm){ /* Yes every two year */
8396: stepsize=2;
8397: }
1.296 brouard 8398: hstepm=hstepm/stepm;
1.126 brouard 8399:
1.296 brouard 8400:
8401: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
8402: /* fractional in yp1 *\/ */
8403: /* aintmean=yp; */
8404: /* yp2=modf((yp1*12),&yp); */
8405: /* mintmean=yp; */
8406: /* yp1=modf((yp2*30.5),&yp); */
8407: /* jintmean=yp; */
8408: /* if(jintmean==0) jintmean=1; */
8409: /* if(mintmean==0) mintmean=1; */
1.126 brouard 8410:
1.296 brouard 8411:
8412: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */
8413: /* date2dmy(dateprojd,&jprojd, &mprojd, &anprojd); */
8414: /* date2dmy(dateprojf,&jprojf, &mprojf, &anprojf); */
1.227 brouard 8415: i1=pow(2,cptcoveff);
1.126 brouard 8416: if (cptcovn < 1){i1=1;}
8417:
1.296 brouard 8418: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.126 brouard 8419:
8420: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 8421:
1.126 brouard 8422: /* if (h==(int)(YEARM*yearp)){ */
1.235 brouard 8423: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8424: for(k=1; k<=i1;k++){
1.253 brouard 8425: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 8426: continue;
1.227 brouard 8427: if(invalidvarcomb[k]){
8428: printf("\nCombination (%d) projection ignored because no cases \n",k);
8429: continue;
8430: }
8431: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
8432: for(j=1;j<=cptcoveff;j++) {
8433: fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8434: }
1.235 brouard 8435: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 8436: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.235 brouard 8437: }
1.227 brouard 8438: fprintf(ficresf," yearproj age");
8439: for(j=1; j<=nlstate+ndeath;j++){
8440: for(i=1; i<=nlstate;i++)
8441: fprintf(ficresf," p%d%d",i,j);
8442: fprintf(ficresf," wp.%d",j);
8443: }
1.296 brouard 8444: for (yearp=0; yearp<=(anprojf-anprojd);yearp +=stepsize) {
1.227 brouard 8445: fprintf(ficresf,"\n");
1.296 brouard 8446: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jprojd,mprojd,anprojd+yearp);
1.270 brouard 8447: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
8448: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 8449: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
8450: nhstepm = nhstepm/hstepm;
8451: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8452: oldm=oldms;savm=savms;
1.268 brouard 8453: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 8454: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 8455: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 8456: for (h=0; h<=nhstepm; h++){
8457: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 8458: break;
8459: }
8460: }
8461: fprintf(ficresf,"\n");
8462: for(j=1;j<=cptcoveff;j++)
8463: fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.296 brouard 8464: fprintf(ficresf,"%.f %.f ",anprojd+yearp,agec+h*hstepm/YEARM*stepm);
1.268 brouard 8465:
8466: for(j=1; j<=nlstate+ndeath;j++) {
8467: ppij=0.;
8468: for(i=1; i<=nlstate;i++) {
1.278 brouard 8469: if (mobilav>=1)
8470: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
8471: else { /* even if mobilav==-1 we use mobaverage, probs may not sums to 1 */
8472: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
8473: }
1.268 brouard 8474: fprintf(ficresf," %.3f", p3mat[i][j][h]);
8475: } /* end i */
8476: fprintf(ficresf," %.3f", ppij);
8477: }/* end j */
1.227 brouard 8478: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8479: } /* end agec */
1.266 brouard 8480: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
8481: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 8482: } /* end yearp */
8483: } /* end k */
1.219 brouard 8484:
1.126 brouard 8485: fclose(ficresf);
1.215 brouard 8486: printf("End of Computing forecasting \n");
8487: fprintf(ficlog,"End of Computing forecasting\n");
8488:
1.126 brouard 8489: }
8490:
1.269 brouard 8491: /************** Back Forecasting ******************/
1.296 brouard 8492: /* 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){ */
8493: 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){
8494: /* back1, year, month, day of starting backprojection
1.267 brouard 8495: agemin, agemax range of age
8496: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 8497: anback2 year of end of backprojection (same day and month as back1).
8498: prevacurrent and prev are prevalences.
1.267 brouard 8499: */
8500: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
8501: double agec; /* generic age */
1.296 brouard 8502: double agelim, ppij, ppi, yp,yp1,yp2,jintmean,mintmean,aintmean;
1.267 brouard 8503: double *popeffectif,*popcount;
8504: double ***p3mat;
8505: /* double ***mobaverage; */
8506: char fileresfb[FILENAMELENGTH];
8507:
1.268 brouard 8508: agelim=AGEINF;
1.267 brouard 8509: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8510: in each health status at the date of interview (if between dateprev1 and dateprev2).
8511: We still use firstpass and lastpass as another selection.
8512: */
8513: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8514: /* firstpass, lastpass, stepm, weightopt, model); */
8515:
8516: /*Do we need to compute prevalence again?*/
8517:
8518: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
8519:
8520: strcpy(fileresfb,"FB_");
8521: strcat(fileresfb,fileresu);
8522: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
8523: printf("Problem with back forecast resultfile: %s\n", fileresfb);
8524: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
8525: }
8526: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8527: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8528:
8529: if (cptcoveff==0) ncodemax[cptcoveff]=1;
8530:
8531:
8532: stepsize=(int) (stepm+YEARM-1)/YEARM;
8533: if (stepm<=12) stepsize=1;
8534: if(estepm < stepm){
8535: printf ("Problem %d lower than %d\n",estepm, stepm);
8536: }
1.270 brouard 8537: else{
8538: hstepm=estepm;
8539: }
8540: if(estepm >= stepm){ /* Yes every two year */
8541: stepsize=2;
8542: }
1.267 brouard 8543:
8544: hstepm=hstepm/stepm;
1.296 brouard 8545: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
8546: /* fractional in yp1 *\/ */
8547: /* aintmean=yp; */
8548: /* yp2=modf((yp1*12),&yp); */
8549: /* mintmean=yp; */
8550: /* yp1=modf((yp2*30.5),&yp); */
8551: /* jintmean=yp; */
8552: /* if(jintmean==0) jintmean=1; */
8553: /* if(mintmean==0) jintmean=1; */
1.267 brouard 8554:
8555: i1=pow(2,cptcoveff);
8556: if (cptcovn < 1){i1=1;}
8557:
1.296 brouard 8558: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
8559: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 8560:
8561: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
8562:
8563: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8564: for(k=1; k<=i1;k++){
8565: if(i1 != 1 && TKresult[nres]!= k)
8566: continue;
8567: if(invalidvarcomb[k]){
8568: printf("\nCombination (%d) projection ignored because no cases \n",k);
8569: continue;
8570: }
1.268 brouard 8571: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.267 brouard 8572: for(j=1;j<=cptcoveff;j++) {
8573: fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8574: }
8575: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8576: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
8577: }
8578: fprintf(ficresfb," yearbproj age");
8579: for(j=1; j<=nlstate+ndeath;j++){
8580: for(i=1; i<=nlstate;i++)
1.268 brouard 8581: fprintf(ficresfb," b%d%d",i,j);
8582: fprintf(ficresfb," b.%d",j);
1.267 brouard 8583: }
1.296 brouard 8584: for (yearp=0; yearp>=(anbackf-anbackd);yearp -=stepsize) {
1.267 brouard 8585: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
8586: fprintf(ficresfb,"\n");
1.296 brouard 8587: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jbackd,mbackd,anbackd+yearp);
1.273 brouard 8588: /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
1.270 brouard 8589: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
8590: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 8591: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
1.271 brouard 8592: nhstepm=(int) (agec-agelim) *YEARM/stepm;/* nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
1.267 brouard 8593: nhstepm = nhstepm/hstepm;
8594: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8595: oldm=oldms;savm=savms;
1.268 brouard 8596: /* computes hbxij at age agec over 1 to nhstepm */
1.271 brouard 8597: /* printf("####prevbackforecast debug agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
1.267 brouard 8598: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 8599: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
8600: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
8601: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 8602: for (h=0; h<=nhstepm; h++){
1.268 brouard 8603: if (h*hstepm/YEARM*stepm ==-yearp) {
8604: break;
8605: }
8606: }
8607: fprintf(ficresfb,"\n");
8608: for(j=1;j<=cptcoveff;j++)
8609: fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.296 brouard 8610: fprintf(ficresfb,"%.f %.f ",anbackd+yearp,agec-h*hstepm/YEARM*stepm);
1.268 brouard 8611: for(i=1; i<=nlstate+ndeath;i++) {
8612: ppij=0.;ppi=0.;
8613: for(j=1; j<=nlstate;j++) {
8614: /* if (mobilav==1) */
1.269 brouard 8615: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
8616: ppi=ppi+prevacurrent[(int)agec][j][k];
8617: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
8618: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 8619: /* else { */
8620: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
8621: /* } */
1.268 brouard 8622: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
8623: } /* end j */
8624: if(ppi <0.99){
8625: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
8626: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
8627: }
8628: fprintf(ficresfb," %.3f", ppij);
8629: }/* end j */
1.267 brouard 8630: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8631: } /* end agec */
8632: } /* end yearp */
8633: } /* end k */
1.217 brouard 8634:
1.267 brouard 8635: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 8636:
1.267 brouard 8637: fclose(ficresfb);
8638: printf("End of Computing Back forecasting \n");
8639: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 8640:
1.267 brouard 8641: }
1.217 brouard 8642:
1.269 brouard 8643: /* Variance of prevalence limit: varprlim */
8644: 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 8645: /*------- Variance of forward period (stable) prevalence------*/
1.269 brouard 8646:
8647: char fileresvpl[FILENAMELENGTH];
8648: FILE *ficresvpl;
8649: double **oldm, **savm;
8650: double **varpl; /* Variances of prevalence limits by age */
8651: int i1, k, nres, j ;
8652:
8653: strcpy(fileresvpl,"VPL_");
8654: strcat(fileresvpl,fileresu);
8655: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
1.288 brouard 8656: printf("Problem with variance of forward period (stable) prevalence resultfile: %s\n", fileresvpl);
1.269 brouard 8657: exit(0);
8658: }
1.288 brouard 8659: printf("Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
8660: fprintf(ficlog, "Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
1.269 brouard 8661:
8662: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
8663: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
8664:
8665: i1=pow(2,cptcoveff);
8666: if (cptcovn < 1){i1=1;}
8667:
8668: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8669: for(k=1; k<=i1;k++){
8670: if(i1 != 1 && TKresult[nres]!= k)
8671: continue;
8672: fprintf(ficresvpl,"\n#****** ");
8673: printf("\n#****** ");
8674: fprintf(ficlog,"\n#****** ");
8675: for(j=1;j<=cptcoveff;j++) {
8676: fprintf(ficresvpl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8677: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8678: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8679: }
8680: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
8681: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8682: fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8683: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8684: }
8685: fprintf(ficresvpl,"******\n");
8686: printf("******\n");
8687: fprintf(ficlog,"******\n");
8688:
8689: varpl=matrix(1,nlstate,(int) bage, (int) fage);
8690: oldm=oldms;savm=savms;
8691: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
8692: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
8693: /*}*/
8694: }
8695:
8696: fclose(ficresvpl);
1.288 brouard 8697: printf("done variance-covariance of forward period prevalence\n");fflush(stdout);
8698: fprintf(ficlog,"done variance-covariance of forward period prevalence\n");fflush(ficlog);
1.269 brouard 8699:
8700: }
8701: /* Variance of back prevalence: varbprlim */
8702: 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){
8703: /*------- Variance of back (stable) prevalence------*/
8704:
8705: char fileresvbl[FILENAMELENGTH];
8706: FILE *ficresvbl;
8707:
8708: double **oldm, **savm;
8709: double **varbpl; /* Variances of back prevalence limits by age */
8710: int i1, k, nres, j ;
8711:
8712: strcpy(fileresvbl,"VBL_");
8713: strcat(fileresvbl,fileresu);
8714: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
8715: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
8716: exit(0);
8717: }
8718: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
8719: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
8720:
8721:
8722: i1=pow(2,cptcoveff);
8723: if (cptcovn < 1){i1=1;}
8724:
8725: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8726: for(k=1; k<=i1;k++){
8727: if(i1 != 1 && TKresult[nres]!= k)
8728: continue;
8729: fprintf(ficresvbl,"\n#****** ");
8730: printf("\n#****** ");
8731: fprintf(ficlog,"\n#****** ");
8732: for(j=1;j<=cptcoveff;j++) {
8733: fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8734: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8735: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8736: }
8737: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
8738: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8739: fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8740: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8741: }
8742: fprintf(ficresvbl,"******\n");
8743: printf("******\n");
8744: fprintf(ficlog,"******\n");
8745:
8746: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
8747: oldm=oldms;savm=savms;
8748:
8749: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
8750: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
8751: /*}*/
8752: }
8753:
8754: fclose(ficresvbl);
8755: printf("done variance-covariance of back prevalence\n");fflush(stdout);
8756: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
8757:
8758: } /* End of varbprlim */
8759:
1.126 brouard 8760: /************** Forecasting *****not tested NB*************/
1.227 brouard 8761: /* 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 8762:
1.227 brouard 8763: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
8764: /* int *popage; */
8765: /* double calagedatem, agelim, kk1, kk2; */
8766: /* double *popeffectif,*popcount; */
8767: /* double ***p3mat,***tabpop,***tabpopprev; */
8768: /* /\* double ***mobaverage; *\/ */
8769: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 8770:
1.227 brouard 8771: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8772: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8773: /* agelim=AGESUP; */
8774: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 8775:
1.227 brouard 8776: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 8777:
8778:
1.227 brouard 8779: /* strcpy(filerespop,"POP_"); */
8780: /* strcat(filerespop,fileresu); */
8781: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
8782: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
8783: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
8784: /* } */
8785: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
8786: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 8787:
1.227 brouard 8788: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 8789:
1.227 brouard 8790: /* /\* if (mobilav!=0) { *\/ */
8791: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
8792: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
8793: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
8794: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
8795: /* /\* } *\/ */
8796: /* /\* } *\/ */
1.126 brouard 8797:
1.227 brouard 8798: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
8799: /* if (stepm<=12) stepsize=1; */
1.126 brouard 8800:
1.227 brouard 8801: /* agelim=AGESUP; */
1.126 brouard 8802:
1.227 brouard 8803: /* hstepm=1; */
8804: /* hstepm=hstepm/stepm; */
1.218 brouard 8805:
1.227 brouard 8806: /* if (popforecast==1) { */
8807: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
8808: /* printf("Problem with population file : %s\n",popfile);exit(0); */
8809: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
8810: /* } */
8811: /* popage=ivector(0,AGESUP); */
8812: /* popeffectif=vector(0,AGESUP); */
8813: /* popcount=vector(0,AGESUP); */
1.126 brouard 8814:
1.227 brouard 8815: /* i=1; */
8816: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 8817:
1.227 brouard 8818: /* imx=i; */
8819: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
8820: /* } */
1.218 brouard 8821:
1.227 brouard 8822: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
8823: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
8824: /* k=k+1; */
8825: /* fprintf(ficrespop,"\n#******"); */
8826: /* for(j=1;j<=cptcoveff;j++) { */
8827: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
8828: /* } */
8829: /* fprintf(ficrespop,"******\n"); */
8830: /* fprintf(ficrespop,"# Age"); */
8831: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
8832: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 8833:
1.227 brouard 8834: /* for (cpt=0; cpt<=0;cpt++) { */
8835: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 8836:
1.227 brouard 8837: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
8838: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
8839: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 8840:
1.227 brouard 8841: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8842: /* oldm=oldms;savm=savms; */
8843: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 8844:
1.227 brouard 8845: /* for (h=0; h<=nhstepm; h++){ */
8846: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
8847: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
8848: /* } */
8849: /* for(j=1; j<=nlstate+ndeath;j++) { */
8850: /* kk1=0.;kk2=0; */
8851: /* for(i=1; i<=nlstate;i++) { */
8852: /* if (mobilav==1) */
8853: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
8854: /* else { */
8855: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
8856: /* } */
8857: /* } */
8858: /* if (h==(int)(calagedatem+12*cpt)){ */
8859: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
8860: /* /\*fprintf(ficrespop," %.3f", kk1); */
8861: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
8862: /* } */
8863: /* } */
8864: /* for(i=1; i<=nlstate;i++){ */
8865: /* kk1=0.; */
8866: /* for(j=1; j<=nlstate;j++){ */
8867: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
8868: /* } */
8869: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
8870: /* } */
1.218 brouard 8871:
1.227 brouard 8872: /* if (h==(int)(calagedatem+12*cpt)) */
8873: /* for(j=1; j<=nlstate;j++) */
8874: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
8875: /* } */
8876: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8877: /* } */
8878: /* } */
1.218 brouard 8879:
1.227 brouard 8880: /* /\******\/ */
1.218 brouard 8881:
1.227 brouard 8882: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
8883: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
8884: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
8885: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
8886: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 8887:
1.227 brouard 8888: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8889: /* oldm=oldms;savm=savms; */
8890: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
8891: /* for (h=0; h<=nhstepm; h++){ */
8892: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
8893: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
8894: /* } */
8895: /* for(j=1; j<=nlstate+ndeath;j++) { */
8896: /* kk1=0.;kk2=0; */
8897: /* for(i=1; i<=nlstate;i++) { */
8898: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
8899: /* } */
8900: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
8901: /* } */
8902: /* } */
8903: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8904: /* } */
8905: /* } */
8906: /* } */
8907: /* } */
1.218 brouard 8908:
1.227 brouard 8909: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 8910:
1.227 brouard 8911: /* if (popforecast==1) { */
8912: /* free_ivector(popage,0,AGESUP); */
8913: /* free_vector(popeffectif,0,AGESUP); */
8914: /* free_vector(popcount,0,AGESUP); */
8915: /* } */
8916: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8917: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8918: /* fclose(ficrespop); */
8919: /* } /\* End of popforecast *\/ */
1.218 brouard 8920:
1.126 brouard 8921: int fileappend(FILE *fichier, char *optionfich)
8922: {
8923: if((fichier=fopen(optionfich,"a"))==NULL) {
8924: printf("Problem with file: %s\n", optionfich);
8925: fprintf(ficlog,"Problem with file: %s\n", optionfich);
8926: return (0);
8927: }
8928: fflush(fichier);
8929: return (1);
8930: }
8931:
8932:
8933: /**************** function prwizard **********************/
8934: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
8935: {
8936:
8937: /* Wizard to print covariance matrix template */
8938:
1.164 brouard 8939: char ca[32], cb[32];
8940: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 8941: int numlinepar;
8942:
8943: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
8944: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
8945: for(i=1; i <=nlstate; i++){
8946: jj=0;
8947: for(j=1; j <=nlstate+ndeath; j++){
8948: if(j==i) continue;
8949: jj++;
8950: /*ca[0]= k+'a'-1;ca[1]='\0';*/
8951: printf("%1d%1d",i,j);
8952: fprintf(ficparo,"%1d%1d",i,j);
8953: for(k=1; k<=ncovmodel;k++){
8954: /* printf(" %lf",param[i][j][k]); */
8955: /* fprintf(ficparo," %lf",param[i][j][k]); */
8956: printf(" 0.");
8957: fprintf(ficparo," 0.");
8958: }
8959: printf("\n");
8960: fprintf(ficparo,"\n");
8961: }
8962: }
8963: printf("# Scales (for hessian or gradient estimation)\n");
8964: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
8965: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
8966: for(i=1; i <=nlstate; i++){
8967: jj=0;
8968: for(j=1; j <=nlstate+ndeath; j++){
8969: if(j==i) continue;
8970: jj++;
8971: fprintf(ficparo,"%1d%1d",i,j);
8972: printf("%1d%1d",i,j);
8973: fflush(stdout);
8974: for(k=1; k<=ncovmodel;k++){
8975: /* printf(" %le",delti3[i][j][k]); */
8976: /* fprintf(ficparo," %le",delti3[i][j][k]); */
8977: printf(" 0.");
8978: fprintf(ficparo," 0.");
8979: }
8980: numlinepar++;
8981: printf("\n");
8982: fprintf(ficparo,"\n");
8983: }
8984: }
8985: printf("# Covariance matrix\n");
8986: /* # 121 Var(a12)\n\ */
8987: /* # 122 Cov(b12,a12) Var(b12)\n\ */
8988: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
8989: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
8990: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
8991: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
8992: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
8993: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
