Annotation of imach/src/imach.c, revision 1.329
1.329 ! brouard 1: /* $Id: imach.c,v 1.328 2022/07/27 17:40:48 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.329 ! brouard 4: Revision 1.328 2022/07/27 17:40:48 brouard
! 5: Summary: valgrind bug fixed by initializing to zero DummyV as well as Tage
! 6:
1.328 brouard 7: Revision 1.327 2022/07/27 14:47:35 brouard
8: Summary: Still a problem for one-step probabilities in case of quantitative variables
9:
1.327 brouard 10: Revision 1.326 2022/07/26 17:33:55 brouard
11: Summary: some test with nres=1
12:
1.326 brouard 13: Revision 1.325 2022/07/25 14:27:23 brouard
14: Summary: r30
15:
16: * imach.c (Module): Error cptcovn instead of nsd in bmij (was
17: coredumped, revealed by Feiuno, thank you.
18:
1.325 brouard 19: Revision 1.324 2022/07/23 17:44:26 brouard
20: *** empty log message ***
21:
1.324 brouard 22: Revision 1.323 2022/07/22 12:30:08 brouard
23: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
24:
1.323 brouard 25: Revision 1.322 2022/07/22 12:27:48 brouard
26: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
27:
1.322 brouard 28: Revision 1.321 2022/07/22 12:04:24 brouard
29: Summary: r28
30:
31: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
32:
1.321 brouard 33: Revision 1.320 2022/06/02 05:10:11 brouard
34: *** empty log message ***
35:
1.320 brouard 36: Revision 1.319 2022/06/02 04:45:11 brouard
37: * imach.c (Module): Adding the Wald tests from the log to the main
38: htm for better display of the maximum likelihood estimators.
39:
1.319 brouard 40: Revision 1.318 2022/05/24 08:10:59 brouard
41: * imach.c (Module): Some attempts to find a bug of wrong estimates
42: of confidencce intervals with product in the equation modelC
43:
1.318 brouard 44: Revision 1.317 2022/05/15 15:06:23 brouard
45: * imach.c (Module): Some minor improvements
46:
1.317 brouard 47: Revision 1.316 2022/05/11 15:11:31 brouard
48: Summary: r27
49:
1.316 brouard 50: Revision 1.315 2022/05/11 15:06:32 brouard
51: *** empty log message ***
52:
1.315 brouard 53: Revision 1.314 2022/04/13 17:43:09 brouard
54: * imach.c (Module): Adding link to text data files
55:
1.314 brouard 56: Revision 1.313 2022/04/11 15:57:42 brouard
57: * imach.c (Module): Error in rewriting the 'r' file with yearsfproj or yearsbproj fixed
58:
1.313 brouard 59: Revision 1.312 2022/04/05 21:24:39 brouard
60: *** empty log message ***
61:
1.312 brouard 62: Revision 1.311 2022/04/05 21:03:51 brouard
63: Summary: Fixed quantitative covariates
64:
65: Fixed covariates (dummy or quantitative)
66: with missing values have never been allowed but are ERRORS and
67: program quits. Standard deviations of fixed covariates were
68: wrongly computed. Mean and standard deviations of time varying
69: covariates are still not computed.
70:
1.311 brouard 71: Revision 1.310 2022/03/17 08:45:53 brouard
72: Summary: 99r25
73:
74: Improving detection of errors: result lines should be compatible with
75: the model.
76:
1.310 brouard 77: Revision 1.309 2021/05/20 12:39:14 brouard
78: Summary: Version 0.99r24
79:
1.309 brouard 80: Revision 1.308 2021/03/31 13:11:57 brouard
81: Summary: Version 0.99r23
82:
83:
84: * imach.c (Module): Still bugs in the result loop. Thank to Holly Benett
85:
1.308 brouard 86: Revision 1.307 2021/03/08 18:11:32 brouard
87: Summary: 0.99r22 fixed bug on result:
88:
1.307 brouard 89: Revision 1.306 2021/02/20 15:44:02 brouard
90: Summary: Version 0.99r21
91:
92: * imach.c (Module): Fix bug on quitting after result lines!
93: (Module): Version 0.99r21
94:
1.306 brouard 95: Revision 1.305 2021/02/20 15:28:30 brouard
96: * imach.c (Module): Fix bug on quitting after result lines!
97:
1.305 brouard 98: Revision 1.304 2021/02/12 11:34:20 brouard
99: * imach.c (Module): The use of a Windows BOM (huge) file is now an error
100:
1.304 brouard 101: Revision 1.303 2021/02/11 19:50:15 brouard
102: * (Module): imach.c Someone entered 'results:' instead of 'result:'. Now it is an error which is printed.
103:
1.303 brouard 104: Revision 1.302 2020/02/22 21:00:05 brouard
105: * (Module): imach.c Update mle=-3 (for computing Life expectancy
106: and life table from the data without any state)
107:
1.302 brouard 108: Revision 1.301 2019/06/04 13:51:20 brouard
109: Summary: Error in 'r'parameter file backcast yearsbproj instead of yearsfproj
110:
1.301 brouard 111: Revision 1.300 2019/05/22 19:09:45 brouard
112: Summary: version 0.99r19 of May 2019
113:
1.300 brouard 114: Revision 1.299 2019/05/22 18:37:08 brouard
115: Summary: Cleaned 0.99r19
116:
1.299 brouard 117: Revision 1.298 2019/05/22 18:19:56 brouard
118: *** empty log message ***
119:
1.298 brouard 120: Revision 1.297 2019/05/22 17:56:10 brouard
121: Summary: Fix bug by moving date2dmy and nhstepm which gaefin=-1
122:
1.297 brouard 123: Revision 1.296 2019/05/20 13:03:18 brouard
124: Summary: Projection syntax simplified
125:
126:
127: We can now start projections, forward or backward, from the mean date
128: of inteviews up to or down to a number of years of projection:
129: prevforecast=1 yearsfproj=15.3 mobil_average=0
130: or
131: prevforecast=1 starting-proj-date=1/1/2007 final-proj-date=12/31/2017 mobil_average=0
132: or
133: prevbackcast=1 yearsbproj=12.3 mobil_average=1
134: or
135: prevbackcast=1 starting-back-date=1/10/1999 final-back-date=1/1/1985 mobil_average=1
136:
1.296 brouard 137: Revision 1.295 2019/05/18 09:52:50 brouard
138: Summary: doxygen tex bug
139:
1.295 brouard 140: Revision 1.294 2019/05/16 14:54:33 brouard
141: Summary: There was some wrong lines added
142:
1.294 brouard 143: Revision 1.293 2019/05/09 15:17:34 brouard
144: *** empty log message ***
145:
1.293 brouard 146: Revision 1.292 2019/05/09 14:17:20 brouard
147: Summary: Some updates
148:
1.292 brouard 149: Revision 1.291 2019/05/09 13:44:18 brouard
150: Summary: Before ncovmax
151:
1.291 brouard 152: Revision 1.290 2019/05/09 13:39:37 brouard
153: Summary: 0.99r18 unlimited number of individuals
154:
155: 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.
156:
1.290 brouard 157: Revision 1.289 2018/12/13 09:16:26 brouard
158: Summary: Bug for young ages (<-30) will be in r17
159:
1.289 brouard 160: Revision 1.288 2018/05/02 20:58:27 brouard
161: Summary: Some bugs fixed
162:
1.288 brouard 163: Revision 1.287 2018/05/01 17:57:25 brouard
164: Summary: Bug fixed by providing frequencies only for non missing covariates
165:
1.287 brouard 166: Revision 1.286 2018/04/27 14:27:04 brouard
167: Summary: some minor bugs
168:
1.286 brouard 169: Revision 1.285 2018/04/21 21:02:16 brouard
170: Summary: Some bugs fixed, valgrind tested
171:
1.285 brouard 172: Revision 1.284 2018/04/20 05:22:13 brouard
173: Summary: Computing mean and stdeviation of fixed quantitative variables
174:
1.284 brouard 175: Revision 1.283 2018/04/19 14:49:16 brouard
176: Summary: Some minor bugs fixed
177:
1.283 brouard 178: Revision 1.282 2018/02/27 22:50:02 brouard
179: *** empty log message ***
180:
1.282 brouard 181: Revision 1.281 2018/02/27 19:25:23 brouard
182: Summary: Adding second argument for quitting
183:
1.281 brouard 184: Revision 1.280 2018/02/21 07:58:13 brouard
185: Summary: 0.99r15
186:
187: New Makefile with recent VirtualBox 5.26. Bug in sqrt negatve in imach.c
188:
1.280 brouard 189: Revision 1.279 2017/07/20 13:35:01 brouard
190: Summary: temporary working
191:
1.279 brouard 192: Revision 1.278 2017/07/19 14:09:02 brouard
193: Summary: Bug for mobil_average=0 and prevforecast fixed(?)
194:
1.278 brouard 195: Revision 1.277 2017/07/17 08:53:49 brouard
196: Summary: BOM files can be read now
197:
1.277 brouard 198: Revision 1.276 2017/06/30 15:48:31 brouard
199: Summary: Graphs improvements
200:
1.276 brouard 201: Revision 1.275 2017/06/30 13:39:33 brouard
202: Summary: Saito's color
203:
1.275 brouard 204: Revision 1.274 2017/06/29 09:47:08 brouard
205: Summary: Version 0.99r14
206:
1.274 brouard 207: Revision 1.273 2017/06/27 11:06:02 brouard
208: Summary: More documentation on projections
209:
1.273 brouard 210: Revision 1.272 2017/06/27 10:22:40 brouard
211: Summary: Color of backprojection changed from 6 to 5(yellow)
212:
1.272 brouard 213: Revision 1.271 2017/06/27 10:17:50 brouard
214: Summary: Some bug with rint
215:
1.271 brouard 216: Revision 1.270 2017/05/24 05:45:29 brouard
217: *** empty log message ***
218:
1.270 brouard 219: Revision 1.269 2017/05/23 08:39:25 brouard
220: Summary: Code into subroutine, cleanings
221:
1.269 brouard 222: Revision 1.268 2017/05/18 20:09:32 brouard
223: Summary: backprojection and confidence intervals of backprevalence
224:
1.268 brouard 225: Revision 1.267 2017/05/13 10:25:05 brouard
226: Summary: temporary save for backprojection
227:
1.267 brouard 228: Revision 1.266 2017/05/13 07:26:12 brouard
229: Summary: Version 0.99r13 (improvements and bugs fixed)
230:
1.266 brouard 231: Revision 1.265 2017/04/26 16:22:11 brouard
232: Summary: imach 0.99r13 Some bugs fixed
233:
1.265 brouard 234: Revision 1.264 2017/04/26 06:01:29 brouard
235: Summary: Labels in graphs
236:
1.264 brouard 237: Revision 1.263 2017/04/24 15:23:15 brouard
238: Summary: to save
239:
1.263 brouard 240: Revision 1.262 2017/04/18 16:48:12 brouard
241: *** empty log message ***
242:
1.262 brouard 243: Revision 1.261 2017/04/05 10:14:09 brouard
244: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
245:
1.261 brouard 246: Revision 1.260 2017/04/04 17:46:59 brouard
247: Summary: Gnuplot indexations fixed (humm)
248:
1.260 brouard 249: Revision 1.259 2017/04/04 13:01:16 brouard
250: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
251:
1.259 brouard 252: Revision 1.258 2017/04/03 10:17:47 brouard
253: Summary: Version 0.99r12
254:
255: Some cleanings, conformed with updated documentation.
256:
1.258 brouard 257: Revision 1.257 2017/03/29 16:53:30 brouard
258: Summary: Temp
259:
1.257 brouard 260: Revision 1.256 2017/03/27 05:50:23 brouard
261: Summary: Temporary
262:
1.256 brouard 263: Revision 1.255 2017/03/08 16:02:28 brouard
264: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
265:
1.255 brouard 266: Revision 1.254 2017/03/08 07:13:00 brouard
267: Summary: Fixing data parameter line
268:
1.254 brouard 269: Revision 1.253 2016/12/15 11:59:41 brouard
270: Summary: 0.99 in progress
271:
1.253 brouard 272: Revision 1.252 2016/09/15 21:15:37 brouard
273: *** empty log message ***
274:
1.252 brouard 275: Revision 1.251 2016/09/15 15:01:13 brouard
276: Summary: not working
277:
1.251 brouard 278: Revision 1.250 2016/09/08 16:07:27 brouard
279: Summary: continue
280:
1.250 brouard 281: Revision 1.249 2016/09/07 17:14:18 brouard
282: Summary: Starting values from frequencies
283:
1.249 brouard 284: Revision 1.248 2016/09/07 14:10:18 brouard
285: *** empty log message ***
286:
1.248 brouard 287: Revision 1.247 2016/09/02 11:11:21 brouard
288: *** empty log message ***
289:
1.247 brouard 290: Revision 1.246 2016/09/02 08:49:22 brouard
291: *** empty log message ***
292:
1.246 brouard 293: Revision 1.245 2016/09/02 07:25:01 brouard
294: *** empty log message ***
295:
1.245 brouard 296: Revision 1.244 2016/09/02 07:17:34 brouard
297: *** empty log message ***
298:
1.244 brouard 299: Revision 1.243 2016/09/02 06:45:35 brouard
300: *** empty log message ***
301:
1.243 brouard 302: Revision 1.242 2016/08/30 15:01:20 brouard
303: Summary: Fixing a lots
304:
1.242 brouard 305: Revision 1.241 2016/08/29 17:17:25 brouard
306: Summary: gnuplot problem in Back projection to fix
307:
1.241 brouard 308: Revision 1.240 2016/08/29 07:53:18 brouard
309: Summary: Better
310:
1.240 brouard 311: Revision 1.239 2016/08/26 15:51:03 brouard
312: Summary: Improvement in Powell output in order to copy and paste
313:
314: Author:
315:
1.239 brouard 316: Revision 1.238 2016/08/26 14:23:35 brouard
317: Summary: Starting tests of 0.99
318:
1.238 brouard 319: Revision 1.237 2016/08/26 09:20:19 brouard
320: Summary: to valgrind
321:
1.237 brouard 322: Revision 1.236 2016/08/25 10:50:18 brouard
323: *** empty log message ***
324:
1.236 brouard 325: Revision 1.235 2016/08/25 06:59:23 brouard
326: *** empty log message ***
327:
1.235 brouard 328: Revision 1.234 2016/08/23 16:51:20 brouard
329: *** empty log message ***
330:
1.234 brouard 331: Revision 1.233 2016/08/23 07:40:50 brouard
332: Summary: not working
333:
1.233 brouard 334: Revision 1.232 2016/08/22 14:20:21 brouard
335: Summary: not working
336:
1.232 brouard 337: Revision 1.231 2016/08/22 07:17:15 brouard
338: Summary: not working
339:
1.231 brouard 340: Revision 1.230 2016/08/22 06:55:53 brouard
341: Summary: Not working
342:
1.230 brouard 343: Revision 1.229 2016/07/23 09:45:53 brouard
344: Summary: Completing for func too
345:
1.229 brouard 346: Revision 1.228 2016/07/22 17:45:30 brouard
347: Summary: Fixing some arrays, still debugging
348:
1.227 brouard 349: Revision 1.226 2016/07/12 18:42:34 brouard
350: Summary: temp
351:
1.226 brouard 352: Revision 1.225 2016/07/12 08:40:03 brouard
353: Summary: saving but not running
354:
1.225 brouard 355: Revision 1.224 2016/07/01 13:16:01 brouard
356: Summary: Fixes
357:
1.224 brouard 358: Revision 1.223 2016/02/19 09:23:35 brouard
359: Summary: temporary
360:
1.223 brouard 361: Revision 1.222 2016/02/17 08:14:50 brouard
362: Summary: Probably last 0.98 stable version 0.98r6
363:
1.222 brouard 364: Revision 1.221 2016/02/15 23:35:36 brouard
365: Summary: minor bug
366:
1.220 brouard 367: Revision 1.219 2016/02/15 00:48:12 brouard
368: *** empty log message ***
369:
1.219 brouard 370: Revision 1.218 2016/02/12 11:29:23 brouard
371: Summary: 0.99 Back projections
372:
1.218 brouard 373: Revision 1.217 2015/12/23 17:18:31 brouard
374: Summary: Experimental backcast
375:
1.217 brouard 376: Revision 1.216 2015/12/18 17:32:11 brouard
377: Summary: 0.98r4 Warning and status=-2
378:
379: Version 0.98r4 is now:
380: - displaying an error when status is -1, date of interview unknown and date of death known;
381: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
382: Older changes concerning s=-2, dating from 2005 have been supersed.
383:
1.216 brouard 384: Revision 1.215 2015/12/16 08:52:24 brouard
385: Summary: 0.98r4 working
386:
1.215 brouard 387: Revision 1.214 2015/12/16 06:57:54 brouard
388: Summary: temporary not working
389:
1.214 brouard 390: Revision 1.213 2015/12/11 18:22:17 brouard
391: Summary: 0.98r4
392:
1.213 brouard 393: Revision 1.212 2015/11/21 12:47:24 brouard
394: Summary: minor typo
395:
1.212 brouard 396: Revision 1.211 2015/11/21 12:41:11 brouard
397: Summary: 0.98r3 with some graph of projected cross-sectional
398:
399: Author: Nicolas Brouard
400:
1.211 brouard 401: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 402: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 403: Summary: Adding ftolpl parameter
404: Author: N Brouard
405:
406: We had difficulties to get smoothed confidence intervals. It was due
407: to the period prevalence which wasn't computed accurately. The inner
408: parameter ftolpl is now an outer parameter of the .imach parameter
409: file after estepm. If ftolpl is small 1.e-4 and estepm too,
410: computation are long.
411:
1.209 brouard 412: Revision 1.208 2015/11/17 14:31:57 brouard
413: Summary: temporary
414:
1.208 brouard 415: Revision 1.207 2015/10/27 17:36:57 brouard
416: *** empty log message ***
417:
1.207 brouard 418: Revision 1.206 2015/10/24 07:14:11 brouard
419: *** empty log message ***
420:
1.206 brouard 421: Revision 1.205 2015/10/23 15:50:53 brouard
422: Summary: 0.98r3 some clarification for graphs on likelihood contributions
423:
1.205 brouard 424: Revision 1.204 2015/10/01 16:20:26 brouard
425: Summary: Some new graphs of contribution to likelihood
426:
1.204 brouard 427: Revision 1.203 2015/09/30 17:45:14 brouard
428: Summary: looking at better estimation of the hessian
429:
430: Also a better criteria for convergence to the period prevalence And
431: therefore adding the number of years needed to converge. (The
432: prevalence in any alive state shold sum to one
433:
1.203 brouard 434: Revision 1.202 2015/09/22 19:45:16 brouard
435: Summary: Adding some overall graph on contribution to likelihood. Might change
436:
1.202 brouard 437: Revision 1.201 2015/09/15 17:34:58 brouard
438: Summary: 0.98r0
439:
440: - Some new graphs like suvival functions
441: - Some bugs fixed like model=1+age+V2.
442:
1.201 brouard 443: Revision 1.200 2015/09/09 16:53:55 brouard
444: Summary: Big bug thanks to Flavia
445:
446: Even model=1+age+V2. did not work anymore
447:
1.200 brouard 448: Revision 1.199 2015/09/07 14:09:23 brouard
449: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
450:
1.199 brouard 451: Revision 1.198 2015/09/03 07:14:39 brouard
452: Summary: 0.98q5 Flavia
453:
1.198 brouard 454: Revision 1.197 2015/09/01 18:24:39 brouard
455: *** empty log message ***
456:
1.197 brouard 457: Revision 1.196 2015/08/18 23:17:52 brouard
458: Summary: 0.98q5
459:
1.196 brouard 460: Revision 1.195 2015/08/18 16:28:39 brouard
461: Summary: Adding a hack for testing purpose
462:
463: After reading the title, ftol and model lines, if the comment line has
464: a q, starting with #q, the answer at the end of the run is quit. It
465: permits to run test files in batch with ctest. The former workaround was
466: $ echo q | imach foo.imach
467:
1.195 brouard 468: Revision 1.194 2015/08/18 13:32:00 brouard
469: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
470:
1.194 brouard 471: Revision 1.193 2015/08/04 07:17:42 brouard
472: Summary: 0.98q4
473:
1.193 brouard 474: Revision 1.192 2015/07/16 16:49:02 brouard
475: Summary: Fixing some outputs
476:
1.192 brouard 477: Revision 1.191 2015/07/14 10:00:33 brouard
478: Summary: Some fixes
479:
1.191 brouard 480: Revision 1.190 2015/05/05 08:51:13 brouard
481: Summary: Adding digits in output parameters (7 digits instead of 6)
482:
483: Fix 1+age+.
484:
1.190 brouard 485: Revision 1.189 2015/04/30 14:45:16 brouard
486: Summary: 0.98q2
487:
1.189 brouard 488: Revision 1.188 2015/04/30 08:27:53 brouard
489: *** empty log message ***
490:
1.188 brouard 491: Revision 1.187 2015/04/29 09:11:15 brouard
492: *** empty log message ***
493:
1.187 brouard 494: Revision 1.186 2015/04/23 12:01:52 brouard
495: Summary: V1*age is working now, version 0.98q1
496:
497: Some codes had been disabled in order to simplify and Vn*age was
498: working in the optimization phase, ie, giving correct MLE parameters,
499: but, as usual, outputs were not correct and program core dumped.
500:
1.186 brouard 501: Revision 1.185 2015/03/11 13:26:42 brouard
502: Summary: Inclusion of compile and links command line for Intel Compiler
503:
1.185 brouard 504: Revision 1.184 2015/03/11 11:52:39 brouard
505: Summary: Back from Windows 8. Intel Compiler
506:
1.184 brouard 507: Revision 1.183 2015/03/10 20:34:32 brouard
508: Summary: 0.98q0, trying with directest, mnbrak fixed
509:
510: We use directest instead of original Powell test; probably no
511: incidence on the results, but better justifications;
512: We fixed Numerical Recipes mnbrak routine which was wrong and gave
513: wrong results.
514:
1.183 brouard 515: Revision 1.182 2015/02/12 08:19:57 brouard
516: Summary: Trying to keep directest which seems simpler and more general
517: Author: Nicolas Brouard
518:
1.182 brouard 519: Revision 1.181 2015/02/11 23:22:24 brouard
520: Summary: Comments on Powell added
521:
522: Author:
523:
1.181 brouard 524: Revision 1.180 2015/02/11 17:33:45 brouard
525: Summary: Finishing move from main to function (hpijx and prevalence_limit)
526:
1.180 brouard 527: Revision 1.179 2015/01/04 09:57:06 brouard
528: Summary: back to OS/X
529:
1.179 brouard 530: Revision 1.178 2015/01/04 09:35:48 brouard
531: *** empty log message ***
532:
1.178 brouard 533: Revision 1.177 2015/01/03 18:40:56 brouard
534: Summary: Still testing ilc32 on OSX
535:
1.177 brouard 536: Revision 1.176 2015/01/03 16:45:04 brouard
537: *** empty log message ***
538:
1.176 brouard 539: Revision 1.175 2015/01/03 16:33:42 brouard
540: *** empty log message ***
541:
1.175 brouard 542: Revision 1.174 2015/01/03 16:15:49 brouard
543: Summary: Still in cross-compilation
544:
1.174 brouard 545: Revision 1.173 2015/01/03 12:06:26 brouard
546: Summary: trying to detect cross-compilation
547:
1.173 brouard 548: Revision 1.172 2014/12/27 12:07:47 brouard
549: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
550:
1.172 brouard 551: Revision 1.171 2014/12/23 13:26:59 brouard
552: Summary: Back from Visual C
553:
554: Still problem with utsname.h on Windows
555:
1.171 brouard 556: Revision 1.170 2014/12/23 11:17:12 brouard
557: Summary: Cleaning some \%% back to %%
558:
559: The escape was mandatory for a specific compiler (which one?), but too many warnings.
560:
1.170 brouard 561: Revision 1.169 2014/12/22 23:08:31 brouard
562: Summary: 0.98p
563:
564: Outputs some informations on compiler used, OS etc. Testing on different platforms.
565:
1.169 brouard 566: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 567: Summary: update
1.169 brouard 568:
1.168 brouard 569: Revision 1.167 2014/12/22 13:50:56 brouard
570: Summary: Testing uname and compiler version and if compiled 32 or 64
571:
572: Testing on Linux 64
573:
1.167 brouard 574: Revision 1.166 2014/12/22 11:40:47 brouard
575: *** empty log message ***
576:
1.166 brouard 577: Revision 1.165 2014/12/16 11:20:36 brouard
578: Summary: After compiling on Visual C
579:
580: * imach.c (Module): Merging 1.61 to 1.162
581:
1.165 brouard 582: Revision 1.164 2014/12/16 10:52:11 brouard
583: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
584:
585: * imach.c (Module): Merging 1.61 to 1.162
586:
1.164 brouard 587: Revision 1.163 2014/12/16 10:30:11 brouard
588: * imach.c (Module): Merging 1.61 to 1.162
589:
1.163 brouard 590: Revision 1.162 2014/09/25 11:43:39 brouard
591: Summary: temporary backup 0.99!
592:
1.162 brouard 593: Revision 1.1 2014/09/16 11:06:58 brouard
594: Summary: With some code (wrong) for nlopt
595:
596: Author:
597:
598: Revision 1.161 2014/09/15 20:41:41 brouard
599: Summary: Problem with macro SQR on Intel compiler
600:
1.161 brouard 601: Revision 1.160 2014/09/02 09:24:05 brouard
602: *** empty log message ***
603:
1.160 brouard 604: Revision 1.159 2014/09/01 10:34:10 brouard
605: Summary: WIN32
606: Author: Brouard
607:
1.159 brouard 608: Revision 1.158 2014/08/27 17:11:51 brouard
609: *** empty log message ***
610:
1.158 brouard 611: Revision 1.157 2014/08/27 16:26:55 brouard
612: Summary: Preparing windows Visual studio version
613: Author: Brouard
614:
615: In order to compile on Visual studio, time.h is now correct and time_t
616: and tm struct should be used. difftime should be used but sometimes I
617: just make the differences in raw time format (time(&now).
618: Trying to suppress #ifdef LINUX
619: Add xdg-open for __linux in order to open default browser.
620:
1.157 brouard 621: Revision 1.156 2014/08/25 20:10:10 brouard
622: *** empty log message ***
623:
1.156 brouard 624: Revision 1.155 2014/08/25 18:32:34 brouard
625: Summary: New compile, minor changes
626: Author: Brouard
627:
1.155 brouard 628: Revision 1.154 2014/06/20 17:32:08 brouard
629: Summary: Outputs now all graphs of convergence to period prevalence
630:
1.154 brouard 631: Revision 1.153 2014/06/20 16:45:46 brouard
632: Summary: If 3 live state, convergence to period prevalence on same graph
633: Author: Brouard
634:
1.153 brouard 635: Revision 1.152 2014/06/18 17:54:09 brouard
636: Summary: open browser, use gnuplot on same dir than imach if not found in the path
637:
1.152 brouard 638: Revision 1.151 2014/06/18 16:43:30 brouard
639: *** empty log message ***
640:
1.151 brouard 641: Revision 1.150 2014/06/18 16:42:35 brouard
642: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
643: Author: brouard
644:
1.150 brouard 645: Revision 1.149 2014/06/18 15:51:14 brouard
646: Summary: Some fixes in parameter files errors
647: Author: Nicolas Brouard
648:
1.149 brouard 649: Revision 1.148 2014/06/17 17:38:48 brouard
650: Summary: Nothing new
651: Author: Brouard
652:
653: Just a new packaging for OS/X version 0.98nS
654:
1.148 brouard 655: Revision 1.147 2014/06/16 10:33:11 brouard
656: *** empty log message ***
657:
1.147 brouard 658: Revision 1.146 2014/06/16 10:20:28 brouard
659: Summary: Merge
660: Author: Brouard
661:
662: Merge, before building revised version.