8994: fflush(stdout);
8995: fprintf(ficparo,"# Covariance matrix\n");
8996: /* # 121 Var(a12)\n\ */
8997: /* # 122 Cov(b12,a12) Var(b12)\n\ */
8998: /* # ...\n\ */
8999: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
9000:
9001: for(itimes=1;itimes<=2;itimes++){
9002: jj=0;
9003: for(i=1; i <=nlstate; i++){
9004: for(j=1; j <=nlstate+ndeath; j++){
9005: if(j==i) continue;
9006: for(k=1; k<=ncovmodel;k++){
9007: jj++;
9008: ca[0]= k+'a'-1;ca[1]='\0';
9009: if(itimes==1){
9010: printf("#%1d%1d%d",i,j,k);
9011: fprintf(ficparo,"#%1d%1d%d",i,j,k);
9012: }else{
9013: printf("%1d%1d%d",i,j,k);
9014: fprintf(ficparo,"%1d%1d%d",i,j,k);
9015: /* printf(" %.5le",matcov[i][j]); */
9016: }
9017: ll=0;
9018: for(li=1;li <=nlstate; li++){
9019: for(lj=1;lj <=nlstate+ndeath; lj++){
9020: if(lj==li) continue;
9021: for(lk=1;lk<=ncovmodel;lk++){
9022: ll++;
9023: if(ll<=jj){
9024: cb[0]= lk +'a'-1;cb[1]='\0';
9025: if(ll<jj){
9026: if(itimes==1){
9027: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
9028: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
9029: }else{
9030: printf(" 0.");
9031: fprintf(ficparo," 0.");
9032: }
9033: }else{
9034: if(itimes==1){
9035: printf(" Var(%s%1d%1d)",ca,i,j);
9036: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
9037: }else{
9038: printf(" 0.");
9039: fprintf(ficparo," 0.");
9040: }
9041: }
9042: }
9043: } /* end lk */
9044: } /* end lj */
9045: } /* end li */
9046: printf("\n");
9047: fprintf(ficparo,"\n");
9048: numlinepar++;
9049: } /* end k*/
9050: } /*end j */
9051: } /* end i */
9052: } /* end itimes */
9053:
9054: } /* end of prwizard */
9055: /******************* Gompertz Likelihood ******************************/
9056: double gompertz(double x[])
9057: {
9058: double A,B,L=0.0,sump=0.,num=0.;
9059: int i,n=0; /* n is the size of the sample */
9060:
1.220 brouard 9061: for (i=1;i<=imx ; i++) {
1.126 brouard 9062: sump=sump+weight[i];
9063: /* sump=sump+1;*/
9064: num=num+1;
9065: }
9066:
9067:
9068: /* for (i=0; i<=imx; i++)
9069: 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]);*/
9070:
9071: for (i=1;i<=imx ; i++)
9072: {
9073: if (cens[i] == 1 && wav[i]>1)
9074: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
9075:
9076: if (cens[i] == 0 && wav[i]>1)
9077: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
9078: +log(x[1]/YEARM)+x[2]*(agedc[i]-agegomp)+log(YEARM);
9079:
9080: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
9081: if (wav[i] > 1 ) { /* ??? */
9082: L=L+A*weight[i];
9083: /* 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]);*/
9084: }
9085: }
9086:
9087: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
9088:
9089: return -2*L*num/sump;
9090: }
9091:
1.136 brouard 9092: #ifdef GSL
9093: /******************* Gompertz_f Likelihood ******************************/
9094: double gompertz_f(const gsl_vector *v, void *params)
9095: {
9096: double A,B,LL=0.0,sump=0.,num=0.;
9097: double *x= (double *) v->data;
9098: int i,n=0; /* n is the size of the sample */
9099:
9100: for (i=0;i<=imx-1 ; i++) {
9101: sump=sump+weight[i];
9102: /* sump=sump+1;*/
9103: num=num+1;
9104: }
9105:
9106:
9107: /* for (i=0; i<=imx; i++)
9108: 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]);*/
9109: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
9110: for (i=1;i<=imx ; i++)
9111: {
9112: if (cens[i] == 1 && wav[i]>1)
9113: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
9114:
9115: if (cens[i] == 0 && wav[i]>1)
9116: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
9117: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
9118:
9119: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
9120: if (wav[i] > 1 ) { /* ??? */
9121: LL=LL+A*weight[i];
9122: /* 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]);*/
9123: }
9124: }
9125:
9126: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
9127: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
9128:
9129: return -2*LL*num/sump;
9130: }
9131: #endif
9132:
1.126 brouard 9133: /******************* Printing html file ***********/
1.201 brouard 9134: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 9135: int lastpass, int stepm, int weightopt, char model[],\
9136: int imx, double p[],double **matcov,double agemortsup){
9137: int i,k;
9138:
9139: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
9140: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
9141: for (i=1;i<=2;i++)
9142: 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 9143: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 9144: fprintf(fichtm,"</ul>");
9145:
9146: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
9147:
9148: 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>");
9149:
9150: for (k=agegomp;k<(agemortsup-2);k++)
9151: 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]);
9152:
9153:
9154: fflush(fichtm);
9155: }
9156:
9157: /******************* Gnuplot file **************/
1.201 brouard 9158: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 9159:
9160: char dirfileres[132],optfileres[132];
1.164 brouard 9161:
1.126 brouard 9162: int ng;
9163:
9164:
9165: /*#ifdef windows */
9166: fprintf(ficgp,"cd \"%s\" \n",pathc);
9167: /*#endif */
9168:
9169:
9170: strcpy(dirfileres,optionfilefiname);
9171: strcpy(optfileres,"vpl");
1.199 brouard 9172: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 9173: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 9174: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 9175: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 9176: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
9177:
9178: }
9179:
1.136 brouard 9180: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
9181: {
1.126 brouard 9182:
1.136 brouard 9183: /*-------- data file ----------*/
9184: FILE *fic;
9185: char dummy[]=" ";
1.240 brouard 9186: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 9187: int lstra;
1.136 brouard 9188: int linei, month, year,iout;
9189: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 9190: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 9191: char *stratrunc;
1.223 brouard 9192:
1.240 brouard 9193: DummyV=ivector(1,NCOVMAX); /* 1 to 3 */
9194: FixedV=ivector(1,NCOVMAX); /* 1 to 3 */
1.126 brouard 9195:
1.240 brouard 9196: for(v=1; v <=ncovcol;v++){
9197: DummyV[v]=0;
9198: FixedV[v]=0;
9199: }
9200: for(v=ncovcol+1; v <=ncovcol+nqv;v++){
9201: DummyV[v]=1;
9202: FixedV[v]=0;
9203: }
9204: for(v=ncovcol+nqv+1; v <=ncovcol+nqv+ntv;v++){
9205: DummyV[v]=0;
9206: FixedV[v]=1;
9207: }
9208: for(v=ncovcol+nqv+ntv+1; v <=ncovcol+nqv+ntv+nqtv;v++){
9209: DummyV[v]=1;
9210: FixedV[v]=1;
9211: }
9212: for(v=1; v <=ncovcol+nqv+ntv+nqtv;v++){
9213: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",v,v,DummyV[v],v,FixedV[v]);
9214: 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]);
9215: }
1.126 brouard 9216:
1.136 brouard 9217: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 9218: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
9219: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 9220: }
1.126 brouard 9221:
1.136 brouard 9222: i=1;
9223: linei=0;
9224: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
9225: linei=linei+1;
9226: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
9227: if(line[j] == '\t')
9228: line[j] = ' ';
9229: }
9230: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
9231: ;
9232: };
9233: line[j+1]=0; /* Trims blanks at end of line */
9234: if(line[0]=='#'){
9235: fprintf(ficlog,"Comment line\n%s\n",line);
9236: printf("Comment line\n%s\n",line);
9237: continue;
9238: }
9239: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 9240: strcpy(line, linetmp);
1.223 brouard 9241:
9242: /* Loops on waves */
9243: for (j=maxwav;j>=1;j--){
9244: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 9245: cutv(stra, strb, line, ' ');
9246: if(strb[0]=='.') { /* Missing value */
9247: lval=-1;
9248: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
9249: cotvar[j][ntv+iv][i]=-1; /* For performance reasons */
9250: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
9251: 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);
9252: 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);
9253: return 1;
9254: }
9255: }else{
9256: errno=0;
9257: /* what_kind_of_number(strb); */
9258: dval=strtod(strb,&endptr);
9259: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
9260: /* if(strb != endptr && *endptr == '\0') */
9261: /* dval=dlval; */
9262: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9263: if( strb[0]=='\0' || (*endptr != '\0')){
9264: 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);
9265: 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);
9266: return 1;
9267: }
9268: cotqvar[j][iv][i]=dval;
9269: cotvar[j][ntv+iv][i]=dval;
9270: }
9271: strcpy(line,stra);
1.223 brouard 9272: }/* end loop ntqv */
1.225 brouard 9273:
1.223 brouard 9274: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 9275: cutv(stra, strb, line, ' ');
9276: if(strb[0]=='.') { /* Missing value */
9277: lval=-1;
9278: }else{
9279: errno=0;
9280: lval=strtol(strb,&endptr,10);
9281: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9282: if( strb[0]=='\0' || (*endptr != '\0')){
9283: 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);
9284: 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);
9285: return 1;
9286: }
9287: }
9288: if(lval <-1 || lval >1){
9289: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.223 brouard 9290: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9291: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9292: For example, for multinomial values like 1, 2 and 3,\n \
9293: build V1=0 V2=0 for the reference value (1),\n \
9294: V1=1 V2=0 for (2) \n \
1.223 brouard 9295: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9296: output of IMaCh is often meaningless.\n \
1.223 brouard 9297: Exiting.\n",lval,linei, i,line,j);
1.238 brouard 9298: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.223 brouard 9299: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9300: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9301: For example, for multinomial values like 1, 2 and 3,\n \
9302: build V1=0 V2=0 for the reference value (1),\n \
9303: V1=1 V2=0 for (2) \n \
1.223 brouard 9304: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9305: output of IMaCh is often meaningless.\n \
1.223 brouard 9306: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.238 brouard 9307: return 1;
9308: }
9309: cotvar[j][iv][i]=(double)(lval);
9310: strcpy(line,stra);
1.223 brouard 9311: }/* end loop ntv */
1.225 brouard 9312:
1.223 brouard 9313: /* Statuses at wave */
1.137 brouard 9314: cutv(stra, strb, line, ' ');
1.223 brouard 9315: if(strb[0]=='.') { /* Missing value */
1.238 brouard 9316: lval=-1;
1.136 brouard 9317: }else{
1.238 brouard 9318: errno=0;
9319: lval=strtol(strb,&endptr,10);
9320: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9321: if( strb[0]=='\0' || (*endptr != '\0')){
9322: 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);
9323: 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);
9324: return 1;
9325: }
1.136 brouard 9326: }
1.225 brouard 9327:
1.136 brouard 9328: s[j][i]=lval;
1.225 brouard 9329:
1.223 brouard 9330: /* Date of Interview */
1.136 brouard 9331: strcpy(line,stra);
9332: cutv(stra, strb,line,' ');
1.169 brouard 9333: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9334: }
1.169 brouard 9335: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 9336: month=99;
9337: year=9999;
1.136 brouard 9338: }else{
1.225 brouard 9339: 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);
9340: 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);
9341: return 1;
1.136 brouard 9342: }
9343: anint[j][i]= (double) year;
9344: mint[j][i]= (double)month;
9345: strcpy(line,stra);
1.223 brouard 9346: } /* End loop on waves */
1.225 brouard 9347:
1.223 brouard 9348: /* Date of death */
1.136 brouard 9349: cutv(stra, strb,line,' ');
1.169 brouard 9350: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9351: }
1.169 brouard 9352: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 9353: month=99;
9354: year=9999;
9355: }else{
1.141 brouard 9356: 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 9357: 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);
9358: return 1;
1.136 brouard 9359: }
9360: andc[i]=(double) year;
9361: moisdc[i]=(double) month;
9362: strcpy(line,stra);
9363:
1.223 brouard 9364: /* Date of birth */
1.136 brouard 9365: cutv(stra, strb,line,' ');
1.169 brouard 9366: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9367: }
1.169 brouard 9368: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 9369: month=99;
9370: year=9999;
9371: }else{
1.141 brouard 9372: 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);
9373: 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 9374: return 1;
1.136 brouard 9375: }
9376: if (year==9999) {
1.141 brouard 9377: 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);
9378: 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 9379: return 1;
9380:
1.136 brouard 9381: }
9382: annais[i]=(double)(year);
9383: moisnais[i]=(double)(month);
9384: strcpy(line,stra);
1.225 brouard 9385:
1.223 brouard 9386: /* Sample weight */
1.136 brouard 9387: cutv(stra, strb,line,' ');
9388: errno=0;
9389: dval=strtod(strb,&endptr);
9390: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 9391: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
9392: 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 9393: fflush(ficlog);
9394: return 1;
9395: }
9396: weight[i]=dval;
9397: strcpy(line,stra);
1.225 brouard 9398:
1.223 brouard 9399: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
9400: cutv(stra, strb, line, ' ');
9401: if(strb[0]=='.') { /* Missing value */
1.225 brouard 9402: lval=-1;
1.223 brouard 9403: }else{
1.225 brouard 9404: errno=0;
9405: /* what_kind_of_number(strb); */
9406: dval=strtod(strb,&endptr);
9407: /* if(strb != endptr && *endptr == '\0') */
9408: /* dval=dlval; */
9409: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9410: if( strb[0]=='\0' || (*endptr != '\0')){
9411: 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);
9412: 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);
9413: return 1;
9414: }
9415: coqvar[iv][i]=dval;
1.226 brouard 9416: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 9417: }
9418: strcpy(line,stra);
9419: }/* end loop nqv */
1.136 brouard 9420:
1.223 brouard 9421: /* Covariate values */
1.136 brouard 9422: for (j=ncovcol;j>=1;j--){
9423: cutv(stra, strb,line,' ');
1.223 brouard 9424: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 9425: lval=-1;
1.136 brouard 9426: }else{
1.225 brouard 9427: errno=0;
9428: lval=strtol(strb,&endptr,10);
9429: if( strb[0]=='\0' || (*endptr != '\0')){
9430: 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);
9431: 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);
9432: return 1;
9433: }
1.136 brouard 9434: }
9435: if(lval <-1 || lval >1){
1.225 brouard 9436: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9437: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9438: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9439: For example, for multinomial values like 1, 2 and 3,\n \
9440: build V1=0 V2=0 for the reference value (1),\n \
9441: V1=1 V2=0 for (2) \n \
1.136 brouard 9442: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9443: output of IMaCh is often meaningless.\n \
1.136 brouard 9444: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 9445: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9446: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9447: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9448: For example, for multinomial values like 1, 2 and 3,\n \
9449: build V1=0 V2=0 for the reference value (1),\n \
9450: V1=1 V2=0 for (2) \n \
1.136 brouard 9451: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9452: output of IMaCh is often meaningless.\n \
1.136 brouard 9453: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 9454: return 1;
1.136 brouard 9455: }
9456: covar[j][i]=(double)(lval);
9457: strcpy(line,stra);
9458: }
9459: lstra=strlen(stra);
1.225 brouard 9460:
1.136 brouard 9461: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
9462: stratrunc = &(stra[lstra-9]);
9463: num[i]=atol(stratrunc);
9464: }
9465: else
9466: num[i]=atol(stra);
9467: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
9468: 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;}*/
9469:
9470: i=i+1;
9471: } /* End loop reading data */
1.225 brouard 9472:
1.136 brouard 9473: *imax=i-1; /* Number of individuals */
9474: fclose(fic);
1.225 brouard 9475:
1.136 brouard 9476: return (0);
1.164 brouard 9477: /* endread: */
1.225 brouard 9478: printf("Exiting readdata: ");
9479: fclose(fic);
9480: return (1);
1.223 brouard 9481: }
1.126 brouard 9482:
1.234 brouard 9483: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 9484: char *p1 = *stri, *p2 = *stri;
1.235 brouard 9485: while (*p2 == ' ')
1.234 brouard 9486: p2++;
9487: /* while ((*p1++ = *p2++) !=0) */
9488: /* ; */
9489: /* do */
9490: /* while (*p2 == ' ') */
9491: /* p2++; */
9492: /* while (*p1++ == *p2++); */
9493: *stri=p2;
1.145 brouard 9494: }
9495:
1.235 brouard 9496: int decoderesult ( char resultline[], int nres)
1.230 brouard 9497: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
9498: {
1.235 brouard 9499: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 9500: char resultsav[MAXLINE];
1.234 brouard 9501: int resultmodel[MAXLINE];
9502: int modelresult[MAXLINE];
1.230 brouard 9503: char stra[80], strb[80], strc[80], strd[80],stre[80];
9504:
1.234 brouard 9505: removefirstspace(&resultline);
1.233 brouard 9506: printf("decoderesult:%s\n",resultline);
1.230 brouard 9507:
9508: if (strstr(resultline,"v") !=0){
9509: printf("Error. 'v' must be in upper case 'V' result: %s ",resultline);
9510: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultline);fflush(ficlog);
9511: return 1;
9512: }
9513: trimbb(resultsav, resultline);
9514: if (strlen(resultsav) >1){
9515: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' */
9516: }
1.253 brouard 9517: if(j == 0){ /* Resultline but no = */
9518: TKresult[nres]=0; /* Combination for the nresult and the model */
9519: return (0);
9520: }
9521:
1.234 brouard 9522: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
9523: 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);
9524: 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);
9525: }
9526: for(k=1; k<=j;k++){ /* Loop on any covariate of the result line */
9527: if(nbocc(resultsav,'=') >1){
9528: cutl(stra,strb,resultsav,' '); /* keeps in strb after the first ' '
9529: resultsav= V4=1 V5=25.1 V3=0 strb=V3=0 stra= V4=1 V5=25.1 */
9530: cutl(strc,strd,strb,'='); /* strb:V4=1 strc=1 strd=V4 */
9531: }else
9532: cutl(strc,strd,resultsav,'=');
1.230 brouard 9533: Tvalsel[k]=atof(strc); /* 1 */
1.234 brouard 9534:
1.230 brouard 9535: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
9536: Tvarsel[k]=atoi(strc);
9537: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
9538: /* cptcovsel++; */
9539: if (nbocc(stra,'=') >0)
9540: strcpy(resultsav,stra); /* and analyzes it */
9541: }
1.235 brouard 9542: /* Checking for missing or useless values in comparison of current model needs */
1.236 brouard 9543: for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9544: if(Typevar[k1]==0){ /* Single covariate in model */
1.234 brouard 9545: match=0;
1.236 brouard 9546: for(k2=1; k2 <=j;k2++){/* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.237 brouard 9547: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar[1]=5 == Tvarsel[2]=5 */
1.236 brouard 9548: modelresult[k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.234 brouard 9549: match=1;
9550: break;
9551: }
9552: }
9553: if(match == 0){
9554: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
9555: }
9556: }
9557: }
1.235 brouard 9558: /* Checking for missing or useless values in comparison of current model needs */
9559: for(k2=1; k2 <=j;k2++){ /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 9560: match=0;
1.235 brouard 9561: for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9562: if(Typevar[k1]==0){ /* Single */
1.237 brouard 9563: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 */
1.235 brouard 9564: resultmodel[k1]=k2; /* resultmodel[2]=1 resultmodel[1]=2 resultmodel[3]=3 resultmodel[6]=4 resultmodel[9]=5 */
1.234 brouard 9565: ++match;
9566: }
9567: }
9568: }
9569: if(match == 0){
9570: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
9571: }else if(match > 1){
9572: printf("Error in result line: %d doubled; result: %s, model=%s\n",k2, resultline, model);
9573: }
9574: }
1.235 brouard 9575:
1.234 brouard 9576: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 9577: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9578: /* result line V4=1 V5=25.1 V3=0 V2=8 V1=1 */
9579: /* should give a combination of dummy V4=1, V3=0, V1=1 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 5 + (1offset) = 6*/
9580: /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
9581: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
9582: /* 1 0 0 0 */
9583: /* 2 1 0 0 */
9584: /* 3 0 1 0 */
9585: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 */
9586: /* 5 0 0 1 */
9587: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 */
9588: /* 7 0 1 1 */
9589: /* 8 1 1 1 */
1.237 brouard 9590: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
9591: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
9592: /* V5*age V5 known which value for nres? */
9593: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.235 brouard 9594: for(k1=1, k=0, k4=0, k4q=0; k1 <=cptcovt;k1++){ /* model line */
9595: if( Dummy[k1]==0 && Typevar[k1]==0 ){ /* Single dummy */
1.237 brouard 9596: k3= resultmodel[k1]; /* resultmodel[2(V4)] = 1=k3 */
1.235 brouard 9597: k2=(int)Tvarsel[k3]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
9598: k+=Tvalsel[k3]*pow(2,k4); /* Tvalsel[1]=1 */
1.237 brouard 9599: Tresult[nres][k4+1]=Tvalsel[k3];/* Tresult[nres][1]=1(V4=1) Tresult[nres][2]=0(V3=0) */
9600: Tvresult[nres][k4+1]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
9601: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.235 brouard 9602: printf("Decoderesult Dummy k=%d, V(k2=V%d)= Tvalsel[%d]=%d, 2**(%d)\n",k, k2, k3, (int)Tvalsel[k3], k4);
9603: k4++;;
9604: } else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Single quantitative */
9605: k3q= resultmodel[k1]; /* resultmodel[2] = 1=k3 */
9606: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
1.237 brouard 9607: Tqresult[nres][k4q+1]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
9608: Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
9609: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.235 brouard 9610: printf("Decoderesult Quantitative nres=%d, V(k2q=V%d)= Tvalsel[%d]=%d, Tvarsel[%d]=%f\n",nres, k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]);
9611: k4q++;;
9612: }
9613: }
1.234 brouard 9614:
1.235 brouard 9615: TKresult[nres]=++k; /* Combination for the nresult and the model */
1.230 brouard 9616: return (0);
9617: }
1.235 brouard 9618:
1.230 brouard 9619: int decodemodel( char model[], int lastobs)
9620: /**< This routine decodes the model and returns:
1.224 brouard 9621: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
9622: * - nagesqr = 1 if age*age in the model, otherwise 0.
9623: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
9624: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
9625: * - cptcovage number of covariates with age*products =2
9626: * - cptcovs number of simple covariates
9627: * - 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
9628: * which is a new column after the 9 (ncovcol) variables.
9629: * - if k is a product Vn*Vm covar[k][i] is filled with correct values for each individual
9630: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
9631: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
9632: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
9633: */
1.136 brouard 9634: {
1.238 brouard 9635: int i, j, k, ks, v;
1.227 brouard 9636: int j1, k1, k2, k3, k4;
1.136 brouard 9637: char modelsav[80];
1.145 brouard 9638: char stra[80], strb[80], strc[80], strd[80],stre[80];
1.187 brouard 9639: char *strpt;
1.136 brouard 9640:
1.145 brouard 9641: /*removespace(model);*/
1.136 brouard 9642: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.145 brouard 9643: j=0, j1=0, k1=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 9644: if (strstr(model,"AGE") !=0){
1.192 brouard 9645: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
9646: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 9647: return 1;
9648: }
1.141 brouard 9649: if (strstr(model,"v") !=0){
9650: printf("Error. 'v' must be in upper case 'V' model=%s ",model);
9651: fprintf(ficlog,"Error. 'v' must be in upper case model=%s ",model);fflush(ficlog);
9652: return 1;
9653: }
1.187 brouard 9654: strcpy(modelsav,model);
9655: if ((strpt=strstr(model,"age*age")) !=0){
9656: printf(" strpt=%s, model=%s\n",strpt, model);
9657: if(strpt != model){
1.234 brouard 9658: printf("Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 9659: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 9660: corresponding column of parameters.\n",model);
1.234 brouard 9661: fprintf(ficlog,"Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 9662: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 9663: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 9664: return 1;
1.225 brouard 9665: }
1.187 brouard 9666: nagesqr=1;
9667: if (strstr(model,"+age*age") !=0)
1.234 brouard 9668: substrchaine(modelsav, model, "+age*age");
1.187 brouard 9669: else if (strstr(model,"age*age+") !=0)
1.234 brouard 9670: substrchaine(modelsav, model, "age*age+");
1.187 brouard 9671: else
1.234 brouard 9672: substrchaine(modelsav, model, "age*age");
1.187 brouard 9673: }else
9674: nagesqr=0;
9675: if (strlen(modelsav) >1){
9676: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
9677: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.224 brouard 9678: cptcovs=j+1-j1; /**< Number of simple covariates V1+V1*age+V3 +V3*V4+age*age=> V1 + V3 =5-3=2 */
1.187 brouard 9679: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 9680: * cst, age and age*age
9681: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
9682: /* including age products which are counted in cptcovage.
9683: * but the covariates which are products must be treated
9684: * separately: ncovn=4- 2=2 (V1+V3). */
1.187 brouard 9685: cptcovprod=j1; /**< Number of products V1*V2 +v3*age = 2 */
9686: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.225 brouard 9687:
9688:
1.187 brouard 9689: /* Design
9690: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
9691: * < ncovcol=8 >
9692: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
9693: * k= 1 2 3 4 5 6 7 8
9694: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
9695: * covar[k,i], value of kth covariate if not including age for individual i:
1.224 brouard 9696: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
9697: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 9698: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
9699: * Tage[++cptcovage]=k
9700: * if products, new covar are created after ncovcol with k1
9701: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
9702: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
9703: * 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
9704: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
9705: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
9706: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
9707: * < ncovcol=8 >
9708: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
9709: * k= 1 2 3 4 5 6 7 8 9 10 11 12
9710: * Tvar[k]= 2 1 3 3 10 11 8 8 5 6 7 8
9711: * p Tvar[1]@12={2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
9712: * p Tprod[1]@2={ 6, 5}
9713: *p Tvard[1][1]@4= {7, 8, 5, 6}
9714: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
9715: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
9716: *How to reorganize?
9717: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
9718: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
9719: * {2, 1, 4, 8, 5, 6, 3, 7}
9720: * Struct []
9721: */
1.225 brouard 9722:
1.187 brouard 9723: /* This loop fills the array Tvar from the string 'model'.*/
9724: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
9725: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
9726: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
9727: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
9728: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
9729: /* k=1 Tvar[1]=2 (from V2) */
9730: /* k=5 Tvar[5] */
9731: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 9732: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 9733: /* } */
1.198 brouard 9734: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 9735: /*
9736: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 9737: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
9738: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
9739: }
1.187 brouard 9740: cptcovage=0;
9741: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model */
1.234 brouard 9742: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+'
1.225 brouard 9743: modelsav==V2+V1+V4+V3*age strb=V3*age stra=V2+V1+V4 */
1.234 brouard 9744: if (nbocc(modelsav,'+')==0) strcpy(strb,modelsav); /* and analyzes it */
9745: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
9746: /*scanf("%d",i);*/
9747: if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V4+V3*age strb=V3*age */
9748: cutl(strc,strd,strb,'*'); /**< strd*strc Vm*Vn: strb=V3*age(input) strc=age strd=V3 ; V3*V2 strc=V2, strd=V3 */
9749: if (strcmp(strc,"age")==0) { /**< Model includes age: Vn*age */
9750: /* covar is not filled and then is empty */
9751: cptcovprod--;
9752: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
9753: Tvar[k]=atoi(stre); /* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1 */
9754: Typevar[k]=1; /* 1 for age product */
9755: cptcovage++; /* Sums the number of covariates which include age as a product */
9756: Tage[cptcovage]=k; /* Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */
9757: /*printf("stre=%s ", stre);*/
9758: } else if (strcmp(strd,"age")==0) { /* or age*Vn */
9759: cptcovprod--;
9760: cutl(stre,strb,strc,'V');
9761: Tvar[k]=atoi(stre);
9762: Typevar[k]=1; /* 1 for age product */
9763: cptcovage++;
9764: Tage[cptcovage]=k;
9765: } else { /* Age is not in the model product V2+V1+V1*V4+V3*age+V3*V2 strb=V3*V2*/
9766: /* loops on k1=1 (V3*V2) and k1=2 V4*V3 */
9767: cptcovn++;
9768: cptcovprodnoage++;k1++;
9769: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
9770: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* For model-covariate k tells which data-covariate to use but
9771: because this model-covariate is a construction we invent a new column
9772: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
9773: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2
9774: Tvar[3=V1*V4]=4+1 Tvar[5=V3*V2]=4 + 2= 6, etc */
9775: Typevar[k]=2; /* 2 for double fixed dummy covariates */
9776: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
9777: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 */
9778: Tposprod[k]=k1; /* Tpsprod[3]=1, Tposprod[2]=5 */
9779: Tvard[k1][1] =atoi(strc); /* m 1 for V1*/
9780: Tvard[k1][2] =atoi(stre); /* n 4 for V4*/
9781: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
9782: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
9783: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
1.225 brouard 9784: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
1.234 brouard 9785: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
9786: for (i=1; i<=lastobs;i++){
9787: /* Computes the new covariate which is a product of
9788: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
9789: covar[ncovcol+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
9790: }
9791: } /* End age is not in the model */
9792: } /* End if model includes a product */
9793: else { /* no more sum */
9794: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
9795: /* scanf("%d",i);*/
9796: cutl(strd,strc,strb,'V');
9797: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
9798: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
9799: Tvar[k]=atoi(strd);
9800: Typevar[k]=0; /* 0 for simple covariates */
9801: }
9802: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 9803: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 9804: scanf("%d",i);*/
1.187 brouard 9805: } /* end of loop + on total covariates */
9806: } /* end if strlen(modelsave == 0) age*age might exist */
9807: } /* end if strlen(model == 0) */
1.136 brouard 9808:
9809: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
9810: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 9811:
1.136 brouard 9812: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 9813: printf("cptcovprod=%d ", cptcovprod);
9814: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
9815: scanf("%d ",i);*/
9816:
9817:
1.230 brouard 9818: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
9819: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 9820: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
9821: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
9822: k = 1 2 3 4 5 6 7 8 9
9823: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
9824: Typevar[k]= 0 0 0 2 1 0 2 1 1
1.227 brouard 9825: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
9826: Dummy[k] 1 0 0 0 3 1 1 2 3
9827: Tmodelind[combination of covar]=k;
1.225 brouard 9828: */
9829: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 9830: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 9831: /* 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 9832: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.227 brouard 9833: printf("Model=%s\n\
9834: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
9835: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
9836: 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);
9837: fprintf(ficlog,"Model=%s\n\
9838: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
9839: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
9840: 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 9841: for(k=-1;k<=cptcovt; k++){ Fixed[k]=0; Dummy[k]=0;}
1.234 brouard 9842: 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 */
9843: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 9844: Fixed[k]= 0;
9845: Dummy[k]= 0;
1.225 brouard 9846: ncoveff++;
1.232 brouard 9847: ncovf++;
1.234 brouard 9848: nsd++;
9849: modell[k].maintype= FTYPE;
9850: TvarsD[nsd]=Tvar[k];
9851: TvarsDind[nsd]=k;
9852: TvarF[ncovf]=Tvar[k];
9853: TvarFind[ncovf]=k;
9854: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9855: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9856: }else if( Tvar[k] <=ncovcol && Typevar[k]==2){ /* Product of fixed dummy (<=ncovcol) covariates */
9857: Fixed[k]= 0;
9858: Dummy[k]= 0;
9859: ncoveff++;
9860: ncovf++;
9861: modell[k].maintype= FTYPE;
9862: TvarF[ncovf]=Tvar[k];
9863: TvarFind[ncovf]=k;
1.230 brouard 9864: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.231 brouard 9865: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.240 brouard 9866: }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 9867: Fixed[k]= 0;
9868: Dummy[k]= 1;
1.230 brouard 9869: nqfveff++;
1.234 brouard 9870: modell[k].maintype= FTYPE;
9871: modell[k].subtype= FQ;
9872: nsq++;
9873: TvarsQ[nsq]=Tvar[k];
9874: TvarsQind[nsq]=k;
1.232 brouard 9875: ncovf++;
1.234 brouard 9876: TvarF[ncovf]=Tvar[k];
9877: TvarFind[ncovf]=k;
1.231 brouard 9878: 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 9879: 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 9880: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.227 brouard 9881: Fixed[k]= 1;
9882: Dummy[k]= 0;
1.225 brouard 9883: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 9884: modell[k].maintype= VTYPE;
9885: modell[k].subtype= VD;
9886: nsd++;
9887: TvarsD[nsd]=Tvar[k];
9888: TvarsDind[nsd]=k;
9889: ncovv++; /* Only simple time varying variables */
9890: TvarV[ncovv]=Tvar[k];
1.242 brouard 9891: 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 9892: 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 */
9893: 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 9894: 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);
9895: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 9896: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.234 brouard 9897: Fixed[k]= 1;
9898: Dummy[k]= 1;
9899: nqtveff++;
9900: modell[k].maintype= VTYPE;
9901: modell[k].subtype= VQ;
9902: ncovv++; /* Only simple time varying variables */
9903: nsq++;
9904: TvarsQ[nsq]=Tvar[k];
9905: TvarsQind[nsq]=k;
9906: TvarV[ncovv]=Tvar[k];
1.242 brouard 9907: 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 9908: 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 */
9909: 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 9910: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
9911: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
9912: 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 9913: printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv);
1.227 brouard 9914: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 9915: ncova++;
9916: TvarA[ncova]=Tvar[k];
9917: TvarAind[ncova]=k;
1.231 brouard 9918: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 9919: Fixed[k]= 2;
9920: Dummy[k]= 2;
9921: modell[k].maintype= ATYPE;
9922: modell[k].subtype= APFD;
9923: /* ncoveff++; */
1.227 brouard 9924: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 9925: Fixed[k]= 2;
9926: Dummy[k]= 3;
9927: modell[k].maintype= ATYPE;
9928: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
9929: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 9930: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 9931: Fixed[k]= 3;
9932: Dummy[k]= 2;
9933: modell[k].maintype= ATYPE;
9934: modell[k].subtype= APVD; /* Product age * varying dummy */
9935: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 9936: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 9937: Fixed[k]= 3;
9938: Dummy[k]= 3;
9939: modell[k].maintype= ATYPE;
9940: modell[k].subtype= APVQ; /* Product age * varying quantitative */
9941: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 9942: }
9943: }else if (Typevar[k] == 2) { /* product without age */
9944: k1=Tposprod[k];
9945: if(Tvard[k1][1] <=ncovcol){
1.240 brouard 9946: if(Tvard[k1][2] <=ncovcol){
9947: Fixed[k]= 1;
9948: Dummy[k]= 0;
9949: modell[k].maintype= FTYPE;
9950: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
9951: ncovf++; /* Fixed variables without age */
9952: TvarF[ncovf]=Tvar[k];
9953: TvarFind[ncovf]=k;
9954: }else if(Tvard[k1][2] <=ncovcol+nqv){
9955: Fixed[k]= 0; /* or 2 ?*/
9956: Dummy[k]= 1;
9957: modell[k].maintype= FTYPE;
9958: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
9959: ncovf++; /* Varying variables without age */
9960: TvarF[ncovf]=Tvar[k];
9961: TvarFind[ncovf]=k;
9962: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9963: Fixed[k]= 1;
9964: Dummy[k]= 0;
9965: modell[k].maintype= VTYPE;
9966: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
9967: ncovv++; /* Varying variables without age */
9968: TvarV[ncovv]=Tvar[k];
9969: TvarVind[ncovv]=k;
9970: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9971: Fixed[k]= 1;
9972: Dummy[k]= 1;
9973: modell[k].maintype= VTYPE;
9974: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
9975: ncovv++; /* Varying variables without age */
9976: TvarV[ncovv]=Tvar[k];
9977: TvarVind[ncovv]=k;
9978: }
1.227 brouard 9979: }else if(Tvard[k1][1] <=ncovcol+nqv){
1.240 brouard 9980: if(Tvard[k1][2] <=ncovcol){
9981: Fixed[k]= 0; /* or 2 ?*/
9982: Dummy[k]= 1;
9983: modell[k].maintype= FTYPE;
9984: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
9985: ncovf++; /* Fixed variables without age */
9986: TvarF[ncovf]=Tvar[k];
9987: TvarFind[ncovf]=k;
9988: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9989: Fixed[k]= 1;
9990: Dummy[k]= 1;
9991: modell[k].maintype= VTYPE;
9992: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
9993: ncovv++; /* Varying variables without age */
9994: TvarV[ncovv]=Tvar[k];
9995: TvarVind[ncovv]=k;
9996: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9997: Fixed[k]= 1;
9998: Dummy[k]= 1;
9999: modell[k].maintype= VTYPE;
10000: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
10001: ncovv++; /* Varying variables without age */
10002: TvarV[ncovv]=Tvar[k];
10003: TvarVind[ncovv]=k;
10004: ncovv++; /* Varying variables without age */
10005: TvarV[ncovv]=Tvar[k];
10006: TvarVind[ncovv]=k;
10007: }
1.227 brouard 10008: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){
1.240 brouard 10009: if(Tvard[k1][2] <=ncovcol){
10010: Fixed[k]= 1;
10011: Dummy[k]= 1;
10012: modell[k].maintype= VTYPE;
10013: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
10014: ncovv++; /* Varying variables without age */
10015: TvarV[ncovv]=Tvar[k];
10016: TvarVind[ncovv]=k;
10017: }else if(Tvard[k1][2] <=ncovcol+nqv){
10018: Fixed[k]= 1;
10019: Dummy[k]= 1;
10020: modell[k].maintype= VTYPE;
10021: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
10022: ncovv++; /* Varying variables without age */
10023: TvarV[ncovv]=Tvar[k];
10024: TvarVind[ncovv]=k;
10025: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10026: Fixed[k]= 1;
10027: Dummy[k]= 0;
10028: modell[k].maintype= VTYPE;
10029: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
10030: ncovv++; /* Varying variables without age */
10031: TvarV[ncovv]=Tvar[k];
10032: TvarVind[ncovv]=k;
10033: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10034: Fixed[k]= 1;
10035: Dummy[k]= 1;
10036: modell[k].maintype= VTYPE;
10037: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
10038: ncovv++; /* Varying variables without age */
10039: TvarV[ncovv]=Tvar[k];
10040: TvarVind[ncovv]=k;
10041: }
1.227 brouard 10042: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 10043: if(Tvard[k1][2] <=ncovcol){
10044: Fixed[k]= 1;
10045: Dummy[k]= 1;
10046: modell[k].maintype= VTYPE;
10047: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
10048: ncovv++; /* Varying variables without age */
10049: TvarV[ncovv]=Tvar[k];
10050: TvarVind[ncovv]=k;
10051: }else if(Tvard[k1][2] <=ncovcol+nqv){
10052: Fixed[k]= 1;
10053: Dummy[k]= 1;
10054: modell[k].maintype= VTYPE;
10055: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
10056: ncovv++; /* Varying variables without age */
10057: TvarV[ncovv]=Tvar[k];
10058: TvarVind[ncovv]=k;
10059: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10060: Fixed[k]= 1;
10061: Dummy[k]= 1;
10062: modell[k].maintype= VTYPE;
10063: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
10064: ncovv++; /* Varying variables without age */
10065: TvarV[ncovv]=Tvar[k];
10066: TvarVind[ncovv]=k;
10067: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10068: Fixed[k]= 1;
10069: Dummy[k]= 1;
10070: modell[k].maintype= VTYPE;
10071: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
10072: ncovv++; /* Varying variables without age */
10073: TvarV[ncovv]=Tvar[k];
10074: TvarVind[ncovv]=k;
10075: }
1.227 brouard 10076: }else{
1.240 brouard 10077: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
10078: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
10079: } /*end k1*/
1.225 brouard 10080: }else{
1.226 brouard 10081: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
10082: 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 10083: }
1.227 brouard 10084: 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 10085: printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype);
1.227 brouard 10086: 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]);
10087: }
10088: /* Searching for doublons in the model */
10089: for(k1=1; k1<= cptcovt;k1++){
10090: for(k2=1; k2 <k1;k2++){
1.285 brouard 10091: /* if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){ */
10092: if((Typevar[k1]==Typevar[k2]) && (Fixed[k1]==Fixed[k2]) && (Dummy[k1]==Dummy[k2] )){
1.234 brouard 10093: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
10094: if(Tvar[k1]==Tvar[k2]){
1.285 brouard 10095: 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]);
10096: 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 10097: return(1);
10098: }
10099: }else if (Typevar[k1] ==2){
10100: k3=Tposprod[k1];
10101: k4=Tposprod[k2];
10102: 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])) ){
10103: 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]]);
10104: 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);
10105: return(1);
10106: }
10107: }
1.227 brouard 10108: }
10109: }
1.225 brouard 10110: }
10111: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
10112: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 10113: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
10114: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.137 brouard 10115: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 10116: /*endread:*/
1.225 brouard 10117: printf("Exiting decodemodel: ");
10118: return (1);
1.136 brouard 10119: }
10120:
1.169 brouard 10121: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 10122: {/* Check ages at death */
1.136 brouard 10123: int i, m;
1.218 brouard 10124: int firstone=0;
10125:
1.136 brouard 10126: for (i=1; i<=imx; i++) {
10127: for(m=2; (m<= maxwav); m++) {
10128: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
10129: anint[m][i]=9999;
1.216 brouard 10130: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
10131: s[m][i]=-1;
1.136 brouard 10132: }
10133: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 10134: *nberr = *nberr + 1;
1.218 brouard 10135: if(firstone == 0){
10136: firstone=1;
1.260 brouard 10137: 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 10138: }
1.262 brouard 10139: 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 10140: s[m][i]=-1; /* Droping the death status */
1.136 brouard 10141: }
10142: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 10143: (*nberr)++;
1.259 brouard 10144: 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 10145: 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 10146: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 10147: }
10148: }
10149: }
10150:
10151: for (i=1; i<=imx; i++) {
10152: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
10153: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 10154: 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 10155: if (s[m][i] >= nlstate+1) {
1.169 brouard 10156: if(agedc[i]>0){
10157: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 10158: agev[m][i]=agedc[i];