663:
1.146 brouard 664: Revision 1.145 2014/06/10 21:23:15 brouard
665: Summary: Debugging with valgrind
666: Author: Nicolas Brouard
667:
668: Lot of changes in order to output the results with some covariates
669: After the Edimburgh REVES conference 2014, it seems mandatory to
670: improve the code.
671: No more memory valgrind error but a lot has to be done in order to
672: continue the work of splitting the code into subroutines.
673: Also, decodemodel has been improved. Tricode is still not
674: optimal. nbcode should be improved. Documentation has been added in
675: the source code.
676:
1.144 brouard 677: Revision 1.143 2014/01/26 09:45:38 brouard
678: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
679:
680: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
681: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
682:
1.143 brouard 683: Revision 1.142 2014/01/26 03:57:36 brouard
684: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
685:
686: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
687:
1.142 brouard 688: Revision 1.141 2014/01/26 02:42:01 brouard
689: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
690:
1.141 brouard 691: Revision 1.140 2011/09/02 10:37:54 brouard
692: Summary: times.h is ok with mingw32 now.
693:
1.140 brouard 694: Revision 1.139 2010/06/14 07:50:17 brouard
695: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
696: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
697:
1.139 brouard 698: Revision 1.138 2010/04/30 18:19:40 brouard
699: *** empty log message ***
700:
1.138 brouard 701: Revision 1.137 2010/04/29 18:11:38 brouard
702: (Module): Checking covariates for more complex models
703: than V1+V2. A lot of change to be done. Unstable.
704:
1.137 brouard 705: Revision 1.136 2010/04/26 20:30:53 brouard
706: (Module): merging some libgsl code. Fixing computation
707: of likelione (using inter/intrapolation if mle = 0) in order to
708: get same likelihood as if mle=1.
709: Some cleaning of code and comments added.
710:
1.136 brouard 711: Revision 1.135 2009/10/29 15:33:14 brouard
712: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
713:
1.135 brouard 714: Revision 1.134 2009/10/29 13:18:53 brouard
715: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
716:
1.134 brouard 717: Revision 1.133 2009/07/06 10:21:25 brouard
718: just nforces
719:
1.133 brouard 720: Revision 1.132 2009/07/06 08:22:05 brouard
721: Many tings
722:
1.132 brouard 723: Revision 1.131 2009/06/20 16:22:47 brouard
724: Some dimensions resccaled
725:
1.131 brouard 726: Revision 1.130 2009/05/26 06:44:34 brouard
727: (Module): Max Covariate is now set to 20 instead of 8. A
728: lot of cleaning with variables initialized to 0. Trying to make
729: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
730:
1.130 brouard 731: Revision 1.129 2007/08/31 13:49:27 lievre
732: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
733:
1.129 lievre 734: Revision 1.128 2006/06/30 13:02:05 brouard
735: (Module): Clarifications on computing e.j
736:
1.128 brouard 737: Revision 1.127 2006/04/28 18:11:50 brouard
738: (Module): Yes the sum of survivors was wrong since
739: imach-114 because nhstepm was no more computed in the age
740: loop. Now we define nhstepma in the age loop.
741: (Module): In order to speed up (in case of numerous covariates) we
742: compute health expectancies (without variances) in a first step
743: and then all the health expectancies with variances or standard
744: deviation (needs data from the Hessian matrices) which slows the
745: computation.
746: In the future we should be able to stop the program is only health
747: expectancies and graph are needed without standard deviations.
748:
1.127 brouard 749: Revision 1.126 2006/04/28 17:23:28 brouard
750: (Module): Yes the sum of survivors was wrong since
751: imach-114 because nhstepm was no more computed in the age
752: loop. Now we define nhstepma in the age loop.
753: Version 0.98h
754:
1.126 brouard 755: Revision 1.125 2006/04/04 15:20:31 lievre
756: Errors in calculation of health expectancies. Age was not initialized.
757: Forecasting file added.
758:
759: Revision 1.124 2006/03/22 17:13:53 lievre
760: Parameters are printed with %lf instead of %f (more numbers after the comma).
761: The log-likelihood is printed in the log file
762:
763: Revision 1.123 2006/03/20 10:52:43 brouard
764: * imach.c (Module): <title> changed, corresponds to .htm file
765: name. <head> headers where missing.
766:
767: * imach.c (Module): Weights can have a decimal point as for
768: English (a comma might work with a correct LC_NUMERIC environment,
769: otherwise the weight is truncated).
770: Modification of warning when the covariates values are not 0 or
771: 1.
772: Version 0.98g
773:
774: Revision 1.122 2006/03/20 09:45:41 brouard
775: (Module): Weights can have a decimal point as for
776: English (a comma might work with a correct LC_NUMERIC environment,
777: otherwise the weight is truncated).
778: Modification of warning when the covariates values are not 0 or
779: 1.
780: Version 0.98g
781:
782: Revision 1.121 2006/03/16 17:45:01 lievre
783: * imach.c (Module): Comments concerning covariates added
784:
785: * imach.c (Module): refinements in the computation of lli if
786: status=-2 in order to have more reliable computation if stepm is
787: not 1 month. Version 0.98f
788:
789: Revision 1.120 2006/03/16 15:10:38 lievre
790: (Module): refinements in the computation of lli if
791: status=-2 in order to have more reliable computation if stepm is
792: not 1 month. Version 0.98f
793:
794: Revision 1.119 2006/03/15 17:42:26 brouard
795: (Module): Bug if status = -2, the loglikelihood was
796: computed as likelihood omitting the logarithm. Version O.98e
797:
798: Revision 1.118 2006/03/14 18:20:07 brouard
799: (Module): varevsij Comments added explaining the second
800: table of variances if popbased=1 .
801: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
802: (Module): Function pstamp added
803: (Module): Version 0.98d
804:
805: Revision 1.117 2006/03/14 17:16:22 brouard
806: (Module): varevsij Comments added explaining the second
807: table of variances if popbased=1 .
808: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
809: (Module): Function pstamp added
810: (Module): Version 0.98d
811:
812: Revision 1.116 2006/03/06 10:29:27 brouard
813: (Module): Variance-covariance wrong links and
814: varian-covariance of ej. is needed (Saito).
815:
816: Revision 1.115 2006/02/27 12:17:45 brouard
817: (Module): One freematrix added in mlikeli! 0.98c
818:
819: Revision 1.114 2006/02/26 12:57:58 brouard
820: (Module): Some improvements in processing parameter
821: filename with strsep.
822:
823: Revision 1.113 2006/02/24 14:20:24 brouard
824: (Module): Memory leaks checks with valgrind and:
825: datafile was not closed, some imatrix were not freed and on matrix
826: allocation too.
827:
828: Revision 1.112 2006/01/30 09:55:26 brouard
829: (Module): Back to gnuplot.exe instead of wgnuplot.exe
830:
831: Revision 1.111 2006/01/25 20:38:18 brouard
832: (Module): Lots of cleaning and bugs added (Gompertz)
833: (Module): Comments can be added in data file. Missing date values
834: can be a simple dot '.'.
835:
836: Revision 1.110 2006/01/25 00:51:50 brouard
837: (Module): Lots of cleaning and bugs added (Gompertz)
838:
839: Revision 1.109 2006/01/24 19:37:15 brouard
840: (Module): Comments (lines starting with a #) are allowed in data.
841:
842: Revision 1.108 2006/01/19 18:05:42 lievre
843: Gnuplot problem appeared...
844: To be fixed
845:
846: Revision 1.107 2006/01/19 16:20:37 brouard
847: Test existence of gnuplot in imach path
848:
849: Revision 1.106 2006/01/19 13:24:36 brouard
850: Some cleaning and links added in html output
851:
852: Revision 1.105 2006/01/05 20:23:19 lievre
853: *** empty log message ***
854:
855: Revision 1.104 2005/09/30 16:11:43 lievre
856: (Module): sump fixed, loop imx fixed, and simplifications.
857: (Module): If the status is missing at the last wave but we know
858: that the person is alive, then we can code his/her status as -2
859: (instead of missing=-1 in earlier versions) and his/her
860: contributions to the likelihood is 1 - Prob of dying from last
861: health status (= 1-p13= p11+p12 in the easiest case of somebody in
862: the healthy state at last known wave). Version is 0.98
863:
864: Revision 1.103 2005/09/30 15:54:49 lievre
865: (Module): sump fixed, loop imx fixed, and simplifications.
866:
867: Revision 1.102 2004/09/15 17:31:30 brouard
868: Add the possibility to read data file including tab characters.
869:
870: Revision 1.101 2004/09/15 10:38:38 brouard
871: Fix on curr_time
872:
873: Revision 1.100 2004/07/12 18:29:06 brouard
874: Add version for Mac OS X. Just define UNIX in Makefile
875:
876: Revision 1.99 2004/06/05 08:57:40 brouard
877: *** empty log message ***
878:
879: Revision 1.98 2004/05/16 15:05:56 brouard
880: New version 0.97 . First attempt to estimate force of mortality
881: directly from the data i.e. without the need of knowing the health
882: state at each age, but using a Gompertz model: log u =a + b*age .
883: This is the basic analysis of mortality and should be done before any
884: other analysis, in order to test if the mortality estimated from the
885: cross-longitudinal survey is different from the mortality estimated
886: from other sources like vital statistic data.
887:
888: The same imach parameter file can be used but the option for mle should be -3.
889:
1.324 brouard 890: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 891: former routines in order to include the new code within the former code.
892:
893: The output is very simple: only an estimate of the intercept and of
894: the slope with 95% confident intervals.
895:
896: Current limitations:
897: A) Even if you enter covariates, i.e. with the
898: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
899: B) There is no computation of Life Expectancy nor Life Table.
900:
901: Revision 1.97 2004/02/20 13:25:42 lievre
902: Version 0.96d. Population forecasting command line is (temporarily)
903: suppressed.
904:
905: Revision 1.96 2003/07/15 15:38:55 brouard
906: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
907: rewritten within the same printf. Workaround: many printfs.
908:
909: Revision 1.95 2003/07/08 07:54:34 brouard
910: * imach.c (Repository):
911: (Repository): Using imachwizard code to output a more meaningful covariance
912: matrix (cov(a12,c31) instead of numbers.
913:
914: Revision 1.94 2003/06/27 13:00:02 brouard
915: Just cleaning
916:
917: Revision 1.93 2003/06/25 16:33:55 brouard
918: (Module): On windows (cygwin) function asctime_r doesn't
919: exist so I changed back to asctime which exists.
920: (Module): Version 0.96b
921:
922: Revision 1.92 2003/06/25 16:30:45 brouard
923: (Module): On windows (cygwin) function asctime_r doesn't
924: exist so I changed back to asctime which exists.
925:
926: Revision 1.91 2003/06/25 15:30:29 brouard
927: * imach.c (Repository): Duplicated warning errors corrected.
928: (Repository): Elapsed time after each iteration is now output. It
929: helps to forecast when convergence will be reached. Elapsed time
930: is stamped in powell. We created a new html file for the graphs
931: concerning matrix of covariance. It has extension -cov.htm.
932:
933: Revision 1.90 2003/06/24 12:34:15 brouard
934: (Module): Some bugs corrected for windows. Also, when
935: mle=-1 a template is output in file "or"mypar.txt with the design
936: of the covariance matrix to be input.
937:
938: Revision 1.89 2003/06/24 12:30:52 brouard
939: (Module): Some bugs corrected for windows. Also, when
940: mle=-1 a template is output in file "or"mypar.txt with the design
941: of the covariance matrix to be input.
942:
943: Revision 1.88 2003/06/23 17:54:56 brouard
944: * 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.
945:
946: Revision 1.87 2003/06/18 12:26:01 brouard
947: Version 0.96
948:
949: Revision 1.86 2003/06/17 20:04:08 brouard
950: (Module): Change position of html and gnuplot routines and added
951: routine fileappend.
952:
953: Revision 1.85 2003/06/17 13:12:43 brouard
954: * imach.c (Repository): Check when date of death was earlier that
955: current date of interview. It may happen when the death was just
956: prior to the death. In this case, dh was negative and likelihood
957: was wrong (infinity). We still send an "Error" but patch by
958: assuming that the date of death was just one stepm after the
959: interview.
960: (Repository): Because some people have very long ID (first column)
961: we changed int to long in num[] and we added a new lvector for
962: memory allocation. But we also truncated to 8 characters (left
963: truncation)
964: (Repository): No more line truncation errors.
965:
966: Revision 1.84 2003/06/13 21:44:43 brouard
967: * imach.c (Repository): Replace "freqsummary" at a correct
968: place. It differs from routine "prevalence" which may be called
969: many times. Probs is memory consuming and must be used with
970: parcimony.
971: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
972:
973: Revision 1.83 2003/06/10 13:39:11 lievre
974: *** empty log message ***
975:
976: Revision 1.82 2003/06/05 15:57:20 brouard
977: Add log in imach.c and fullversion number is now printed.
978:
979: */
980: /*
981: Interpolated Markov Chain
982:
983: Short summary of the programme:
984:
1.227 brouard 985: This program computes Healthy Life Expectancies or State-specific
986: (if states aren't health statuses) Expectancies from
987: cross-longitudinal data. Cross-longitudinal data consist in:
988:
989: -1- a first survey ("cross") where individuals from different ages
990: are interviewed on their health status or degree of disability (in
991: the case of a health survey which is our main interest)
992:
993: -2- at least a second wave of interviews ("longitudinal") which
994: measure each change (if any) in individual health status. Health
995: expectancies are computed from the time spent in each health state
996: according to a model. More health states you consider, more time is
997: necessary to reach the Maximum Likelihood of the parameters involved
998: in the model. The simplest model is the multinomial logistic model
999: where pij is the probability to be observed in state j at the second
1000: wave conditional to be observed in state i at the first
1001: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
1002: etc , where 'age' is age and 'sex' is a covariate. If you want to
1003: have a more complex model than "constant and age", you should modify
1004: the program where the markup *Covariates have to be included here
1005: again* invites you to do it. More covariates you add, slower the
1.126 brouard 1006: convergence.
1007:
1008: The advantage of this computer programme, compared to a simple
1009: multinomial logistic model, is clear when the delay between waves is not
1010: identical for each individual. Also, if a individual missed an
1011: intermediate interview, the information is lost, but taken into
1012: account using an interpolation or extrapolation.
1013:
1014: hPijx is the probability to be observed in state i at age x+h
1015: conditional to the observed state i at age x. The delay 'h' can be
1016: split into an exact number (nh*stepm) of unobserved intermediate
1017: states. This elementary transition (by month, quarter,
1018: semester or year) is modelled as a multinomial logistic. The hPx
1019: matrix is simply the matrix product of nh*stepm elementary matrices
1020: and the contribution of each individual to the likelihood is simply
1021: hPijx.
1022:
1023: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 1024: of the life expectancies. It also computes the period (stable) prevalence.
1025:
1026: Back prevalence and projections:
1.227 brouard 1027:
1028: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
1029: double agemaxpar, double ftolpl, int *ncvyearp, double
1030: dateprev1,double dateprev2, int firstpass, int lastpass, int
1031: mobilavproj)
1032:
1033: Computes the back prevalence limit for any combination of
1034: covariate values k at any age between ageminpar and agemaxpar and
1035: returns it in **bprlim. In the loops,
1036:
1037: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
1038: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
1039:
1040: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 1041: Computes for any combination of covariates k and any age between bage and fage
1042: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
1043: oldm=oldms;savm=savms;
1.227 brouard 1044:
1.267 brouard 1045: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 1046: Computes the transition matrix starting at age 'age' over
1047: 'nhstepm*hstepm*stepm' months (i.e. until
1048: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 1049: nhstepm*hstepm matrices.
1050:
1051: Returns p3mat[i][j][h] after calling
1052: p3mat[i][j][h]=matprod2(newm,
1053: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
1054: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
1055: oldm);
1.226 brouard 1056:
1057: Important routines
1058:
1059: - func (or funcone), computes logit (pij) distinguishing
1060: o fixed variables (single or product dummies or quantitative);
1061: o varying variables by:
1062: (1) wave (single, product dummies, quantitative),
1063: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
1064: % fixed dummy (treated) or quantitative (not done because time-consuming);
1065: % varying dummy (not done) or quantitative (not done);
1066: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
1067: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
1068: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
1.325 brouard 1069: o There are 2**cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
1.226 brouard 1070: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 1071:
1.226 brouard 1072:
1073:
1.324 brouard 1074: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
1075: Institut national d'études démographiques, Paris.
1.126 brouard 1076: This software have been partly granted by Euro-REVES, a concerted action
1077: from the European Union.
1078: It is copyrighted identically to a GNU software product, ie programme and
1079: software can be distributed freely for non commercial use. Latest version
1080: can be accessed at http://euroreves.ined.fr/imach .
1081:
1082: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
1083: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
1084:
1085: **********************************************************************/
1086: /*
1087: main
1088: read parameterfile
1089: read datafile
1090: concatwav
1091: freqsummary
1092: if (mle >= 1)
1093: mlikeli
1094: print results files
1095: if mle==1
1096: computes hessian
1097: read end of parameter file: agemin, agemax, bage, fage, estepm
1098: begin-prev-date,...
1099: open gnuplot file
1100: open html file
1.145 brouard 1101: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
1102: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
1103: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
1104: freexexit2 possible for memory heap.
1105:
1106: h Pij x | pij_nom ficrestpij
1107: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
1108: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
1109: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
1110:
1111: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
1112: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
1113: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
1114: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
1115: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
1116:
1.126 brouard 1117: forecasting if prevfcast==1 prevforecast call prevalence()
1118: health expectancies
1119: Variance-covariance of DFLE
1120: prevalence()
1121: movingaverage()
1122: varevsij()
1123: if popbased==1 varevsij(,popbased)
1124: total life expectancies
1125: Variance of period (stable) prevalence
1126: end
1127: */
1128:
1.187 brouard 1129: /* #define DEBUG */
1130: /* #define DEBUGBRENT */
1.203 brouard 1131: /* #define DEBUGLINMIN */
1132: /* #define DEBUGHESS */
1133: #define DEBUGHESSIJ
1.224 brouard 1134: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 1135: #define POWELL /* Instead of NLOPT */
1.224 brouard 1136: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 1137: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
1138: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.319 brouard 1139: /* #define FLATSUP *//* Suppresses directions where likelihood is flat */
1.126 brouard 1140:
1141: #include <math.h>
1142: #include <stdio.h>
1143: #include <stdlib.h>
1144: #include <string.h>
1.226 brouard 1145: #include <ctype.h>
1.159 brouard 1146:
1147: #ifdef _WIN32
1148: #include <io.h>
1.172 brouard 1149: #include <windows.h>
1150: #include <tchar.h>
1.159 brouard 1151: #else
1.126 brouard 1152: #include <unistd.h>
1.159 brouard 1153: #endif
1.126 brouard 1154:
1155: #include <limits.h>
1156: #include <sys/types.h>
1.171 brouard 1157:
1158: #if defined(__GNUC__)
1159: #include <sys/utsname.h> /* Doesn't work on Windows */
1160: #endif
1161:
1.126 brouard 1162: #include <sys/stat.h>
1163: #include <errno.h>
1.159 brouard 1164: /* extern int errno; */
1.126 brouard 1165:
1.157 brouard 1166: /* #ifdef LINUX */
1167: /* #include <time.h> */
1168: /* #include "timeval.h" */
1169: /* #else */
1170: /* #include <sys/time.h> */
1171: /* #endif */
1172:
1.126 brouard 1173: #include <time.h>
1174:
1.136 brouard 1175: #ifdef GSL
1176: #include <gsl/gsl_errno.h>
1177: #include <gsl/gsl_multimin.h>
1178: #endif
1179:
1.167 brouard 1180:
1.162 brouard 1181: #ifdef NLOPT
1182: #include <nlopt.h>
1183: typedef struct {
1184: double (* function)(double [] );
1185: } myfunc_data ;
1186: #endif
1187:
1.126 brouard 1188: /* #include <libintl.h> */
1189: /* #define _(String) gettext (String) */
1190:
1.251 brouard 1191: #define MAXLINE 2048 /* Was 256 and 1024. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 1192:
1193: #define GNUPLOTPROGRAM "gnuplot"
1194: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
1.329 ! brouard 1195: #define FILENAMELENGTH 256
1.126 brouard 1196:
1197: #define GLOCK_ERROR_NOPATH -1 /* empty path */
1198: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
1199:
1.144 brouard 1200: #define MAXPARM 128 /**< Maximum number of parameters for the optimization */
1201: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 1202:
1203: #define NINTERVMAX 8
1.144 brouard 1204: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
1205: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
1.325 brouard 1206: #define NCOVMAX 30 /**< Maximum number of covariates used in the model, including generated covariates V1*V2 or V1*age */
1.197 brouard 1207: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 1208: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
1209: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.290 brouard 1210: /*#define MAXN 20000 */ /* Should by replaced by nobs, real number of observations and unlimited */
1.144 brouard 1211: #define YEARM 12. /**< Number of months per year */
1.218 brouard 1212: /* #define AGESUP 130 */
1.288 brouard 1213: /* #define AGESUP 150 */
1214: #define AGESUP 200
1.268 brouard 1215: #define AGEINF 0
1.218 brouard 1216: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1217: #define AGEBASE 40
1.194 brouard 1218: #define AGEOVERFLOW 1.e20
1.164 brouard 1219: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1220: #ifdef _WIN32
1221: #define DIRSEPARATOR '\\'
1222: #define CHARSEPARATOR "\\"
1223: #define ODIRSEPARATOR '/'
1224: #else
1.126 brouard 1225: #define DIRSEPARATOR '/'
1226: #define CHARSEPARATOR "/"
1227: #define ODIRSEPARATOR '\\'
1228: #endif
1229:
1.329 ! brouard 1230: /* $Id: imach.c,v 1.328 2022/07/27 17:40:48 brouard Exp $ */
1.126 brouard 1231: /* $State: Exp $ */
1.196 brouard 1232: #include "version.h"
1233: char version[]=__IMACH_VERSION__;
1.323 brouard 1234: char copyright[]="July 2022,INED-EUROREVES-Institut de longevite-Japan Society for the Promotion of Science (Grant-in-Aid for Scientific Research 25293121), Intel Software 2015-2020, Nihon University 2021-202, INED 2000-2022";
1.329 ! brouard 1235: char fullversion[]="$Revision: 1.328 $ $Date: 2022/07/27 17:40:48 $";
1.126 brouard 1236: char strstart[80];
1237: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1238: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.187 brouard 1239: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.145 brouard 1240: /* Number of covariates model=V2+V1+ V3*age+V2*V4 */
1241: int cptcovn=0; /**< cptcovn number of covariates added in the model (excepting constant and age and age*product) */
1242: int cptcovt=0; /**< cptcovt number of covariates added in the model (excepting constant and age) */
1.225 brouard 1243: int cptcovs=0; /**< cptcovs number of simple covariates in the model V2+V1 =2 */
1244: int cptcovsnq=0; /**< cptcovsnq number of simple covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1245: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1246: int cptcovprodnoage=0; /**< Number of covariate products without age */
1247: int cptcoveff=0; /* Total number of covariates to vary for printing results */
1.233 brouard 1248: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1249: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.232 brouard 1250: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (dummy of quantitative) in the model */
1.234 brouard 1251: int nsd=0; /**< Total number of single dummy variables (output) */
1252: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1253: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1254: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1255: int ntveff=0; /**< ntveff number of effective time varying variables */
1256: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1257: int cptcov=0; /* Working variable */
1.290 brouard 1258: int nobs=10; /* Number of observations in the data lastobs-firstobs */
1.218 brouard 1259: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.302 brouard 1260: int npar=NPARMAX; /* Number of parameters (nlstate+ndeath-1)*nlstate*ncovmodel; */
1.126 brouard 1261: int nlstate=2; /* Number of live states */
1262: int ndeath=1; /* Number of dead states */
1.130 brouard 1263: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.223 brouard 1264: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable */
1.126 brouard 1265: int popbased=0;
1266:
1267: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1268: int maxwav=0; /* Maxim number of waves */
1269: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1270: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1271: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 1272: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1273: int mle=1, weightopt=0;
1.126 brouard 1274: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1275: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1276: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1277: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1278: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1279: int selected(int kvar); /* Is covariate kvar selected for printing results */
1280:
1.130 brouard 1281: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1282: double **matprod2(); /* test */
1.126 brouard 1283: double **oldm, **newm, **savm; /* Working pointers to matrices */
1284: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1285: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1286:
1.136 brouard 1287: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1288: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1289: FILE *ficlog, *ficrespow;
1.130 brouard 1290: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1291: double fretone; /* Only one call to likelihood */
1.130 brouard 1292: long ipmx=0; /* Number of contributions */