1.214 brouard 10159: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 10160: }else {
1.136 brouard 10161: if ((int)andc[i]!=9999){
10162: nbwarn++;
10163: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
10164: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
10165: agev[m][i]=-1;
10166: }
10167: }
1.169 brouard 10168: } /* agedc > 0 */
1.214 brouard 10169: } /* end if */
1.136 brouard 10170: else if(s[m][i] !=9){ /* Standard case, age in fractional
10171: years but with the precision of a month */
10172: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
10173: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
10174: agev[m][i]=1;
10175: else if(agev[m][i] < *agemin){
10176: *agemin=agev[m][i];
10177: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
10178: }
10179: else if(agev[m][i] >*agemax){
10180: *agemax=agev[m][i];
1.156 brouard 10181: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 10182: }
10183: /*agev[m][i]=anint[m][i]-annais[i];*/
10184: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 10185: } /* en if 9*/
1.136 brouard 10186: else { /* =9 */
1.214 brouard 10187: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 10188: agev[m][i]=1;
10189: s[m][i]=-1;
10190: }
10191: }
1.214 brouard 10192: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 10193: agev[m][i]=1;
1.214 brouard 10194: else{
10195: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
10196: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
10197: agev[m][i]=0;
10198: }
10199: } /* End for lastpass */
10200: }
1.136 brouard 10201:
10202: for (i=1; i<=imx; i++) {
10203: for(m=firstpass; (m<=lastpass); m++){
10204: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 10205: (*nberr)++;
1.136 brouard 10206: 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);
10207: 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);
10208: return 1;
10209: }
10210: }
10211: }
10212:
10213: /*for (i=1; i<=imx; i++){
10214: for (m=firstpass; (m<lastpass); m++){
10215: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
10216: }
10217:
10218: }*/
10219:
10220:
1.139 brouard 10221: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
10222: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 10223:
10224: return (0);
1.164 brouard 10225: /* endread:*/
1.136 brouard 10226: printf("Exiting calandcheckages: ");
10227: return (1);
10228: }
10229:
1.172 brouard 10230: #if defined(_MSC_VER)
10231: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
10232: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
10233: //#include "stdafx.h"
10234: //#include <stdio.h>
10235: //#include <tchar.h>
10236: //#include <windows.h>
10237: //#include <iostream>
10238: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
10239:
10240: LPFN_ISWOW64PROCESS fnIsWow64Process;
10241:
10242: BOOL IsWow64()
10243: {
10244: BOOL bIsWow64 = FALSE;
10245:
10246: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
10247: // (HANDLE, PBOOL);
10248:
10249: //LPFN_ISWOW64PROCESS fnIsWow64Process;
10250:
10251: HMODULE module = GetModuleHandle(_T("kernel32"));
10252: const char funcName[] = "IsWow64Process";
10253: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
10254: GetProcAddress(module, funcName);
10255:
10256: if (NULL != fnIsWow64Process)
10257: {
10258: if (!fnIsWow64Process(GetCurrentProcess(),
10259: &bIsWow64))
10260: //throw std::exception("Unknown error");
10261: printf("Unknown error\n");
10262: }
10263: return bIsWow64 != FALSE;
10264: }
10265: #endif
1.177 brouard 10266:
1.191 brouard 10267: void syscompilerinfo(int logged)
1.292 brouard 10268: {
10269: #include <stdint.h>
10270:
10271: /* #include "syscompilerinfo.h"*/
1.185 brouard 10272: /* command line Intel compiler 32bit windows, XP compatible:*/
10273: /* /GS /W3 /Gy
10274: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
10275: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
10276: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 10277: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
10278: */
10279: /* 64 bits */
1.185 brouard 10280: /*
10281: /GS /W3 /Gy
10282: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
10283: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
10284: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
10285: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
10286: /* Optimization are useless and O3 is slower than O2 */
10287: /*
10288: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
10289: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
10290: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
10291: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
10292: */
1.186 brouard 10293: /* Link is */ /* /OUT:"visual studio
1.185 brouard 10294: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
10295: /PDB:"visual studio
10296: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
10297: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
10298: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
10299: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
10300: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
10301: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
10302: uiAccess='false'"
10303: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
10304: /NOLOGO /TLBID:1
10305: */
1.292 brouard 10306:
10307:
1.177 brouard 10308: #if defined __INTEL_COMPILER
1.178 brouard 10309: #if defined(__GNUC__)
10310: struct utsname sysInfo; /* For Intel on Linux and OS/X */
10311: #endif
1.177 brouard 10312: #elif defined(__GNUC__)
1.179 brouard 10313: #ifndef __APPLE__
1.174 brouard 10314: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 10315: #endif
1.177 brouard 10316: struct utsname sysInfo;
1.178 brouard 10317: int cross = CROSS;
10318: if (cross){
10319: printf("Cross-");
1.191 brouard 10320: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 10321: }
1.174 brouard 10322: #endif
10323:
1.191 brouard 10324: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 10325: #if defined(__clang__)
1.191 brouard 10326: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 10327: #endif
10328: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 10329: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 10330: #endif
10331: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 10332: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 10333: #endif
10334: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 10335: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 10336: #endif
10337: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 10338: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 10339: #endif
10340: #if defined(_MSC_VER)
1.191 brouard 10341: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 10342: #endif
10343: #if defined(__PGI)
1.191 brouard 10344: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 10345: #endif
10346: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 10347: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 10348: #endif
1.191 brouard 10349: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 10350:
1.167 brouard 10351: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
10352: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
10353: // Windows (x64 and x86)
1.191 brouard 10354: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 10355: #elif __unix__ // all unices, not all compilers
10356: // Unix
1.191 brouard 10357: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 10358: #elif __linux__
10359: // linux
1.191 brouard 10360: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 10361: #elif __APPLE__
1.174 brouard 10362: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 10363: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 10364: #endif
10365:
10366: /* __MINGW32__ */
10367: /* __CYGWIN__ */
10368: /* __MINGW64__ */
10369: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
10370: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
10371: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
10372: /* _WIN64 // Defined for applications for Win64. */
10373: /* _M_X64 // Defined for compilations that target x64 processors. */
10374: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 10375:
1.167 brouard 10376: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 10377: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 10378: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 10379: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 10380: #else
1.191 brouard 10381: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 10382: #endif
10383:
1.169 brouard 10384: #if defined(__GNUC__)
10385: # if defined(__GNUC_PATCHLEVEL__)
10386: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10387: + __GNUC_MINOR__ * 100 \
10388: + __GNUC_PATCHLEVEL__)
10389: # else
10390: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10391: + __GNUC_MINOR__ * 100)
10392: # endif
1.174 brouard 10393: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 10394: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 10395:
10396: if (uname(&sysInfo) != -1) {
10397: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 10398: 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 10399: }
10400: else
10401: perror("uname() error");
1.179 brouard 10402: //#ifndef __INTEL_COMPILER
10403: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 10404: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 10405: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 10406: #endif
1.169 brouard 10407: #endif
1.172 brouard 10408:
1.286 brouard 10409: // void main ()
1.172 brouard 10410: // {
1.169 brouard 10411: #if defined(_MSC_VER)
1.174 brouard 10412: if (IsWow64()){
1.191 brouard 10413: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
10414: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 10415: }
10416: else{
1.191 brouard 10417: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
10418: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 10419: }
1.172 brouard 10420: // printf("\nPress Enter to continue...");
10421: // getchar();
10422: // }
10423:
1.169 brouard 10424: #endif
10425:
1.167 brouard 10426:
1.219 brouard 10427: }
1.136 brouard 10428:
1.219 brouard 10429: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.288 brouard 10430: /*--------------- Prevalence limit (forward period or forward stable prevalence) --------------*/
1.235 brouard 10431: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 10432: /* double ftolpl = 1.e-10; */
1.180 brouard 10433: double age, agebase, agelim;
1.203 brouard 10434: double tot;
1.180 brouard 10435:
1.202 brouard 10436: strcpy(filerespl,"PL_");
10437: strcat(filerespl,fileresu);
10438: if((ficrespl=fopen(filerespl,"w"))==NULL) {
1.288 brouard 10439: printf("Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
10440: fprintf(ficlog,"Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
1.202 brouard 10441: }
1.288 brouard 10442: printf("\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
10443: fprintf(ficlog,"\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 10444: pstamp(ficrespl);
1.288 brouard 10445: fprintf(ficrespl,"# Forward period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 10446: fprintf(ficrespl,"#Age ");
10447: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
10448: fprintf(ficrespl,"\n");
1.180 brouard 10449:
1.219 brouard 10450: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 10451:
1.219 brouard 10452: agebase=ageminpar;
10453: agelim=agemaxpar;
1.180 brouard 10454:
1.227 brouard 10455: /* i1=pow(2,ncoveff); */
1.234 brouard 10456: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 10457: if (cptcovn < 1){i1=1;}
1.180 brouard 10458:
1.238 brouard 10459: for(k=1; k<=i1;k++){ /* For each combination k of dummy covariates in the model */
10460: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 10461: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10462: continue;
1.235 brouard 10463:
1.238 brouard 10464: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10465: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
10466: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
10467: /* k=k+1; */
10468: /* to clean */
10469: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10470: fprintf(ficrespl,"#******");
10471: printf("#******");
10472: fprintf(ficlog,"#******");
10473: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10474: fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); /* Here problem for varying dummy*/
10475: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10476: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10477: }
10478: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
10479: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10480: fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10481: fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10482: }
10483: fprintf(ficrespl,"******\n");
10484: printf("******\n");
10485: fprintf(ficlog,"******\n");
10486: if(invalidvarcomb[k]){
10487: printf("\nCombination (%d) ignored because no case \n",k);
10488: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
10489: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
10490: continue;
10491: }
1.219 brouard 10492:
1.238 brouard 10493: fprintf(ficrespl,"#Age ");
10494: for(j=1;j<=cptcoveff;j++) {
10495: fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10496: }
10497: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
10498: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 10499:
1.238 brouard 10500: for (age=agebase; age<=agelim; age++){
10501: /* for (age=agebase; age<=agebase; age++){ */
10502: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres);
10503: fprintf(ficrespl,"%.0f ",age );
10504: for(j=1;j<=cptcoveff;j++)
10505: fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10506: tot=0.;
10507: for(i=1; i<=nlstate;i++){
10508: tot += prlim[i][i];
10509: fprintf(ficrespl," %.5f", prlim[i][i]);
10510: }
10511: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
10512: } /* Age */
10513: /* was end of cptcod */
10514: } /* cptcov */
10515: } /* nres */
1.219 brouard 10516: return 0;
1.180 brouard 10517: }
10518:
1.218 brouard 10519: 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 10520: /*--------------- Back Prevalence limit (backward stable prevalence) --------------*/
1.218 brouard 10521:
10522: /* Computes the back prevalence limit for any combination of covariate values
10523: * at any age between ageminpar and agemaxpar
10524: */
1.235 brouard 10525: int i, j, k, i1, nres=0 ;
1.217 brouard 10526: /* double ftolpl = 1.e-10; */
10527: double age, agebase, agelim;
10528: double tot;
1.218 brouard 10529: /* double ***mobaverage; */
10530: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 10531:
10532: strcpy(fileresplb,"PLB_");
10533: strcat(fileresplb,fileresu);
10534: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
1.288 brouard 10535: printf("Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
10536: fprintf(ficlog,"Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
1.217 brouard 10537: }
1.288 brouard 10538: printf("Computing backward prevalence: result on file '%s' \n", fileresplb);
10539: fprintf(ficlog,"Computing backward prevalence: result on file '%s' \n", fileresplb);
1.217 brouard 10540: pstamp(ficresplb);
1.288 brouard 10541: fprintf(ficresplb,"# Backward prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.217 brouard 10542: fprintf(ficresplb,"#Age ");
10543: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
10544: fprintf(ficresplb,"\n");
10545:
1.218 brouard 10546:
10547: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
10548:
10549: agebase=ageminpar;
10550: agelim=agemaxpar;
10551:
10552:
1.227 brouard 10553: i1=pow(2,cptcoveff);
1.218 brouard 10554: if (cptcovn < 1){i1=1;}
1.227 brouard 10555:
1.238 brouard 10556: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10557: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 10558: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10559: continue;
10560: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10561: fprintf(ficresplb,"#******");
10562: printf("#******");
10563: fprintf(ficlog,"#******");
10564: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10565: fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10566: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10567: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10568: }
10569: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
10570: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10571: fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10572: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10573: }
10574: fprintf(ficresplb,"******\n");
10575: printf("******\n");
10576: fprintf(ficlog,"******\n");
10577: if(invalidvarcomb[k]){
10578: printf("\nCombination (%d) ignored because no cases \n",k);
10579: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
10580: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
10581: continue;
10582: }
1.218 brouard 10583:
1.238 brouard 10584: fprintf(ficresplb,"#Age ");
10585: for(j=1;j<=cptcoveff;j++) {
10586: fprintf(ficresplb,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10587: }
10588: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
10589: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 10590:
10591:
1.238 brouard 10592: for (age=agebase; age<=agelim; age++){
10593: /* for (age=agebase; age<=agebase; age++){ */
10594: if(mobilavproj > 0){
10595: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
10596: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 10597: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 10598: }else if (mobilavproj == 0){
10599: 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);
10600: 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);
10601: exit(1);
10602: }else{
10603: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 10604: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 10605: /* printf("TOTOT\n"); */
10606: /* exit(1); */
1.238 brouard 10607: }
10608: fprintf(ficresplb,"%.0f ",age );
10609: for(j=1;j<=cptcoveff;j++)
10610: fprintf(ficresplb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10611: tot=0.;
10612: for(i=1; i<=nlstate;i++){
10613: tot += bprlim[i][i];
10614: fprintf(ficresplb," %.5f", bprlim[i][i]);
10615: }
10616: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
10617: } /* Age */
10618: /* was end of cptcod */
1.255 brouard 10619: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.238 brouard 10620: } /* end of any combination */
10621: } /* end of nres */
1.218 brouard 10622: /* hBijx(p, bage, fage); */
10623: /* fclose(ficrespijb); */
10624:
10625: return 0;
1.217 brouard 10626: }
1.218 brouard 10627:
1.180 brouard 10628: int hPijx(double *p, int bage, int fage){
10629: /*------------- h Pij x at various ages ------------*/
10630:
10631: int stepsize;
10632: int agelim;
10633: int hstepm;
10634: int nhstepm;
1.235 brouard 10635: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 10636:
10637: double agedeb;
10638: double ***p3mat;
10639:
1.201 brouard 10640: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
1.180 brouard 10641: if((ficrespij=fopen(filerespij,"w"))==NULL) {
10642: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
10643: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
10644: }
10645: printf("Computing pij: result on file '%s' \n", filerespij);
10646: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
10647:
10648: stepsize=(int) (stepm+YEARM-1)/YEARM;
10649: /*if (stepm<=24) stepsize=2;*/
10650:
10651: agelim=AGESUP;
10652: hstepm=stepsize*YEARM; /* Every year of age */
10653: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
1.218 brouard 10654:
1.180 brouard 10655: /* hstepm=1; aff par mois*/
10656: pstamp(ficrespij);
10657: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
1.227 brouard 10658: i1= pow(2,cptcoveff);
1.218 brouard 10659: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10660: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
10661: /* k=k+1; */
1.235 brouard 10662: for(nres=1; nres <= nresult; nres++) /* For each resultline */
10663: for(k=1; k<=i1;k++){
1.253 brouard 10664: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 10665: continue;
1.183 brouard 10666: fprintf(ficrespij,"\n#****** ");
1.227 brouard 10667: for(j=1;j<=cptcoveff;j++)
1.198 brouard 10668: fprintf(ficrespij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 10669: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
10670: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10671: fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10672: }
1.183 brouard 10673: fprintf(ficrespij,"******\n");
10674:
10675: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
10676: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
10677: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
10678:
10679: /* nhstepm=nhstepm*YEARM; aff par mois*/
1.180 brouard 10680:
1.183 brouard 10681: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10682: oldm=oldms;savm=savms;
1.235 brouard 10683: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.183 brouard 10684: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
10685: for(i=1; i<=nlstate;i++)
10686: for(j=1; j<=nlstate+ndeath;j++)
10687: fprintf(ficrespij," %1d-%1d",i,j);
10688: fprintf(ficrespij,"\n");
10689: for (h=0; h<=nhstepm; h++){
10690: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
10691: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.180 brouard 10692: for(i=1; i<=nlstate;i++)
10693: for(j=1; j<=nlstate+ndeath;j++)
1.183 brouard 10694: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.180 brouard 10695: fprintf(ficrespij,"\n");
10696: }
1.183 brouard 10697: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10698: fprintf(ficrespij,"\n");
10699: }
1.180 brouard 10700: /*}*/
10701: }
1.218 brouard 10702: return 0;
1.180 brouard 10703: }
1.218 brouard 10704:
10705: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 10706: /*------------- h Bij x at various ages ------------*/
10707:
10708: int stepsize;
1.218 brouard 10709: /* int agelim; */
10710: int ageminl;
1.217 brouard 10711: int hstepm;
10712: int nhstepm;
1.238 brouard 10713: int h, i, i1, j, k, nres;
1.218 brouard 10714:
1.217 brouard 10715: double agedeb;
10716: double ***p3mat;
1.218 brouard 10717:
10718: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
10719: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
10720: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
10721: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
10722: }
10723: printf("Computing pij back: result on file '%s' \n", filerespijb);
10724: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
10725:
10726: stepsize=(int) (stepm+YEARM-1)/YEARM;
10727: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 10728:
1.218 brouard 10729: /* agelim=AGESUP; */
1.289 brouard 10730: ageminl=AGEINF; /* was 30 */
1.218 brouard 10731: hstepm=stepsize*YEARM; /* Every year of age */
10732: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
10733:
10734: /* hstepm=1; aff par mois*/
10735: pstamp(ficrespijb);
1.255 brouard 10736: 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 10737: i1= pow(2,cptcoveff);
1.218 brouard 10738: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10739: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