1.126 brouard 1293: double sw; /* Sum of weights */
1294: char filerespow[FILENAMELENGTH];
1295: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1296: FILE *ficresilk;
1297: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1298: FILE *ficresprobmorprev;
1299: FILE *fichtm, *fichtmcov; /* Html File */
1300: FILE *ficreseij;
1301: char filerese[FILENAMELENGTH];
1302: FILE *ficresstdeij;
1303: char fileresstde[FILENAMELENGTH];
1304: FILE *ficrescveij;
1305: char filerescve[FILENAMELENGTH];
1306: FILE *ficresvij;
1307: char fileresv[FILENAMELENGTH];
1.269 brouard 1308:
1.126 brouard 1309: char title[MAXLINE];
1.234 brouard 1310: char model[MAXLINE]; /**< The model line */
1.217 brouard 1311: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1312: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1313: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1314: char command[FILENAMELENGTH];
1315: int outcmd=0;
1316:
1.217 brouard 1317: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1318: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1319: char filelog[FILENAMELENGTH]; /* Log file */
1320: char filerest[FILENAMELENGTH];
1321: char fileregp[FILENAMELENGTH];
1322: char popfile[FILENAMELENGTH];
1323:
1324: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1325:
1.157 brouard 1326: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1327: /* struct timezone tzp; */
1328: /* extern int gettimeofday(); */
1329: struct tm tml, *gmtime(), *localtime();
1330:
1331: extern time_t time();
1332:
1333: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1334: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1335: struct tm tm;
1336:
1.126 brouard 1337: char strcurr[80], strfor[80];
1338:
1339: char *endptr;
1340: long lval;
1341: double dval;
1342:
1343: #define NR_END 1
1344: #define FREE_ARG char*
1345: #define FTOL 1.0e-10
1346:
1347: #define NRANSI
1.240 brouard 1348: #define ITMAX 200
1349: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1350:
1351: #define TOL 2.0e-4
1352:
1353: #define CGOLD 0.3819660
1354: #define ZEPS 1.0e-10
1355: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1356:
1357: #define GOLD 1.618034
1358: #define GLIMIT 100.0
1359: #define TINY 1.0e-20
1360:
1361: static double maxarg1,maxarg2;
1362: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1363: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1364:
1365: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1366: #define rint(a) floor(a+0.5)
1.166 brouard 1367: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1368: #define mytinydouble 1.0e-16
1.166 brouard 1369: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1370: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1371: /* static double dsqrarg; */
1372: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1373: static double sqrarg;
1374: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1375: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1376: int agegomp= AGEGOMP;
1377:
1378: int imx;
1379: int stepm=1;
1380: /* Stepm, step in month: minimum step interpolation*/
1381:
1382: int estepm;
1383: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1384:
1385: int m,nb;
1386: long *num;
1.197 brouard 1387: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1388: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1389: covariate for which somebody answered excluding
1390: undefined. Usually 2: 0 and 1. */
1391: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1392: covariate for which somebody answered including
1393: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1394: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1395: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1396: double ***mobaverage, ***mobaverages; /* New global variable */
1.126 brouard 1397: double *ageexmed,*agecens;
1398: double dateintmean=0;
1.296 brouard 1399: double anprojd, mprojd, jprojd; /* For eventual projections */
1400: double anprojf, mprojf, jprojf;
1.126 brouard 1401:
1.296 brouard 1402: double anbackd, mbackd, jbackd; /* For eventual backprojections */
1403: double anbackf, mbackf, jbackf;
1404: double jintmean,mintmean,aintmean;
1.126 brouard 1405: double *weight;
1406: int **s; /* Status */
1.141 brouard 1407: double *agedc;
1.145 brouard 1408: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1409: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1410: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1411: double **coqvar; /* Fixed quantitative covariate nqv */
1412: double ***cotvar; /* Time varying covariate ntv */
1.225 brouard 1413: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1414: double idx;
1415: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.319 brouard 1416: /* Some documentation */
1417: /* Design original data
1418: * V1 V2 V3 V4 V5 V6 V7 V8 Weight ddb ddth d1st s1 V9 V10 V11 V12 s2 V9 V10 V11 V12
1419: * < ncovcol=6 > nqv=2 (V7 V8) dv dv dv qtv dv dv dvv qtv
1420: * ntv=3 nqtv=1
1421: * cptcovn number of covariates (not including constant and age) = # of + plus 1 = 10+1=11
1422: * For time varying covariate, quanti or dummies
1423: * cotqvar[wav][iv(1 to nqtv)][i]= [1][12][i]=(V12) quanti
1424: * cotvar[wav][ntv+iv][i]= [3+(1 to nqtv)][i]=(V12) quanti
1425: * cotvar[wav][iv(1 to ntv)][i]= [1][1][i]=(V9) dummies at wav 1
1426: * cotvar[wav][iv(1 to ntv)][i]= [1][2][i]=(V10) dummies at wav 1
1427: * covar[k,i], value of kth fixed covariate dummy or quanti :
1428: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
1429: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 + V9 + V9*age + V10
1430: * k= 1 2 3 4 5 6 7 8 9 10 11
1431: */
1432: /* According to the model, more columns can be added to covar by the product of covariates */
1.318 brouard 1433: /* ncovcol=1(Males=0 Females=1) nqv=1(raedyrs) ntv=2(withoutiadl=0 withiadl=1, witoutadl=0 withoutadl=1) nqtv=1(bmi) nlstate=3 ndeath=1
1434: # States 1=Coresidence, 2 Living alone, 3 Institution
1435: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1436: */
1.319 brouard 1437: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1438: /* k 1 2 3 4 5 6 7 8 9 */
1439: /*Typevar[k]= 0 0 0 2 1 0 2 1 0 *//*0 for simple covariate (dummy, quantitative,*/
1440: /* fixed or varying), 1 for age product, 2 for*/
1441: /* product */
1442: /*Dummy[k]= 1 0 0 1 3 1 1 2 0 *//*Dummy[k] 0=dummy (0 1), 1 quantitative */
1443: /*(single or product without age), 2 dummy*/
1444: /* with age product, 3 quant with age product*/
1445: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 */
1446: /* nsd 1 2 3 */ /* Counting single dummies covar fixed or tv */
1447: /*TvarsD[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1448: /*TvarsDind[k] 2 3 9 */ /* position K of single dummy cova */
1449: /* nsq 1 2 */ /* Counting single quantit tv */
1450: /* TvarsQ[k] 5 2 */ /* Number of single quantitative cova */
1451: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1452: /* Tprod[i]=k 1 2 */ /* Position in model of the ith prod without age */
1453: /* cptcovage 1 2 */ /* Counting cov*age in the model equation */
1454: /* Tage[cptcovage]=k 5 8 */ /* Position in the model of ith cov*age */
1455: /* Tvard[1][1]@4={4,3,1,2} V4*V3 V1*V2 */ /* Position in model of the ith prod without age */
1456: /* TvarF TvarF[1]=Tvar[6]=2, TvarF[2]=Tvar[7]=7, TvarF[3]=Tvar[9]=1 ID of fixed covariates or product V2, V1*V2, V1 */
1.320 brouard 1457: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.234 brouard 1458: /* Type */
1459: /* V 1 2 3 4 5 */
1460: /* F F V V V */
1461: /* D Q D D Q */
1462: /* */
1463: int *TvarsD;
1464: int *TvarsDind;
1465: int *TvarsQ;
1466: int *TvarsQind;
1467:
1.318 brouard 1468: #define MAXRESULTLINESPONE 10+1
1.235 brouard 1469: int nresult=0;
1.258 brouard 1470: int parameterline=0; /* # of the parameter (type) line */
1.318 brouard 1471: int TKresult[MAXRESULTLINESPONE];
1472: int Tresult[MAXRESULTLINESPONE][NCOVMAX];/* For dummy variable , value (output) */
1473: int Tinvresult[MAXRESULTLINESPONE][NCOVMAX];/* For dummy variable , value (output) */
1474: int Tvresult[MAXRESULTLINESPONE][NCOVMAX]; /* For dummy variable , variable # (output) */
1475: double Tqresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , value (output) */
1476: double Tqinvresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , value (output) */
1477: int Tvqresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , variable # (output) */
1478:
1479: /* ncovcol=1(Males=0 Females=1) nqv=1(raedyrs) ntv=2(withoutiadl=0 withiadl=1, witoutadl=0 withoutadl=1) nqtv=1(bmi) nlstate=3 ndeath=1
1480: # States 1=Coresidence, 2 Living alone, 3 Institution
1481: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1482: */
1.234 brouard 1483: /* 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 1484: 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 */
1485: 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 */
1486: 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 */
1487: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1488: 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 */
1489: 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 1490: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1491: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1492: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1493: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1494: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1495: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1496: 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 */
1497: 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 */
1498:
1.230 brouard 1499: int *Tvarsel; /**< Selected covariates for output */
1500: double *Tvalsel; /**< Selected modality value of covariate for output */
1.226 brouard 1501: int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.227 brouard 1502: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1503: 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 1504: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1505: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1506: int *Tage;
1.227 brouard 1507: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1508: 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 1509: 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*/
1510: 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 1511: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1512: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1513: int **Tvard;
1514: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1515: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1516: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1517: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1518: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1519: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1520: double *lsurv, *lpop, *tpop;
1521:
1.231 brouard 1522: #define FD 1; /* Fixed dummy covariate */
1523: #define FQ 2; /* Fixed quantitative covariate */
1524: #define FP 3; /* Fixed product covariate */
1525: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1526: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1527: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1528: #define VD 10; /* Varying dummy covariate */
1529: #define VQ 11; /* Varying quantitative covariate */
1530: #define VP 12; /* Varying product covariate */
1531: #define VPDD 13; /* Varying product dummy*dummy covariate */
1532: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1533: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1534: #define APFD 16; /* Age product * fixed dummy covariate */
1535: #define APFQ 17; /* Age product * fixed quantitative covariate */
1536: #define APVD 18; /* Age product * varying dummy covariate */
1537: #define APVQ 19; /* Age product * varying quantitative covariate */
1538:
1539: #define FTYPE 1; /* Fixed covariate */
1540: #define VTYPE 2; /* Varying covariate (loop in wave) */
1541: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1542:
1543: struct kmodel{
1544: int maintype; /* main type */
1545: int subtype; /* subtype */
1546: };
1547: struct kmodel modell[NCOVMAX];
1548:
1.143 brouard 1549: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1550: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1551:
1552: /**************** split *************************/
1553: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1554: {
1555: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1556: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1557: */
1558: char *ss; /* pointer */
1.186 brouard 1559: int l1=0, l2=0; /* length counters */
1.126 brouard 1560:
1561: l1 = strlen(path ); /* length of path */
1562: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1563: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1564: if ( ss == NULL ) { /* no directory, so determine current directory */
1565: strcpy( name, path ); /* we got the fullname name because no directory */
1566: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1567: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1568: /* get current working directory */
1569: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1570: #ifdef WIN32
1571: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1572: #else
1573: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1574: #endif
1.126 brouard 1575: return( GLOCK_ERROR_GETCWD );
1576: }
1577: /* got dirc from getcwd*/
1578: printf(" DIRC = %s \n",dirc);
1.205 brouard 1579: } else { /* strip directory from path */
1.126 brouard 1580: ss++; /* after this, the filename */
1581: l2 = strlen( ss ); /* length of filename */
1582: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1583: strcpy( name, ss ); /* save file name */
1584: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1585: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1586: printf(" DIRC2 = %s \n",dirc);
1587: }
1588: /* We add a separator at the end of dirc if not exists */
1589: l1 = strlen( dirc ); /* length of directory */
1590: if( dirc[l1-1] != DIRSEPARATOR ){
1591: dirc[l1] = DIRSEPARATOR;
1592: dirc[l1+1] = 0;
1593: printf(" DIRC3 = %s \n",dirc);
1594: }
1595: ss = strrchr( name, '.' ); /* find last / */
1596: if (ss >0){
1597: ss++;
1598: strcpy(ext,ss); /* save extension */
1599: l1= strlen( name);
1600: l2= strlen(ss)+1;
1601: strncpy( finame, name, l1-l2);
1602: finame[l1-l2]= 0;
1603: }
1604:
1605: return( 0 ); /* we're done */
1606: }
1607:
1608:
1609: /******************************************/
1610:
1611: void replace_back_to_slash(char *s, char*t)
1612: {
1613: int i;
1614: int lg=0;
1615: i=0;
1616: lg=strlen(t);
1617: for(i=0; i<= lg; i++) {
1618: (s[i] = t[i]);
1619: if (t[i]== '\\') s[i]='/';
1620: }
1621: }
1622:
1.132 brouard 1623: char *trimbb(char *out, char *in)
1.137 brouard 1624: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1625: char *s;
1626: s=out;
1627: while (*in != '\0'){
1.137 brouard 1628: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1629: in++;
1630: }
1631: *out++ = *in++;
1632: }
1633: *out='\0';
1634: return s;
1635: }
1636:
1.187 brouard 1637: /* char *substrchaine(char *out, char *in, char *chain) */
1638: /* { */
1639: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1640: /* char *s, *t; */
1641: /* t=in;s=out; */
1642: /* while ((*in != *chain) && (*in != '\0')){ */
1643: /* *out++ = *in++; */
1644: /* } */
1645:
1646: /* /\* *in matches *chain *\/ */
1647: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1648: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1649: /* } */
1650: /* in--; chain--; */
1651: /* while ( (*in != '\0')){ */
1652: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1653: /* *out++ = *in++; */
1654: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1655: /* } */
1656: /* *out='\0'; */
1657: /* out=s; */
1658: /* return out; */
1659: /* } */
1660: char *substrchaine(char *out, char *in, char *chain)
1661: {
1662: /* Substract chain 'chain' from 'in', return and output 'out' */
1663: /* in="V1+V1*age+age*age+V2", chain="age*age" */
1664:
1665: char *strloc;
1666:
1667: strcpy (out, in);
1668: strloc = strstr(out, chain); /* strloc points to out at age*age+V2 */
1669: printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out);
1670: if(strloc != NULL){
1671: /* will affect out */ /* strloc+strlenc(chain)=+V2 */ /* Will also work in Unicode */
1672: memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1);
1673: /* strcpy (strloc, strloc +strlen(chain));*/
1674: }
1675: printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out);
1676: return out;
1677: }
1678:
1679:
1.145 brouard 1680: char *cutl(char *blocc, char *alocc, char *in, char occ)
1681: {
1.187 brouard 1682: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.145 brouard 1683: and alocc starts after first occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1.310 brouard 1684: gives alocc="abcdef" and blocc="ghi2j".
1.145 brouard 1685: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1686: */
1.160 brouard 1687: char *s, *t;
1.145 brouard 1688: t=in;s=in;
1689: while ((*in != occ) && (*in != '\0')){
1690: *alocc++ = *in++;
1691: }
1692: if( *in == occ){
1693: *(alocc)='\0';
1694: s=++in;
1695: }
1696:
1697: if (s == t) {/* occ not found */
1698: *(alocc-(in-s))='\0';
1699: in=s;
1700: }
1701: while ( *in != '\0'){
1702: *blocc++ = *in++;
1703: }
1704:
1705: *blocc='\0';
1706: return t;
1707: }
1.137 brouard 1708: char *cutv(char *blocc, char *alocc, char *in, char occ)
1709: {
1.187 brouard 1710: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1711: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1712: gives blocc="abcdef2ghi" and alocc="j".
1713: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1714: */
1715: char *s, *t;
1716: t=in;s=in;
1717: while (*in != '\0'){
1718: while( *in == occ){
1719: *blocc++ = *in++;
1720: s=in;
1721: }
1722: *blocc++ = *in++;
1723: }
1724: if (s == t) /* occ not found */
1725: *(blocc-(in-s))='\0';
1726: else
1727: *(blocc-(in-s)-1)='\0';
1728: in=s;
1729: while ( *in != '\0'){
1730: *alocc++ = *in++;
1731: }
1732:
1733: *alocc='\0';
1734: return s;
1735: }
1736:
1.126 brouard 1737: int nbocc(char *s, char occ)
1738: {
1739: int i,j=0;
1740: int lg=20;
1741: i=0;
1742: lg=strlen(s);
1743: for(i=0; i<= lg; i++) {
1.234 brouard 1744: if (s[i] == occ ) j++;
1.126 brouard 1745: }
1746: return j;
1747: }
1748:
1.137 brouard 1749: /* void cutv(char *u,char *v, char*t, char occ) */
1750: /* { */
1751: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1752: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1753: /* gives u="abcdef2ghi" and v="j" *\/ */
1754: /* int i,lg,j,p=0; */
1755: /* i=0; */
1756: /* lg=strlen(t); */
1757: /* for(j=0; j<=lg-1; j++) { */
1758: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1759: /* } */
1.126 brouard 1760:
1.137 brouard 1761: /* for(j=0; j<p; j++) { */
1762: /* (u[j] = t[j]); */
1763: /* } */
1764: /* u[p]='\0'; */
1.126 brouard 1765:
1.137 brouard 1766: /* for(j=0; j<= lg; j++) { */
1767: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1768: /* } */
1769: /* } */
1.126 brouard 1770:
1.160 brouard 1771: #ifdef _WIN32
1772: char * strsep(char **pp, const char *delim)
1773: {
1774: char *p, *q;
1775:
1776: if ((p = *pp) == NULL)
1777: return 0;
1778: if ((q = strpbrk (p, delim)) != NULL)
1779: {
1780: *pp = q + 1;
1781: *q = '\0';
1782: }
1783: else
1784: *pp = 0;
1785: return p;
1786: }
1787: #endif
1788:
1.126 brouard 1789: /********************** nrerror ********************/
1790:
1791: void nrerror(char error_text[])
1792: {
1793: fprintf(stderr,"ERREUR ...\n");
1794: fprintf(stderr,"%s\n",error_text);
1795: exit(EXIT_FAILURE);
1796: }
1797: /*********************** vector *******************/
1798: double *vector(int nl, int nh)
1799: {
1800: double *v;
1801: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
1802: if (!v) nrerror("allocation failure in vector");
1803: return v-nl+NR_END;
1804: }
1805:
1806: /************************ free vector ******************/
1807: void free_vector(double*v, int nl, int nh)
1808: {
1809: free((FREE_ARG)(v+nl-NR_END));
1810: }
1811:
1812: /************************ivector *******************************/
1813: int *ivector(long nl,long nh)
1814: {
1815: int *v;
1816: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
1817: if (!v) nrerror("allocation failure in ivector");
1818: return v-nl+NR_END;
1819: }
1820:
1821: /******************free ivector **************************/
1822: void free_ivector(int *v, long nl, long nh)
1823: {
1824: free((FREE_ARG)(v+nl-NR_END));
1825: }
1826:
1827: /************************lvector *******************************/
1828: long *lvector(long nl,long nh)
1829: {
1830: long *v;
1831: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
1832: if (!v) nrerror("allocation failure in ivector");
1833: return v-nl+NR_END;
1834: }
1835:
1836: /******************free lvector **************************/
1837: void free_lvector(long *v, long nl, long nh)
1838: {
1839: free((FREE_ARG)(v+nl-NR_END));
1840: }
1841:
1842: /******************* imatrix *******************************/
1843: int **imatrix(long nrl, long nrh, long ncl, long nch)
1844: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
1845: {
1846: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
1847: int **m;
1848:
1849: /* allocate pointers to rows */
1850: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
1851: if (!m) nrerror("allocation failure 1 in matrix()");
1852: m += NR_END;
1853: m -= nrl;
1854:
1855:
1856: /* allocate rows and set pointers to them */
1857: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
1858: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1859: m[nrl] += NR_END;
1860: m[nrl] -= ncl;
1861:
1862: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
1863:
1864: /* return pointer to array of pointers to rows */
1865: return m;
1866: }
1867:
1868: /****************** free_imatrix *************************/
1869: void free_imatrix(m,nrl,nrh,ncl,nch)
1870: int **m;
1871: long nch,ncl,nrh,nrl;
1872: /* free an int matrix allocated by imatrix() */
1873: {
1874: free((FREE_ARG) (m[nrl]+ncl-NR_END));
1875: free((FREE_ARG) (m+nrl-NR_END));
1876: }
1877:
1878: /******************* matrix *******************************/
1879: double **matrix(long nrl, long nrh, long ncl, long nch)
1880: {
1881: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
1882: double **m;
1883:
1884: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1885: if (!m) nrerror("allocation failure 1 in matrix()");
1886: m += NR_END;
1887: m -= nrl;
1888:
1889: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1890: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1891: m[nrl] += NR_END;
1892: m[nrl] -= ncl;
1893:
1894: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1895: return m;
1.145 brouard 1896: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
1897: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
1898: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 1899: */
1900: }
1901:
1902: /*************************free matrix ************************/
1903: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
1904: {
1905: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1906: free((FREE_ARG)(m+nrl-NR_END));
1907: }
1908:
1909: /******************* ma3x *******************************/
1910: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
1911: {
1912: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
1913: double ***m;
1914:
1915: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1916: if (!m) nrerror("allocation failure 1 in matrix()");
1917: m += NR_END;
1918: m -= nrl;
1919:
1920: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1921: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1922: m[nrl] += NR_END;
1923: m[nrl] -= ncl;
1924:
1925: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1926:
1927: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
1928: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
1929: m[nrl][ncl] += NR_END;
1930: m[nrl][ncl] -= nll;
1931: for (j=ncl+1; j<=nch; j++)
1932: m[nrl][j]=m[nrl][j-1]+nlay;
1933:
1934: for (i=nrl+1; i<=nrh; i++) {
1935: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
1936: for (j=ncl+1; j<=nch; j++)
1937: m[i][j]=m[i][j-1]+nlay;
1938: }
1939: return m;
1940: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
1941: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
1942: */
1943: }
1944:
1945: /*************************free ma3x ************************/
1946: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
1947: {
1948: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
1949: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1950: free((FREE_ARG)(m+nrl-NR_END));
1951: }
1952:
1953: /*************** function subdirf ***********/
1954: char *subdirf(char fileres[])
1955: {
1956: /* Caution optionfilefiname is hidden */
1957: strcpy(tmpout,optionfilefiname);
1958: strcat(tmpout,"/"); /* Add to the right */
1959: strcat(tmpout,fileres);
1960: return tmpout;
1961: }
1962:
1963: /*************** function subdirf2 ***********/
1964: char *subdirf2(char fileres[], char *preop)
1965: {
1.314 brouard 1966: /* Example subdirf2(optionfilefiname,"FB_") with optionfilefiname="texte", result="texte/FB_texte"
1967: Errors in subdirf, 2, 3 while printing tmpout is
1.315 brouard 1968: rewritten within the same printf. Workaround: many printfs */
1.126 brouard 1969: /* Caution optionfilefiname is hidden */
1970: strcpy(tmpout,optionfilefiname);
1971: strcat(tmpout,"/");
1972: strcat(tmpout,preop);
1973: strcat(tmpout,fileres);
1974: return tmpout;
1975: }
1976:
1977: /*************** function subdirf3 ***********/
1978: char *subdirf3(char fileres[], char *preop, char *preop2)
1979: {
1980:
1981: /* Caution optionfilefiname is hidden */
1982: strcpy(tmpout,optionfilefiname);
1983: strcat(tmpout,"/");
1984: strcat(tmpout,preop);
1985: strcat(tmpout,preop2);
1986: strcat(tmpout,fileres);
1987: return tmpout;
1988: }
1.213 brouard 1989:
1990: /*************** function subdirfext ***********/
1991: char *subdirfext(char fileres[], char *preop, char *postop)
1992: {
1993:
1994: strcpy(tmpout,preop);
1995: strcat(tmpout,fileres);
1996: strcat(tmpout,postop);
1997: return tmpout;
1998: }
1.126 brouard 1999:
1.213 brouard 2000: /*************** function subdirfext3 ***********/
2001: char *subdirfext3(char fileres[], char *preop, char *postop)
2002: {
2003:
2004: /* Caution optionfilefiname is hidden */
2005: strcpy(tmpout,optionfilefiname);
2006: strcat(tmpout,"/");
2007: strcat(tmpout,preop);
2008: strcat(tmpout,fileres);
2009: strcat(tmpout,postop);
2010: return tmpout;
2011: }
2012:
1.162 brouard 2013: char *asc_diff_time(long time_sec, char ascdiff[])
2014: {
2015: long sec_left, days, hours, minutes;
2016: days = (time_sec) / (60*60*24);
2017: sec_left = (time_sec) % (60*60*24);
2018: hours = (sec_left) / (60*60) ;
2019: sec_left = (sec_left) %(60*60);
2020: minutes = (sec_left) /60;
2021: sec_left = (sec_left) % (60);
2022: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
2023: return ascdiff;
2024: }
2025:
1.126 brouard 2026: /***************** f1dim *************************/
2027: extern int ncom;
2028: extern double *pcom,*xicom;
2029: extern double (*nrfunc)(double []);
2030:
2031: double f1dim(double x)
2032: {
2033: int j;
2034: double f;
2035: double *xt;
2036:
2037: xt=vector(1,ncom);
2038: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
2039: f=(*nrfunc)(xt);
2040: free_vector(xt,1,ncom);
2041: return f;
2042: }
2043:
2044: /*****************brent *************************/
2045: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 2046: {
2047: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
2048: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
2049: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
2050: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
2051: * returned function value.