10740: /* k=k+1; */
1.238 brouard 10741: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10742: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 10743: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10744: continue;
10745: fprintf(ficrespijb,"\n#****** ");
10746: for(j=1;j<=cptcoveff;j++)
10747: fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10748: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
10749: fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10750: }
10751: fprintf(ficrespijb,"******\n");
1.264 brouard 10752: if(invalidvarcomb[k]){ /* Is it necessary here? */
1.238 brouard 10753: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
10754: continue;
10755: }
10756:
10757: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
10758: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
10759: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
1.297 brouard 10760: 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 */
10761: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 or 28*/
1.238 brouard 10762:
10763: /* nhstepm=nhstepm*YEARM; aff par mois*/
10764:
1.266 brouard 10765: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
10766: /* and memory limitations if stepm is small */
10767:
1.238 brouard 10768: /* oldm=oldms;savm=savms; */
10769: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.267 brouard 10770: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.238 brouard 10771: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
1.255 brouard 10772: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
1.217 brouard 10773: for(i=1; i<=nlstate;i++)
10774: for(j=1; j<=nlstate+ndeath;j++)
1.238 brouard 10775: fprintf(ficrespijb," %1d-%1d",i,j);
1.217 brouard 10776: fprintf(ficrespijb,"\n");
1.238 brouard 10777: for (h=0; h<=nhstepm; h++){
10778: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
10779: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
10780: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
10781: for(i=1; i<=nlstate;i++)
10782: for(j=1; j<=nlstate+ndeath;j++)
10783: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);
10784: fprintf(ficrespijb,"\n");
10785: }
10786: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10787: fprintf(ficrespijb,"\n");
10788: } /* end age deb */
10789: } /* end combination */
10790: } /* end nres */
1.218 brouard 10791: return 0;
10792: } /* hBijx */
1.217 brouard 10793:
1.180 brouard 10794:
1.136 brouard 10795: /***********************************************/
10796: /**************** Main Program *****************/
10797: /***********************************************/
10798:
10799: int main(int argc, char *argv[])
10800: {
10801: #ifdef GSL
10802: const gsl_multimin_fminimizer_type *T;
10803: size_t iteri = 0, it;
10804: int rval = GSL_CONTINUE;
10805: int status = GSL_SUCCESS;
10806: double ssval;
10807: #endif
10808: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.290 brouard 10809: int i,j, k, iter=0,m,size=100, cptcod; /* Suppressing because nobs */
10810: /* int i,j, k, n=MAXN,iter=0,m,size=100, cptcod; */
1.209 brouard 10811: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 10812: int jj, ll, li, lj, lk;
1.136 brouard 10813: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 10814: int num_filled;
1.136 brouard 10815: int itimes;
10816: int NDIM=2;
10817: int vpopbased=0;
1.235 brouard 10818: int nres=0;
1.258 brouard 10819: int endishere=0;
1.277 brouard 10820: int noffset=0;
1.274 brouard 10821: int ncurrv=0; /* Temporary variable */
10822:
1.164 brouard 10823: char ca[32], cb[32];
1.136 brouard 10824: /* FILE *fichtm; *//* Html File */
10825: /* FILE *ficgp;*/ /*Gnuplot File */
10826: struct stat info;
1.191 brouard 10827: double agedeb=0.;
1.194 brouard 10828:
10829: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 10830: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 10831:
1.165 brouard 10832: double fret;
1.191 brouard 10833: double dum=0.; /* Dummy variable */
1.136 brouard 10834: double ***p3mat;
1.218 brouard 10835: /* double ***mobaverage; */
1.164 brouard 10836:
10837: char line[MAXLINE];
1.197 brouard 10838: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
10839:
1.234 brouard 10840: char modeltemp[MAXLINE];
1.230 brouard 10841: char resultline[MAXLINE];
10842:
1.136 brouard 10843: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 10844: char *tok, *val; /* pathtot */
1.290 brouard 10845: int firstobs=1, lastobs=10; /* nobs = lastobs-firstobs declared globally ;*/
1.195 brouard 10846: int c, h , cpt, c2;
1.191 brouard 10847: int jl=0;
10848: int i1, j1, jk, stepsize=0;
1.194 brouard 10849: int count=0;
10850:
1.164 brouard 10851: int *tab;
1.136 brouard 10852: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.296 brouard 10853: /* double anprojd, mprojd, jprojd; /\* For eventual projections *\/ */
10854: /* double anprojf, mprojf, jprojf; */
10855: /* double jintmean,mintmean,aintmean; */
10856: int prvforecast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
10857: int prvbackcast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
10858: double yrfproj= 10.0; /* Number of years of forward projections */
10859: double yrbproj= 10.0; /* Number of years of backward projections */
10860: int prevbcast=0; /* defined as global for mlikeli and mle, replacing backcast */
1.136 brouard 10861: int mobilav=0,popforecast=0;
1.191 brouard 10862: int hstepm=0, nhstepm=0;
1.136 brouard 10863: int agemortsup;
10864: float sumlpop=0.;
10865: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
10866: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
10867:
1.191 brouard 10868: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 10869: double ftolpl=FTOL;
10870: double **prlim;
1.217 brouard 10871: double **bprlim;
1.136 brouard 10872: double ***param; /* Matrix of parameters */
1.251 brouard 10873: double ***paramstart; /* Matrix of starting parameter values */
10874: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 10875: double **matcov; /* Matrix of covariance */
1.203 brouard 10876: double **hess; /* Hessian matrix */
1.136 brouard 10877: double ***delti3; /* Scale */
10878: double *delti; /* Scale */
10879: double ***eij, ***vareij;
10880: double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 10881:
1.136 brouard 10882: double *epj, vepp;
1.164 brouard 10883:
1.273 brouard 10884: double dateprev1, dateprev2;
1.296 brouard 10885: double jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000, dateproj1=0, dateproj2=0, dateprojd=0, dateprojf=0;
10886: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000, dateback1=0, dateback2=0, datebackd=0, datebackf=0;
10887:
1.217 brouard 10888:
1.136 brouard 10889: double **ximort;
1.145 brouard 10890: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 10891: int *dcwave;
10892:
1.164 brouard 10893: char z[1]="c";
1.136 brouard 10894:
10895: /*char *strt;*/
10896: char strtend[80];
1.126 brouard 10897:
1.164 brouard 10898:
1.126 brouard 10899: /* setlocale (LC_ALL, ""); */
10900: /* bindtextdomain (PACKAGE, LOCALEDIR); */
10901: /* textdomain (PACKAGE); */
10902: /* setlocale (LC_CTYPE, ""); */
10903: /* setlocale (LC_MESSAGES, ""); */
10904:
10905: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 10906: rstart_time = time(NULL);
10907: /* (void) gettimeofday(&start_time,&tzp);*/
10908: start_time = *localtime(&rstart_time);
1.126 brouard 10909: curr_time=start_time;
1.157 brouard 10910: /*tml = *localtime(&start_time.tm_sec);*/
10911: /* strcpy(strstart,asctime(&tml)); */
10912: strcpy(strstart,asctime(&start_time));
1.126 brouard 10913:
10914: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 10915: /* tp.tm_sec = tp.tm_sec +86400; */
10916: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 10917: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
10918: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
10919: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 10920: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 10921: /* strt=asctime(&tmg); */
10922: /* printf("Time(after) =%s",strstart); */
10923: /* (void) time (&time_value);
10924: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
10925: * tm = *localtime(&time_value);
10926: * strstart=asctime(&tm);
10927: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
10928: */
10929:
10930: nberr=0; /* Number of errors and warnings */
10931: nbwarn=0;
1.184 brouard 10932: #ifdef WIN32
10933: _getcwd(pathcd, size);
10934: #else
1.126 brouard 10935: getcwd(pathcd, size);
1.184 brouard 10936: #endif
1.191 brouard 10937: syscompilerinfo(0);
1.196 brouard 10938: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 10939: if(argc <=1){
10940: printf("\nEnter the parameter file name: ");
1.205 brouard 10941: if(!fgets(pathr,FILENAMELENGTH,stdin)){
10942: printf("ERROR Empty parameter file name\n");
10943: goto end;
10944: }
1.126 brouard 10945: i=strlen(pathr);
10946: if(pathr[i-1]=='\n')
10947: pathr[i-1]='\0';
1.156 brouard 10948: i=strlen(pathr);
1.205 brouard 10949: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 10950: pathr[i-1]='\0';
1.205 brouard 10951: }
10952: i=strlen(pathr);
10953: if( i==0 ){
10954: printf("ERROR Empty parameter file name\n");
10955: goto end;
10956: }
10957: for (tok = pathr; tok != NULL; ){
1.126 brouard 10958: printf("Pathr |%s|\n",pathr);
10959: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
10960: printf("val= |%s| pathr=%s\n",val,pathr);
10961: strcpy (pathtot, val);
10962: if(pathr[0] == '\0') break; /* Dirty */
10963: }
10964: }
1.281 brouard 10965: else if (argc<=2){
10966: strcpy(pathtot,argv[1]);
10967: }
1.126 brouard 10968: else{
10969: strcpy(pathtot,argv[1]);
1.281 brouard 10970: strcpy(z,argv[2]);
10971: printf("\nargv[2]=%s z=%c\n",argv[2],z[0]);
1.126 brouard 10972: }
10973: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
10974: /*cygwin_split_path(pathtot,path,optionfile);
10975: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
10976: /* cutv(path,optionfile,pathtot,'\\');*/
10977:
10978: /* Split argv[0], imach program to get pathimach */
10979: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
10980: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
10981: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
10982: /* strcpy(pathimach,argv[0]); */
10983: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
10984: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
10985: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 10986: #ifdef WIN32
10987: _chdir(path); /* Can be a relative path */
10988: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
10989: #else
1.126 brouard 10990: chdir(path); /* Can be a relative path */
1.184 brouard 10991: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
10992: #endif
10993: printf("Current directory %s!\n",pathcd);
1.126 brouard 10994: strcpy(command,"mkdir ");
10995: strcat(command,optionfilefiname);
10996: if((outcmd=system(command)) != 0){
1.169 brouard 10997: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 10998: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
10999: /* fclose(ficlog); */
11000: /* exit(1); */
11001: }
11002: /* if((imk=mkdir(optionfilefiname))<0){ */
11003: /* perror("mkdir"); */
11004: /* } */
11005:
11006: /*-------- arguments in the command line --------*/
11007:
1.186 brouard 11008: /* Main Log file */
1.126 brouard 11009: strcat(filelog, optionfilefiname);
11010: strcat(filelog,".log"); /* */
11011: if((ficlog=fopen(filelog,"w"))==NULL) {
11012: printf("Problem with logfile %s\n",filelog);
11013: goto end;
11014: }
11015: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 11016: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 11017: fprintf(ficlog,"\nEnter the parameter file name: \n");
11018: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
11019: path=%s \n\
11020: optionfile=%s\n\
11021: optionfilext=%s\n\
1.156 brouard 11022: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 11023:
1.197 brouard 11024: syscompilerinfo(1);
1.167 brouard 11025:
1.126 brouard 11026: printf("Local time (at start):%s",strstart);
11027: fprintf(ficlog,"Local time (at start): %s",strstart);
11028: fflush(ficlog);
11029: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 11030: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 11031:
11032: /* */
11033: strcpy(fileres,"r");
11034: strcat(fileres, optionfilefiname);
1.201 brouard 11035: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 11036: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 11037: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 11038:
1.186 brouard 11039: /* Main ---------arguments file --------*/
1.126 brouard 11040:
11041: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 11042: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
11043: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 11044: fflush(ficlog);
1.149 brouard 11045: /* goto end; */
11046: exit(70);
1.126 brouard 11047: }
11048:
11049: strcpy(filereso,"o");
1.201 brouard 11050: strcat(filereso,fileresu);
1.126 brouard 11051: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
11052: printf("Problem with Output resultfile: %s\n", filereso);
11053: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
11054: fflush(ficlog);
11055: goto end;
11056: }
1.278 brouard 11057: /*-------- Rewriting parameter file ----------*/
11058: strcpy(rfileres,"r"); /* "Rparameterfile */
11059: strcat(rfileres,optionfilefiname); /* Parameter file first name */
11060: strcat(rfileres,"."); /* */
11061: strcat(rfileres,optionfilext); /* Other files have txt extension */
11062: if((ficres =fopen(rfileres,"w"))==NULL) {
11063: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
11064: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
11065: fflush(ficlog);
11066: goto end;
11067: }
11068: fprintf(ficres,"#IMaCh %s\n",version);
1.126 brouard 11069:
1.278 brouard 11070:
1.126 brouard 11071: /* Reads comments: lines beginning with '#' */
11072: numlinepar=0;
1.277 brouard 11073: /* Is it a BOM UTF-8 Windows file? */
11074: /* First parameter line */
1.197 brouard 11075: while(fgets(line, MAXLINE, ficpar)) {
1.277 brouard 11076: noffset=0;
11077: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
11078: {
11079: noffset=noffset+3;
11080: printf("# File is an UTF8 Bom.\n"); // 0xBF
11081: }
11082: else if( line[0] == (char)0xFE && line[1] == (char)0xFF)
11083: {
11084: noffset=noffset+2;
11085: printf("# File is an UTF16BE BOM file\n");
11086: }
11087: else if( line[0] == 0 && line[1] == 0)
11088: {
11089: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
11090: noffset=noffset+4;
11091: printf("# File is an UTF16BE BOM file\n");
11092: }
11093: } else{
11094: ;/*printf(" Not a BOM file\n");*/
11095: }
11096:
1.197 brouard 11097: /* If line starts with a # it is a comment */
1.277 brouard 11098: if (line[noffset] == '#') {
1.197 brouard 11099: numlinepar++;
11100: fputs(line,stdout);
11101: fputs(line,ficparo);
1.278 brouard 11102: fputs(line,ficres);
1.197 brouard 11103: fputs(line,ficlog);
11104: continue;
11105: }else
11106: break;
11107: }
11108: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
11109: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
11110: if (num_filled != 5) {
11111: printf("Should be 5 parameters\n");
1.283 brouard 11112: fprintf(ficlog,"Should be 5 parameters\n");
1.197 brouard 11113: }
1.126 brouard 11114: numlinepar++;
1.197 brouard 11115: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.283 brouard 11116: fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
11117: fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
11118: fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.197 brouard 11119: }
11120: /* Second parameter line */
11121: while(fgets(line, MAXLINE, ficpar)) {
1.283 brouard 11122: /* while(fscanf(ficpar,"%[^\n]", line)) { */
11123: /* If line starts with a # it is a comment. Strangely fgets reads the EOL and fputs doesn't */
1.197 brouard 11124: if (line[0] == '#') {
11125: numlinepar++;
1.283 brouard 11126: printf("%s",line);
11127: fprintf(ficres,"%s",line);
11128: fprintf(ficparo,"%s",line);
11129: fprintf(ficlog,"%s",line);
1.197 brouard 11130: continue;
11131: }else
11132: break;
11133: }
1.223 brouard 11134: 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", \
11135: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
11136: if (num_filled != 11) {
11137: 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 11138: printf("but line=%s\n",line);
1.283 brouard 11139: 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");
11140: fprintf(ficlog,"but line=%s\n",line);
1.197 brouard 11141: }
1.286 brouard 11142: if( lastpass > maxwav){
11143: printf("Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
11144: fprintf(ficlog,"Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
11145: fflush(ficlog);
11146: goto end;
11147: }
11148: 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 11149: 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 11150: 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 11151: 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 11152: }
1.203 brouard 11153: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 11154: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 11155: /* Third parameter line */
11156: while(fgets(line, MAXLINE, ficpar)) {
11157: /* If line starts with a # it is a comment */
11158: if (line[0] == '#') {
11159: numlinepar++;
1.283 brouard 11160: printf("%s",line);
11161: fprintf(ficres,"%s",line);
11162: fprintf(ficparo,"%s",line);
11163: fprintf(ficlog,"%s",line);
1.197 brouard 11164: continue;
11165: }else
11166: break;
11167: }
1.201 brouard 11168: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){
1.279 brouard 11169: if (num_filled != 1){
11170: printf("ERROR %d: Model should be at minimum 'model=1+age' %s\n",num_filled, line);
11171: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age' %s\n",num_filled, line);
1.197 brouard 11172: model[0]='\0';
11173: goto end;
11174: }
11175: else{
11176: if (model[0]=='+'){
11177: for(i=1; i<=strlen(model);i++)
11178: modeltemp[i-1]=model[i];
1.201 brouard 11179: strcpy(model,modeltemp);
1.197 brouard 11180: }
11181: }
1.199 brouard 11182: /* printf(" model=1+age%s modeltemp= %s, model=%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 11183: printf("model=1+age+%s\n",model);fflush(stdout);
1.283 brouard 11184: fprintf(ficparo,"model=1+age+%s\n",model);fflush(stdout);
11185: fprintf(ficres,"model=1+age+%s\n",model);fflush(stdout);
11186: fprintf(ficlog,"model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 11187: }
11188: /* 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); */
11189: /* numlinepar=numlinepar+3; /\* In general *\/ */
11190: /* 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 11191: /* 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); */
11192: /* 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 11193: fflush(ficlog);
1.190 brouard 11194: /* if(model[0]=='#'|| model[0]== '\0'){ */
11195: if(model[0]=='#'){
1.279 brouard 11196: printf("Error in 'model' line: model should start with 'model=1+age+' and end without space \n \
11197: 'model=1+age+' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age' or \n \
11198: 'model=1+age+V1+V2' or 'model=1+age+V1+V2+V1*V2' etc. \n"); \
1.187 brouard 11199: if(mle != -1){
1.279 brouard 11200: 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 11201: exit(1);
11202: }
11203: }
1.126 brouard 11204: while((c=getc(ficpar))=='#' && c!= EOF){
11205: ungetc(c,ficpar);
11206: fgets(line, MAXLINE, ficpar);
11207: numlinepar++;
1.195 brouard 11208: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
11209: z[0]=line[1];
11210: }
11211: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 11212: fputs(line, stdout);
11213: //puts(line);
1.126 brouard 11214: fputs(line,ficparo);
11215: fputs(line,ficlog);
11216: }
11217: ungetc(c,ficpar);
11218:
11219:
1.290 brouard 11220: covar=matrix(0,NCOVMAX,firstobs,lastobs); /**< used in readdata */
11221: if(nqv>=1)coqvar=matrix(1,nqv,firstobs,lastobs); /**< Fixed quantitative covariate */
11222: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,firstobs,lastobs); /**< Time varying quantitative covariate */
11223: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,firstobs,lastobs); /**< Time varying covariate (dummy and quantitative)*/
1.136 brouard 11224: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
11225: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
11226: v1+v2*age+v2*v3 makes cptcovn = 3
11227: */
11228: if (strlen(model)>1)
1.187 brouard 11229: 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 11230: else
1.187 brouard 11231: ncovmodel=2; /* Constant and age */
1.133 brouard 11232: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
11233: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 11234: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
11235: 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);
11236: 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);
11237: fflush(stdout);
11238: fclose (ficlog);
11239: goto end;
11240: }
1.126 brouard 11241: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
11242: delti=delti3[1][1];
11243: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
11244: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 11245: /* We could also provide initial parameters values giving by simple logistic regression
11246: * only one way, that is without matrix product. We will have nlstate maximizations */
11247: /* for(i=1;i<nlstate;i++){ */
11248: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
11249: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
11250: /* } */
1.126 brouard 11251: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 11252: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
11253: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 11254: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
11255: fclose (ficparo);
11256: fclose (ficlog);
11257: goto end;
11258: exit(0);
1.220 brouard 11259: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 11260: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 11261: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
11262: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 11263: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
11264: matcov=matrix(1,npar,1,npar);
1.203 brouard 11265: hess=matrix(1,npar,1,npar);
1.220 brouard 11266: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 11267: /* Read guessed parameters */
1.126 brouard 11268: /* Reads comments: lines beginning with '#' */
11269: while((c=getc(ficpar))=='#' && c!= EOF){
11270: ungetc(c,ficpar);
11271: fgets(line, MAXLINE, ficpar);
11272: numlinepar++;
1.141 brouard 11273: fputs(line,stdout);
1.126 brouard 11274: fputs(line,ficparo);
11275: fputs(line,ficlog);
11276: }
11277: ungetc(c,ficpar);
11278:
11279: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 11280: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 11281: for(i=1; i <=nlstate; i++){
1.234 brouard 11282: j=0;
1.126 brouard 11283: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 11284: if(jj==i) continue;
11285: j++;
1.292 brouard 11286: while((c=getc(ficpar))=='#' && c!= EOF){
11287: ungetc(c,ficpar);
11288: fgets(line, MAXLINE, ficpar);
11289: numlinepar++;