2052: */
1.126 brouard 2053: int iter;
2054: double a,b,d,etemp;
1.159 brouard 2055: double fu=0,fv,fw,fx;
1.164 brouard 2056: double ftemp=0.;
1.126 brouard 2057: double p,q,r,tol1,tol2,u,v,w,x,xm;
2058: double e=0.0;
2059:
2060: a=(ax < cx ? ax : cx);
2061: b=(ax > cx ? ax : cx);
2062: x=w=v=bx;
2063: fw=fv=fx=(*f)(x);
2064: for (iter=1;iter<=ITMAX;iter++) {
2065: xm=0.5*(a+b);
2066: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
2067: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
2068: printf(".");fflush(stdout);
2069: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 2070: #ifdef DEBUGBRENT
1.126 brouard 2071: 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);
2072: 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);
2073: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
2074: #endif
2075: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
2076: *xmin=x;
2077: return fx;
2078: }
2079: ftemp=fu;
2080: if (fabs(e) > tol1) {
2081: r=(x-w)*(fx-fv);
2082: q=(x-v)*(fx-fw);
2083: p=(x-v)*q-(x-w)*r;
2084: q=2.0*(q-r);
2085: if (q > 0.0) p = -p;
2086: q=fabs(q);
2087: etemp=e;
2088: e=d;
2089: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 2090: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 2091: else {
1.224 brouard 2092: d=p/q;
2093: u=x+d;
2094: if (u-a < tol2 || b-u < tol2)
2095: d=SIGN(tol1,xm-x);
1.126 brouard 2096: }
2097: } else {
2098: d=CGOLD*(e=(x >= xm ? a-x : b-x));
2099: }
2100: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
2101: fu=(*f)(u);
2102: if (fu <= fx) {
2103: if (u >= x) a=x; else b=x;
2104: SHFT(v,w,x,u)
1.183 brouard 2105: SHFT(fv,fw,fx,fu)
2106: } else {
2107: if (u < x) a=u; else b=u;
2108: if (fu <= fw || w == x) {
1.224 brouard 2109: v=w;
2110: w=u;
2111: fv=fw;
2112: fw=fu;
1.183 brouard 2113: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 2114: v=u;
2115: fv=fu;
1.183 brouard 2116: }
2117: }
1.126 brouard 2118: }
2119: nrerror("Too many iterations in brent");
2120: *xmin=x;
2121: return fx;
2122: }
2123:
2124: /****************** mnbrak ***********************/
2125:
2126: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
2127: double (*func)(double))
1.183 brouard 2128: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
2129: the downhill direction (defined by the function as evaluated at the initial points) and returns
2130: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
2131: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
2132: */
1.126 brouard 2133: double ulim,u,r,q, dum;
2134: double fu;
1.187 brouard 2135:
2136: double scale=10.;
2137: int iterscale=0;
2138:
2139: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
2140: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
2141:
2142:
2143: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
2144: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
2145: /* *bx = *ax - (*ax - *bx)/scale; */
2146: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
2147: /* } */
2148:
1.126 brouard 2149: if (*fb > *fa) {
2150: SHFT(dum,*ax,*bx,dum)
1.183 brouard 2151: SHFT(dum,*fb,*fa,dum)
2152: }
1.126 brouard 2153: *cx=(*bx)+GOLD*(*bx-*ax);
2154: *fc=(*func)(*cx);
1.183 brouard 2155: #ifdef DEBUG
1.224 brouard 2156: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
2157: 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 2158: #endif
1.224 brouard 2159: 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 2160: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 2161: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 2162: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 2163: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
2164: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
2165: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 2166: fu=(*func)(u);
1.163 brouard 2167: #ifdef DEBUG
2168: /* f(x)=A(x-u)**2+f(u) */
2169: double A, fparabu;
2170: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2171: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 2172: 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);
2173: 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 2174: /* And thus,it can be that fu > *fc even if fparabu < *fc */
2175: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
2176: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
2177: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 2178: #endif
1.184 brouard 2179: #ifdef MNBRAKORIGINAL
1.183 brouard 2180: #else
1.191 brouard 2181: /* if (fu > *fc) { */
2182: /* #ifdef DEBUG */
2183: /* printf("mnbrak4 fu > fc \n"); */
2184: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
2185: /* #endif */
2186: /* /\* 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 *\\/ *\/ */
2187: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
2188: /* dum=u; /\* Shifting c and u *\/ */
2189: /* u = *cx; */
2190: /* *cx = dum; */
2191: /* dum = fu; */
2192: /* fu = *fc; */
2193: /* *fc =dum; */
2194: /* } else { /\* end *\/ */
2195: /* #ifdef DEBUG */
2196: /* printf("mnbrak3 fu < fc \n"); */
2197: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
2198: /* #endif */
2199: /* dum=u; /\* Shifting c and u *\/ */
2200: /* u = *cx; */
2201: /* *cx = dum; */
2202: /* dum = fu; */
2203: /* fu = *fc; */
2204: /* *fc =dum; */
2205: /* } */
1.224 brouard 2206: #ifdef DEBUGMNBRAK
2207: double A, fparabu;
2208: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2209: fparabu= *fa - A*(*ax-u)*(*ax-u);
2210: 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);
2211: 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 2212: #endif
1.191 brouard 2213: dum=u; /* Shifting c and u */
2214: u = *cx;
2215: *cx = dum;
2216: dum = fu;
2217: fu = *fc;
2218: *fc =dum;
1.183 brouard 2219: #endif
1.162 brouard 2220: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 2221: #ifdef DEBUG
1.224 brouard 2222: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
2223: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 2224: #endif
1.126 brouard 2225: fu=(*func)(u);
2226: if (fu < *fc) {
1.183 brouard 2227: #ifdef DEBUG
1.224 brouard 2228: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2229: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2230: #endif
2231: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
2232: SHFT(*fb,*fc,fu,(*func)(u))
2233: #ifdef DEBUG
2234: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 2235: #endif
2236: }
1.162 brouard 2237: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 2238: #ifdef DEBUG
1.224 brouard 2239: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
2240: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 2241: #endif
1.126 brouard 2242: u=ulim;
2243: fu=(*func)(u);
1.183 brouard 2244: } else { /* u could be left to b (if r > q parabola has a maximum) */
2245: #ifdef DEBUG
1.224 brouard 2246: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
2247: 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 2248: #endif
1.126 brouard 2249: u=(*cx)+GOLD*(*cx-*bx);
2250: fu=(*func)(u);
1.224 brouard 2251: #ifdef DEBUG
2252: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2253: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2254: #endif
1.183 brouard 2255: } /* end tests */
1.126 brouard 2256: SHFT(*ax,*bx,*cx,u)
1.183 brouard 2257: SHFT(*fa,*fb,*fc,fu)
2258: #ifdef DEBUG
1.224 brouard 2259: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2260: 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 2261: #endif
2262: } /* 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 2263: }
2264:
2265: /*************** linmin ************************/
1.162 brouard 2266: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2267: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2268: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2269: the value of func at the returned location p . This is actually all accomplished by calling the
2270: routines mnbrak and brent .*/
1.126 brouard 2271: int ncom;
2272: double *pcom,*xicom;
2273: double (*nrfunc)(double []);
2274:
1.224 brouard 2275: #ifdef LINMINORIGINAL
1.126 brouard 2276: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2277: #else
2278: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2279: #endif
1.126 brouard 2280: {
2281: double brent(double ax, double bx, double cx,
2282: double (*f)(double), double tol, double *xmin);
2283: double f1dim(double x);
2284: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2285: double *fc, double (*func)(double));
2286: int j;
2287: double xx,xmin,bx,ax;
2288: double fx,fb,fa;
1.187 brouard 2289:
1.203 brouard 2290: #ifdef LINMINORIGINAL
2291: #else
2292: double scale=10., axs, xxs; /* Scale added for infinity */
2293: #endif
2294:
1.126 brouard 2295: ncom=n;
2296: pcom=vector(1,n);
2297: xicom=vector(1,n);
2298: nrfunc=func;
2299: for (j=1;j<=n;j++) {
2300: pcom[j]=p[j];
1.202 brouard 2301: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2302: }
1.187 brouard 2303:
1.203 brouard 2304: #ifdef LINMINORIGINAL
2305: xx=1.;
2306: #else
2307: axs=0.0;
2308: xxs=1.;
2309: do{
2310: xx= xxs;
2311: #endif
1.187 brouard 2312: ax=0.;
2313: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2314: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2315: /* 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)) */
2316: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2317: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2318: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2319: /* 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 2320: #ifdef LINMINORIGINAL
2321: #else
2322: if (fx != fx){
1.224 brouard 2323: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2324: printf("|");
2325: fprintf(ficlog,"|");
1.203 brouard 2326: #ifdef DEBUGLINMIN
1.224 brouard 2327: 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 2328: #endif
2329: }
1.224 brouard 2330: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2331: #endif
2332:
1.191 brouard 2333: #ifdef DEBUGLINMIN
2334: 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 2335: 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 2336: #endif
1.224 brouard 2337: #ifdef LINMINORIGINAL
2338: #else
1.317 brouard 2339: if(fb == fx){ /* Flat function in the direction */
2340: xmin=xx;
1.224 brouard 2341: *flat=1;
1.317 brouard 2342: }else{
1.224 brouard 2343: *flat=0;
2344: #endif
2345: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2346: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2347: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2348: /* fmin = f(p[j] + xmin * xi[j]) */
2349: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2350: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2351: #ifdef DEBUG
1.224 brouard 2352: 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);
2353: 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);
2354: #endif
2355: #ifdef LINMINORIGINAL
2356: #else
2357: }
1.126 brouard 2358: #endif
1.191 brouard 2359: #ifdef DEBUGLINMIN
2360: printf("linmin end ");
1.202 brouard 2361: fprintf(ficlog,"linmin end ");
1.191 brouard 2362: #endif
1.126 brouard 2363: for (j=1;j<=n;j++) {
1.203 brouard 2364: #ifdef LINMINORIGINAL
2365: xi[j] *= xmin;
2366: #else
2367: #ifdef DEBUGLINMIN
2368: if(xxs <1.0)
2369: printf(" before xi[%d]=%12.8f", j,xi[j]);
2370: #endif
2371: 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) */
2372: #ifdef DEBUGLINMIN
2373: if(xxs <1.0)
2374: 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 );
2375: #endif
2376: #endif
1.187 brouard 2377: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2378: }
1.191 brouard 2379: #ifdef DEBUGLINMIN
1.203 brouard 2380: printf("\n");
1.191 brouard 2381: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2382: 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 2383: for (j=1;j<=n;j++) {
1.202 brouard 2384: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2385: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2386: if(j % ncovmodel == 0){
1.191 brouard 2387: printf("\n");
1.202 brouard 2388: fprintf(ficlog,"\n");
2389: }
1.191 brouard 2390: }
1.203 brouard 2391: #else
1.191 brouard 2392: #endif
1.126 brouard 2393: free_vector(xicom,1,n);
2394: free_vector(pcom,1,n);
2395: }
2396:
2397:
2398: /*************** powell ************************/
1.162 brouard 2399: /*
1.317 brouard 2400: Minimization of a function func of n variables. Input consists in an initial starting point
2401: p[1..n] ; an initial matrix xi[1..n][1..n] whose columns contain the initial set of di-
2402: rections (usually the n unit vectors); and ftol, the fractional tolerance in the function value
2403: such that failure to decrease by more than this amount in one iteration signals doneness. On
1.162 brouard 2404: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2405: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2406: */
1.224 brouard 2407: #ifdef LINMINORIGINAL
2408: #else
2409: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2410: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2411: #endif
1.126 brouard 2412: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2413: double (*func)(double []))
2414: {
1.224 brouard 2415: #ifdef LINMINORIGINAL
2416: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2417: double (*func)(double []));
1.224 brouard 2418: #else
1.241 brouard 2419: void linmin(double p[], double xi[], int n, double *fret,
2420: double (*func)(double []),int *flat);
1.224 brouard 2421: #endif
1.239 brouard 2422: int i,ibig,j,jk,k;
1.126 brouard 2423: double del,t,*pt,*ptt,*xit;
1.181 brouard 2424: double directest;
1.126 brouard 2425: double fp,fptt;
2426: double *xits;
2427: int niterf, itmp;
2428:
2429: pt=vector(1,n);
2430: ptt=vector(1,n);
2431: xit=vector(1,n);
2432: xits=vector(1,n);
2433: *fret=(*func)(p);
2434: for (j=1;j<=n;j++) pt[j]=p[j];
1.202 brouard 2435: rcurr_time = time(NULL);
1.126 brouard 2436: for (*iter=1;;++(*iter)) {
2437: ibig=0;
2438: del=0.0;
1.157 brouard 2439: rlast_time=rcurr_time;
2440: /* (void) gettimeofday(&curr_time,&tzp); */
2441: rcurr_time = time(NULL);
2442: curr_time = *localtime(&rcurr_time);
1.324 brouard 2443: printf("\nPowell iter=%d -2*LL=%.12f gain=%.12f=%.3g %ld sec. %ld sec.",*iter,*fret, fp-*fret,fp-*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout);
2444: fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f gain=%.12f=%.3g %ld sec. %ld sec.",*iter,*fret, fp-*fret,fp-*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog);
1.157 brouard 2445: /* fprintf(ficrespow,"%d %.12f %ld",*iter,*fret,curr_time.tm_sec-start_time.tm_sec); */
1.324 brouard 2446: fp=(*fret); /* From former iteration or initial value */
1.192 brouard 2447: for (i=1;i<=n;i++) {
1.126 brouard 2448: fprintf(ficrespow," %.12lf", p[i]);
2449: }
1.239 brouard 2450: fprintf(ficrespow,"\n");fflush(ficrespow);
2451: printf("\n#model= 1 + age ");
2452: fprintf(ficlog,"\n#model= 1 + age ");
2453: if(nagesqr==1){
1.241 brouard 2454: printf(" + age*age ");
2455: fprintf(ficlog," + age*age ");
1.239 brouard 2456: }
2457: for(j=1;j <=ncovmodel-2;j++){
2458: if(Typevar[j]==0) {
2459: printf(" + V%d ",Tvar[j]);
2460: fprintf(ficlog," + V%d ",Tvar[j]);
2461: }else if(Typevar[j]==1) {
2462: printf(" + V%d*age ",Tvar[j]);
2463: fprintf(ficlog," + V%d*age ",Tvar[j]);
2464: }else if(Typevar[j]==2) {
2465: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2466: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2467: }
2468: }
1.126 brouard 2469: printf("\n");
1.239 brouard 2470: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2471: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2472: fprintf(ficlog,"\n");
1.239 brouard 2473: for(i=1,jk=1; i <=nlstate; i++){
2474: for(k=1; k <=(nlstate+ndeath); k++){
2475: if (k != i) {
2476: printf("%d%d ",i,k);
2477: fprintf(ficlog,"%d%d ",i,k);
2478: for(j=1; j <=ncovmodel; j++){
2479: printf("%12.7f ",p[jk]);
2480: fprintf(ficlog,"%12.7f ",p[jk]);
2481: jk++;
2482: }
2483: printf("\n");
2484: fprintf(ficlog,"\n");
2485: }
2486: }
2487: }
1.241 brouard 2488: if(*iter <=3 && *iter >1){
1.157 brouard 2489: tml = *localtime(&rcurr_time);
2490: strcpy(strcurr,asctime(&tml));
2491: rforecast_time=rcurr_time;
1.126 brouard 2492: itmp = strlen(strcurr);
2493: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2494: strcurr[itmp-1]='\0';
1.162 brouard 2495: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2496: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.126 brouard 2497: for(niterf=10;niterf<=30;niterf+=10){
1.241 brouard 2498: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2499: forecast_time = *localtime(&rforecast_time);
2500: strcpy(strfor,asctime(&forecast_time));
2501: itmp = strlen(strfor);
2502: if(strfor[itmp-1]=='\n')
2503: strfor[itmp-1]='\0';
2504: 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);
2505: 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 2506: }
2507: }
1.187 brouard 2508: for (i=1;i<=n;i++) { /* For each direction i */
2509: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2510: fptt=(*fret);
2511: #ifdef DEBUG
1.203 brouard 2512: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2513: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2514: #endif
1.203 brouard 2515: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2516: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2517: #ifdef LINMINORIGINAL
1.188 brouard 2518: linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.224 brouard 2519: #else
2520: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2521: flatdir[i]=flat; /* Function is vanishing in that direction i */
2522: #endif
2523: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2524: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2525: /* because that direction will be replaced unless the gain del is small */
2526: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2527: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2528: /* with the new direction. */
2529: del=fabs(fptt-(*fret));
2530: ibig=i;
1.126 brouard 2531: }
2532: #ifdef DEBUG
2533: printf("%d %.12e",i,(*fret));
2534: fprintf(ficlog,"%d %.12e",i,(*fret));
2535: for (j=1;j<=n;j++) {
1.224 brouard 2536: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2537: printf(" x(%d)=%.12e",j,xit[j]);
2538: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2539: }
2540: for(j=1;j<=n;j++) {
1.225 brouard 2541: printf(" p(%d)=%.12e",j,p[j]);
2542: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2543: }
2544: printf("\n");
2545: fprintf(ficlog,"\n");
2546: #endif
1.187 brouard 2547: } /* end loop on each direction i */
2548: /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
1.188 brouard 2549: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.187 brouard 2550: /* New value of last point Pn is not computed, P(n-1) */
1.319 brouard 2551: for(j=1;j<=n;j++) {
2552: if(flatdir[j] >0){
2553: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2554: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
1.302 brouard 2555: }
1.319 brouard 2556: /* printf("\n"); */
2557: /* fprintf(ficlog,"\n"); */
2558: }
1.243 brouard 2559: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
2560: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2561: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2562: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2563: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2564: /* decreased of more than 3.84 */
2565: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2566: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2567: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2568:
1.188 brouard 2569: /* Starting the program with initial values given by a former maximization will simply change */
2570: /* the scales of the directions and the directions, because the are reset to canonical directions */
2571: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2572: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2573: #ifdef DEBUG
2574: int k[2],l;
2575: k[0]=1;
2576: k[1]=-1;
2577: printf("Max: %.12e",(*func)(p));
2578: fprintf(ficlog,"Max: %.12e",(*func)(p));
2579: for (j=1;j<=n;j++) {
2580: printf(" %.12e",p[j]);
2581: fprintf(ficlog," %.12e",p[j]);
2582: }
2583: printf("\n");
2584: fprintf(ficlog,"\n");
2585: for(l=0;l<=1;l++) {
2586: for (j=1;j<=n;j++) {
2587: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2588: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2589: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2590: }
2591: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2592: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2593: }
2594: #endif
2595:
2596: free_vector(xit,1,n);
2597: free_vector(xits,1,n);
2598: free_vector(ptt,1,n);
2599: free_vector(pt,1,n);
2600: return;
1.192 brouard 2601: } /* enough precision */
1.240 brouard 2602: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2603: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2604: ptt[j]=2.0*p[j]-pt[j];
2605: xit[j]=p[j]-pt[j];
2606: pt[j]=p[j];
2607: }
1.181 brouard 2608: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2609: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2610: if (*iter <=4) {
1.225 brouard 2611: #else
2612: #endif
1.224 brouard 2613: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2614: #else
1.161 brouard 2615: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2616: #endif
1.162 brouard 2617: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2618: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2619: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2620: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2621: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2622: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2623: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2624: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2625: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2626: /* Even if f3 <f1, directest can be negative and t >0 */
2627: /* mu² and del² are equal when f3=f1 */
2628: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2629: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2630: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2631: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2632: #ifdef NRCORIGINAL
2633: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2634: #else
2635: 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 2636: t= t- del*SQR(fp-fptt);
1.183 brouard 2637: #endif
1.202 brouard 2638: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2639: #ifdef DEBUG
1.181 brouard 2640: 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);
2641: 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 2642: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2643: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2644: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2645: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2646: 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);
2647: 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);
2648: #endif
1.183 brouard 2649: #ifdef POWELLORIGINAL
2650: if (t < 0.0) { /* Then we use it for new direction */
2651: #else
1.182 brouard 2652: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2653: 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 2654: 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 2655: 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 2656: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2657: }
1.181 brouard 2658: if (directest < 0.0) { /* Then we use it for new direction */
2659: #endif
1.191 brouard 2660: #ifdef DEBUGLINMIN
1.234 brouard 2661: printf("Before linmin in direction P%d-P0\n",n);
2662: for (j=1;j<=n;j++) {
2663: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2664: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2665: if(j % ncovmodel == 0){
2666: printf("\n");
2667: fprintf(ficlog,"\n");
2668: }
2669: }
1.224 brouard 2670: #endif
2671: #ifdef LINMINORIGINAL
1.234 brouard 2672: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2673: #else
1.234 brouard 2674: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2675: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2676: #endif
1.234 brouard 2677:
1.191 brouard 2678: #ifdef DEBUGLINMIN
1.234 brouard 2679: for (j=1;j<=n;j++) {
2680: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2681: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2682: if(j % ncovmodel == 0){
2683: printf("\n");
2684: fprintf(ficlog,"\n");
2685: }
2686: }
1.224 brouard 2687: #endif
1.234 brouard 2688: for (j=1;j<=n;j++) {
2689: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2690: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2691: }
1.224 brouard 2692: #ifdef LINMINORIGINAL
2693: #else
1.234 brouard 2694: for (j=1, flatd=0;j<=n;j++) {
2695: if(flatdir[j]>0)
2696: flatd++;
2697: }
2698: if(flatd >0){
1.255 brouard 2699: printf("%d flat directions: ",flatd);
2700: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 2701: for (j=1;j<=n;j++) {
2702: if(flatdir[j]>0){
2703: printf("%d ",j);
2704: fprintf(ficlog,"%d ",j);
2705: }
2706: }
2707: printf("\n");
2708: fprintf(ficlog,"\n");
1.319 brouard 2709: #ifdef FLATSUP
2710: free_vector(xit,1,n);
2711: free_vector(xits,1,n);
2712: free_vector(ptt,1,n);
2713: free_vector(pt,1,n);
2714: return;
2715: #endif
1.234 brouard 2716: }
1.191 brouard 2717: #endif
1.234 brouard 2718: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2719: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2720:
1.126 brouard 2721: #ifdef DEBUG
1.234 brouard 2722: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2723: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2724: for(j=1;j<=n;j++){
2725: printf(" %lf",xit[j]);
2726: fprintf(ficlog," %lf",xit[j]);
2727: }
2728: printf("\n");
2729: fprintf(ficlog,"\n");
1.126 brouard 2730: #endif
1.192 brouard 2731: } /* end of t or directest negative */
1.224 brouard 2732: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2733: #else
1.234 brouard 2734: } /* end if (fptt < fp) */
1.192 brouard 2735: #endif
1.225 brouard 2736: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2737: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2738: #else
1.224 brouard 2739: #endif
1.234 brouard 2740: } /* loop iteration */
1.126 brouard 2741: }
1.234 brouard 2742:
1.126 brouard 2743: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 2744:
1.235 brouard 2745: 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 2746: {
1.279 brouard 2747: /**< Computes the prevalence limit in each live state at age x and for covariate combination ij
2748: * (and selected quantitative values in nres)
2749: * by left multiplying the unit
2750: * matrix by transitions matrix until convergence is reached with precision ftolpl
2751: * Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I
2752: * Wx is row vector: population in state 1, population in state 2, population dead
2753: * or prevalence in state 1, prevalence in state 2, 0
2754: * newm is the matrix after multiplications, its rows are identical at a factor.
2755: * Inputs are the parameter, age, a tolerance for the prevalence limit ftolpl.
2756: * Output is prlim.
2757: * Initial matrix pimij
2758: */
1.206 brouard 2759: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2760: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2761: /* 0, 0 , 1} */
2762: /*
2763: * and after some iteration: */
2764: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2765: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2766: /* 0, 0 , 1} */
2767: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2768: /* {0.51571254859325999, 0.4842874514067399, */
2769: /* 0.51326036147820708, 0.48673963852179264} */
2770: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 2771:
1.126 brouard 2772: int i, ii,j,k;
1.209 brouard 2773: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 2774: /* double **matprod2(); */ /* test */
1.218 brouard 2775: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 2776: double **newm;
1.209 brouard 2777: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 2778: int ncvloop=0;
1.288 brouard 2779: int first=0;
1.169 brouard 2780:
1.209 brouard 2781: min=vector(1,nlstate);
2782: max=vector(1,nlstate);
2783: meandiff=vector(1,nlstate);
2784:
1.218 brouard 2785: /* Starting with matrix unity */
1.126 brouard 2786: for (ii=1;ii<=nlstate+ndeath;ii++)
2787: for (j=1;j<=nlstate+ndeath;j++){
2788: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2789: }
1.169 brouard 2790:
2791: cov[1]=1.;
2792:
2793: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 2794: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 2795: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 2796: ncvloop++;
1.126 brouard 2797: newm=savm;
2798: /* Covariates have to be included here again */
1.138 brouard 2799: cov[2]=agefin;
1.319 brouard 2800: if(nagesqr==1){
2801: cov[3]= agefin*agefin;
2802: }
1.234 brouard 2803: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2804: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2805: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.319 brouard 2806: /* cov[++k1]=nbcode[TvarsD[k]][codtabm(ij,k)]; */
1.235 brouard 2807: /* 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 2808: }
2809: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2810: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
1.319 brouard 2811: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2812: /* cov[++k1]=Tqresult[nres][k]; */
1.235 brouard 2813: /* 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 2814: }
1.237 brouard 2815: for (k=1; k<=cptcovage;k++){ /* For product with age */
1.319 brouard 2816: if(Dummy[Tage[k]]==2){ /* dummy with age */
1.234 brouard 2817: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
1.319 brouard 2818: /* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
2819: } else if(Dummy[Tage[k]]==3){ /* quantitative with age */
2820: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
2821: /* cov[++k1]=Tqresult[nres][k]; */
1.234 brouard 2822: }
1.235 brouard 2823: /* 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 2824: }
1.237 brouard 2825: for (k=1; k<=cptcovprod;k++){ /* For product without age */
1.235 brouard 2826: /* 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]); */
1.329 ! brouard 2827: if(Dummy[Tvard[k][1]]==0){
! 2828: if(Dummy[Tvard[k][2]]==0){
1.237 brouard 2829: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
1.319 brouard 2830: /* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.237 brouard 2831: }else{
2832: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
1.319 brouard 2833: /* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; */
1.237 brouard 2834: }
2835: }else{
1.329 ! brouard 2836: if(Dummy[Tvard[k][2]]==0){
1.237 brouard 2837: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
1.319 brouard 2838: /* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; */
1.237 brouard 2839: }else{
2840: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
1.319 brouard 2841: /* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
1.237 brouard 2842: }
2843: }
1.234 brouard 2844: }
1.138 brouard 2845: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2846: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2847: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 2848: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2849: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.319 brouard 2850: /* age and covariate values of ij are in 'cov' */
1.142 brouard 2851: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 2852:
1.126 brouard 2853: savm=oldm;
2854: oldm=newm;
1.209 brouard 2855:
2856: for(j=1; j<=nlstate; j++){
2857: max[j]=0.;
2858: min[j]=1.;
2859: }
2860: for(i=1;i<=nlstate;i++){
2861: sumnew=0;
2862: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
2863: for(j=1; j<=nlstate; j++){
2864: prlim[i][j]= newm[i][j]/(1-sumnew);
2865: max[j]=FMAX(max[j],prlim[i][j]);
2866: min[j]=FMIN(min[j],prlim[i][j]);
2867: }
2868: }
2869:
1.126 brouard 2870: maxmax=0.;
1.209 brouard 2871: for(j=1; j<=nlstate; j++){
2872: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
2873: maxmax=FMAX(maxmax,meandiff[j]);
2874: /* 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 2875: } /* j loop */
1.203 brouard 2876: *ncvyear= (int)age- (int)agefin;
1.208 brouard 2877: /* 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 2878: if(maxmax < ftolpl){
1.209 brouard 2879: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
2880: free_vector(min,1,nlstate);
2881: free_vector(max,1,nlstate);
2882: free_vector(meandiff,1,nlstate);
1.126 brouard 2883: return prlim;
2884: }
1.288 brouard 2885: } /* agefin loop */
1.208 brouard 2886: /* After some age loop it doesn't converge */
1.288 brouard 2887: if(!first){
2888: first=1;
2889: 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);
1.317 brouard 2890: 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);
2891: }else if (first >=1 && first <10){
2892: 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);
2893: first++;
2894: }else if (first ==10){
2895: 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);
2896: printf("Warning: the stable prevalence dit not converge. This warning came too often, IMaCh will stop notifying, even in its log file. Look at the graphs to appreciate the non convergence.\n");
2897: fprintf(ficlog,"Warning: the stable prevalence no convergence; too many cases, giving up noticing, even in log file\n");
2898: first++;
1.288 brouard 2899: }
2900:
1.209 brouard 2901: /* 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); */
2902: free_vector(min,1,nlstate);
2903: free_vector(max,1,nlstate);
2904: free_vector(meandiff,1,nlstate);
1.208 brouard 2905:
1.169 brouard 2906: return prlim; /* should not reach here */
1.126 brouard 2907: }
2908:
1.217 brouard 2909:
2910: /**** Back Prevalence limit (stable or period prevalence) ****************/
2911:
1.218 brouard 2912: /* 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) */
2913: /* 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 2914: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 2915: {
1.264 brouard 2916: /* 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 2917: matrix by transitions matrix until convergence is reached with precision ftolpl */
2918: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
2919: /* Wx is row vector: population in state 1, population in state 2, population dead */
2920: /* or prevalence in state 1, prevalence in state 2, 0 */
2921: /* newm is the matrix after multiplications, its rows are identical at a factor */
2922: /* Initial matrix pimij */
2923: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2924: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2925: /* 0, 0 , 1} */
2926: /*
2927: * and after some iteration: */
2928: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2929: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2930: /* 0, 0 , 1} */
2931: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2932: /* {0.51571254859325999, 0.4842874514067399, */
2933: /* 0.51326036147820708, 0.48673963852179264} */
2934: /* If we start from prlim again, prlim tends to a constant matrix */
2935:
2936: int i, ii,j,k;
1.247 brouard 2937: int first=0;
1.217 brouard 2938: double *min, *max, *meandiff, maxmax,sumnew=0.;
2939: /* double **matprod2(); */ /* test */
2940: double **out, cov[NCOVMAX+1], **bmij();
2941: double **newm;
1.218 brouard 2942: double **dnewm, **doldm, **dsavm; /* for use */
2943: double **oldm, **savm; /* for use */
2944:
1.217 brouard 2945: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
2946: int ncvloop=0;
2947:
2948: min=vector(1,nlstate);
2949: max=vector(1,nlstate);
2950: meandiff=vector(1,nlstate);
2951:
1.266 brouard 2952: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
2953: oldm=oldms; savm=savms;
2954:
2955: /* Starting with matrix unity */
2956: for (ii=1;ii<=nlstate+ndeath;ii++)
2957: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 2958: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2959: }
2960:
2961: cov[1]=1.;
2962:
2963: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
2964: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 2965: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
1.288 brouard 2966: /* for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
2967: for(agefin=age; agefin<FMIN(AGESUP,age+delaymax); agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 2968: ncvloop++;
1.218 brouard 2969: newm=savm; /* oldm should be kept from previous iteration or unity at start */
2970: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 2971: /* Covariates have to be included here again */
2972: cov[2]=agefin;
1.319 brouard 2973: if(nagesqr==1){
1.217 brouard 2974: cov[3]= agefin*agefin;;
1.319 brouard 2975: }
1.242 brouard 2976: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2977: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2978: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.264 brouard 2979: /* 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 2980: }
2981: /* for (k=1; k<=cptcovn;k++) { */
2982: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
2983: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
2984: /* /\* 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])]); *\/ */
2985: /* } */
2986: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2987: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
2988: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2989: /* 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]); */
2990: }
2991: /* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; */
2992: /* for (k=1; k<=cptcovprod;k++) /\* Useless *\/ */
2993: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\/ */
2994: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */
2995: for (k=1; k<=cptcovage;k++){ /* For product with age */
1.319 brouard 2996: /* if(Dummy[Tvar[Tage[k]]]== 2){ /\* dummy with age *\/ ERROR ???*/
2997: if(Dummy[Tage[k]]== 2){ /* dummy with age */
1.242 brouard 2998: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
1.319 brouard 2999: } else if(Dummy[Tage[k]]== 3){ /* quantitative with age */
3000: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
1.242 brouard 3001: }
3002: /* 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]); */
3003: }
3004: for (k=1; k<=cptcovprod;k++){ /* For product without age */
3005: /* 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]); */
1.329 ! brouard 3006: if(Dummy[Tvard[k][1]]==0){
! 3007: if(Dummy[Tvard[k][2]]==0){
1.242 brouard 3008: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
3009: }else{
3010: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
3011: }
3012: }else{
1.329 ! brouard 3013: if(Dummy[Tvard[k][2]]==0){
1.242 brouard 3014: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
3015: }else{
3016: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
3017: }
3018: }
1.217 brouard 3019: }
3020:
3021: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
3022: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
3023: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
3024: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3025: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 3026: /* ij should be linked to the correct index of cov */
3027: /* age and covariate values ij are in 'cov', but we need to pass
3028: * ij for the observed prevalence at age and status and covariate
3029: * number: prevacurrent[(int)agefin][ii][ij]
3030: */
3031: /* 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 *\/ */
3032: /* 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 *\/ */
3033: 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 3034: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 3035: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
3036: /* for(i=1; i<=nlstate+ndeath; i++) { */
3037: /* printf("%d newm= ",i); */
3038: /* for(j=1;j<=nlstate+ndeath;j++) { */
3039: /* printf("%f ",newm[i][j]); */
3040: /* } */
3041: /* printf("oldm * "); */
3042: /* for(j=1;j<=nlstate+ndeath;j++) { */
3043: /* printf("%f ",oldm[i][j]); */
3044: /* } */
1.268 brouard 3045: /* printf(" bmmij "); */
1.266 brouard 3046: /* for(j=1;j<=nlstate+ndeath;j++) { */
3047: /* printf("%f ",pmmij[i][j]); */
3048: /* } */
3049: /* printf("\n"); */
3050: /* } */
3051: /* } */
1.217 brouard 3052: savm=oldm;
3053: oldm=newm;
1.266 brouard 3054:
1.217 brouard 3055: for(j=1; j<=nlstate; j++){
3056: max[j]=0.;
3057: min[j]=1.;
3058: }
3059: for(j=1; j<=nlstate; j++){
3060: for(i=1;i<=nlstate;i++){
1.234 brouard 3061: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
3062: bprlim[i][j]= newm[i][j];
3063: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
3064: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 3065: }
3066: }
1.218 brouard 3067:
1.217 brouard 3068: maxmax=0.;
3069: for(i=1; i<=nlstate; i++){
1.318 brouard 3070: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column, could be nan! */
1.217 brouard 3071: maxmax=FMAX(maxmax,meandiff[i]);
3072: /* 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 3073: } /* i loop */
1.217 brouard 3074: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 3075: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3076: if(maxmax < ftolpl){
1.220 brouard 3077: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3078: free_vector(min,1,nlstate);
3079: free_vector(max,1,nlstate);
3080: free_vector(meandiff,1,nlstate);
3081: return bprlim;
3082: }
1.288 brouard 3083: } /* agefin loop */
1.217 brouard 3084: /* After some age loop it doesn't converge */
1.288 brouard 3085: if(!first){
1.247 brouard 3086: first=1;
3087: 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\
3088: 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);
3089: }
3090: 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 3091: 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);
3092: /* 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); */
3093: free_vector(min,1,nlstate);
3094: free_vector(max,1,nlstate);
3095: free_vector(meandiff,1,nlstate);
3096:
3097: return bprlim; /* should not reach here */
3098: }
3099:
1.126 brouard 3100: /*************** transition probabilities ***************/
3101:
3102: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
3103: {
1.138 brouard 3104: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 3105: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 3106: model to the ncovmodel covariates (including constant and age).