11290: fputs(line,stdout);
11291: fputs(line,ficparo);
11292: fputs(line,ficlog);
11293: }
11294: ungetc(c,ficpar);
1.234 brouard 11295: fscanf(ficpar,"%1d%1d",&i1,&j1);
11296: if ((i1 != i) || (j1 != jj)){
11297: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 11298: It might be a problem of design; if ncovcol and the model are correct\n \
11299: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 11300: exit(1);
11301: }
11302: fprintf(ficparo,"%1d%1d",i1,j1);
11303: if(mle==1)
11304: printf("%1d%1d",i,jj);
11305: fprintf(ficlog,"%1d%1d",i,jj);
11306: for(k=1; k<=ncovmodel;k++){
11307: fscanf(ficpar," %lf",¶m[i][j][k]);
11308: if(mle==1){
11309: printf(" %lf",param[i][j][k]);
11310: fprintf(ficlog," %lf",param[i][j][k]);
11311: }
11312: else
11313: fprintf(ficlog," %lf",param[i][j][k]);
11314: fprintf(ficparo," %lf",param[i][j][k]);
11315: }
11316: fscanf(ficpar,"\n");
11317: numlinepar++;
11318: if(mle==1)
11319: printf("\n");
11320: fprintf(ficlog,"\n");
11321: fprintf(ficparo,"\n");
1.126 brouard 11322: }
11323: }
11324: fflush(ficlog);
1.234 brouard 11325:
1.251 brouard 11326: /* Reads parameters values */
1.126 brouard 11327: p=param[1][1];
1.251 brouard 11328: pstart=paramstart[1][1];
1.126 brouard 11329:
11330: /* Reads comments: lines beginning with '#' */
11331: while((c=getc(ficpar))=='#' && c!= EOF){
11332: ungetc(c,ficpar);
11333: fgets(line, MAXLINE, ficpar);
11334: numlinepar++;
1.141 brouard 11335: fputs(line,stdout);
1.126 brouard 11336: fputs(line,ficparo);
11337: fputs(line,ficlog);
11338: }
11339: ungetc(c,ficpar);
11340:
11341: for(i=1; i <=nlstate; i++){
11342: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 11343: fscanf(ficpar,"%1d%1d",&i1,&j1);
11344: if ( (i1-i) * (j1-j) != 0){
11345: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
11346: exit(1);
11347: }
11348: printf("%1d%1d",i,j);
11349: fprintf(ficparo,"%1d%1d",i1,j1);
11350: fprintf(ficlog,"%1d%1d",i1,j1);
11351: for(k=1; k<=ncovmodel;k++){
11352: fscanf(ficpar,"%le",&delti3[i][j][k]);
11353: printf(" %le",delti3[i][j][k]);
11354: fprintf(ficparo," %le",delti3[i][j][k]);
11355: fprintf(ficlog," %le",delti3[i][j][k]);
11356: }
11357: fscanf(ficpar,"\n");
11358: numlinepar++;
11359: printf("\n");
11360: fprintf(ficparo,"\n");
11361: fprintf(ficlog,"\n");
1.126 brouard 11362: }
11363: }
11364: fflush(ficlog);
1.234 brouard 11365:
1.145 brouard 11366: /* Reads covariance matrix */
1.126 brouard 11367: delti=delti3[1][1];
1.220 brouard 11368:
11369:
1.126 brouard 11370: /* 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 11371:
1.126 brouard 11372: /* Reads comments: lines beginning with '#' */
11373: while((c=getc(ficpar))=='#' && c!= EOF){
11374: ungetc(c,ficpar);
11375: fgets(line, MAXLINE, ficpar);
11376: numlinepar++;
1.141 brouard 11377: fputs(line,stdout);
1.126 brouard 11378: fputs(line,ficparo);
11379: fputs(line,ficlog);
11380: }
11381: ungetc(c,ficpar);
1.220 brouard 11382:
1.126 brouard 11383: matcov=matrix(1,npar,1,npar);
1.203 brouard 11384: hess=matrix(1,npar,1,npar);
1.131 brouard 11385: for(i=1; i <=npar; i++)
11386: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 11387:
1.194 brouard 11388: /* Scans npar lines */
1.126 brouard 11389: for(i=1; i <=npar; i++){
1.226 brouard 11390: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 11391: if(count != 3){
1.226 brouard 11392: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11393: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11394: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11395: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11396: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11397: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11398: exit(1);
1.220 brouard 11399: }else{
1.226 brouard 11400: if(mle==1)
11401: printf("%1d%1d%d",i1,j1,jk);
11402: }
11403: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
11404: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 11405: for(j=1; j <=i; j++){
1.226 brouard 11406: fscanf(ficpar," %le",&matcov[i][j]);
11407: if(mle==1){
11408: printf(" %.5le",matcov[i][j]);
11409: }
11410: fprintf(ficlog," %.5le",matcov[i][j]);
11411: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 11412: }
11413: fscanf(ficpar,"\n");
11414: numlinepar++;
11415: if(mle==1)
1.220 brouard 11416: printf("\n");
1.126 brouard 11417: fprintf(ficlog,"\n");
11418: fprintf(ficparo,"\n");
11419: }
1.194 brouard 11420: /* End of read covariance matrix npar lines */
1.126 brouard 11421: for(i=1; i <=npar; i++)
11422: for(j=i+1;j<=npar;j++)
1.226 brouard 11423: matcov[i][j]=matcov[j][i];
1.126 brouard 11424:
11425: if(mle==1)
11426: printf("\n");
11427: fprintf(ficlog,"\n");
11428:
11429: fflush(ficlog);
11430:
11431: } /* End of mle != -3 */
1.218 brouard 11432:
1.186 brouard 11433: /* Main data
11434: */
1.290 brouard 11435: nobs=lastobs-firstobs+1; /* was = lastobs;*/
11436: /* num=lvector(1,n); */
11437: /* moisnais=vector(1,n); */
11438: /* annais=vector(1,n); */
11439: /* moisdc=vector(1,n); */
11440: /* andc=vector(1,n); */
11441: /* weight=vector(1,n); */
11442: /* agedc=vector(1,n); */
11443: /* cod=ivector(1,n); */
11444: /* for(i=1;i<=n;i++){ */
11445: num=lvector(firstobs,lastobs);
11446: moisnais=vector(firstobs,lastobs);
11447: annais=vector(firstobs,lastobs);
11448: moisdc=vector(firstobs,lastobs);
11449: andc=vector(firstobs,lastobs);
11450: weight=vector(firstobs,lastobs);
11451: agedc=vector(firstobs,lastobs);
11452: cod=ivector(firstobs,lastobs);
11453: for(i=firstobs;i<=lastobs;i++){
1.234 brouard 11454: num[i]=0;
11455: moisnais[i]=0;
11456: annais[i]=0;
11457: moisdc[i]=0;
11458: andc[i]=0;
11459: agedc[i]=0;
11460: cod[i]=0;
11461: weight[i]=1.0; /* Equal weights, 1 by default */
11462: }
1.290 brouard 11463: mint=matrix(1,maxwav,firstobs,lastobs);
11464: anint=matrix(1,maxwav,firstobs,lastobs);
11465: s=imatrix(1,maxwav+1,firstobs,lastobs); /* s[i][j] health state for wave i and individual j */
1.126 brouard 11466: tab=ivector(1,NCOVMAX);
1.144 brouard 11467: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 11468: 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 11469:
1.136 brouard 11470: /* Reads data from file datafile */
11471: if (readdata(datafile, firstobs, lastobs, &imx)==1)
11472: goto end;
11473:
11474: /* Calculation of the number of parameters from char model */
1.234 brouard 11475: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 11476: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
11477: k=3 V4 Tvar[k=3]= 4 (from V4)
11478: k=2 V1 Tvar[k=2]= 1 (from V1)
11479: k=1 Tvar[1]=2 (from V2)
1.234 brouard 11480: */
11481:
11482: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
11483: TvarsDind=ivector(1,NCOVMAX); /* */
11484: TvarsD=ivector(1,NCOVMAX); /* */
11485: TvarsQind=ivector(1,NCOVMAX); /* */
11486: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 11487: TvarF=ivector(1,NCOVMAX); /* */
11488: TvarFind=ivector(1,NCOVMAX); /* */
11489: TvarV=ivector(1,NCOVMAX); /* */
11490: TvarVind=ivector(1,NCOVMAX); /* */
11491: TvarA=ivector(1,NCOVMAX); /* */
11492: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 11493: TvarFD=ivector(1,NCOVMAX); /* */
11494: TvarFDind=ivector(1,NCOVMAX); /* */
11495: TvarFQ=ivector(1,NCOVMAX); /* */
11496: TvarFQind=ivector(1,NCOVMAX); /* */
11497: TvarVD=ivector(1,NCOVMAX); /* */
11498: TvarVDind=ivector(1,NCOVMAX); /* */
11499: TvarVQ=ivector(1,NCOVMAX); /* */
11500: TvarVQind=ivector(1,NCOVMAX); /* */
11501:
1.230 brouard 11502: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 11503: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 11504: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
11505: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
11506: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.137 brouard 11507: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
11508: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
11509: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
11510: */
11511: /* For model-covariate k tells which data-covariate to use but
11512: because this model-covariate is a construction we invent a new column
11513: ncovcol + k1
11514: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
11515: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 11516: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
11517: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 11518: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
11519: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 11520: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 11521: */
1.145 brouard 11522: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
11523: 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 11524: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
11525: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.145 brouard 11526: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 11527: 4 covariates (3 plus signs)
11528: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
11529: */
1.230 brouard 11530: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 11531: * individual dummy, fixed or varying:
11532: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
11533: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 11534: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
11535: * V1 df, V2 qf, V3 & V4 dv, V5 qv
11536: * Tmodelind[1]@9={9,0,3,2,}*/
11537: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
11538: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 11539: * individual quantitative, fixed or varying:
11540: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
11541: * 3, 1, 0, 0, 0, 0, 0, 0},
11542: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.186 brouard 11543: /* Main decodemodel */
11544:
1.187 brouard 11545:
1.223 brouard 11546: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 11547: goto end;
11548:
1.137 brouard 11549: if((double)(lastobs-imx)/(double)imx > 1.10){
11550: nbwarn++;
11551: 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);
11552: 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);
11553: }
1.136 brouard 11554: /* if(mle==1){*/
1.137 brouard 11555: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
11556: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 11557: }
11558:
11559: /*-calculation of age at interview from date of interview and age at death -*/
11560: agev=matrix(1,maxwav,1,imx);
11561:
11562: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
11563: goto end;
11564:
1.126 brouard 11565:
1.136 brouard 11566: agegomp=(int)agemin;
1.290 brouard 11567: free_vector(moisnais,firstobs,lastobs);
11568: free_vector(annais,firstobs,lastobs);
1.126 brouard 11569: /* free_matrix(mint,1,maxwav,1,n);
11570: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 11571: /* free_vector(moisdc,1,n); */
11572: /* free_vector(andc,1,n); */
1.145 brouard 11573: /* */
11574:
1.126 brouard 11575: wav=ivector(1,imx);
1.214 brouard 11576: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
11577: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
11578: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
11579: 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.*/
11580: bh=imatrix(1,lastpass-firstpass+2,1,imx);
11581: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 11582:
11583: /* Concatenates waves */
1.214 brouard 11584: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
11585: Death is a valid wave (if date is known).
11586: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
11587: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
11588: and mw[mi+1][i]. dh depends on stepm.
11589: */
11590:
1.126 brouard 11591: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 11592: /* Concatenates waves */
1.145 brouard 11593:
1.290 brouard 11594: free_vector(moisdc,firstobs,lastobs);
11595: free_vector(andc,firstobs,lastobs);
1.215 brouard 11596:
1.126 brouard 11597: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
11598: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
11599: ncodemax[1]=1;
1.145 brouard 11600: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 11601: cptcoveff=0;
1.220 brouard 11602: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
11603: tricode(&cptcoveff,Tvar,nbcode,imx, Ndum); /**< Fills nbcode[Tvar[j]][l]; */
1.227 brouard 11604: }
11605:
11606: ncovcombmax=pow(2,cptcoveff);
11607: invalidvarcomb=ivector(1, ncovcombmax);
11608: for(i=1;i<ncovcombmax;i++)
11609: invalidvarcomb[i]=0;
11610:
1.211 brouard 11611: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 11612: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 11613: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 11614:
1.200 brouard 11615: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 11616: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 11617: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 11618: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
11619: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
11620: * (currently 0 or 1) in the data.
11621: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
11622: * corresponding modality (h,j).
11623: */
11624:
1.145 brouard 11625: h=0;
11626: /*if (cptcovn > 0) */
1.126 brouard 11627: m=pow(2,cptcoveff);
11628:
1.144 brouard 11629: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 11630: * For k=4 covariates, h goes from 1 to m=2**k
11631: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
11632: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.186 brouard 11633: * h\k 1 2 3 4
1.143 brouard 11634: *______________________________
11635: * 1 i=1 1 i=1 1 i=1 1 i=1 1
11636: * 2 2 1 1 1
11637: * 3 i=2 1 2 1 1
11638: * 4 2 2 1 1
11639: * 5 i=3 1 i=2 1 2 1
11640: * 6 2 1 2 1
11641: * 7 i=4 1 2 2 1
11642: * 8 2 2 2 1
1.197 brouard 11643: * 9 i=5 1 i=3 1 i=2 1 2
11644: * 10 2 1 1 2
11645: * 11 i=6 1 2 1 2
11646: * 12 2 2 1 2
11647: * 13 i=7 1 i=4 1 2 2
11648: * 14 2 1 2 2
11649: * 15 i=8 1 2 2 2
11650: * 16 2 2 2 2
1.143 brouard 11651: */
1.212 brouard 11652: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 11653: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
11654: * and the value of each covariate?
11655: * V1=1, V2=1, V3=2, V4=1 ?
11656: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
11657: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
11658: * In order to get the real value in the data, we use nbcode
11659: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
11660: * We are keeping this crazy system in order to be able (in the future?)
11661: * to have more than 2 values (0 or 1) for a covariate.
11662: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
11663: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
11664: * bbbbbbbb
11665: * 76543210
11666: * h-1 00000101 (6-1=5)
1.219 brouard 11667: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 11668: * &
11669: * 1 00000001 (1)
1.219 brouard 11670: * 00000000 = 1 & ((h-1) >> (k-1))
11671: * +1= 00000001 =1
1.211 brouard 11672: *
11673: * h=14, k=3 => h'=h-1=13, k'=k-1=2
11674: * h' 1101 =2^3+2^2+0x2^1+2^0
11675: * >>k' 11
11676: * & 00000001
11677: * = 00000001
11678: * +1 = 00000010=2 = codtabm(14,3)
11679: * Reverse h=6 and m=16?
11680: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
11681: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
11682: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
11683: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
11684: * V3=decodtabm(14,3,2**4)=2
11685: * h'=13 1101 =2^3+2^2+0x2^1+2^0
11686: *(h-1) >> (j-1) 0011 =13 >> 2
11687: * &1 000000001
11688: * = 000000001
11689: * +1= 000000010 =2
11690: * 2211
11691: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
11692: * V3=2
1.220 brouard 11693: * codtabm and decodtabm are identical
1.211 brouard 11694: */
11695:
1.145 brouard 11696:
11697: free_ivector(Ndum,-1,NCOVMAX);
11698:
11699:
1.126 brouard 11700:
1.186 brouard 11701: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 11702: strcpy(optionfilegnuplot,optionfilefiname);
11703: if(mle==-3)
1.201 brouard 11704: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 11705: strcat(optionfilegnuplot,".gp");
11706:
11707: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
11708: printf("Problem with file %s",optionfilegnuplot);
11709: }
11710: else{
1.204 brouard 11711: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 11712: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 11713: //fprintf(ficgp,"set missing 'NaNq'\n");
11714: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 11715: }
11716: /* fclose(ficgp);*/
1.186 brouard 11717:
11718:
11719: /* Initialisation of --------- index.htm --------*/
1.126 brouard 11720:
11721: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
11722: if(mle==-3)
1.201 brouard 11723: strcat(optionfilehtm,"-MORT_");
1.126 brouard 11724: strcat(optionfilehtm,".htm");
11725: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 11726: printf("Problem with %s \n",optionfilehtm);
11727: exit(0);
1.126 brouard 11728: }
11729:
11730: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
11731: strcat(optionfilehtmcov,"-cov.htm");
11732: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
11733: printf("Problem with %s \n",optionfilehtmcov), exit(0);
11734: }
11735: else{
11736: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
11737: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 11738: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 11739: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
11740: }
11741:
1.213 brouard 11742: 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 11743: <hr size=\"2\" color=\"#EC5E5E\"> \n\
11744: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 11745: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 11746: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n\
1.126 brouard 11747: \n\
11748: <hr size=\"2\" color=\"#EC5E5E\">\
11749: <ul><li><h4>Parameter files</h4>\n\
11750: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
11751: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
11752: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
11753: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
11754: - Date and time at start: %s</ul>\n",\
11755: optionfilehtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model,\
11756: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
11757: fileres,fileres,\
11758: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
11759: fflush(fichtm);
11760:
11761: strcpy(pathr,path);
11762: strcat(pathr,optionfilefiname);
1.184 brouard 11763: #ifdef WIN32
11764: _chdir(optionfilefiname); /* Move to directory named optionfile */
11765: #else
1.126 brouard 11766: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 11767: #endif
11768:
1.126 brouard 11769:
1.220 brouard 11770: /* Calculates basic frequencies. Computes observed prevalence at single age
11771: and for any valid combination of covariates
1.126 brouard 11772: and prints on file fileres'p'. */
1.251 brouard 11773: freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 11774: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 11775:
11776: fprintf(fichtm,"\n");
1.286 brouard 11777: 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 11778: ftol, stepm);
11779: fprintf(fichtm,"\n<li>Number of fixed dummy covariates: ncovcol=%d ", ncovcol);
11780: ncurrv=1;
11781: for(i=ncurrv; i <=ncovcol; i++) fprintf(fichtm,"V%d ", i);
11782: fprintf(fichtm,"\n<li> Number of fixed quantitative variables: nqv=%d ", nqv);
11783: ncurrv=i;
11784: for(i=ncurrv; i <=ncurrv-1+nqv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 11785: fprintf(fichtm,"\n<li> Number of time varying (wave varying) dummy covariates: ntv=%d ", ntv);
1.274 brouard 11786: ncurrv=i;
11787: for(i=ncurrv; i <=ncurrv-1+ntv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 11788: fprintf(fichtm,"\n<li>Number of time varying quantitative covariates: nqtv=%d ", nqtv);
1.274 brouard 11789: ncurrv=i;
11790: for(i=ncurrv; i <=ncurrv-1+nqtv; i++) fprintf(fichtm,"V%d ", i);
11791: 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", \
11792: nlstate, ndeath, maxwav, mle, weightopt);
11793:
11794: fprintf(fichtm,"<h4> Diagram of states <a href=\"%s_.svg\">%s_.svg</a></h4> \n\
11795: <img src=\"%s_.svg\">", subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"));
11796:
11797:
11798: fprintf(fichtm,"\n<h4>Some descriptive statistics </h4>\n<br>Total number of observations=%d <br>\n\
1.126 brouard 11799: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
11800: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
1.274 brouard 11801: imx,agemin,agemax,jmin,jmax,jmean);
1.126 brouard 11802: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 11803: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11804: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11805: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11806: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 11807:
1.126 brouard 11808: /* For Powell, parameters are in a vector p[] starting at p[1]
11809: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
11810: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
11811:
11812: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 11813: /* For mortality only */
1.126 brouard 11814: if (mle==-3){
1.136 brouard 11815: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 11816: for(i=1;i<=NDIM;i++)
11817: for(j=1;j<=NDIM;j++)
11818: ximort[i][j]=0.;
1.186 brouard 11819: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.290 brouard 11820: cens=ivector(firstobs,lastobs);
11821: ageexmed=vector(firstobs,lastobs);
11822: agecens=vector(firstobs,lastobs);
11823: dcwave=ivector(firstobs,lastobs);
1.223 brouard 11824:
1.126 brouard 11825: for (i=1; i<=imx; i++){
11826: dcwave[i]=-1;
11827: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 11828: if (s[m][i]>nlstate) {
11829: dcwave[i]=m;
11830: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
11831: break;
11832: }
1.126 brouard 11833: }
1.226 brouard 11834:
1.126 brouard 11835: for (i=1; i<=imx; i++) {
11836: if (wav[i]>0){
1.226 brouard 11837: ageexmed[i]=agev[mw[1][i]][i];
11838: j=wav[i];
11839: agecens[i]=1.;
11840:
11841: if (ageexmed[i]> 1 && wav[i] > 0){
11842: agecens[i]=agev[mw[j][i]][i];
11843: cens[i]= 1;
11844: }else if (ageexmed[i]< 1)
11845: cens[i]= -1;
11846: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
11847: cens[i]=0 ;
1.126 brouard 11848: }
11849: else cens[i]=-1;
11850: }
11851:
11852: for (i=1;i<=NDIM;i++) {
11853: for (j=1;j<=NDIM;j++)
1.226 brouard 11854: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 11855: }
11856:
1.145 brouard 11857: /*p[1]=0.0268; p[NDIM]=0.083;*/
1.126 brouard 11858: /*printf("%lf %lf", p[1], p[2]);*/
11859:
11860:
1.136 brouard 11861: #ifdef GSL
11862: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 11863: #else
1.126 brouard 11864: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 11865: #endif
1.201 brouard 11866: strcpy(filerespow,"POW-MORT_");
11867: strcat(filerespow,fileresu);
1.126 brouard 11868: if((ficrespow=fopen(filerespow,"w"))==NULL) {
11869: printf("Problem with resultfile: %s\n", filerespow);
11870: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
11871: }
1.136 brouard 11872: #ifdef GSL
11873: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 11874: #else