3107: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3108: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3109: ncth covariate in the global vector x is given by the formula:
3110: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3111: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3112: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3113: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 3114: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 3115: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 3116: Sum on j ps[i][j] should equal to 1.
1.138 brouard 3117: */
3118: double s1, lnpijopii;
1.126 brouard 3119: /*double t34;*/
1.164 brouard 3120: int i,j, nc, ii, jj;
1.126 brouard 3121:
1.223 brouard 3122: for(i=1; i<= nlstate; i++){
3123: for(j=1; j<i;j++){
3124: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3125: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3126: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3127: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3128: }
3129: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3130: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3131: }
3132: for(j=i+1; j<=nlstate+ndeath;j++){
3133: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3134: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3135: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3136: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3137: }
3138: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3139: }
3140: }
1.218 brouard 3141:
1.223 brouard 3142: for(i=1; i<= nlstate; i++){
3143: s1=0;
3144: for(j=1; j<i; j++){
3145: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3146: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3147: }
3148: for(j=i+1; j<=nlstate+ndeath; j++){
3149: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3150: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3151: }
3152: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3153: ps[i][i]=1./(s1+1.);
3154: /* Computing other pijs */
3155: for(j=1; j<i; j++)
1.325 brouard 3156: ps[i][j]= exp(ps[i][j])*ps[i][i];/* Bug valgrind */
1.223 brouard 3157: for(j=i+1; j<=nlstate+ndeath; j++)
3158: ps[i][j]= exp(ps[i][j])*ps[i][i];
3159: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3160: } /* end i */
1.218 brouard 3161:
1.223 brouard 3162: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3163: for(jj=1; jj<= nlstate+ndeath; jj++){
3164: ps[ii][jj]=0;
3165: ps[ii][ii]=1;
3166: }
3167: }
1.294 brouard 3168:
3169:
1.223 brouard 3170: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3171: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3172: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3173: /* } */
3174: /* printf("\n "); */
3175: /* } */
3176: /* printf("\n ");printf("%lf ",cov[2]);*/
3177: /*
3178: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 3179: goto end;*/
1.266 brouard 3180: return ps; /* Pointer is unchanged since its call */
1.126 brouard 3181: }
3182:
1.218 brouard 3183: /*************** backward transition probabilities ***************/
3184:
3185: /* 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 ) */
3186: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
3187: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
3188: {
1.302 brouard 3189: /* Computes the backward probability at age agefin, cov[2], and covariate combination 'ij'. In fact cov is already filled and x too.
1.266 brouard 3190: * 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 3191: */
1.218 brouard 3192: int i, ii, j,k;
1.222 brouard 3193:
3194: double **out, **pmij();
3195: double sumnew=0.;
1.218 brouard 3196: double agefin;
1.292 brouard 3197: 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 3198: double **dnewm, **dsavm, **doldm;
3199: double **bbmij;
3200:
1.218 brouard 3201: doldm=ddoldms; /* global pointers */
1.222 brouard 3202: dnewm=ddnewms;
3203: dsavm=ddsavms;
1.318 brouard 3204:
3205: /* Debug */
3206: /* printf("Bmij ij=%d, cov[2}=%f\n", ij, cov[2]); */
1.222 brouard 3207: agefin=cov[2];
1.268 brouard 3208: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 3209: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 3210: the observed prevalence (with this covariate ij) at beginning of transition */
3211: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 3212:
3213: /* P_x */
1.325 brouard 3214: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm *//* Bug valgrind */
1.268 brouard 3215: /* outputs pmmij which is a stochastic matrix in row */
3216:
3217: /* Diag(w_x) */
1.292 brouard 3218: /* Rescaling the cross-sectional prevalence: Problem with prevacurrent which can be zero */
1.268 brouard 3219: sumnew=0.;
1.269 brouard 3220: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 3221: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.297 brouard 3222: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 3223: sumnew+=prevacurrent[(int)agefin][ii][ij];
3224: }
3225: if(sumnew >0.01){ /* At least some value in the prevalence */
3226: for (ii=1;ii<=nlstate+ndeath;ii++){
3227: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 3228: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 3229: }
3230: }else{
3231: for (ii=1;ii<=nlstate+ndeath;ii++){
3232: for (j=1;j<=nlstate+ndeath;j++)
3233: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
3234: }
3235: /* if(sumnew <0.9){ */
3236: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
3237: /* } */
3238: }
3239: k3=0.0; /* We put the last diagonal to 0 */
3240: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
3241: doldm[ii][ii]= k3;
3242: }
3243: /* End doldm, At the end doldm is diag[(w_i)] */
3244:
1.292 brouard 3245: /* Left product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm): diag[(w_i)*Px */
3246: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* was a Bug Valgrind */
1.268 brouard 3247:
1.292 brouard 3248: /* Diag(Sum_i w^i_x p^ij_x, should be the prevalence at age x+stepm */
1.268 brouard 3249: /* 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 3250: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 3251: sumnew=0.;
1.222 brouard 3252: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 3253: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 3254: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 3255: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 3256: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 3257: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 3258: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3259: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 3260: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3261: /* }else */
1.268 brouard 3262: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
3263: } /*End ii */
3264: } /* 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 */
3265:
1.292 brouard 3266: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* was a Bug Valgrind */
1.268 brouard 3267: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 3268: /* end bmij */
1.266 brouard 3269: return ps; /*pointer is unchanged */
1.218 brouard 3270: }
1.217 brouard 3271: /*************** transition probabilities ***************/
3272:
1.218 brouard 3273: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 3274: {
3275: /* According to parameters values stored in x and the covariate's values stored in cov,
3276: computes the probability to be observed in state j being in state i by appying the
3277: model to the ncovmodel covariates (including constant and age).
3278: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3279: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3280: ncth covariate in the global vector x is given by the formula:
3281: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3282: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3283: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3284: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
3285: Outputs ps[i][j] the probability to be observed in j being in j according to
3286: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
3287: */
3288: double s1, lnpijopii;
3289: /*double t34;*/
3290: int i,j, nc, ii, jj;
3291:
1.234 brouard 3292: for(i=1; i<= nlstate; i++){
3293: for(j=1; j<i;j++){
3294: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3295: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3296: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3297: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3298: }
3299: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3300: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3301: }
3302: for(j=i+1; j<=nlstate+ndeath;j++){
3303: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3304: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3305: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3306: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3307: }
3308: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3309: }
3310: }
3311:
3312: for(i=1; i<= nlstate; i++){
3313: s1=0;
3314: for(j=1; j<i; j++){
3315: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3316: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3317: }
3318: for(j=i+1; j<=nlstate+ndeath; j++){
3319: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3320: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3321: }
3322: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3323: ps[i][i]=1./(s1+1.);
3324: /* Computing other pijs */
3325: for(j=1; j<i; j++)
3326: ps[i][j]= exp(ps[i][j])*ps[i][i];
3327: for(j=i+1; j<=nlstate+ndeath; j++)
3328: ps[i][j]= exp(ps[i][j])*ps[i][i];
3329: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3330: } /* end i */
3331:
3332: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3333: for(jj=1; jj<= nlstate+ndeath; jj++){
3334: ps[ii][jj]=0;
3335: ps[ii][ii]=1;
3336: }
3337: }
1.296 brouard 3338: /* Added for prevbcast */ /* Transposed matrix too */
1.234 brouard 3339: for(jj=1; jj<= nlstate+ndeath; jj++){
3340: s1=0.;
3341: for(ii=1; ii<= nlstate+ndeath; ii++){
3342: s1+=ps[ii][jj];
3343: }
3344: for(ii=1; ii<= nlstate; ii++){
3345: ps[ii][jj]=ps[ii][jj]/s1;
3346: }
3347: }
3348: /* Transposition */
3349: for(jj=1; jj<= nlstate+ndeath; jj++){
3350: for(ii=jj; ii<= nlstate+ndeath; ii++){
3351: s1=ps[ii][jj];
3352: ps[ii][jj]=ps[jj][ii];
3353: ps[jj][ii]=s1;
3354: }
3355: }
3356: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3357: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3358: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3359: /* } */
3360: /* printf("\n "); */
3361: /* } */
3362: /* printf("\n ");printf("%lf ",cov[2]);*/
3363: /*
3364: for(i=1; i<= npar; i++) printf("%f ",x[i]);
3365: goto end;*/
3366: return ps;
1.217 brouard 3367: }
3368:
3369:
1.126 brouard 3370: /**************** Product of 2 matrices ******************/
3371:
1.145 brouard 3372: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 3373: {
3374: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
3375: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
3376: /* in, b, out are matrice of pointers which should have been initialized
3377: before: only the contents of out is modified. The function returns
3378: a pointer to pointers identical to out */
1.145 brouard 3379: int i, j, k;
1.126 brouard 3380: for(i=nrl; i<= nrh; i++)
1.145 brouard 3381: for(k=ncolol; k<=ncoloh; k++){
3382: out[i][k]=0.;
3383: for(j=ncl; j<=nch; j++)
3384: out[i][k] +=in[i][j]*b[j][k];
3385: }
1.126 brouard 3386: return out;
3387: }
3388:
3389:
3390: /************* Higher Matrix Product ***************/
3391:
1.235 brouard 3392: 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 3393: {
1.218 brouard 3394: /* Computes the transition matrix starting at age 'age' and combination of covariate values corresponding to ij over
1.126 brouard 3395: 'nhstepm*hstepm*stepm' months (i.e. until
3396: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3397: nhstepm*hstepm matrices.
3398: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3399: (typically every 2 years instead of every month which is too big
3400: for the memory).
3401: Model is determined by parameters x and covariates have to be
3402: included manually here.
3403:
3404: */
3405:
3406: int i, j, d, h, k;
1.131 brouard 3407: double **out, cov[NCOVMAX+1];
1.126 brouard 3408: double **newm;
1.187 brouard 3409: double agexact;
1.214 brouard 3410: double agebegin, ageend;
1.126 brouard 3411:
3412: /* Hstepm could be zero and should return the unit matrix */
3413: for (i=1;i<=nlstate+ndeath;i++)
3414: for (j=1;j<=nlstate+ndeath;j++){
3415: oldm[i][j]=(i==j ? 1.0 : 0.0);
3416: po[i][j][0]=(i==j ? 1.0 : 0.0);
3417: }
3418: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3419: for(h=1; h <=nhstepm; h++){
3420: for(d=1; d <=hstepm; d++){
3421: newm=savm;
3422: /* Covariates have to be included here again */
3423: cov[1]=1.;
1.214 brouard 3424: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3425: cov[2]=agexact;
1.319 brouard 3426: if(nagesqr==1){
1.227 brouard 3427: cov[3]= agexact*agexact;
1.319 brouard 3428: }
1.235 brouard 3429: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
1.319 brouard 3430: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
3431: /* codtabm(ij,k) (1 & (ij-1) >> (k-1))+1 */
3432: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
3433: /* k 1 2 3 4 5 6 7 8 9 */
3434: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 */
3435: /* nsd 1 2 3 */ /* Counting single dummies covar fixed or tv */
3436: /*TvarsD[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
3437: /*TvarsDind[k] 2 3 9 */ /* position K of single dummy cova */
1.235 brouard 3438: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3439: /* 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)); */
3440: }
3441: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3442: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
1.319 brouard 3443: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
1.235 brouard 3444: /* 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]); */
3445: }
1.319 brouard 3446: for (k=1; k<=cptcovage;k++){ /* For product with age V1+V1*age +V4 +age*V3 */
3447: /* 1+2 Tage[1]=2 TVar[2]=1 Dummy[2]=2, Tage[2]=4 TVar[4]=3 Dummy[4]=3 quant*/
3448: /* */
3449: if(Dummy[Tage[k]]== 2){ /* dummy with age */
3450: /* if(Dummy[Tvar[Tage[k]]]== 2){ /\* dummy with age *\/ */
1.235 brouard 3451: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
1.319 brouard 3452: } else if(Dummy[Tage[k]]== 3){ /* quantitative with age */
3453: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
1.235 brouard 3454: }
3455: /* 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]); */
3456: }
1.319 brouard 3457: for (k=1; k<=cptcovprod;k++){ /* For product without age */
1.235 brouard 3458: /* 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]); */
1.319 brouard 3459: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.329 ! brouard 3460: if(Dummy[Tvard[k][1]]==0){
! 3461: if(Dummy[Tvard[k][2]]==0){
1.319 brouard 3462: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
3463: }else{
3464: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
3465: }
3466: }else{
1.329 ! brouard 3467: if(Dummy[Tvard[k][2]]==0){
1.319 brouard 3468: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
3469: }else{
3470: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
3471: }
3472: }
1.235 brouard 3473: }
3474: /* for (k=1; k<=cptcovn;k++) */
3475: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3476: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3477: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3478: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3479: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3480:
3481:
1.126 brouard 3482: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3483: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.319 brouard 3484: /* right multiplication of oldm by the current matrix */
1.126 brouard 3485: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3486: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3487: /* if((int)age == 70){ */
3488: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3489: /* for(i=1; i<=nlstate+ndeath; i++) { */
3490: /* printf("%d pmmij ",i); */
3491: /* for(j=1;j<=nlstate+ndeath;j++) { */
3492: /* printf("%f ",pmmij[i][j]); */
3493: /* } */
3494: /* printf(" oldm "); */
3495: /* for(j=1;j<=nlstate+ndeath;j++) { */
3496: /* printf("%f ",oldm[i][j]); */
3497: /* } */
3498: /* printf("\n"); */
3499: /* } */
3500: /* } */
1.126 brouard 3501: savm=oldm;
3502: oldm=newm;
3503: }
3504: for(i=1; i<=nlstate+ndeath; i++)
3505: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 3506: po[i][j][h]=newm[i][j];
3507: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3508: }
1.128 brouard 3509: /*printf("h=%d ",h);*/
1.126 brouard 3510: } /* end h */
1.267 brouard 3511: /* printf("\n H=%d \n",h); */
1.126 brouard 3512: return po;
3513: }
3514:
1.217 brouard 3515: /************* Higher Back Matrix Product ***************/
1.218 brouard 3516: /* 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 3517: 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 3518: {
1.266 brouard 3519: /* For a combination of dummy covariate ij, computes the transition matrix starting at age 'age' over
1.217 brouard 3520: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3521: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3522: nhstepm*hstepm matrices.
3523: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3524: (typically every 2 years instead of every month which is too big
1.217 brouard 3525: for the memory).
1.218 brouard 3526: Model is determined by parameters x and covariates have to be
1.266 brouard 3527: included manually here. Then we use a call to bmij(x and cov)
3528: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 3529: */
1.217 brouard 3530:
3531: int i, j, d, h, k;
1.266 brouard 3532: double **out, cov[NCOVMAX+1], **bmij();
3533: double **newm, ***newmm;
1.217 brouard 3534: double agexact;
3535: double agebegin, ageend;
1.222 brouard 3536: double **oldm, **savm;
1.217 brouard 3537:
1.266 brouard 3538: newmm=po; /* To be saved */
3539: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 3540: /* Hstepm could be zero and should return the unit matrix */
3541: for (i=1;i<=nlstate+ndeath;i++)
3542: for (j=1;j<=nlstate+ndeath;j++){
3543: oldm[i][j]=(i==j ? 1.0 : 0.0);
3544: po[i][j][0]=(i==j ? 1.0 : 0.0);
3545: }
3546: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3547: for(h=1; h <=nhstepm; h++){
3548: for(d=1; d <=hstepm; d++){
3549: newm=savm;
3550: /* Covariates have to be included here again */
3551: cov[1]=1.;
1.271 brouard 3552: agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 3553: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
1.318 brouard 3554: /* Debug */
3555: /* printf("hBxij age=%lf, agexact=%lf\n", age, agexact); */
1.217 brouard 3556: cov[2]=agexact;
3557: if(nagesqr==1)
1.222 brouard 3558: cov[3]= agexact*agexact;
1.325 brouard 3559: for (k=1; k<=nsd;k++){ /* For single dummy covariates only *//* cptcovn error */
1.266 brouard 3560: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3561: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
1.325 brouard 3562: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];/* Bug valgrind */
1.266 brouard 3563: /* 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)); */
3564: }
1.267 brouard 3565: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3566: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3567: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3568: /* 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]); */
3569: }
1.319 brouard 3570: for (k=1; k<=cptcovage;k++){ /* Should start at cptcovn+1 *//* For product with age */
3571: /* if(Dummy[Tvar[Tage[k]]]== 2){ /\* dummy with age error!!!*\/ */
3572: if(Dummy[Tage[k]]== 2){ /* dummy with age */
1.267 brouard 3573: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
1.319 brouard 3574: } else if(Dummy[Tage[k]]== 3){ /* quantitative with age */
1.267 brouard 3575: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3576: }
3577: /* 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]); */
3578: }
3579: for (k=1; k<=cptcovprod;k++){ /* Useless because included in cptcovn */
1.222 brouard 3580: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.329 ! brouard 3581: if(Dummy[Tvard[k][1]]==0){
! 3582: if(Dummy[Tvard[k][2]]==0){
1.325 brouard 3583: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
3584: }else{
3585: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
3586: }
3587: }else{
1.329 ! brouard 3588: if(Dummy[Tvard[k][2]]==0){
1.325 brouard 3589: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
3590: }else{
3591: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
3592: }
3593: }
1.267 brouard 3594: }
1.217 brouard 3595: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3596: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.267 brouard 3597:
1.218 brouard 3598: /* Careful transposed matrix */
1.266 brouard 3599: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 3600: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3601: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3602: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.325 brouard 3603: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);/* Bug valgrind */
1.217 brouard 3604: /* if((int)age == 70){ */
3605: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3606: /* for(i=1; i<=nlstate+ndeath; i++) { */
3607: /* printf("%d pmmij ",i); */
3608: /* for(j=1;j<=nlstate+ndeath;j++) { */
3609: /* printf("%f ",pmmij[i][j]); */
3610: /* } */
3611: /* printf(" oldm "); */
3612: /* for(j=1;j<=nlstate+ndeath;j++) { */
3613: /* printf("%f ",oldm[i][j]); */
3614: /* } */
3615: /* printf("\n"); */
3616: /* } */
3617: /* } */
3618: savm=oldm;
3619: oldm=newm;
3620: }
3621: for(i=1; i<=nlstate+ndeath; i++)
3622: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 3623: po[i][j][h]=newm[i][j];
1.268 brouard 3624: /* if(h==nhstepm) */
3625: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 3626: }
1.268 brouard 3627: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 3628: } /* end h */
1.268 brouard 3629: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 3630: return po;
3631: }
3632:
3633:
1.162 brouard 3634: #ifdef NLOPT
3635: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
3636: double fret;
3637: double *xt;
3638: int j;
3639: myfunc_data *d2 = (myfunc_data *) pd;
3640: /* xt = (p1-1); */
3641: xt=vector(1,n);
3642: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
3643:
3644: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
3645: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
3646: printf("Function = %.12lf ",fret);
3647: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
3648: printf("\n");
3649: free_vector(xt,1,n);
3650: return fret;
3651: }
3652: #endif
1.126 brouard 3653:
3654: /*************** log-likelihood *************/
3655: double func( double *x)
3656: {
1.226 brouard 3657: int i, ii, j, k, mi, d, kk;
3658: int ioffset=0;
3659: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
3660: double **out;
3661: double lli; /* Individual log likelihood */
3662: int s1, s2;
1.228 brouard 3663: 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 3664: double bbh, survp;
3665: long ipmx;
3666: double agexact;
3667: /*extern weight */
3668: /* We are differentiating ll according to initial status */
3669: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3670: /*for(i=1;i<imx;i++)
3671: printf(" %d\n",s[4][i]);
3672: */
1.162 brouard 3673:
1.226 brouard 3674: ++countcallfunc;
1.162 brouard 3675:
1.226 brouard 3676: cov[1]=1.;
1.126 brouard 3677:
1.226 brouard 3678: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3679: ioffset=0;
1.226 brouard 3680: if(mle==1){
3681: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3682: /* Computes the values of the ncovmodel covariates of the model
3683: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
3684: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
3685: to be observed in j being in i according to the model.
3686: */
1.243 brouard 3687: ioffset=2+nagesqr ;
1.233 brouard 3688: /* Fixed */
1.319 brouard 3689: for (k=1; k<=ncovf;k++){ /* For each fixed covariate dummu or quant or prod */
3690: /* # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi */
3691: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
3692: /* TvarF[1]=Tvar[6]=2, TvarF[2]=Tvar[7]=7, TvarF[3]=Tvar[9]=1 ID of fixed covariates or product V2, V1*V2, V1 */
1.320 brouard 3693: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.319 brouard 3694: 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 (TvarFind[1]=6)*/
3695: /* V1*V2 (7) TvarFind[2]=7, TvarFind[3]=9 */
1.234 brouard 3696: }
1.226 brouard 3697: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
1.319 brouard 3698: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
1.226 brouard 3699: has been calculated etc */
3700: /* For an individual i, wav[i] gives the number of effective waves */
3701: /* We compute the contribution to Likelihood of each effective transition
3702: mw[mi][i] is real wave of the mi th effectve wave */
3703: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
3704: s2=s[mw[mi+1][i]][i];
3705: And the iv th varying covariate is the cotvar[mw[mi+1][i]][iv][i]
3706: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
3707: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
3708: */
3709: for(mi=1; mi<= wav[i]-1; mi++){
1.319 brouard 3710: for(k=1; k <= ncovv ; k++){ /* Varying covariates in the model (single and product but no age )"V5+V4+V3+V4*V3+V5*age+V1*age+V1" +TvarVind 1,2,3,4(V4*V3) Tvar[1]@7{5, 4, 3, 6, 5, 1, 1 ; 6 because the created covar is after V5 and is 6, minus 1+1, 3,2,1,4 positions in cotvar*/
3711: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; but where is the crossproduct? */
1.242 brouard 3712: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
1.234 brouard 3713: }
3714: for (ii=1;ii<=nlstate+ndeath;ii++)
3715: for (j=1;j<=nlstate+ndeath;j++){
3716: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3717: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3718: }
3719: for(d=0; d<dh[mi][i]; d++){
3720: newm=savm;
3721: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3722: cov[2]=agexact;
3723: if(nagesqr==1)
3724: cov[3]= agexact*agexact; /* Should be changed here */
3725: for (kk=1; kk<=cptcovage;kk++) {
1.318 brouard 3726: if(!FixedV[Tvar[Tage[kk]]])
3727: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
3728: else
3729: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
1.234 brouard 3730: }
3731: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3732: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3733: savm=oldm;
3734: oldm=newm;
3735: } /* end mult */
3736:
3737: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
3738: /* But now since version 0.9 we anticipate for bias at large stepm.
3739: * If stepm is larger than one month (smallest stepm) and if the exact delay
3740: * (in months) between two waves is not a multiple of stepm, we rounded to
3741: * the nearest (and in case of equal distance, to the lowest) interval but now
3742: * we keep into memory the bias bh[mi][i] and also the previous matrix product
3743: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
3744: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 3745: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
3746: * -stepm/2 to stepm/2 .
3747: * For stepm=1 the results are the same as for previous versions of Imach.
3748: * For stepm > 1 the results are less biased than in previous versions.
3749: */
1.234 brouard 3750: s1=s[mw[mi][i]][i];
3751: s2=s[mw[mi+1][i]][i];
3752: bbh=(double)bh[mi][i]/(double)stepm;
3753: /* bias bh is positive if real duration
3754: * is higher than the multiple of stepm and negative otherwise.
3755: */
3756: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
3757: if( s2 > nlstate){
3758: /* i.e. if s2 is a death state and if the date of death is known
3759: then the contribution to the likelihood is the probability to
3760: die between last step unit time and current step unit time,
3761: which is also equal to probability to die before dh
3762: minus probability to die before dh-stepm .
3763: In version up to 0.92 likelihood was computed
3764: as if date of death was unknown. Death was treated as any other
3765: health state: the date of the interview describes the actual state
3766: and not the date of a change in health state. The former idea was
3767: to consider that at each interview the state was recorded
3768: (healthy, disable or death) and IMaCh was corrected; but when we
3769: introduced the exact date of death then we should have modified
3770: the contribution of an exact death to the likelihood. This new
3771: contribution is smaller and very dependent of the step unit
3772: stepm. It is no more the probability to die between last interview
3773: and month of death but the probability to survive from last
3774: interview up to one month before death multiplied by the
3775: probability to die within a month. Thanks to Chris
3776: Jackson for correcting this bug. Former versions increased
3777: mortality artificially. The bad side is that we add another loop
3778: which slows down the processing. The difference can be up to 10%
3779: lower mortality.
3780: */
3781: /* If, at the beginning of the maximization mostly, the
3782: cumulative probability or probability to be dead is
3783: constant (ie = 1) over time d, the difference is equal to
3784: 0. out[s1][3] = savm[s1][3]: probability, being at state
3785: s1 at precedent wave, to be dead a month before current
3786: wave is equal to probability, being at state s1 at
3787: precedent wave, to be dead at mont of the current
3788: wave. Then the observed probability (that this person died)
3789: is null according to current estimated parameter. In fact,
3790: it should be very low but not zero otherwise the log go to
3791: infinity.
3792: */
1.183 brouard 3793: /* #ifdef INFINITYORIGINAL */
3794: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3795: /* #else */
3796: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
3797: /* lli=log(mytinydouble); */
3798: /* else */
3799: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3800: /* #endif */
1.226 brouard 3801: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3802:
1.226 brouard 3803: } else if ( s2==-1 ) { /* alive */
3804: for (j=1,survp=0. ; j<=nlstate; j++)
3805: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3806: /*survp += out[s1][j]; */
3807: lli= log(survp);
3808: }
3809: else if (s2==-4) {
3810: for (j=3,survp=0. ; j<=nlstate; j++)
3811: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3812: lli= log(survp);
3813: }
3814: else if (s2==-5) {
3815: for (j=1,survp=0. ; j<=2; j++)
3816: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3817: lli= log(survp);
3818: }
3819: else{
3820: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3821: /* 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 */
3822: }
3823: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
3824: /*if(lli ==000.0)*/
3825: /*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); */
3826: ipmx +=1;
3827: sw += weight[i];
3828: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3829: /* if (lli < log(mytinydouble)){ */
3830: /* 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); */
3831: /* 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]); */
3832: /* } */
3833: } /* end of wave */
3834: } /* end of individual */
3835: } else if(mle==2){
3836: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.319 brouard 3837: ioffset=2+nagesqr ;
3838: for (k=1; k<=ncovf;k++)
3839: cov[ioffset+TvarFind[k]]=covar[Tvar[TvarFind[k]]][i];
1.226 brouard 3840: for(mi=1; mi<= wav[i]-1; mi++){
1.319 brouard 3841: for(k=1; k <= ncovv ; k++){
3842: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
3843: }
1.226 brouard 3844: for (ii=1;ii<=nlstate+ndeath;ii++)
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: }
3849: for(d=0; d<=dh[mi][i]; d++){
3850: newm=savm;
3851: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3852: cov[2]=agexact;
3853: if(nagesqr==1)
3854: cov[3]= agexact*agexact;
3855: for (kk=1; kk<=cptcovage;kk++) {
3856: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3857: }
3858: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3859: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3860: savm=oldm;
3861: oldm=newm;
3862: } /* end mult */
3863:
3864: s1=s[mw[mi][i]][i];
3865: s2=s[mw[mi+1][i]][i];
3866: bbh=(double)bh[mi][i]/(double)stepm;
3867: 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 */
3868: ipmx +=1;
3869: sw += weight[i];
3870: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3871: } /* end of wave */
3872: } /* end of individual */
3873: } else if(mle==3){ /* exponential inter-extrapolation */
3874: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3875: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3876: for(mi=1; mi<= wav[i]-1; mi++){
3877: for (ii=1;ii<=nlstate+ndeath;ii++)
3878: for (j=1;j<=nlstate+ndeath;j++){
3879: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3880: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3881: }
3882: for(d=0; d<dh[mi][i]; d++){
3883: newm=savm;
3884: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3885: cov[2]=agexact;
3886: if(nagesqr==1)
3887: cov[3]= agexact*agexact;
3888: for (kk=1; kk<=cptcovage;kk++) {
3889: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3890: }
3891: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3892: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3893: savm=oldm;
3894: oldm=newm;
3895: } /* end mult */
3896:
3897: s1=s[mw[mi][i]][i];
3898: s2=s[mw[mi+1][i]][i];
3899: bbh=(double)bh[mi][i]/(double)stepm;
3900: 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 */
3901: ipmx +=1;
3902: sw += weight[i];
3903: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3904: } /* end of wave */
3905: } /* end of individual */
3906: }else if (mle==4){ /* ml=4 no inter-extrapolation */
3907: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3908: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3909: for(mi=1; mi<= wav[i]-1; mi++){
3910: for (ii=1;ii<=nlstate+ndeath;ii++)
3911: for (j=1;j<=nlstate+ndeath;j++){
3912: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3913: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3914: }
3915: for(d=0; d<dh[mi][i]; d++){
3916: newm=savm;
3917: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3918: cov[2]=agexact;
3919: if(nagesqr==1)
3920: cov[3]= agexact*agexact;
3921: for (kk=1; kk<=cptcovage;kk++) {
3922: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3923: }
1.126 brouard 3924:
1.226 brouard 3925: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3926: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3927: savm=oldm;
3928: oldm=newm;
3929: } /* end mult */
3930:
3931: s1=s[mw[mi][i]][i];
3932: s2=s[mw[mi+1][i]][i];
3933: if( s2 > nlstate){
3934: lli=log(out[s1][s2] - savm[s1][s2]);
3935: } else if ( s2==-1 ) { /* alive */
3936: for (j=1,survp=0. ; j<=nlstate; j++)
3937: survp += out[s1][j];
3938: lli= log(survp);
3939: }else{
3940: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3941: }
3942: ipmx +=1;
3943: sw += weight[i];
3944: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.126 brouard 3945: /* 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 3946: } /* end of wave */
3947: } /* end of individual */
3948: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
3949: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3950: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3951: for(mi=1; mi<= wav[i]-1; mi++){
3952: for (ii=1;ii<=nlstate+ndeath;ii++)
3953: for (j=1;j<=nlstate+ndeath;j++){
3954: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3955: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3956: }
3957: for(d=0; d<dh[mi][i]; d++){
3958: newm=savm;
3959: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3960: cov[2]=agexact;
3961: if(nagesqr==1)
3962: cov[3]= agexact*agexact;
3963: for (kk=1; kk<=cptcovage;kk++) {
3964: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3965: }
1.126 brouard 3966:
1.226 brouard 3967: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3968: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3969: savm=oldm;
3970: oldm=newm;
3971: } /* end mult */
3972:
3973: s1=s[mw[mi][i]][i];
3974: s2=s[mw[mi+1][i]][i];
3975: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3976: ipmx +=1;
3977: sw += weight[i];
3978: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3979: /*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]);*/
3980: } /* end of wave */
3981: } /* end of individual */
3982: } /* End of if */
3983: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3984: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3985: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3986: return -l;
1.126 brouard 3987: }
3988:
3989: /*************** log-likelihood *************/
3990: double funcone( double *x)
3991: {
1.228 brouard 3992: /* Same as func but slower because of a lot of printf and if */
1.126 brouard 3993: int i, ii, j, k, mi, d, kk;
1.228 brouard 3994: int ioffset=0;
1.131 brouard 3995: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 3996: double **out;
3997: double lli; /* Individual log likelihood */
3998: double llt;
3999: int s1, s2;
1.228 brouard 4000: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
4001:
1.126 brouard 4002: double bbh, survp;
1.187 brouard 4003: double agexact;
1.214 brouard 4004: double agebegin, ageend;
1.126 brouard 4005: /*extern weight */
4006: /* We are differentiating ll according to initial status */
4007: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
4008: /*for(i=1;i<imx;i++)
4009: printf(" %d\n",s[4][i]);
4010: */
4011: cov[1]=1.;
4012:
4013: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 4014: ioffset=0;
4015: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.243 brouard 4016: /* ioffset=2+nagesqr+cptcovage; */
4017: ioffset=2+nagesqr;
1.232 brouard 4018: /* Fixed */
1.224 brouard 4019: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 4020: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
1.311 brouard 4021: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products *//* Missing values are set to -1 but should be dropped */
1.232 brouard 4022: 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)*/
4023: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
4024: /* cov[2+6]=covar[Tvar[6]][i]; */
4025: /* cov[2+6]=covar[2][i]; V2 */
4026: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
4027: /* cov[2+7]=covar[Tvar[7]][i]; */
4028: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
4029: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
4030: /* cov[2+9]=covar[Tvar[9]][i]; */
4031: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 4032: }
1.232 brouard 4033: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
4034: /* 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?)*\/ */
4035: /* } */
1.231 brouard 4036: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
4037: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
4038: /* } */
1.225 brouard 4039:
1.233 brouard 4040:
4041: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.232 brouard 4042: /* Wave varying (but not age varying) */
4043: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 4044: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
4045: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
4046: }
1.232 brouard 4047: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates (single??)*\/ */
1.242 brouard 4048: /* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; /\* Counting the # varying covariate from 1 to ntveff *\/ */
4049: /* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; */
4050: /* k=ioffset-2-nagesqr-cptcovage+itv; /\* position in simple model *\/ */
4051: /* cov[ioffset+itv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; */
4052: /* 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 4053: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 4054: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
4055: /* /\* 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]); *\/ */
4056: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 4057: /* } */
1.126 brouard 4058: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 4059: for (j=1;j<=nlstate+ndeath;j++){
4060: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4061: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4062: }
1.214 brouard 4063:
4064: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
4065: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
4066: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 4067: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 4068: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
4069: and mw[mi+1][i]. dh depends on stepm.*/
4070: newm=savm;
1.247 brouard 4071: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 4072: cov[2]=agexact;
4073: if(nagesqr==1)
4074: cov[3]= agexact*agexact;
4075: for (kk=1; kk<=cptcovage;kk++) {
4076: if(!FixedV[Tvar[Tage[kk]]])
4077: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4078: else
4079: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
4080: }
4081: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
4082: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
4083: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4084: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4085: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
4086: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
4087: savm=oldm;
4088: oldm=newm;
1.126 brouard 4089: } /* end mult */
4090:
4091: s1=s[mw[mi][i]][i];
4092: s2=s[mw[mi+1][i]][i];
1.217 brouard 4093: /* if(s2==-1){ */
1.268 brouard 4094: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 4095: /* /\* exit(1); *\/ */
4096: /* } */
1.126 brouard 4097: bbh=(double)bh[mi][i]/(double)stepm;
4098: /* bias is positive if real duration
4099: * is higher than the multiple of stepm and negative otherwise.
4100: */
4101: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 4102: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 4103: } else if ( s2==-1 ) { /* alive */
1.242 brouard 4104: for (j=1,survp=0. ; j<=nlstate; j++)
4105: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
4106: lli= log(survp);
1.126 brouard 4107: }else if (mle==1){
1.242 brouard 4108: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 4109: } else if(mle==2){
1.242 brouard 4110: 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 4111: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 4112: 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 4113: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 4114: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 4115: } else{ /* mle=0 back to 1 */
1.242 brouard 4116: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
4117: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 4118: } /* End of if */
4119: ipmx +=1;
4120: sw += weight[i];
4121: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.132 brouard 4122: /*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 4123: if(globpr){
1.246 brouard 4124: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 4125: %11.6f %11.6f %11.6f ", \
1.242 brouard 4126: 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 4127: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.242 brouard 4128: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
4129: llt +=ll[k]*gipmx/gsw;
4130: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
4131: }
4132: fprintf(ficresilk," %10.6f\n", -llt);
1.126 brouard 4133: }
1.232 brouard 4134: } /* end of wave */
4135: } /* end of individual */
4136: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
4137: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
4138: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
4139: if(globpr==0){ /* First time we count the contributions and weights */
4140: gipmx=ipmx;
4141: gsw=sw;
4142: }
4143: return -l;
1.126 brouard 4144: }
4145:
4146:
4147: /*************** function likelione ***********/
1.292 brouard 4148: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*func)(double []))
1.126 brouard 4149: {
4150: /* This routine should help understanding what is done with
4151: the selection of individuals/waves and
4152: to check the exact contribution to the likelihood.
4153: Plotting could be done.
4154: */
4155: int k;
4156:
4157: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 4158: strcpy(fileresilk,"ILK_");
1.202 brouard 4159: strcat(fileresilk,fileresu);
1.126 brouard 4160: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
4161: printf("Problem with resultfile: %s\n", fileresilk);
4162: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
4163: }
1.214 brouard 4164: 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");
4165: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 4166: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
4167: for(k=1; k<=nlstate; k++)
4168: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
4169: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total)\n");
4170: }
4171:
1.292 brouard 4172: *fretone=(*func)(p);
1.126 brouard 4173: if(*globpri !=0){
4174: fclose(ficresilk);
1.205 brouard 4175: if (mle ==0)
4176: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
4177: else if(mle >=1)
4178: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
4179: 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 4180: fprintf(fichtm,"\n<br>Equation of the model: <b>model=1+age+%s</b><br>\n",model);
1.208 brouard 4181:
4182: for (k=1; k<= nlstate ; k++) {
1.211 brouard 4183: 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 4184: <img src=\"%s-p%dj.png\">",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
4185: }
1.207 brouard 4186: 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 4187: <img src=\"%s-ori.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 4188: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.204 brouard 4189: <img src=\"%s-dest.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 4190: fflush(fichtm);
1.205 brouard 4191: }
1.126 brouard 4192: return;
4193: }
4194:
4195:
4196: /*********** Maximum Likelihood Estimation ***************/
4197:
4198: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
4199: {
1.319 brouard 4200: int i,j,k, jk, jkk=0, iter=0;
1.126 brouard 4201: double **xi;
4202: double fret;
4203: double fretone; /* Only one call to likelihood */
4204: /* char filerespow[FILENAMELENGTH];*/
1.162 brouard 4205:
4206: #ifdef NLOPT
4207: int creturn;
4208: nlopt_opt opt;
4209: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
4210: double *lb;
4211: double minf; /* the minimum objective value, upon return */
4212: double * p1; /* Shifted parameters from 0 instead of 1 */
4213: myfunc_data dinst, *d = &dinst;
4214: #endif
4215:
4216:
1.126 brouard 4217: xi=matrix(1,npar,1,npar);
4218: for (i=1;i<=npar;i++)
4219: for (j=1;j<=npar;j++)
4220: xi[i][j]=(i==j ? 1.0 : 0.0);
4221: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 4222: strcpy(filerespow,"POW_");
1.126 brouard 4223: strcat(filerespow,fileres);
4224: if((ficrespow=fopen(filerespow,"w"))==NULL) {
4225: printf("Problem with resultfile: %s\n", filerespow);
4226: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
4227: }
4228: fprintf(ficrespow,"# Powell\n# iter -2*LL");
4229: for (i=1;i<=nlstate;i++)
4230: for(j=1;j<=nlstate+ndeath;j++)
4231: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
4232: fprintf(ficrespow,"\n");
1.162 brouard 4233: #ifdef POWELL
1.319 brouard 4234: #ifdef LINMINORIGINAL
4235: #else /* LINMINORIGINAL */
4236:
4237: flatdir=ivector(1,npar);
4238: for (j=1;j<=npar;j++) flatdir[j]=0;
4239: #endif /*LINMINORIGINAL */
4240:
4241: #ifdef FLATSUP
4242: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
4243: /* reorganizing p by suppressing flat directions */
4244: for(i=1, jk=1; i <=nlstate; i++){
4245: for(k=1; k <=(nlstate+ndeath); k++){
4246: if (k != i) {
4247: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
4248: if(flatdir[jk]==1){
4249: printf(" To be skipped %d%d flatdir[%d]=%d ",i,k,jk, flatdir[jk]);
4250: }
4251: for(j=1; j <=ncovmodel; j++){
4252: printf("%12.7f ",p[jk]);
4253: jk++;
4254: }
4255: printf("\n");
4256: }
4257: }
4258: }
4259: /* skipping */
4260: /* for(i=1, jk=1, jkk=1;(flatdir[jk]==0)&& (i <=nlstate); i++){ */
4261: for(i=1, jk=1, jkk=1;i <=nlstate; i++){
4262: for(k=1; k <=(nlstate+ndeath); k++){
4263: if (k != i) {
4264: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
4265: if(flatdir[jk]==1){
4266: printf(" To be skipped %d%d flatdir[%d]=%d jk=%d p[%d] ",i,k,jk, flatdir[jk],jk, jk);
4267: for(j=1; j <=ncovmodel; jk++,j++){
4268: printf(" p[%d]=%12.7f",jk, p[jk]);
4269: /*q[jjk]=p[jk];*/
4270: }
4271: }else{
4272: printf(" To be kept %d%d flatdir[%d]=%d jk=%d q[%d]=p[%d] ",i,k,jk, flatdir[jk],jk, jkk, jk);
4273: for(j=1; j <=ncovmodel; jk++,jkk++,j++){
4274: printf(" p[%d]=%12.7f=q[%d]",jk, p[jk],jkk);
4275: /*q[jjk]=p[jk];*/
4276: }
4277: }
4278: printf("\n");
4279: }
4280: fflush(stdout);
4281: }
4282: }
4283: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
4284: #else /* FLATSUP */
1.126 brouard 4285: powell(p,xi,npar,ftol,&iter,&fret,func);
1.319 brouard 4286: #endif /* FLATSUP */
4287:
4288: #ifdef LINMINORIGINAL
4289: #else
4290: free_ivector(flatdir,1,npar);
4291: #endif /* LINMINORIGINAL*/
4292: #endif /* POWELL */
1.126 brouard 4293:
1.162 brouard 4294: #ifdef NLOPT
4295: #ifdef NEWUOA
4296: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
4297: #else
4298: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
4299: #endif
4300: lb=vector(0,npar-1);
4301: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
4302: nlopt_set_lower_bounds(opt, lb);
4303: nlopt_set_initial_step1(opt, 0.1);
4304:
4305: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
4306: d->function = func;
4307: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
4308: nlopt_set_min_objective(opt, myfunc, d);
4309: nlopt_set_xtol_rel(opt, ftol);
4310: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
4311: printf("nlopt failed! %d\n",creturn);
4312: }
4313: else {
4314: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
4315: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
4316: iter=1; /* not equal */
4317: }
4318: nlopt_destroy(opt);
4319: #endif
1.319 brouard 4320: #ifdef FLATSUP
4321: /* npared = npar -flatd/ncovmodel; */
4322: /* xired= matrix(1,npared,1,npared); */
4323: /* paramred= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel); */
4324: /* powell(pred,xired,npared,ftol,&iter,&fret,flatdir,func); */
4325: /* free_matrix(xire,1,npared,1,npared); */
4326: #else /* FLATSUP */
4327: #endif /* FLATSUP */
1.126 brouard 4328: free_matrix(xi,1,npar,1,npar);
4329: fclose(ficrespow);
1.203 brouard 4330: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
4331: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 4332: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 4333:
4334: }
4335:
4336: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 4337: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 4338: {
4339: double **a,**y,*x,pd;
1.203 brouard 4340: /* double **hess; */
1.164 brouard 4341: int i, j;
1.126 brouard 4342: int *indx;
4343:
4344: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 4345: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 4346: void lubksb(double **a, int npar, int *indx, double b[]) ;
4347: void ludcmp(double **a, int npar, int *indx, double *d) ;
4348: double gompertz(double p[]);
1.203 brouard 4349: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 4350:
4351: printf("\nCalculation of the hessian matrix. Wait...\n");
4352: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
4353: for (i=1;i<=npar;i++){
1.203 brouard 4354: printf("%d-",i);fflush(stdout);
4355: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 4356:
4357: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
4358:
4359: /* printf(" %f ",p[i]);
4360: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
4361: }
4362:
4363: for (i=1;i<=npar;i++) {
4364: for (j=1;j<=npar;j++) {
4365: if (j>i) {
1.203 brouard 4366: printf(".%d-%d",i,j);fflush(stdout);
4367: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
4368: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 4369:
4370: hess[j][i]=hess[i][j];
4371: /*printf(" %lf ",hess[i][j]);*/
4372: }
4373: }
4374: }
4375: printf("\n");
4376: fprintf(ficlog,"\n");
4377:
4378: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
4379: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
4380:
4381: a=matrix(1,npar,1,npar);
4382: y=matrix(1,npar,1,npar);
4383: x=vector(1,npar);
4384: indx=ivector(1,npar);
4385: for (i=1;i<=npar;i++)
4386: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
4387: ludcmp(a,npar,indx,&pd);
4388:
4389: for (j=1;j<=npar;j++) {
4390: for (i=1;i<=npar;i++) x[i]=0;
4391: x[j]=1;
4392: lubksb(a,npar,indx,x);
4393: for (i=1;i<=npar;i++){
4394: matcov[i][j]=x[i];
4395: }
4396: }
4397:
4398: printf("\n#Hessian matrix#\n");
4399: fprintf(ficlog,"\n#Hessian matrix#\n");
4400: for (i=1;i<=npar;i++) {
4401: for (j=1;j<=npar;j++) {
1.203 brouard 4402: printf("%.6e ",hess[i][j]);
4403: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 4404: }
4405: printf("\n");
4406: fprintf(ficlog,"\n");
4407: }
4408:
1.203 brouard 4409: /* printf("\n#Covariance matrix#\n"); */
4410: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
4411: /* for (i=1;i<=npar;i++) { */
4412: /* for (j=1;j<=npar;j++) { */
4413: /* printf("%.6e ",matcov[i][j]); */
4414: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
4415: /* } */
4416: /* printf("\n"); */
4417: /* fprintf(ficlog,"\n"); */
4418: /* } */
4419:
1.126 brouard 4420: /* Recompute Inverse */
1.203 brouard 4421: /* for (i=1;i<=npar;i++) */
4422: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
4423: /* ludcmp(a,npar,indx,&pd); */
4424:
4425: /* printf("\n#Hessian matrix recomputed#\n"); */
4426:
4427: /* for (j=1;j<=npar;j++) { */
4428: /* for (i=1;i<=npar;i++) x[i]=0; */
4429: /* x[j]=1; */
4430: /* lubksb(a,npar,indx,x); */
4431: /* for (i=1;i<=npar;i++){ */
4432: /* y[i][j]=x[i]; */
4433: /* printf("%.3e ",y[i][j]); */
4434: /* fprintf(ficlog,"%.3e ",y[i][j]); */
4435: /* } */
4436: /* printf("\n"); */
4437: /* fprintf(ficlog,"\n"); */
4438: /* } */
4439:
4440: /* Verifying the inverse matrix */
4441: #ifdef DEBUGHESS
4442: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 4443:
1.203 brouard 4444: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
4445: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 4446:
4447: for (j=1;j<=npar;j++) {
4448: for (i=1;i<=npar;i++){
1.203 brouard 4449: printf("%.2f ",y[i][j]);
4450: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 4451: }
4452: printf("\n");
4453: fprintf(ficlog,"\n");
4454: }
1.203 brouard 4455: #endif
1.126 brouard 4456:
4457: free_matrix(a,1,npar,1,npar);
4458: free_matrix(y,1,npar,1,npar);
4459: free_vector(x,1,npar);
4460: free_ivector(indx,1,npar);
1.203 brouard 4461: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 4462:
4463:
4464: }
4465:
4466: /*************** hessian matrix ****************/
4467: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 4468: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 4469: int i;
4470: int l=1, lmax=20;
1.203 brouard 4471: double k1,k2, res, fx;
1.132 brouard 4472: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 4473: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
4474: int k=0,kmax=10;
4475: double l1;
4476:
4477: fx=func(x);
4478: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 4479: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 4480: l1=pow(10,l);
4481: delts=delt;
4482: for(k=1 ; k <kmax; k=k+1){
4483: delt = delta*(l1*k);
4484: p2[theta]=x[theta] +delt;
1.145 brouard 4485: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 4486: p2[theta]=x[theta]-delt;
4487: k2=func(p2)-fx;
4488: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 4489: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 4490:
1.203 brouard 4491: #ifdef DEBUGHESSII
1.126 brouard 4492: 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);
4493: 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);
4494: #endif
4495: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
4496: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
4497: k=kmax;
4498: }
4499: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 4500: k=kmax; l=lmax*10;
1.126 brouard 4501: }
4502: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
4503: delts=delt;
4504: }
1.203 brouard 4505: } /* End loop k */
1.126 brouard 4506: }
4507: delti[theta]=delts;
4508: return res;
4509:
4510: }
4511:
1.203 brouard 4512: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 4513: {
4514: int i;
1.164 brouard 4515: int l=1, lmax=20;
1.126 brouard 4516: double k1,k2,k3,k4,res,fx;
1.132 brouard 4517: double p2[MAXPARM+1];
1.203 brouard 4518: int k, kmax=1;
4519: double v1, v2, cv12, lc1, lc2;
1.208 brouard 4520:
4521: int firstime=0;
1.203 brouard 4522:
1.126 brouard 4523: fx=func(x);
1.203 brouard 4524: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 4525: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 4526: p2[thetai]=x[thetai]+delti[thetai]*k;
4527: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4528: k1=func(p2)-fx;
4529:
1.203 brouard 4530: p2[thetai]=x[thetai]+delti[thetai]*k;
4531: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4532: k2=func(p2)-fx;
4533:
1.203 brouard 4534: p2[thetai]=x[thetai]-delti[thetai]*k;
4535: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4536: k3=func(p2)-fx;
4537:
1.203 brouard 4538: p2[thetai]=x[thetai]-delti[thetai]*k;
4539: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4540: k4=func(p2)-fx;
1.203 brouard 4541: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
4542: if(k1*k2*k3*k4 <0.){
1.208 brouard 4543: firstime=1;
1.203 brouard 4544: kmax=kmax+10;
1.208 brouard 4545: }
4546: if(kmax >=10 || firstime ==1){
1.246 brouard 4547: 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);
4548: 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 4549: 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);
4550: 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);
4551: }
4552: #ifdef DEBUGHESSIJ
4553: v1=hess[thetai][thetai];
4554: v2=hess[thetaj][thetaj];
4555: cv12=res;
4556: /* Computing eigen value of Hessian matrix */
4557: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4558: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4559: if ((lc2 <0) || (lc1 <0) ){
4560: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4561: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4562: 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);
4563: 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);
4564: }
1.126 brouard 4565: #endif
4566: }
4567: return res;
4568: }
4569:
1.203 brouard 4570: /* Not done yet: Was supposed to fix if not exactly at the maximum */
4571: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
4572: /* { */
4573: /* int i; */
4574: /* int l=1, lmax=20; */
4575: /* double k1,k2,k3,k4,res,fx; */
4576: /* double p2[MAXPARM+1]; */
4577: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
4578: /* int k=0,kmax=10; */
4579: /* double l1; */
4580:
4581: /* fx=func(x); */
4582: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
4583: /* l1=pow(10,l); */
4584: /* delts=delt; */
4585: /* for(k=1 ; k <kmax; k=k+1){ */
4586: /* delt = delti*(l1*k); */
4587: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
4588: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4589: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4590: /* k1=func(p2)-fx; */
4591:
4592: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4593: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4594: /* k2=func(p2)-fx; */
4595:
4596: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4597: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4598: /* k3=func(p2)-fx; */
4599:
4600: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4601: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4602: /* k4=func(p2)-fx; */
4603: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
4604: /* #ifdef DEBUGHESSIJ */
4605: /* 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); */
4606: /* 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); */
4607: /* #endif */
4608: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
4609: /* k=kmax; */
4610: /* } */
4611: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
4612: /* k=kmax; l=lmax*10; */
4613: /* } */
4614: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
4615: /* delts=delt; */
4616: /* } */
4617: /* } /\* End loop k *\/ */
4618: /* } */
4619: /* delti[theta]=delts; */
4620: /* return res; */
4621: /* } */
4622:
4623:
1.126 brouard 4624: /************** Inverse of matrix **************/
4625: void ludcmp(double **a, int n, int *indx, double *d)
4626: {
4627: int i,imax,j,k;
4628: double big,dum,sum,temp;
4629: double *vv;
4630:
4631: vv=vector(1,n);
4632: *d=1.0;
4633: for (i=1;i<=n;i++) {
4634: big=0.0;
4635: for (j=1;j<=n;j++)
4636: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 4637: if (big == 0.0){
4638: printf(" Singular Hessian matrix at row %d:\n",i);
4639: for (j=1;j<=n;j++) {
4640: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
4641: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
4642: }
4643: fflush(ficlog);
4644: fclose(ficlog);
4645: nrerror("Singular matrix in routine ludcmp");
4646: }
1.126 brouard 4647: vv[i]=1.0/big;
4648: }
4649: for (j=1;j<=n;j++) {
4650: for (i=1;i<j;i++) {
4651: sum=a[i][j];
4652: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
4653: a[i][j]=sum;
4654: }
4655: big=0.0;
4656: for (i=j;i<=n;i++) {
4657: sum=a[i][j];
4658: for (k=1;k<j;k++)
4659: sum -= a[i][k]*a[k][j];
4660: a[i][j]=sum;
4661: if ( (dum=vv[i]*fabs(sum)) >= big) {
4662: big=dum;
4663: imax=i;
4664: }
4665: }
4666: if (j != imax) {
4667: for (k=1;k<=n;k++) {
4668: dum=a[imax][k];
4669: a[imax][k]=a[j][k];
4670: a[j][k]=dum;
4671: }
4672: *d = -(*d);
4673: vv[imax]=vv[j];
4674: }
4675: indx[j]=imax;
4676: if (a[j][j] == 0.0) a[j][j]=TINY;
4677: if (j != n) {
4678: dum=1.0/(a[j][j]);
4679: for (i=j+1;i<=n;i++) a[i][j] *= dum;
4680: }
4681: }
4682: free_vector(vv,1,n); /* Doesn't work */
4683: ;
4684: }
4685:
4686: void lubksb(double **a, int n, int *indx, double b[])
4687: {
4688: int i,ii=0,ip,j;
4689: double sum;
4690:
4691: for (i=1;i<=n;i++) {
4692: ip=indx[i];
4693: sum=b[ip];
4694: b[ip]=b[i];
4695: if (ii)
4696: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
4697: else if (sum) ii=i;
4698: b[i]=sum;
4699: }
4700: for (i=n;i>=1;i--) {
4701: sum=b[i];
4702: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
4703: b[i]=sum/a[i][i];
4704: }
4705: }
4706:
4707: void pstamp(FILE *fichier)
4708: {
1.196 brouard 4709: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 4710: }
4711:
1.297 brouard 4712: void date2dmy(double date,double *day, double *month, double *year){
4713: double yp=0., yp1=0., yp2=0.;
4714:
4715: yp1=modf(date,&yp);/* extracts integral of date in yp and
4716: fractional in yp1 */
4717: *year=yp;
4718: yp2=modf((yp1*12),&yp);
4719: *month=yp;
4720: yp1=modf((yp2*30.5),&yp);
4721: *day=yp;
4722: if(*day==0) *day=1;
4723: if(*month==0) *month=1;
4724: }
4725:
1.253 brouard 4726:
4727:
1.126 brouard 4728: /************ Frequencies ********************/
1.251 brouard 4729: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 4730: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
4731: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 4732: { /* Some frequencies as well as proposing some starting values */
1.226 brouard 4733:
1.265 brouard 4734: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 4735: int iind=0, iage=0;
4736: int mi; /* Effective wave */
4737: int first;
4738: double ***freq; /* Frequencies */
1.268 brouard 4739: 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 */
4740: 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 4741: double *meanq, *stdq, *idq;
1.226 brouard 4742: double **meanqt;
4743: double *pp, **prop, *posprop, *pospropt;
4744: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
4745: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
4746: double agebegin, ageend;
4747:
4748: pp=vector(1,nlstate);
1.251 brouard 4749: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4750: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
4751: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
4752: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
4753: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.284 brouard 4754: stdq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.283 brouard 4755: idq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.226 brouard 4756: meanqt=matrix(1,lastpass,1,nqtveff);
4757: strcpy(fileresp,"P_");
4758: strcat(fileresp,fileresu);
4759: /*strcat(fileresphtm,fileresu);*/
4760: if((ficresp=fopen(fileresp,"w"))==NULL) {
4761: printf("Problem with prevalence resultfile: %s\n", fileresp);
4762: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
4763: exit(0);
4764: }
1.240 brouard 4765:
1.226 brouard 4766: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
4767: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
4768: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4769: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4770: fflush(ficlog);
4771: exit(70);
4772: }
4773: else{
4774: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 4775: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4776: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4777: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4778: }
1.319 brouard 4779: fprintf(ficresphtm,"Current page is file <a href=\"%s\">%s</a><br>\n\n<h4>Frequencies (weight=%d) and prevalence by age at begin of transition and dummy covariate value at beginning of transition</h4>\n",fileresphtm, fileresphtm, weightopt);
1.240 brouard 4780:
1.226 brouard 4781: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
4782: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
4783: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4784: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4785: fflush(ficlog);
4786: exit(70);
1.240 brouard 4787: } else{
1.226 brouard 4788: fprintf(ficresphtmfr,"<html><head>\n<title>IMaCh PHTM_Frequency table %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.319 brouard 4789: ,<hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4790: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4791: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4792: }
1.319 brouard 4793: fprintf(ficresphtmfr,"Current page is file <a href=\"%s\">%s</a><br>\n\n<h4>(weight=%d) 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,weightopt);
1.240 brouard 4794:
1.253 brouard 4795: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
4796: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 4797: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4798: j1=0;
1.126 brouard 4799:
1.227 brouard 4800: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
4801: j=cptcoveff; /* Only dummy covariates of the model */
1.226 brouard 4802: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 4803:
4804:
1.226 brouard 4805: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
4806: reference=low_education V1=0,V2=0
4807: med_educ V1=1 V2=0,
4808: high_educ V1=0 V2=1
4809: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcoveff
4810: */
1.249 brouard 4811: dateintsum=0;
4812: k2cpt=0;
4813:
1.253 brouard 4814: if(cptcoveff == 0 )
1.265 brouard 4815: nl=1; /* Constant and age model only */
1.253 brouard 4816: else
4817: nl=2;
1.265 brouard 4818:
4819: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
4820: /* Loop on nj=1 or 2 if dummy covariates j!=0
4821: * Loop on j1(1 to 2**cptcoveff) covariate combination
4822: * freq[s1][s2][iage] =0.