1.126 brouard 11875: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 11876: #endif
1.126 brouard 11877: /* for (i=1;i<=nlstate;i++)
11878: for(j=1;j<=nlstate+ndeath;j++)
11879: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
11880: */
11881: fprintf(ficrespow,"\n");
1.136 brouard 11882: #ifdef GSL
11883: /* gsl starts here */
11884: T = gsl_multimin_fminimizer_nmsimplex;
11885: gsl_multimin_fminimizer *sfm = NULL;
11886: gsl_vector *ss, *x;
11887: gsl_multimin_function minex_func;
11888:
11889: /* Initial vertex size vector */
11890: ss = gsl_vector_alloc (NDIM);
11891:
11892: if (ss == NULL){
11893: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
11894: }
11895: /* Set all step sizes to 1 */
11896: gsl_vector_set_all (ss, 0.001);
11897:
11898: /* Starting point */
1.126 brouard 11899:
1.136 brouard 11900: x = gsl_vector_alloc (NDIM);
11901:
11902: if (x == NULL){
11903: gsl_vector_free(ss);
11904: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
11905: }
11906:
11907: /* Initialize method and iterate */
11908: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 11909: /* gsl_vector_set(x, 0, 0.0268); */
11910: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 11911: gsl_vector_set(x, 0, p[1]);
11912: gsl_vector_set(x, 1, p[2]);
11913:
11914: minex_func.f = &gompertz_f;
11915: minex_func.n = NDIM;
11916: minex_func.params = (void *)&p; /* ??? */
11917:
11918: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
11919: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
11920:
11921: printf("Iterations beginning .....\n\n");
11922: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
11923:
11924: iteri=0;
11925: while (rval == GSL_CONTINUE){
11926: iteri++;
11927: status = gsl_multimin_fminimizer_iterate(sfm);
11928:
11929: if (status) printf("error: %s\n", gsl_strerror (status));
11930: fflush(0);
11931:
11932: if (status)
11933: break;
11934:
11935: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
11936: ssval = gsl_multimin_fminimizer_size (sfm);
11937:
11938: if (rval == GSL_SUCCESS)
11939: printf ("converged to a local maximum at\n");
11940:
11941: printf("%5d ", iteri);
11942: for (it = 0; it < NDIM; it++){
11943: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
11944: }
11945: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
11946: }
11947:
11948: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
11949:
11950: gsl_vector_free(x); /* initial values */
11951: gsl_vector_free(ss); /* inital step size */
11952: for (it=0; it<NDIM; it++){
11953: p[it+1]=gsl_vector_get(sfm->x,it);
11954: fprintf(ficrespow," %.12lf", p[it]);
11955: }
11956: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
11957: #endif
11958: #ifdef POWELL
11959: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
11960: #endif
1.126 brouard 11961: fclose(ficrespow);
11962:
1.203 brouard 11963: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 11964:
11965: for(i=1; i <=NDIM; i++)
11966: for(j=i+1;j<=NDIM;j++)
1.220 brouard 11967: matcov[i][j]=matcov[j][i];
1.126 brouard 11968:
11969: printf("\nCovariance matrix\n ");
1.203 brouard 11970: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 11971: for(i=1; i <=NDIM; i++) {
11972: for(j=1;j<=NDIM;j++){
1.220 brouard 11973: printf("%f ",matcov[i][j]);
11974: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 11975: }
1.203 brouard 11976: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 11977: }
11978:
11979: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 11980: for (i=1;i<=NDIM;i++) {
1.126 brouard 11981: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 11982: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
11983: }
1.126 brouard 11984: lsurv=vector(1,AGESUP);
11985: lpop=vector(1,AGESUP);
11986: tpop=vector(1,AGESUP);
11987: lsurv[agegomp]=100000;
11988:
11989: for (k=agegomp;k<=AGESUP;k++) {
11990: agemortsup=k;
11991: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
11992: }
11993:
11994: for (k=agegomp;k<agemortsup;k++)
11995: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
11996:
11997: for (k=agegomp;k<agemortsup;k++){
11998: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
11999: sumlpop=sumlpop+lpop[k];
12000: }
12001:
12002: tpop[agegomp]=sumlpop;
12003: for (k=agegomp;k<(agemortsup-3);k++){
12004: /* tpop[k+1]=2;*/
12005: tpop[k+1]=tpop[k]-lpop[k];
12006: }
12007:
12008:
12009: printf("\nAge lx qx dx Lx Tx e(x)\n");
12010: for (k=agegomp;k<(agemortsup-2);k++)
12011: 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]);
12012:
12013:
12014: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 12015: ageminpar=50;
12016: agemaxpar=100;
1.194 brouard 12017: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
12018: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
12019: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12020: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
12021: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
12022: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12023: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 12024: }else{
12025: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
12026: 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 12027: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 12028: }
1.201 brouard 12029: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 12030: stepm, weightopt,\
12031: model,imx,p,matcov,agemortsup);
12032:
12033: free_vector(lsurv,1,AGESUP);
12034: free_vector(lpop,1,AGESUP);
12035: free_vector(tpop,1,AGESUP);
1.220 brouard 12036: free_matrix(ximort,1,NDIM,1,NDIM);
1.290 brouard 12037: free_ivector(dcwave,firstobs,lastobs);
12038: free_vector(agecens,firstobs,lastobs);
12039: free_vector(ageexmed,firstobs,lastobs);
12040: free_ivector(cens,firstobs,lastobs);
1.220 brouard 12041: #ifdef GSL
1.136 brouard 12042: #endif
1.186 brouard 12043: } /* Endof if mle==-3 mortality only */
1.205 brouard 12044: /* Standard */
12045: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
12046: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
12047: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 12048: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 12049: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
12050: for (k=1; k<=npar;k++)
12051: printf(" %d %8.5f",k,p[k]);
12052: printf("\n");
1.205 brouard 12053: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
12054: /* mlikeli uses func not funcone */
1.247 brouard 12055: /* for(i=1;i<nlstate;i++){ */
12056: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
12057: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
12058: /* } */
1.205 brouard 12059: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
12060: }
12061: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
12062: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
12063: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
12064: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
12065: }
12066: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 12067: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
12068: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
12069: for (k=1; k<=npar;k++)
12070: printf(" %d %8.5f",k,p[k]);
12071: printf("\n");
12072:
12073: /*--------- results files --------------*/
1.283 brouard 12074: /* 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 12075:
12076:
12077: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
12078: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
12079: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
12080: for(i=1,jk=1; i <=nlstate; i++){
12081: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 12082: if (k != i) {
12083: printf("%d%d ",i,k);
12084: fprintf(ficlog,"%d%d ",i,k);
12085: fprintf(ficres,"%1d%1d ",i,k);
12086: for(j=1; j <=ncovmodel; j++){
12087: printf("%12.7f ",p[jk]);
12088: fprintf(ficlog,"%12.7f ",p[jk]);
12089: fprintf(ficres,"%12.7f ",p[jk]);
12090: jk++;
12091: }
12092: printf("\n");
12093: fprintf(ficlog,"\n");
12094: fprintf(ficres,"\n");
12095: }
1.126 brouard 12096: }
12097: }
1.203 brouard 12098: if(mle != 0){
12099: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 12100: ftolhess=ftol; /* Usually correct */
1.203 brouard 12101: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
12102: 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");
12103: 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");
12104: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 12105: for(k=1; k <=(nlstate+ndeath); k++){
12106: if (k != i) {
12107: printf("%d%d ",i,k);
12108: fprintf(ficlog,"%d%d ",i,k);
12109: for(j=1; j <=ncovmodel; j++){
12110: 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]));
12111: 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]));
12112: jk++;
12113: }
12114: printf("\n");
12115: fprintf(ficlog,"\n");
12116: }
12117: }
1.193 brouard 12118: }
1.203 brouard 12119: } /* end of hesscov and Wald tests */
1.225 brouard 12120:
1.203 brouard 12121: /* */
1.126 brouard 12122: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
12123: printf("# Scales (for hessian or gradient estimation)\n");
12124: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
12125: for(i=1,jk=1; i <=nlstate; i++){
12126: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 12127: if (j!=i) {
12128: fprintf(ficres,"%1d%1d",i,j);
12129: printf("%1d%1d",i,j);
12130: fprintf(ficlog,"%1d%1d",i,j);
12131: for(k=1; k<=ncovmodel;k++){
12132: printf(" %.5e",delti[jk]);
12133: fprintf(ficlog," %.5e",delti[jk]);
12134: fprintf(ficres," %.5e",delti[jk]);
12135: jk++;
12136: }
12137: printf("\n");
12138: fprintf(ficlog,"\n");
12139: fprintf(ficres,"\n");
12140: }
1.126 brouard 12141: }
12142: }
12143:
12144: 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 12145: if(mle >= 1) /* To big for the screen */
1.126 brouard 12146: 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");
12147: 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");
12148: /* # 121 Var(a12)\n\ */
12149: /* # 122 Cov(b12,a12) Var(b12)\n\ */
12150: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
12151: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
12152: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
12153: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
12154: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
12155: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
12156:
12157:
12158: /* Just to have a covariance matrix which will be more understandable
12159: even is we still don't want to manage dictionary of variables
12160: */
12161: for(itimes=1;itimes<=2;itimes++){
12162: jj=0;
12163: for(i=1; i <=nlstate; i++){
1.225 brouard 12164: for(j=1; j <=nlstate+ndeath; j++){
12165: if(j==i) continue;
12166: for(k=1; k<=ncovmodel;k++){
12167: jj++;
12168: ca[0]= k+'a'-1;ca[1]='\0';
12169: if(itimes==1){
12170: if(mle>=1)
12171: printf("#%1d%1d%d",i,j,k);
12172: fprintf(ficlog,"#%1d%1d%d",i,j,k);
12173: fprintf(ficres,"#%1d%1d%d",i,j,k);
12174: }else{
12175: if(mle>=1)
12176: printf("%1d%1d%d",i,j,k);
12177: fprintf(ficlog,"%1d%1d%d",i,j,k);
12178: fprintf(ficres,"%1d%1d%d",i,j,k);
12179: }
12180: ll=0;
12181: for(li=1;li <=nlstate; li++){
12182: for(lj=1;lj <=nlstate+ndeath; lj++){
12183: if(lj==li) continue;
12184: for(lk=1;lk<=ncovmodel;lk++){
12185: ll++;
12186: if(ll<=jj){
12187: cb[0]= lk +'a'-1;cb[1]='\0';
12188: if(ll<jj){
12189: if(itimes==1){
12190: if(mle>=1)
12191: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12192: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12193: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12194: }else{
12195: if(mle>=1)
12196: printf(" %.5e",matcov[jj][ll]);
12197: fprintf(ficlog," %.5e",matcov[jj][ll]);
12198: fprintf(ficres," %.5e",matcov[jj][ll]);
12199: }
12200: }else{
12201: if(itimes==1){
12202: if(mle>=1)
12203: printf(" Var(%s%1d%1d)",ca,i,j);
12204: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
12205: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
12206: }else{
12207: if(mle>=1)
12208: printf(" %.7e",matcov[jj][ll]);
12209: fprintf(ficlog," %.7e",matcov[jj][ll]);
12210: fprintf(ficres," %.7e",matcov[jj][ll]);
12211: }
12212: }
12213: }
12214: } /* end lk */
12215: } /* end lj */
12216: } /* end li */
12217: if(mle>=1)
12218: printf("\n");
12219: fprintf(ficlog,"\n");
12220: fprintf(ficres,"\n");
12221: numlinepar++;
12222: } /* end k*/
12223: } /*end j */
1.126 brouard 12224: } /* end i */
12225: } /* end itimes */
12226:
12227: fflush(ficlog);
12228: fflush(ficres);
1.225 brouard 12229: while(fgets(line, MAXLINE, ficpar)) {
12230: /* If line starts with a # it is a comment */
12231: if (line[0] == '#') {
12232: numlinepar++;
12233: fputs(line,stdout);
12234: fputs(line,ficparo);
12235: fputs(line,ficlog);
1.299 brouard 12236: fputs(line,ficres);
1.225 brouard 12237: continue;
12238: }else
12239: break;
12240: }
12241:
1.209 brouard 12242: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
12243: /* ungetc(c,ficpar); */
12244: /* fgets(line, MAXLINE, ficpar); */
12245: /* fputs(line,stdout); */
12246: /* fputs(line,ficparo); */
12247: /* } */
12248: /* ungetc(c,ficpar); */
1.126 brouard 12249:
12250: estepm=0;
1.209 brouard 12251: 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 12252:
12253: if (num_filled != 6) {
12254: 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);
12255: 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);
12256: goto end;
12257: }
12258: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
12259: }
12260: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
12261: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
12262:
1.209 brouard 12263: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 12264: if (estepm==0 || estepm < stepm) estepm=stepm;
12265: if (fage <= 2) {
12266: bage = ageminpar;
12267: fage = agemaxpar;
12268: }
12269:
12270: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 12271: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
12272: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 12273:
1.186 brouard 12274: /* Other stuffs, more or less useful */
1.254 brouard 12275: while(fgets(line, MAXLINE, ficpar)) {
12276: /* If line starts with a # it is a comment */
12277: if (line[0] == '#') {
12278: numlinepar++;
12279: fputs(line,stdout);
12280: fputs(line,ficparo);
12281: fputs(line,ficlog);
1.299 brouard 12282: fputs(line,ficres);
1.254 brouard 12283: continue;
12284: }else
12285: break;
12286: }
12287:
12288: 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){
12289:
12290: if (num_filled != 7) {
12291: 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);
12292: 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);
12293: goto end;
12294: }
12295: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
12296: 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);
12297: 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);
12298: 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 12299: }
1.254 brouard 12300:
12301: while(fgets(line, MAXLINE, ficpar)) {
12302: /* If line starts with a # it is a comment */
12303: if (line[0] == '#') {
12304: numlinepar++;
12305: fputs(line,stdout);
12306: fputs(line,ficparo);
12307: fputs(line,ficlog);
1.299 brouard 12308: fputs(line,ficres);
1.254 brouard 12309: continue;
12310: }else
12311: break;
1.126 brouard 12312: }
12313:
12314:
12315: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
12316: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
12317:
1.254 brouard 12318: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
12319: if (num_filled != 1) {
12320: 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);
12321: 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);
12322: goto end;
12323: }
12324: printf("pop_based=%d\n",popbased);
12325: fprintf(ficlog,"pop_based=%d\n",popbased);
12326: fprintf(ficparo,"pop_based=%d\n",popbased);
12327: fprintf(ficres,"pop_based=%d\n",popbased);
12328: }
12329:
1.258 brouard 12330: /* Results */
12331: nresult=0;
12332: do{
12333: if(!fgets(line, MAXLINE, ficpar)){
12334: endishere=1;
12335: parameterline=14;
12336: }else if (line[0] == '#') {
12337: /* If line starts with a # it is a comment */
1.254 brouard 12338: numlinepar++;
12339: fputs(line,stdout);
12340: fputs(line,ficparo);
12341: fputs(line,ficlog);
1.299 brouard 12342: fputs(line,ficres);
1.254 brouard 12343: continue;
1.258 brouard 12344: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
12345: parameterline=11;
1.296 brouard 12346: else if(sscanf(line,"prevbackcast=%[^\n]\n",modeltemp))
1.258 brouard 12347: parameterline=12;
12348: else if(sscanf(line,"result:%[^\n]\n",modeltemp))
12349: parameterline=13;
12350: else{
12351: parameterline=14;
1.254 brouard 12352: }
1.258 brouard 12353: switch (parameterline){
12354: case 11:
1.296 brouard 12355: 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)){
12356: 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 12357: 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);
12358: 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);
12359: 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);
12360: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 12361: dateproj1=anproj1+(mproj1-1)/12.+(jproj1-1)/365.;
12362: dateproj2=anproj2+(mproj2-1)/12.+(jproj2-1)/365.;
1.296 brouard 12363: prvforecast = 1;
12364: }
12365: else if((num_filled=sscanf(line,"prevforecast=%d yearsfproj=%lf mobil_average=%d\n",&prevfcast,&yrfproj,&mobilavproj)) !=EOF){/* && (num_filled == 3))*/
1.299 brouard 12366: printf("prevforecast=%d yearsfproj=%lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
12367: fprintf(ficlog,"prevforecast=%d yearsfproj=%lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
12368: fprintf(ficres,"prevforecast=%d yearsfproj=%lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
1.296 brouard 12369: prvforecast = 2;
12370: }
12371: else {
12372: 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);
12373: 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);
12374: goto end;
1.258 brouard 12375: }
1.254 brouard 12376: break;
1.258 brouard 12377: case 12:
1.296 brouard 12378: 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)){
12379: 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);
12380: 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);
12381: 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);
12382: 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);
12383: /* day and month of back2 are not used but only year anback2.*/
1.273 brouard 12384: dateback1=anback1+(mback1-1)/12.+(jback1-1)/365.;
12385: dateback2=anback2+(mback2-1)/12.+(jback2-1)/365.;
1.296 brouard 12386: prvbackcast = 1;
12387: }
12388: else if((num_filled=sscanf(line,"prevbackcast=%d yearsbproj=%lf mobil_average=%d\n",&prevbcast,&yrbproj,&mobilavproj)) ==3){/* && (num_filled == 3))*/
1.299 brouard 12389: printf("prevbackcast=%d yearsbproj=%lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
12390: fprintf(ficlog,"prevbackcast=%d yearsfproj=%lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
12391: fprintf(ficres,"prevbackcast=%d yearsfproj=%lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
1.296 brouard 12392: prvbackcast = 2;
12393: }
12394: else {
12395: 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);
12396: 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);
12397: goto end;
1.258 brouard 12398: }
1.230 brouard 12399: break;
1.258 brouard 12400: case 13:
12401: if((num_filled=sscanf(line,"result:%[^\n]\n",resultline)) !=EOF){
12402: if (num_filled == 0){
12403: resultline[0]='\0';
12404: printf("Warning %d: no result line! It should be at minimum 'result: V2=0 V1=1 or result:.\n%s\n", num_filled, line);
12405: 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);
12406: break;
12407: } else if (num_filled != 1){
12408: printf("ERROR %d: result line! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",num_filled, line);
12409: fprintf(ficlog,"ERROR %d: result line! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",num_filled, line);
12410: }
12411: nresult++; /* Sum of resultlines */
12412: printf("Result %d: result=%s\n",nresult, resultline);
12413: if(nresult > MAXRESULTLINES){
12414: printf("ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\n",MAXRESULTLINES,nresult);
12415: fprintf(ficlog,"ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\n",MAXRESULTLINES,nresult);
12416: goto end;
12417: }
12418: decoderesult(resultline, nresult); /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
12419: fprintf(ficparo,"result: %s\n",resultline);
12420: fprintf(ficres,"result: %s\n",resultline);
12421: fprintf(ficlog,"result: %s\n",resultline);
1.230 brouard 12422: break;
1.258 brouard 12423: case 14:
1.259 brouard 12424: if(ncovmodel >2 && nresult==0 ){
12425: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 12426: goto end;
12427: }
1.259 brouard 12428: break;
1.258 brouard 12429: default:
12430: nresult=1;
12431: decoderesult(".",nresult ); /* No covariate */
12432: }
12433: } /* End switch parameterline */
12434: }while(endishere==0); /* End do */
1.126 brouard 12435:
1.230 brouard 12436: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 12437: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 12438:
12439: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 12440: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 12441: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 12442: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12443: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 12444: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 12445: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12446: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 12447: }else{
1.270 brouard 12448: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
1.296 brouard 12449: /* It seems that anprojd which is computed from the mean year at interview which is known yet because of freqsummary */
12450: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */ /* Done in freqsummary */
12451: if(prvforecast==1){
12452: dateprojd=(jproj1+12*mproj1+365*anproj1)/365;
12453: jprojd=jproj1;
12454: mprojd=mproj1;
12455: anprojd=anproj1;
12456: dateprojf=(jproj2+12*mproj2+365*anproj2)/365;
12457: jprojf=jproj2;
12458: mprojf=mproj2;
12459: anprojf=anproj2;
12460: } else if(prvforecast == 2){
12461: dateprojd=dateintmean;
12462: date2dmy(dateprojd,&jprojd, &mprojd, &anprojd);
12463: dateprojf=dateintmean+yrfproj;
12464: date2dmy(dateprojf,&jprojf, &mprojf, &anprojf);
12465: }
12466: if(prvbackcast==1){
12467: datebackd=(jback1+12*mback1+365*anback1)/365;
12468: jbackd=jback1;
12469: mbackd=mback1;
12470: anbackd=anback1;
12471: datebackf=(jback2+12*mback2+365*anback2)/365;
12472: jbackf=jback2;
12473: mbackf=mback2;
12474: anbackf=anback2;
12475: } else if(prvbackcast == 2){
12476: datebackd=dateintmean;
12477: date2dmy(datebackd,&jbackd, &mbackd, &anbackd);
12478: datebackf=dateintmean-yrbproj;
12479: date2dmy(datebackf,&jbackf, &mbackf, &anbackf);
12480: }
12481:
12482: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, prevbcast, pathc,p, (int)anprojd-bage, (int)anbackd-fage);
1.220 brouard 12483: }
12484: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.296 brouard 12485: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,prevbcast, estepm, \
12486: jprev1,mprev1,anprev1,dateprev1, dateprojd, datebackd,jprev2,mprev2,anprev2,dateprev2,dateprojf, datebackf);