4823: * Loop on iind
4824: * ++freq[s1][s2][iage] weighted
4825: * end iind
4826: * if covariate and j!0
4827: * headers Variable on one line
4828: * endif cov j!=0
4829: * header of frequency table by age
4830: * Loop on age
4831: * pp[s1]+=freq[s1][s2][iage] weighted
4832: * pos+=freq[s1][s2][iage] weighted
4833: * Loop on s1 initial state
4834: * fprintf(ficresp
4835: * end s1
4836: * end age
4837: * if j!=0 computes starting values
4838: * end compute starting values
4839: * end j1
4840: * end nl
4841: */
1.253 brouard 4842: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
4843: if(nj==1)
4844: j=0; /* First pass for the constant */
1.265 brouard 4845: else{
1.253 brouard 4846: j=cptcoveff; /* Other passes for the covariate values */
1.265 brouard 4847: }
1.251 brouard 4848: first=1;
1.265 brouard 4849: 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 4850: posproptt=0.;
4851: /*printf("cptcoveff=%d Tvaraff=%d", cptcoveff,Tvaraff[1]);
4852: scanf("%d", i);*/
4853: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 4854: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 4855: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 4856: freq[i][s2][m]=0;
1.251 brouard 4857:
4858: for (i=1; i<=nlstate; i++) {
1.240 brouard 4859: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 4860: prop[i][m]=0;
4861: posprop[i]=0;
4862: pospropt[i]=0;
4863: }
1.283 brouard 4864: for (z1=1; z1<= nqfveff; z1++) { /* zeroing for each combination j1 as well as for the total */
1.284 brouard 4865: idq[z1]=0.;
4866: meanq[z1]=0.;
4867: stdq[z1]=0.;
1.283 brouard 4868: }
4869: /* for (z1=1; z1<= nqtveff; z1++) { */
1.251 brouard 4870: /* for(m=1;m<=lastpass;m++){ */
1.283 brouard 4871: /* meanqt[m][z1]=0.; */
4872: /* } */
4873: /* } */
1.251 brouard 4874: /* dateintsum=0; */
4875: /* k2cpt=0; */
4876:
1.265 brouard 4877: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 4878: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
4879: bool=1;
4880: if(j !=0){
4881: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
4882: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
4883: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
4884: /* if(Tvaraff[z1] ==-20){ */
4885: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
4886: /* }else if(Tvaraff[z1] ==-10){ */
4887: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
4888: /* }else */
4889: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]){ /* for combination j1 of covariates */
1.265 brouard 4890: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 4891: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
4892: /* 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",
4893: bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),
4894: j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
4895: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
4896: } /* Onlyf fixed */
4897: } /* end z1 */
4898: } /* cptcovn > 0 */
4899: } /* end any */
4900: }/* end j==0 */
1.265 brouard 4901: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 4902: /* for(m=firstpass; m<=lastpass; m++){ */
1.284 brouard 4903: for(mi=1; mi<wav[iind];mi++){ /* For each wave */
1.251 brouard 4904: m=mw[mi][iind];
4905: if(j!=0){
4906: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
4907: for (z1=1; z1<=cptcoveff; z1++) {
4908: if( Fixed[Tmodelind[z1]]==1){
4909: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
4910: if (cotvar[m][iv][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality. If covariate's
4911: value is -1, we don't select. It differs from the
4912: constant and age model which counts them. */
4913: bool=0; /* not selected */
4914: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
4915: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
4916: bool=0;
4917: }
4918: }
4919: }
4920: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
4921: } /* end j==0 */
4922: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
1.284 brouard 4923: if(bool==1){ /*Selected */
1.251 brouard 4924: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
4925: and mw[mi+1][iind]. dh depends on stepm. */
4926: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
4927: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
4928: if(m >=firstpass && m <=lastpass){
4929: k2=anint[m][iind]+(mint[m][iind]/12.);
4930: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
4931: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
4932: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
4933: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
4934: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
4935: if (m<lastpass) {
4936: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
4937: /* 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]); */
4938: if(s[m][iind]==-1)
4939: 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.));
4940: freq[s[m][iind]][s[m+1][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
1.311 brouard 4941: for (z1=1; z1<= nqfveff; z1++) { /* Quantitative variables, calculating mean on known values only */
4942: if(!isnan(covar[ncovcol+z1][iind])){
4943: idq[z1]=idq[z1]+weight[iind];
4944: meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /* Computes mean of quantitative with selected filter */
4945: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; *//*error*/
4946: stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]; /* *weight[iind];*/ /* Computes mean of quantitative with selected filter */
4947: }
1.284 brouard 4948: }
1.251 brouard 4949: /* if((int)agev[m][iind] == 55) */
4950: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
4951: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
4952: 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 4953: }
1.251 brouard 4954: } /* end if between passes */
4955: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
4956: dateintsum=dateintsum+k2; /* on all covariates ?*/
4957: k2cpt++;
4958: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 4959: }
1.251 brouard 4960: }else{
4961: bool=1;
4962: }/* end bool 2 */
4963: } /* end m */
1.284 brouard 4964: /* for (z1=1; z1<= nqfveff; z1++) { /\* Quantitative variables, calculating mean *\/ */
4965: /* idq[z1]=idq[z1]+weight[iind]; */
4966: /* meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /\* Computes mean of quantitative with selected filter *\/ */
4967: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /\* *weight[iind];*\/ /\* Computes mean of quantitative with selected filter *\/ */
4968: /* } */
1.251 brouard 4969: } /* end bool */
4970: } /* end iind = 1 to imx */
1.319 brouard 4971: /* prop[s][age] is fed for any initial and valid live state as well as
1.251 brouard 4972: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
4973:
4974:
4975: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.265 brouard 4976: if(cptcoveff==0 && nj==1) /* no covariate and first pass */
4977: pstamp(ficresp);
1.251 brouard 4978: if (cptcoveff>0 && j!=0){
1.265 brouard 4979: pstamp(ficresp);
1.251 brouard 4980: printf( "\n#********** Variable ");
4981: fprintf(ficresp, "\n#********** Variable ");
4982: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
4983: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
4984: fprintf(ficlog, "\n#********** Variable ");
4985: for (z1=1; z1<=cptcoveff; z1++){
4986: if(!FixedV[Tvaraff[z1]]){
4987: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4988: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4989: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4990: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4991: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.250 brouard 4992: }else{
1.251 brouard 4993: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4994: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4995: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4996: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4997: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4998: }
4999: }
5000: printf( "**********\n#");
5001: fprintf(ficresp, "**********\n#");
5002: fprintf(ficresphtm, "**********</h3>\n");
5003: fprintf(ficresphtmfr, "**********</h3>\n");
5004: fprintf(ficlog, "**********\n");
5005: }
1.284 brouard 5006: /*
5007: Printing means of quantitative variables if any
5008: */
5009: for (z1=1; z1<= nqfveff; z1++) {
1.311 brouard 5010: fprintf(ficlog,"Mean of fixed quantitative variable V%d on %.3g (weighted) individuals sum=%f", ncovcol+z1, idq[z1], meanq[z1]);
1.312 brouard 5011: fprintf(ficlog,", mean=%.3g\n",meanq[z1]/idq[z1]);
1.284 brouard 5012: if(weightopt==1){
5013: printf(" Weighted mean and standard deviation of");
5014: fprintf(ficlog," Weighted mean and standard deviation of");
5015: fprintf(ficresphtmfr," Weighted mean and standard deviation of");
5016: }
1.311 brouard 5017: /* mu = \frac{w x}{\sum w}
5018: var = \frac{\sum w (x-mu)^2}{\sum w} = \frac{w x^2}{\sum w} - mu^2
5019: */
5020: printf(" fixed quantitative variable V%d on %.3g (weighted) representatives of the population : %8.5g (%8.5g)\n", ncovcol+z1, idq[z1],meanq[z1]/idq[z1], sqrt(stdq[z1]/idq[z1]-meanq[z1]*meanq[z1]/idq[z1]/idq[z1]));
5021: fprintf(ficlog," fixed quantitative variable V%d on %.3g (weighted) representatives of the population : %8.5g (%8.5g)\n", ncovcol+z1, idq[z1],meanq[z1]/idq[z1], sqrt(stdq[z1]/idq[z1]-meanq[z1]*meanq[z1]/idq[z1]/idq[z1]));
5022: fprintf(ficresphtmfr," fixed quantitative variable V%d on %.3g (weighted) representatives of the population : %8.5g (%8.5g)<p>\n", ncovcol+z1, idq[z1],meanq[z1]/idq[z1], sqrt(stdq[z1]/idq[z1]-meanq[z1]*meanq[z1]/idq[z1]/idq[z1]));
1.284 brouard 5023: }
5024: /* for (z1=1; z1<= nqtveff; z1++) { */
5025: /* for(m=1;m<=lastpass;m++){ */
5026: /* fprintf(ficresphtmfr,"V quantitative id %d, pass id=%d, mean=%f<p>\n", z1, m, meanqt[m][z1]); */
5027: /* } */
5028: /* } */
1.283 brouard 5029:
1.251 brouard 5030: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.265 brouard 5031: if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
5032: fprintf(ficresp, " Age");
5033: 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 5034: for(i=1; i<=nlstate;i++) {
1.265 brouard 5035: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 5036: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
5037: }
1.265 brouard 5038: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 5039: fprintf(ficresphtm, "\n");
5040:
5041: /* Header of frequency table by age */
5042: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
5043: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 5044: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 5045: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5046: if(s2!=0 && m!=0)
5047: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 5048: }
1.226 brouard 5049: }
1.251 brouard 5050: fprintf(ficresphtmfr, "\n");
5051:
5052: /* For each age */
5053: for(iage=iagemin; iage <= iagemax+3; iage++){
5054: fprintf(ficresphtm,"<tr>");
5055: if(iage==iagemax+1){
5056: fprintf(ficlog,"1");
5057: fprintf(ficresphtmfr,"<tr><th>0</th> ");
5058: }else if(iage==iagemax+2){
5059: fprintf(ficlog,"0");
5060: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
5061: }else if(iage==iagemax+3){
5062: fprintf(ficlog,"Total");
5063: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
5064: }else{
1.240 brouard 5065: if(first==1){
1.251 brouard 5066: first=0;
5067: printf("See log file for details...\n");
5068: }
5069: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
5070: fprintf(ficlog,"Age %d", iage);
5071: }
1.265 brouard 5072: for(s1=1; s1 <=nlstate ; s1++){
5073: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
5074: pp[s1] += freq[s1][m][iage];
1.251 brouard 5075: }
1.265 brouard 5076: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5077: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 5078: pos += freq[s1][m][iage];
5079: if(pp[s1]>=1.e-10){
1.251 brouard 5080: if(first==1){
1.265 brouard 5081: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5082: }
1.265 brouard 5083: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5084: }else{
5085: if(first==1)
1.265 brouard 5086: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
5087: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 5088: }
5089: }
5090:
1.265 brouard 5091: for(s1=1; s1 <=nlstate ; s1++){
5092: /* posprop[s1]=0; */
5093: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
5094: pp[s1] += freq[s1][m][iage];
5095: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
5096:
5097: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
5098: pos += pp[s1]; /* pos is the total number of transitions until this age */
5099: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
5100: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5101: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
5102: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5103: }
5104:
5105: /* Writing ficresp */
5106: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
5107: if( iage <= iagemax){
5108: fprintf(ficresp," %d",iage);
5109: }
5110: }else if( nj==2){
5111: if( iage <= iagemax){
5112: fprintf(ficresp," %d",iage);
5113: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
5114: }
1.240 brouard 5115: }
1.265 brouard 5116: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 5117: if(pos>=1.e-5){
1.251 brouard 5118: if(first==1)
1.265 brouard 5119: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
5120: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 5121: }else{
5122: if(first==1)
1.265 brouard 5123: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
5124: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 5125: }
5126: if( iage <= iagemax){
5127: if(pos>=1.e-5){
1.265 brouard 5128: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
5129: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5130: }else if( nj==2){
5131: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5132: }
5133: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5134: /*probs[iage][s1][j1]= pp[s1]/pos;*/
5135: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
5136: } else{
5137: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
5138: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 5139: }
1.240 brouard 5140: }
1.265 brouard 5141: pospropt[s1] +=posprop[s1];
5142: } /* end loop s1 */
1.251 brouard 5143: /* pospropt=0.; */
1.265 brouard 5144: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 5145: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5146: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 5147: if(first==1){
1.265 brouard 5148: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5149: }
1.265 brouard 5150: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
5151: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5152: }
1.265 brouard 5153: if(s1!=0 && m!=0)
5154: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 5155: }
1.265 brouard 5156: } /* end loop s1 */
1.251 brouard 5157: posproptt=0.;
1.265 brouard 5158: for(s1=1; s1 <=nlstate; s1++){
5159: posproptt += pospropt[s1];
1.251 brouard 5160: }
5161: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 5162: fprintf(ficresphtm,"</tr>\n");
5163: if((cptcoveff==0 && nj==1)|| nj==2 ) {
5164: if(iage <= iagemax)
5165: fprintf(ficresp,"\n");
1.240 brouard 5166: }
1.251 brouard 5167: if(first==1)
5168: printf("Others in log...\n");
5169: fprintf(ficlog,"\n");
5170: } /* end loop age iage */
1.265 brouard 5171:
1.251 brouard 5172: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 5173: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5174: if(posproptt < 1.e-5){
1.265 brouard 5175: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 5176: }else{
1.265 brouard 5177: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 5178: }
1.226 brouard 5179: }
1.251 brouard 5180: fprintf(ficresphtm,"</tr>\n");
5181: fprintf(ficresphtm,"</table>\n");
5182: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 5183: if(posproptt < 1.e-5){
1.251 brouard 5184: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
5185: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 5186: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
5187: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 5188: invalidvarcomb[j1]=1;
1.226 brouard 5189: }else{
1.251 brouard 5190: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced.</p>",j1);
5191: invalidvarcomb[j1]=0;
1.226 brouard 5192: }
1.251 brouard 5193: fprintf(ficresphtmfr,"</table>\n");
5194: fprintf(ficlog,"\n");
5195: if(j!=0){
5196: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 5197: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5198: for(k=1; k <=(nlstate+ndeath); k++){
5199: if (k != i) {
1.265 brouard 5200: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 5201: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 5202: if(j1==1){ /* All dummy covariates to zero */
5203: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
5204: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 5205: printf("%d%d ",i,k);
5206: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5207: 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]));
5208: 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]));
5209: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 5210: }
1.253 brouard 5211: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
5212: for(iage=iagemin; iage <= iagemax+3; iage++){
5213: x[iage]= (double)iage;
5214: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 5215: /* 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 5216: }
1.268 brouard 5217: /* Some are not finite, but linreg will ignore these ages */
5218: no=0;
1.253 brouard 5219: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 5220: pstart[s1]=b;
5221: pstart[s1-1]=a;
1.252 brouard 5222: }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 */
5223: 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]);
5224: 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 5225: 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 5226: printf("%d%d ",i,k);
5227: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5228: 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 5229: }else{ /* Other cases, like quantitative fixed or varying covariates */
5230: ;
5231: }
5232: /* printf("%12.7f )", param[i][jj][k]); */
5233: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5234: s1++;
1.251 brouard 5235: } /* end jj */
5236: } /* end k!= i */
5237: } /* end k */
1.265 brouard 5238: } /* end i, s1 */
1.251 brouard 5239: } /* end j !=0 */
5240: } /* end selected combination of covariate j1 */
5241: if(j==0){ /* We can estimate starting values from the occurences in each case */
5242: printf("#Freqsummary: Starting values for the constants:\n");
5243: fprintf(ficlog,"\n");
1.265 brouard 5244: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5245: for(k=1; k <=(nlstate+ndeath); k++){
5246: if (k != i) {
5247: printf("%d%d ",i,k);
5248: fprintf(ficlog,"%d%d ",i,k);
5249: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 5250: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 5251: if(jj==1){ /* Age has to be done */
1.265 brouard 5252: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
5253: 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]));
5254: 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 5255: }
5256: /* printf("%12.7f )", param[i][jj][k]); */
5257: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5258: s1++;
1.250 brouard 5259: }
1.251 brouard 5260: printf("\n");
5261: fprintf(ficlog,"\n");
1.250 brouard 5262: }
5263: }
1.284 brouard 5264: } /* end of state i */
1.251 brouard 5265: printf("#Freqsummary\n");
5266: fprintf(ficlog,"\n");
1.265 brouard 5267: for(s1=-1; s1 <=nlstate+ndeath; s1++){
5268: for(s2=-1; s2 <=nlstate+ndeath; s2++){
5269: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
5270: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
5271: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
5272: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
5273: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
5274: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 5275: /* } */
5276: }
1.265 brouard 5277: } /* end loop s1 */
1.251 brouard 5278:
5279: printf("\n");
5280: fprintf(ficlog,"\n");
5281: } /* end j=0 */
1.249 brouard 5282: } /* end j */
1.252 brouard 5283:
1.253 brouard 5284: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 5285: for(i=1, jk=1; i <=nlstate; i++){
5286: for(j=1; j <=nlstate+ndeath; j++){
5287: if(j!=i){
5288: /*ca[0]= k+'a'-1;ca[1]='\0';*/
5289: printf("%1d%1d",i,j);
5290: fprintf(ficparo,"%1d%1d",i,j);
5291: for(k=1; k<=ncovmodel;k++){
5292: /* printf(" %lf",param[i][j][k]); */
5293: /* fprintf(ficparo," %lf",param[i][j][k]); */
5294: p[jk]=pstart[jk];
5295: printf(" %f ",pstart[jk]);
5296: fprintf(ficparo," %f ",pstart[jk]);
5297: jk++;
5298: }
5299: printf("\n");
5300: fprintf(ficparo,"\n");
5301: }
5302: }
5303: }
5304: } /* end mle=-2 */
1.226 brouard 5305: dateintmean=dateintsum/k2cpt;
1.296 brouard 5306: date2dmy(dateintmean,&jintmean,&mintmean,&aintmean);
1.240 brouard 5307:
1.226 brouard 5308: fclose(ficresp);
5309: fclose(ficresphtm);
5310: fclose(ficresphtmfr);
1.283 brouard 5311: free_vector(idq,1,nqfveff);
1.226 brouard 5312: free_vector(meanq,1,nqfveff);
1.284 brouard 5313: free_vector(stdq,1,nqfveff);
1.226 brouard 5314: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 5315: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
5316: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 5317: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 5318: free_vector(pospropt,1,nlstate);
5319: free_vector(posprop,1,nlstate);
1.251 brouard 5320: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 5321: free_vector(pp,1,nlstate);
5322: /* End of freqsummary */
5323: }
1.126 brouard 5324:
1.268 brouard 5325: /* Simple linear regression */
5326: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
5327:
5328: /* y=a+bx regression */
5329: double sumx = 0.0; /* sum of x */
5330: double sumx2 = 0.0; /* sum of x**2 */
5331: double sumxy = 0.0; /* sum of x * y */
5332: double sumy = 0.0; /* sum of y */
5333: double sumy2 = 0.0; /* sum of y**2 */
5334: double sume2 = 0.0; /* sum of square or residuals */
5335: double yhat;
5336:
5337: double denom=0;
5338: int i;
5339: int ne=*no;
5340:
5341: for ( i=ifi, ne=0;i<=ila;i++) {
5342: if(!isfinite(x[i]) || !isfinite(y[i])){
5343: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5344: continue;
5345: }
5346: ne=ne+1;
5347: sumx += x[i];
5348: sumx2 += x[i]*x[i];
5349: sumxy += x[i] * y[i];
5350: sumy += y[i];
5351: sumy2 += y[i]*y[i];
5352: denom = (ne * sumx2 - sumx*sumx);
5353: /* 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); */
5354: }
5355:
5356: denom = (ne * sumx2 - sumx*sumx);
5357: if (denom == 0) {
5358: // vertical, slope m is infinity
5359: *b = INFINITY;
5360: *a = 0;
5361: if (r) *r = 0;
5362: return 1;
5363: }
5364:
5365: *b = (ne * sumxy - sumx * sumy) / denom;
5366: *a = (sumy * sumx2 - sumx * sumxy) / denom;
5367: if (r!=NULL) {
5368: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
5369: sqrt((sumx2 - sumx*sumx/ne) *
5370: (sumy2 - sumy*sumy/ne));
5371: }
5372: *no=ne;
5373: for ( i=ifi, ne=0;i<=ila;i++) {
5374: if(!isfinite(x[i]) || !isfinite(y[i])){
5375: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5376: continue;
5377: }
5378: ne=ne+1;
5379: yhat = y[i] - *a -*b* x[i];
5380: sume2 += yhat * yhat ;
5381:
5382: denom = (ne * sumx2 - sumx*sumx);
5383: /* 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); */
5384: }
5385: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
5386: *sa= *sb * sqrt(sumx2/ne);
5387:
5388: return 0;
5389: }
5390:
1.126 brouard 5391: /************ Prevalence ********************/
1.227 brouard 5392: 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)
5393: {
5394: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
5395: in each health status at the date of interview (if between dateprev1 and dateprev2).
5396: We still use firstpass and lastpass as another selection.
5397: */
1.126 brouard 5398:
1.227 brouard 5399: int i, m, jk, j1, bool, z1,j, iv;
5400: int mi; /* Effective wave */
5401: int iage;
5402: double agebegin, ageend;
5403:
5404: double **prop;
5405: double posprop;
5406: double y2; /* in fractional years */
5407: int iagemin, iagemax;
5408: int first; /** to stop verbosity which is redirected to log file */
5409:
5410: iagemin= (int) agemin;
5411: iagemax= (int) agemax;
5412: /*pp=vector(1,nlstate);*/
1.251 brouard 5413: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5414: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
5415: j1=0;
1.222 brouard 5416:
1.227 brouard 5417: /*j=cptcoveff;*/
5418: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 5419:
1.288 brouard 5420: first=0;
1.227 brouard 5421: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of covariate */
5422: for (i=1; i<=nlstate; i++)
1.251 brouard 5423: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 5424: prop[i][iage]=0.0;
5425: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
5426: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
5427: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
5428:
5429: for (i=1; i<=imx; i++) { /* Each individual */
5430: bool=1;
5431: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
5432: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
5433: m=mw[mi][i];
5434: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
5435: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
5436: for (z1=1; z1<=cptcoveff; z1++){
5437: if( Fixed[Tmodelind[z1]]==1){
5438: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
5439: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality */
5440: bool=0;
5441: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
5442: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
5443: bool=0;
5444: }
5445: }
5446: if(bool==1){ /* Otherwise we skip that wave/person */
5447: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
5448: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
5449: if(m >=firstpass && m <=lastpass){
5450: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
5451: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
5452: if(agev[m][i]==0) agev[m][i]=iagemax+1;
5453: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 5454: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 5455: 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);
5456: exit(1);
5457: }
5458: if (s[m][i]>0 && s[m][i]<=nlstate) {
5459: /*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]]);*/
5460: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
5461: prop[s[m][i]][iagemax+3] += weight[i];
5462: } /* end valid statuses */
5463: } /* end selection of dates */
5464: } /* end selection of waves */
5465: } /* end bool */
5466: } /* end wave */
5467: } /* end individual */
5468: for(i=iagemin; i <= iagemax+3; i++){
5469: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
5470: posprop += prop[jk][i];
5471: }
5472:
5473: for(jk=1; jk <=nlstate ; jk++){
5474: if( i <= iagemax){
5475: if(posprop>=1.e-5){
5476: probs[i][jk][j1]= prop[jk][i]/posprop;
5477: } else{
1.288 brouard 5478: if(!first){
5479: first=1;
1.266 brouard 5480: 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]);
5481: }else{
1.288 brouard 5482: 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 5483: }
5484: }
5485: }
5486: }/* end jk */
5487: }/* end i */
1.222 brouard 5488: /*} *//* end i1 */
1.227 brouard 5489: } /* end j1 */
1.222 brouard 5490:
1.227 brouard 5491: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
5492: /*free_vector(pp,1,nlstate);*/
1.251 brouard 5493: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5494: } /* End of prevalence */
1.126 brouard 5495:
5496: /************* Waves Concatenation ***************/
5497:
5498: 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)
5499: {
1.298 brouard 5500: /* 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 5501: Death is a valid wave (if date is known).