1.220 brouard 12487:
1.225 brouard 12488: /*------------ free_vector -------------*/
12489: /* chdir(path); */
1.220 brouard 12490:
1.215 brouard 12491: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
12492: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
12493: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
12494: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.290 brouard 12495: free_lvector(num,firstobs,lastobs);
12496: free_vector(agedc,firstobs,lastobs);
1.126 brouard 12497: /*free_matrix(covar,0,NCOVMAX,1,n);*/
12498: /*free_matrix(covar,1,NCOVMAX,1,n);*/
12499: fclose(ficparo);
12500: fclose(ficres);
1.220 brouard 12501:
12502:
1.186 brouard 12503: /* Other results (useful)*/
1.220 brouard 12504:
12505:
1.126 brouard 12506: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 12507: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
12508: prlim=matrix(1,nlstate,1,nlstate);
1.209 brouard 12509: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 12510: fclose(ficrespl);
12511:
12512: /*------------- h Pij x at various ages ------------*/
1.180 brouard 12513: /*#include "hpijx.h"*/
12514: hPijx(p, bage, fage);
1.145 brouard 12515: fclose(ficrespij);
1.227 brouard 12516:
1.220 brouard 12517: /* ncovcombmax= pow(2,cptcoveff); */
1.219 brouard 12518: /*-------------- Variance of one-step probabilities---*/
1.145 brouard 12519: k=1;
1.126 brouard 12520: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 12521:
1.269 brouard 12522: /* Prevalence for each covariate combination in probs[age][status][cov] */
12523: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
12524: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 12525: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 12526: for(k=1;k<=ncovcombmax;k++)
12527: probs[i][j][k]=0.;
1.269 brouard 12528: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
12529: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 12530: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 12531: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
12532: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 12533: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 12534: for(k=1;k<=ncovcombmax;k++)
12535: mobaverages[i][j][k]=0.;
1.219 brouard 12536: mobaverage=mobaverages;
12537: if (mobilav!=0) {
1.235 brouard 12538: printf("Movingaveraging observed prevalence\n");
1.258 brouard 12539: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 12540: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
12541: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
12542: printf(" Error in movingaverage mobilav=%d\n",mobilav);
12543: }
1.269 brouard 12544: } else if (mobilavproj !=0) {
1.235 brouard 12545: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 12546: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 12547: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
12548: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
12549: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
12550: }
1.269 brouard 12551: }else{
12552: printf("Internal error moving average\n");
12553: fflush(stdout);
12554: exit(1);
1.219 brouard 12555: }
12556: }/* end if moving average */
1.227 brouard 12557:
1.126 brouard 12558: /*---------- Forecasting ------------------*/
1.296 brouard 12559: if(prevfcast==1){
12560: /* /\* if(stepm ==1){*\/ */
12561: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
12562: /*This done previously after freqsummary.*/
12563: /* dateprojd=(jproj1+12*mproj1+365*anproj1)/365; */
12564: /* dateprojf=(jproj2+12*mproj2+365*anproj2)/365; */
12565:
12566: /* } else if (prvforecast==2){ */
12567: /* /\* if(stepm ==1){*\/ */
12568: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
12569: /* } */
12570: /*prevforecast(fileresu, dateintmean, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);*/
12571: prevforecast(fileresu,dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, p, cptcoveff);
1.126 brouard 12572: }
1.269 brouard 12573:
1.296 brouard 12574: /* Prevbcasting */
12575: if(prevbcast==1){
1.219 brouard 12576: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12577: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12578: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12579:
12580: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
12581:
12582: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 12583:
1.219 brouard 12584: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
12585: fclose(ficresplb);
12586:
1.222 brouard 12587: hBijx(p, bage, fage, mobaverage);
12588: fclose(ficrespijb);
1.219 brouard 12589:
1.296 brouard 12590: /* /\* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, *\/ */
12591: /* /\* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); *\/ */
12592: /* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, */
12593: /* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); */
12594: prevbackforecast(fileresu, mobaverage, dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2,
12595: mobilavproj, bage, fage, firstpass, lastpass, p, cptcoveff);
12596:
12597:
1.269 brouard 12598: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 12599:
12600:
1.269 brouard 12601: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 12602: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
12603: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
12604: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.296 brouard 12605: } /* end Prevbcasting */
1.268 brouard 12606:
1.186 brouard 12607:
12608: /* ------ Other prevalence ratios------------ */
1.126 brouard 12609:
1.215 brouard 12610: free_ivector(wav,1,imx);
12611: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
12612: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
12613: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 12614:
12615:
1.127 brouard 12616: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 12617:
1.201 brouard 12618: strcpy(filerese,"E_");
12619: strcat(filerese,fileresu);
1.126 brouard 12620: if((ficreseij=fopen(filerese,"w"))==NULL) {
12621: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
12622: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
12623: }
1.208 brouard 12624: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
12625: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 12626:
12627: pstamp(ficreseij);
1.219 brouard 12628:
1.235 brouard 12629: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
12630: if (cptcovn < 1){i1=1;}
12631:
12632: for(nres=1; nres <= nresult; nres++) /* For each resultline */
12633: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 12634: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 12635: continue;
1.219 brouard 12636: fprintf(ficreseij,"\n#****** ");
1.235 brouard 12637: printf("\n#****** ");
1.225 brouard 12638: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 12639: fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 12640: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12641: }
12642: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12643: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12644: fprintf(ficreseij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
1.219 brouard 12645: }
12646: fprintf(ficreseij,"******\n");
1.235 brouard 12647: printf("******\n");
1.219 brouard 12648:
12649: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12650: oldm=oldms;savm=savms;
1.235 brouard 12651: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 12652:
1.219 brouard 12653: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 12654: }
12655: fclose(ficreseij);
1.208 brouard 12656: printf("done evsij\n");fflush(stdout);
12657: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 12658:
1.218 brouard 12659:
1.227 brouard 12660: /*---------- State-specific expectancies and variances ------------*/
1.218 brouard 12661:
1.201 brouard 12662: strcpy(filerest,"T_");
12663: strcat(filerest,fileresu);
1.127 brouard 12664: if((ficrest=fopen(filerest,"w"))==NULL) {
12665: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
12666: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
12667: }
1.208 brouard 12668: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
12669: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 12670: strcpy(fileresstde,"STDE_");
12671: strcat(fileresstde,fileresu);
1.126 brouard 12672: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 12673: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
12674: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 12675: }
1.227 brouard 12676: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
12677: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 12678:
1.201 brouard 12679: strcpy(filerescve,"CVE_");
12680: strcat(filerescve,fileresu);
1.126 brouard 12681: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 12682: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
12683: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 12684: }
1.227 brouard 12685: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
12686: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 12687:
1.201 brouard 12688: strcpy(fileresv,"V_");
12689: strcat(fileresv,fileresu);
1.126 brouard 12690: if((ficresvij=fopen(fileresv,"w"))==NULL) {
12691: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
12692: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
12693: }
1.227 brouard 12694: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
12695: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 12696:
1.235 brouard 12697: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
12698: if (cptcovn < 1){i1=1;}
12699:
12700: for(nres=1; nres <= nresult; nres++) /* For each resultline */
12701: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 12702: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 12703: continue;
1.242 brouard 12704: printf("\n#****** Result for:");
12705: fprintf(ficrest,"\n#****** Result for:");
12706: fprintf(ficlog,"\n#****** Result for:");
1.227 brouard 12707: for(j=1;j<=cptcoveff;j++){
12708: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12709: fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12710: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12711: }
1.235 brouard 12712: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12713: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12714: fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12715: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12716: }
1.208 brouard 12717: fprintf(ficrest,"******\n");
1.227 brouard 12718: fprintf(ficlog,"******\n");
12719: printf("******\n");
1.208 brouard 12720:
12721: fprintf(ficresstdeij,"\n#****** ");
12722: fprintf(ficrescveij,"\n#****** ");
1.225 brouard 12723: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 12724: fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12725: fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.208 brouard 12726: }
1.235 brouard 12727: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12728: fprintf(ficresstdeij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12729: fprintf(ficrescveij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12730: }
1.208 brouard 12731: fprintf(ficresstdeij,"******\n");
12732: fprintf(ficrescveij,"******\n");
12733:
12734: fprintf(ficresvij,"\n#****** ");
1.238 brouard 12735: /* pstamp(ficresvij); */
1.225 brouard 12736: for(j=1;j<=cptcoveff;j++)
1.227 brouard 12737: fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 12738: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12739: fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12740: }
1.208 brouard 12741: fprintf(ficresvij,"******\n");
12742:
12743: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12744: oldm=oldms;savm=savms;
1.235 brouard 12745: printf(" cvevsij ");
12746: fprintf(ficlog, " cvevsij ");
12747: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 12748: printf(" end cvevsij \n ");
12749: fprintf(ficlog, " end cvevsij \n ");
12750:
12751: /*
12752: */
12753: /* goto endfree; */
12754:
12755: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12756: pstamp(ficrest);
12757:
1.269 brouard 12758: epj=vector(1,nlstate+1);
1.208 brouard 12759: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 12760: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
12761: cptcod= 0; /* To be deleted */
12762: printf("varevsij vpopbased=%d \n",vpopbased);
12763: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 12764: 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 12765: 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 ");
12766: if(vpopbased==1)
12767: 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);
12768: else
1.288 brouard 12769: fprintf(ficrest,"the age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 12770: fprintf(ficrest,"# Age popbased mobilav e.. (std) ");
12771: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
12772: fprintf(ficrest,"\n");
12773: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
1.288 brouard 12774: printf("Computing age specific forward period (stable) prevalences in each health state \n");
12775: fprintf(ficlog,"Computing age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 12776: for(age=bage; age <=fage ;age++){
1.235 brouard 12777: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 12778: if (vpopbased==1) {
12779: if(mobilav ==0){
12780: for(i=1; i<=nlstate;i++)
12781: prlim[i][i]=probs[(int)age][i][k];
12782: }else{ /* mobilav */
12783: for(i=1; i<=nlstate;i++)
12784: prlim[i][i]=mobaverage[(int)age][i][k];
12785: }
12786: }
1.219 brouard 12787:
1.227 brouard 12788: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
12789: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
12790: /* printf(" age %4.0f ",age); */
12791: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
12792: for(i=1, epj[j]=0.;i <=nlstate;i++) {
12793: epj[j] += prlim[i][i]*eij[i][j][(int)age];
12794: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
12795: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
12796: }
12797: epj[nlstate+1] +=epj[j];
12798: }
12799: /* printf(" age %4.0f \n",age); */
1.219 brouard 12800:
1.227 brouard 12801: for(i=1, vepp=0.;i <=nlstate;i++)
12802: for(j=1;j <=nlstate;j++)
12803: vepp += vareij[i][j][(int)age];
12804: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
12805: for(j=1;j <=nlstate;j++){
12806: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
12807: }
12808: fprintf(ficrest,"\n");
12809: }
1.208 brouard 12810: } /* End vpopbased */
1.269 brouard 12811: free_vector(epj,1,nlstate+1);
1.208 brouard 12812: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
12813: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 12814: printf("done selection\n");fflush(stdout);
12815: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 12816:
1.235 brouard 12817: } /* End k selection */
1.227 brouard 12818:
12819: printf("done State-specific expectancies\n");fflush(stdout);
12820: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
12821:
1.288 brouard 12822: /* variance-covariance of forward period prevalence*/
1.269 brouard 12823: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 12824:
1.227 brouard 12825:
1.290 brouard 12826: free_vector(weight,firstobs,lastobs);
1.227 brouard 12827: free_imatrix(Tvard,1,NCOVMAX,1,2);
1.290 brouard 12828: free_imatrix(s,1,maxwav+1,firstobs,lastobs);
12829: free_matrix(anint,1,maxwav,firstobs,lastobs);
12830: free_matrix(mint,1,maxwav,firstobs,lastobs);
12831: free_ivector(cod,firstobs,lastobs);
1.227 brouard 12832: free_ivector(tab,1,NCOVMAX);
12833: fclose(ficresstdeij);
12834: fclose(ficrescveij);
12835: fclose(ficresvij);
12836: fclose(ficrest);
12837: fclose(ficpar);
12838:
12839:
1.126 brouard 12840: /*---------- End : free ----------------*/
1.219 brouard 12841: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 12842: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
12843: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 12844: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
12845: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 12846: } /* mle==-3 arrives here for freeing */
1.227 brouard 12847: /* endfree:*/
12848: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
12849: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
12850: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.290 brouard 12851: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,firstobs,lastobs);
12852: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,firstobs,lastobs);
12853: if(nqv>=1)free_matrix(coqvar,1,nqv,firstobs,lastobs);
12854: free_matrix(covar,0,NCOVMAX,firstobs,lastobs);
1.227 brouard 12855: free_matrix(matcov,1,npar,1,npar);
12856: free_matrix(hess,1,npar,1,npar);
12857: /*free_vector(delti,1,npar);*/
12858: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
12859: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 12860: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 12861: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
12862:
12863: free_ivector(ncodemax,1,NCOVMAX);
12864: free_ivector(ncodemaxwundef,1,NCOVMAX);
12865: free_ivector(Dummy,-1,NCOVMAX);
12866: free_ivector(Fixed,-1,NCOVMAX);
1.238 brouard 12867: free_ivector(DummyV,1,NCOVMAX);
12868: free_ivector(FixedV,1,NCOVMAX);
1.227 brouard 12869: free_ivector(Typevar,-1,NCOVMAX);
12870: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 12871: free_ivector(TvarsQ,1,NCOVMAX);
12872: free_ivector(TvarsQind,1,NCOVMAX);
12873: free_ivector(TvarsD,1,NCOVMAX);
12874: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 12875: free_ivector(TvarFD,1,NCOVMAX);
12876: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 12877: free_ivector(TvarF,1,NCOVMAX);
12878: free_ivector(TvarFind,1,NCOVMAX);
12879: free_ivector(TvarV,1,NCOVMAX);
12880: free_ivector(TvarVind,1,NCOVMAX);
12881: free_ivector(TvarA,1,NCOVMAX);
12882: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 12883: free_ivector(TvarFQ,1,NCOVMAX);
12884: free_ivector(TvarFQind,1,NCOVMAX);
12885: free_ivector(TvarVD,1,NCOVMAX);
12886: free_ivector(TvarVDind,1,NCOVMAX);
12887: free_ivector(TvarVQ,1,NCOVMAX);
12888: free_ivector(TvarVQind,1,NCOVMAX);
1.230 brouard 12889: free_ivector(Tvarsel,1,NCOVMAX);
12890: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 12891: free_ivector(Tposprod,1,NCOVMAX);
12892: free_ivector(Tprod,1,NCOVMAX);
12893: free_ivector(Tvaraff,1,NCOVMAX);
12894: free_ivector(invalidvarcomb,1,ncovcombmax);
12895: free_ivector(Tage,1,NCOVMAX);
12896: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 12897: free_ivector(TmodelInvind,1,NCOVMAX);
12898: free_ivector(TmodelInvQind,1,NCOVMAX);
1.227 brouard 12899:
12900: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
12901: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 12902: fflush(fichtm);
12903: fflush(ficgp);
12904:
1.227 brouard 12905:
1.126 brouard 12906: if((nberr >0) || (nbwarn>0)){
1.216 brouard 12907: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
12908: 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 12909: }else{
12910: printf("End of Imach\n");
12911: fprintf(ficlog,"End of Imach\n");
12912: }
12913: printf("See log file on %s\n",filelog);
12914: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 12915: /*(void) gettimeofday(&end_time,&tzp);*/
12916: rend_time = time(NULL);
12917: end_time = *localtime(&rend_time);
12918: /* tml = *localtime(&end_time.tm_sec); */
12919: strcpy(strtend,asctime(&end_time));
1.126 brouard 12920: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
12921: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 12922: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 12923:
1.157 brouard 12924: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
12925: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
12926: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 12927: /* printf("Total time was %d uSec.\n", total_usecs);*/
12928: /* if(fileappend(fichtm,optionfilehtm)){ */
12929: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
12930: fclose(fichtm);
12931: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
12932: fclose(fichtmcov);
12933: fclose(ficgp);
12934: fclose(ficlog);
12935: /*------ End -----------*/
1.227 brouard 12936:
1.281 brouard 12937:
12938: /* Executes gnuplot */
1.227 brouard 12939:
12940: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 12941: #ifdef WIN32
1.227 brouard 12942: if (_chdir(pathcd) != 0)
12943: printf("Can't move to directory %s!\n",path);
12944: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 12945: #else
1.227 brouard 12946: if(chdir(pathcd) != 0)
12947: printf("Can't move to directory %s!\n", path);
12948: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 12949: #endif
1.126 brouard 12950: printf("Current directory %s!\n",pathcd);
12951: /*strcat(plotcmd,CHARSEPARATOR);*/
12952: sprintf(plotcmd,"gnuplot");
1.157 brouard 12953: #ifdef _WIN32
1.126 brouard 12954: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
12955: #endif
12956: if(!stat(plotcmd,&info)){
1.158 brouard 12957: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 12958: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 12959: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 12960: }else
12961: strcpy(pplotcmd,plotcmd);
1.157 brouard 12962: #ifdef __unix
1.126 brouard 12963: strcpy(plotcmd,GNUPLOTPROGRAM);
12964: if(!stat(plotcmd,&info)){
1.158 brouard 12965: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 12966: }else
12967: strcpy(pplotcmd,plotcmd);
12968: #endif
12969: }else
12970: strcpy(pplotcmd,plotcmd);
12971:
12972: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 12973: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.292 brouard 12974: strcpy(pplotcmd,plotcmd);
1.227 brouard 12975:
1.126 brouard 12976: if((outcmd=system(plotcmd)) != 0){
1.292 brouard 12977: printf("Error in gnuplot, command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 12978: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 12979: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.292 brouard 12980: if((outcmd=system(plotcmd)) != 0){
1.153 brouard 12981: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.292 brouard 12982: strcpy(plotcmd,pplotcmd);
12983: }
1.126 brouard 12984: }
1.158 brouard 12985: printf(" Successful, please wait...");
1.126 brouard 12986: while (z[0] != 'q') {
12987: /* chdir(path); */
1.154 brouard 12988: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 12989: scanf("%s",z);
12990: /* if (z[0] == 'c') system("./imach"); */
12991: if (z[0] == 'e') {
1.158 brouard 12992: #ifdef __APPLE__
1.152 brouard 12993: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 12994: #elif __linux
12995: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 12996: #else
1.152 brouard 12997: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 12998: #endif
12999: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
13000: system(pplotcmd);
1.126 brouard 13001: }
13002: else if (z[0] == 'g') system(plotcmd);
13003: else if (z[0] == 'q') exit(0);
13004: }
1.227 brouard 13005: end:
1.126 brouard 13006: while (z[0] != 'q') {
1.195 brouard 13007: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 13008: scanf("%s",z);
13009: }
1.283 brouard 13010: printf("End\n");
1.282 brouard 13011: exit(0);
1.126 brouard 13012: }
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