5502: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
5503: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
1.298 brouard 5504: and mw[mi+1][i]. dh depends on stepm. s[m][i] exists for any wave from firstpass to lastpass
1.227 brouard 5505: */
1.126 brouard 5506:
1.224 brouard 5507: int i=0, mi=0, m=0, mli=0;
1.126 brouard 5508: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
5509: double sum=0., jmean=0.;*/
1.224 brouard 5510: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 5511: int j, k=0,jk, ju, jl;
5512: double sum=0.;
5513: first=0;
1.214 brouard 5514: firstwo=0;
1.217 brouard 5515: firsthree=0;
1.218 brouard 5516: firstfour=0;
1.164 brouard 5517: jmin=100000;
1.126 brouard 5518: jmax=-1;
5519: jmean=0.;
1.224 brouard 5520:
5521: /* Treating live states */
1.214 brouard 5522: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 5523: mi=0; /* First valid wave */
1.227 brouard 5524: mli=0; /* Last valid wave */
1.309 brouard 5525: m=firstpass; /* Loop on waves */
5526: while(s[m][i] <= nlstate){ /* a live state or unknown state */
1.227 brouard 5527: 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 */
5528: mli=m-1;/* mw[++mi][i]=m-1; */
5529: }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 */
1.309 brouard 5530: mw[++mi][i]=m; /* Valid wave: incrementing mi and updating mi; mw[mi] is the wave number of mi_th valid transition */
1.227 brouard 5531: mli=m;
1.224 brouard 5532: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
5533: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 5534: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 5535: }
1.309 brouard 5536: else{ /* m = lastpass, eventual special issue with warning */
1.224 brouard 5537: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 5538: break;
1.224 brouard 5539: #else
1.317 brouard 5540: if(s[m][i]==-1 && (int) andc[i] == 9999 && (int)anint[m][i] != 9999){ /* no death date and known date of interview, case -2 (vital status unknown is warned later */
1.227 brouard 5541: if(firsthree == 0){
1.302 brouard 5542: 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 5543: firsthree=1;
1.317 brouard 5544: }else if(firsthree >=1 && firsthree < 10){
5545: 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);
5546: firsthree++;
5547: }else if(firsthree == 10){
5548: printf("Information, too many Information flags: no more reported to log either\n");
5549: fprintf(ficlog,"Information, too many Information flags: no more reported to log either\n");
5550: firsthree++;
5551: }else{
5552: firsthree++;
1.227 brouard 5553: }
1.309 brouard 5554: mw[++mi][i]=m; /* Valid transition with unknown status */
1.227 brouard 5555: mli=m;
5556: }
5557: if(s[m][i]==-2){ /* Vital status is really unknown */
5558: nbwarn++;
1.309 brouard 5559: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified?not a transition */
1.227 brouard 5560: 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);
5561: 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);
5562: }
5563: break;
5564: }
5565: break;
1.224 brouard 5566: #endif
1.227 brouard 5567: }/* End m >= lastpass */
1.126 brouard 5568: }/* end while */
1.224 brouard 5569:
1.227 brouard 5570: /* 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 5571: /* After last pass */
1.224 brouard 5572: /* Treating death states */
1.214 brouard 5573: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 5574: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
5575: /* } */
1.126 brouard 5576: mi++; /* Death is another wave */
5577: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 5578: /* Only death is a correct wave */
1.126 brouard 5579: mw[mi][i]=m;
1.257 brouard 5580: } /* else not in a death state */
1.224 brouard 5581: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 5582: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 5583: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.309 brouard 5584: if((andc[i]+moisdc[i]/12.) <=(anint[m][i]+mint[m][i]/12.)){ /* month of death occured before last wave month and status should have been death instead of -1 */
1.227 brouard 5585: nbwarn++;
5586: if(firstfiv==0){
1.309 brouard 5587: printf("Warning! Death for individual %ld line=%d occurred at %d/%d before last wave %d, interviewed on %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 );
1.227 brouard 5588: firstfiv=1;
5589: }else{
1.309 brouard 5590: fprintf(ficlog,"Warning! Death for individual %ld line=%d occurred at %d/%d before last wave %d, interviewed on %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 );
1.227 brouard 5591: }
1.309 brouard 5592: s[m][i]=nlstate+1; /* Fixing the status as death. Be careful if multiple death states */
5593: }else{ /* Month of Death occured afer last wave month, potential bias */
1.227 brouard 5594: nberr++;
5595: if(firstwo==0){
1.309 brouard 5596: printf("Error! Death for individual %ld line=%d occurred at %d/%d after last wave %d interviewed at %d/%d with status %d. Potential bias if other individuals are still alive on this date but ignored. This case (%d)/wave (%d) is skipped, no contribution to likelihood. Please add a new fictitious wave at the date of last vital status scan, with a dead status. 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], s[m][i], i,m );
1.227 brouard 5597: firstwo=1;
5598: }
1.309 brouard 5599: fprintf(ficlog,"Error! Death for individual %ld line=%d occurred at %d/%d after last wave %d interviewed at %d/%d with status %d. Potential bias if other individuals are still alive on this date but ignored. This case (%d)/wave (%d) is skipped, no contribution to likelihood. Please add a new fictitious wave at the date of last vital status scan, with a dead status. See documentation\n\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], s[m][i], i,m );
1.227 brouard 5600: }
1.257 brouard 5601: }else{ /* if date of interview is unknown */
1.227 brouard 5602: /* death is known but not confirmed by death status at any wave */
5603: if(firstfour==0){
1.309 brouard 5604: 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 with status %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], s[m][i], i,m );
1.227 brouard 5605: firstfour=1;
5606: }
1.309 brouard 5607: 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 with status %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], s[m][i], i,m );
1.214 brouard 5608: }
1.224 brouard 5609: } /* end if date of death is known */
5610: #endif
1.309 brouard 5611: wav[i]=mi; /* mi should be the last effective wave (or mli), */
5612: /* wav[i]=mw[mi][i]; */
1.126 brouard 5613: if(mi==0){
5614: nbwarn++;
5615: if(first==0){
1.227 brouard 5616: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
5617: first=1;
1.126 brouard 5618: }
5619: if(first==1){
1.227 brouard 5620: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 5621: }
5622: } /* end mi==0 */
5623: } /* End individuals */
1.214 brouard 5624: /* wav and mw are no more changed */
1.223 brouard 5625:
1.317 brouard 5626: printf("Information, you have to check %d informations which haven't been logged!\n",firsthree);
5627: fprintf(ficlog,"Information, you have to check %d informations which haven't been logged!\n",firsthree);
5628:
5629:
1.126 brouard 5630: for(i=1; i<=imx; i++){
5631: for(mi=1; mi<wav[i];mi++){
5632: if (stepm <=0)
1.227 brouard 5633: dh[mi][i]=1;
1.126 brouard 5634: else{
1.260 brouard 5635: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 5636: if (agedc[i] < 2*AGESUP) {
5637: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
5638: if(j==0) j=1; /* Survives at least one month after exam */
5639: else if(j<0){
5640: nberr++;
5641: 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]);
5642: j=1; /* Temporary Dangerous patch */
5643: 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);
5644: 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]);
5645: 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);
5646: }
5647: k=k+1;
5648: if (j >= jmax){
5649: jmax=j;
5650: ijmax=i;
5651: }
5652: if (j <= jmin){
5653: jmin=j;
5654: ijmin=i;
5655: }
5656: sum=sum+j;
5657: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
5658: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
5659: }
5660: }
5661: else{
5662: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 5663: /* 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 5664:
1.227 brouard 5665: k=k+1;
5666: if (j >= jmax) {
5667: jmax=j;
5668: ijmax=i;
5669: }
5670: else if (j <= jmin){
5671: jmin=j;
5672: ijmin=i;
5673: }
5674: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
5675: /*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]);*/
5676: if(j<0){
5677: nberr++;
5678: 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]);
5679: 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]);
5680: }
5681: sum=sum+j;
5682: }
5683: jk= j/stepm;
5684: jl= j -jk*stepm;
5685: ju= j -(jk+1)*stepm;
5686: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
5687: if(jl==0){
5688: dh[mi][i]=jk;
5689: bh[mi][i]=0;
5690: }else{ /* We want a negative bias in order to only have interpolation ie
5691: * to avoid the price of an extra matrix product in likelihood */
5692: dh[mi][i]=jk+1;
5693: bh[mi][i]=ju;
5694: }
5695: }else{
5696: if(jl <= -ju){
5697: dh[mi][i]=jk;
5698: bh[mi][i]=jl; /* bias is positive if real duration
5699: * is higher than the multiple of stepm and negative otherwise.
5700: */
5701: }
5702: else{
5703: dh[mi][i]=jk+1;
5704: bh[mi][i]=ju;
5705: }
5706: if(dh[mi][i]==0){
5707: dh[mi][i]=1; /* At least one step */
5708: bh[mi][i]=ju; /* At least one step */
5709: /* 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);*/
5710: }
5711: } /* end if mle */
1.126 brouard 5712: }
5713: } /* end wave */
5714: }
5715: jmean=sum/k;
5716: 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 5717: 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 5718: }
1.126 brouard 5719:
5720: /*********** Tricode ****************************/
1.220 brouard 5721: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 5722: {
5723: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
5724: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
5725: * Boring subroutine which should only output nbcode[Tvar[j]][k]
5726: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
5727: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
5728: */
1.130 brouard 5729:
1.242 brouard 5730: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
5731: int modmaxcovj=0; /* Modality max of covariates j */
5732: int cptcode=0; /* Modality max of covariates j */
5733: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 5734:
5735:
1.242 brouard 5736: /* cptcoveff=0; */
5737: /* *cptcov=0; */
1.126 brouard 5738:
1.242 brouard 5739: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.285 brouard 5740: for (k=1; k <= maxncov; k++)
5741: for(j=1; j<=2; j++)
5742: nbcode[k][j]=0; /* Valgrind */
1.126 brouard 5743:
1.242 brouard 5744: /* Loop on covariates without age and products and no quantitative variable */
5745: for (k=1; k<=cptcovt; k++) { /* From model V1 + V2*age + V3 + V3*V4 keeps V1 + V3 = 2 only */
5746: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
5747: if(Dummy[k]==0 && Typevar[k] !=1){ /* Dummy covariate and not age product */
5748: switch(Fixed[k]) {
5749: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
1.311 brouard 5750: modmaxcovj=0;
5751: modmincovj=0;
1.242 brouard 5752: 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*/
5753: ij=(int)(covar[Tvar[k]][i]);
5754: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
5755: * If product of Vn*Vm, still boolean *:
5756: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
5757: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
5758: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
5759: modality of the nth covariate of individual i. */
5760: if (ij > modmaxcovj)
5761: modmaxcovj=ij;
5762: else if (ij < modmincovj)
5763: modmincovj=ij;
1.287 brouard 5764: if (ij <0 || ij >1 ){
1.311 brouard 5765: printf("ERROR, IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
5766: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
5767: fflush(ficlog);
5768: exit(1);
1.287 brouard 5769: }
5770: if ((ij < -1) || (ij > NCOVMAX)){
1.242 brouard 5771: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
5772: exit(1);
5773: }else
5774: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
5775: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
5776: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
5777: /* getting the maximum value of the modality of the covariate
5778: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
5779: female ies 1, then modmaxcovj=1.
5780: */
5781: } /* end for loop on individuals i */
5782: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5783: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5784: cptcode=modmaxcovj;
5785: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
5786: /*for (i=0; i<=cptcode; i++) {*/
5787: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
5788: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5789: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5790: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
5791: if( j != -1){
5792: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
5793: covariate for which somebody answered excluding
5794: undefined. Usually 2: 0 and 1. */
5795: }
5796: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
5797: covariate for which somebody answered including
5798: undefined. Usually 3: -1, 0 and 1. */
5799: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
5800: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
5801: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 5802:
1.242 brouard 5803: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
5804: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
5805: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
5806: /* modmincovj=3; modmaxcovj = 7; */
5807: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
5808: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
5809: /* defining two dummy variables: variables V1_1 and V1_2.*/
5810: /* nbcode[Tvar[j]][ij]=k; */
5811: /* nbcode[Tvar[j]][1]=0; */
5812: /* nbcode[Tvar[j]][2]=1; */
5813: /* nbcode[Tvar[j]][3]=2; */
5814: /* To be continued (not working yet). */
5815: ij=0; /* ij is similar to i but can jump over null modalities */
1.287 brouard 5816:
5817: /* 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*/
5818: /* Skipping the case of missing values by reducing nbcode to 0 and 1 and not -1, 0, 1 */
5819: /* model=V1+V2+V3, if V2=-1, 0 or 1, then nbcode[2][1]=0 and nbcode[2][2]=1 instead of
5820: * nbcode[2][1]=-1, nbcode[2][2]=0 and nbcode[2][3]=1 */
5821: /*, could be restored in the future */
5822: 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 5823: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
5824: break;
5825: }
5826: ij++;
1.287 brouard 5827: 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 5828: cptcode = ij; /* New max modality for covar j */
5829: } /* end of loop on modality i=-1 to 1 or more */
5830: break;
5831: case 1: /* Testing on varying covariate, could be simple and
5832: * should look at waves or product of fixed *
5833: * varying. No time to test -1, assuming 0 and 1 only */
5834: ij=0;
5835: for(i=0; i<=1;i++){
5836: nbcode[Tvar[k]][++ij]=i;
5837: }
5838: break;
5839: default:
5840: break;
5841: } /* end switch */
5842: } /* end dummy test */
1.311 brouard 5843: if(Dummy[k]==1 && Typevar[k] !=1){ /* Dummy covariate and not age product */
5844: 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*/
5845: if(isnan(covar[Tvar[k]][i])){
5846: printf("ERROR, IMaCh doesn't treat fixed quantitative covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
5847: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
5848: fflush(ficlog);
5849: exit(1);
5850: }
5851: }
5852: }
1.287 brouard 5853: } /* 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 5854:
5855: for (k=-1; k< maxncov; k++) Ndum[k]=0;
5856: /* Look at fixed dummy (single or product) covariates to check empty modalities */
5857: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
5858: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
5859: 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 */
5860: 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 */
5861: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
5862: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
5863:
5864: ij=0;
5865: /* for (i=0; i<= maxncov-1; i++) { /\* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) *\/ */
5866: for (k=1; k<= cptcovt; k++) { /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
5867: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
5868: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
5869: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy and non empty in the model */
5870: /* If product not in single variable we don't print results */
5871: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
5872: ++ij;/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, */
5873: 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*/
5874: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
5875: 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 */
5876: if(Fixed[k]!=0)
5877: anyvaryingduminmodel=1;
5878: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
5879: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
5880: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
5881: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
5882: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
5883: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
5884: }
5885: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
5886: /* ij--; */
5887: /* cptcoveff=ij; /\*Number of total covariates*\/ */
5888: *cptcov=ij; /*Number of total real effective covariates: effective
5889: * because they can be excluded from the model and real
5890: * if in the model but excluded because missing values, but how to get k from ij?*/
5891: for(j=ij+1; j<= cptcovt; j++){
5892: Tvaraff[j]=0;
5893: Tmodelind[j]=0;
5894: }
5895: for(j=ntveff+1; j<= cptcovt; j++){
5896: TmodelInvind[j]=0;
5897: }
5898: /* To be sorted */
5899: ;
5900: }
1.126 brouard 5901:
1.145 brouard 5902:
1.126 brouard 5903: /*********** Health Expectancies ****************/
5904:
1.235 brouard 5905: 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 5906:
5907: {
5908: /* Health expectancies, no variances */
1.329 ! brouard 5909: /* cij is the combination in the list of combination of dummy covariates */
! 5910: /* strstart is a string of time at start of computing */
1.164 brouard 5911: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 5912: int nhstepma, nstepma; /* Decreasing with age */
5913: double age, agelim, hf;
5914: double ***p3mat;
5915: double eip;
5916:
1.238 brouard 5917: /* pstamp(ficreseij); */
1.126 brouard 5918: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
5919: fprintf(ficreseij,"# Age");
5920: for(i=1; i<=nlstate;i++){
5921: for(j=1; j<=nlstate;j++){
5922: fprintf(ficreseij," e%1d%1d ",i,j);
5923: }
5924: fprintf(ficreseij," e%1d. ",i);
5925: }
5926: fprintf(ficreseij,"\n");
5927:
5928:
5929: if(estepm < stepm){
5930: printf ("Problem %d lower than %d\n",estepm, stepm);
5931: }
5932: else hstepm=estepm;
5933: /* We compute the life expectancy from trapezoids spaced every estepm months
5934: * This is mainly to measure the difference between two models: for example
5935: * if stepm=24 months pijx are given only every 2 years and by summing them
5936: * we are calculating an estimate of the Life Expectancy assuming a linear
5937: * progression in between and thus overestimating or underestimating according
5938: * to the curvature of the survival function. If, for the same date, we
5939: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5940: * to compare the new estimate of Life expectancy with the same linear
5941: * hypothesis. A more precise result, taking into account a more precise
5942: * curvature will be obtained if estepm is as small as stepm. */
5943:
5944: /* For example we decided to compute the life expectancy with the smallest unit */
5945: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5946: nhstepm is the number of hstepm from age to agelim
5947: nstepm is the number of stepm from age to agelin.
1.270 brouard 5948: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 5949: and note for a fixed period like estepm months */
5950: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5951: survival function given by stepm (the optimization length). Unfortunately it
5952: means that if the survival funtion is printed only each two years of age and if
5953: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5954: results. So we changed our mind and took the option of the best precision.
5955: */
5956: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5957:
5958: agelim=AGESUP;
5959: /* If stepm=6 months */
5960: /* Computed by stepm unit matrices, product of hstepm matrices, stored
5961: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
5962:
5963: /* nhstepm age range expressed in number of stepm */
5964: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5965: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5966: /* if (stepm >= YEARM) hstepm=1;*/
5967: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5968: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5969:
5970: for (age=bage; age<=fage; age ++){
5971: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5972: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5973: /* if (stepm >= YEARM) hstepm=1;*/
5974: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
5975:
5976: /* If stepm=6 months */
5977: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5978: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5979:
1.235 brouard 5980: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 5981:
5982: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
5983:
5984: printf("%d|",(int)age);fflush(stdout);
5985: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5986:
5987: /* Computing expectancies */
5988: for(i=1; i<=nlstate;i++)
5989: for(j=1; j<=nlstate;j++)
5990: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5991: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
5992:
5993: /* 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]);*/
5994:
5995: }
5996:
5997: fprintf(ficreseij,"%3.0f",age );
5998: for(i=1; i<=nlstate;i++){
5999: eip=0;
6000: for(j=1; j<=nlstate;j++){
6001: eip +=eij[i][j][(int)age];
6002: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
6003: }
6004: fprintf(ficreseij,"%9.4f", eip );
6005: }
6006: fprintf(ficreseij,"\n");
6007:
6008: }
6009: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6010: printf("\n");
6011: fprintf(ficlog,"\n");
6012:
6013: }
6014:
1.235 brouard 6015: 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 6016:
6017: {
6018: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 6019: to initial status i, ei. .
1.126 brouard 6020: */
6021: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
6022: int nhstepma, nstepma; /* Decreasing with age */
6023: double age, agelim, hf;
6024: double ***p3matp, ***p3matm, ***varhe;
6025: double **dnewm,**doldm;
6026: double *xp, *xm;
6027: double **gp, **gm;
6028: double ***gradg, ***trgradg;
6029: int theta;
6030:
6031: double eip, vip;
6032:
6033: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
6034: xp=vector(1,npar);
6035: xm=vector(1,npar);
6036: dnewm=matrix(1,nlstate*nlstate,1,npar);
6037: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
6038:
6039: pstamp(ficresstdeij);
6040: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
6041: fprintf(ficresstdeij,"# Age");
6042: for(i=1; i<=nlstate;i++){
6043: for(j=1; j<=nlstate;j++)
6044: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
6045: fprintf(ficresstdeij," e%1d. ",i);
6046: }
6047: fprintf(ficresstdeij,"\n");
6048:
6049: pstamp(ficrescveij);
6050: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
6051: fprintf(ficrescveij,"# Age");
6052: for(i=1; i<=nlstate;i++)
6053: for(j=1; j<=nlstate;j++){
6054: cptj= (j-1)*nlstate+i;
6055: for(i2=1; i2<=nlstate;i2++)
6056: for(j2=1; j2<=nlstate;j2++){
6057: cptj2= (j2-1)*nlstate+i2;
6058: if(cptj2 <= cptj)
6059: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
6060: }
6061: }
6062: fprintf(ficrescveij,"\n");
6063:
6064: if(estepm < stepm){
6065: printf ("Problem %d lower than %d\n",estepm, stepm);
6066: }
6067: else hstepm=estepm;
6068: /* We compute the life expectancy from trapezoids spaced every estepm months
6069: * This is mainly to measure the difference between two models: for example
6070: * if stepm=24 months pijx are given only every 2 years and by summing them
6071: * we are calculating an estimate of the Life Expectancy assuming a linear
6072: * progression in between and thus overestimating or underestimating according
6073: * to the curvature of the survival function. If, for the same date, we
6074: * estimate the model with stepm=1 month, we can keep estepm to 24 months
6075: * to compare the new estimate of Life expectancy with the same linear
6076: * hypothesis. A more precise result, taking into account a more precise
6077: * curvature will be obtained if estepm is as small as stepm. */
6078:
6079: /* For example we decided to compute the life expectancy with the smallest unit */
6080: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6081: nhstepm is the number of hstepm from age to agelim
6082: nstepm is the number of stepm from age to agelin.
6083: Look at hpijx to understand the reason of that which relies in memory size
6084: and note for a fixed period like estepm months */
6085: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
6086: survival function given by stepm (the optimization length). Unfortunately it
6087: means that if the survival funtion is printed only each two years of age and if
6088: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6089: results. So we changed our mind and took the option of the best precision.
6090: */
6091: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6092:
6093: /* If stepm=6 months */
6094: /* nhstepm age range expressed in number of stepm */
6095: agelim=AGESUP;
6096: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
6097: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6098: /* if (stepm >= YEARM) hstepm=1;*/
6099: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6100:
6101: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6102: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6103: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
6104: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
6105: gp=matrix(0,nhstepm,1,nlstate*nlstate);
6106: gm=matrix(0,nhstepm,1,nlstate*nlstate);
6107:
6108: for (age=bage; age<=fage; age ++){
6109: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6110: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6111: /* if (stepm >= YEARM) hstepm=1;*/
6112: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 6113:
1.126 brouard 6114: /* If stepm=6 months */
6115: /* Computed by stepm unit matrices, product of hstepma matrices, stored
6116: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
6117:
6118: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 6119:
1.126 brouard 6120: /* Computing Variances of health expectancies */
6121: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
6122: decrease memory allocation */
6123: for(theta=1; theta <=npar; theta++){
6124: for(i=1; i<=npar; i++){
1.222 brouard 6125: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6126: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 6127: }
1.235 brouard 6128: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
6129: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 6130:
1.126 brouard 6131: for(j=1; j<= nlstate; j++){
1.222 brouard 6132: for(i=1; i<=nlstate; i++){
6133: for(h=0; h<=nhstepm-1; h++){
6134: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
6135: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
6136: }
6137: }
1.126 brouard 6138: }
1.218 brouard 6139:
1.126 brouard 6140: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 6141: for(h=0; h<=nhstepm-1; h++){
6142: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
6143: }
1.126 brouard 6144: }/* End theta */
6145:
6146:
6147: for(h=0; h<=nhstepm-1; h++)
6148: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 6149: for(theta=1; theta <=npar; theta++)
6150: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 6151:
1.218 brouard 6152:
1.222 brouard 6153: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 6154: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 6155: varhe[ij][ji][(int)age] =0.;
1.218 brouard 6156:
1.222 brouard 6157: printf("%d|",(int)age);fflush(stdout);
6158: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
6159: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 6160: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 6161: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
6162: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
6163: for(ij=1;ij<=nlstate*nlstate;ij++)
6164: for(ji=1;ji<=nlstate*nlstate;ji++)
6165: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 6166: }
6167: }
1.320 brouard 6168: /* if((int)age ==50){ */
6169: /* printf(" age=%d cij=%d nres=%d varhe[%d][%d]=%f ",(int)age, cij, nres, 1,2,varhe[1][2]); */
6170: /* } */
1.126 brouard 6171: /* Computing expectancies */
1.235 brouard 6172: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 6173: for(i=1; i<=nlstate;i++)
6174: for(j=1; j<=nlstate;j++)
1.222 brouard 6175: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
6176: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 6177:
1.222 brouard 6178: /* 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 6179:
1.222 brouard 6180: }
1.269 brouard 6181:
6182: /* Standard deviation of expectancies ij */
1.126 brouard 6183: fprintf(ficresstdeij,"%3.0f",age );
6184: for(i=1; i<=nlstate;i++){
6185: eip=0.;
6186: vip=0.;
6187: for(j=1; j<=nlstate;j++){
1.222 brouard 6188: eip += eij[i][j][(int)age];
6189: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
6190: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
6191: 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 6192: }
6193: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
6194: }
6195: fprintf(ficresstdeij,"\n");
1.218 brouard 6196:
1.269 brouard 6197: /* Variance of expectancies ij */
1.126 brouard 6198: fprintf(ficrescveij,"%3.0f",age );
6199: for(i=1; i<=nlstate;i++)
6200: for(j=1; j<=nlstate;j++){
1.222 brouard 6201: cptj= (j-1)*nlstate+i;
6202: for(i2=1; i2<=nlstate;i2++)
6203: for(j2=1; j2<=nlstate;j2++){
6204: cptj2= (j2-1)*nlstate+i2;
6205: if(cptj2 <= cptj)
6206: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
6207: }
1.126 brouard 6208: }
6209: fprintf(ficrescveij,"\n");
1.218 brouard 6210:
1.126 brouard 6211: }
6212: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
6213: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
6214: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
6215: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
6216: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6217: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6218: printf("\n");
6219: fprintf(ficlog,"\n");
1.218 brouard 6220:
1.126 brouard 6221: free_vector(xm,1,npar);
6222: free_vector(xp,1,npar);
6223: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
6224: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
6225: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
6226: }
1.218 brouard 6227:
1.126 brouard 6228: /************ Variance ******************/
1.235 brouard 6229: 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 6230: {
1.279 brouard 6231: /** Variance of health expectancies
6232: * double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);
6233: * double **newm;
6234: * int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)
6235: */
1.218 brouard 6236:
6237: /* int movingaverage(); */
6238: double **dnewm,**doldm;
6239: double **dnewmp,**doldmp;
6240: int i, j, nhstepm, hstepm, h, nstepm ;
1.288 brouard 6241: int first=0;
1.218 brouard 6242: int k;
6243: double *xp;
1.279 brouard 6244: double **gp, **gm; /**< for var eij */
6245: double ***gradg, ***trgradg; /**< for var eij */
6246: double **gradgp, **trgradgp; /**< for var p point j */
6247: double *gpp, *gmp; /**< for var p point j */
6248: double **varppt; /**< for var p point j nlstate to nlstate+ndeath */
1.218 brouard 6249: double ***p3mat;
6250: double age,agelim, hf;
6251: /* double ***mobaverage; */
6252: int theta;
6253: char digit[4];
6254: char digitp[25];
6255:
6256: char fileresprobmorprev[FILENAMELENGTH];
6257:
6258: if(popbased==1){
6259: if(mobilav!=0)
6260: strcpy(digitp,"-POPULBASED-MOBILAV_");
6261: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
6262: }
6263: else
6264: strcpy(digitp,"-STABLBASED_");
1.126 brouard 6265:
1.218 brouard 6266: /* if (mobilav!=0) { */
6267: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6268: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
6269: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
6270: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
6271: /* } */
6272: /* } */
6273:
6274: strcpy(fileresprobmorprev,"PRMORPREV-");
6275: sprintf(digit,"%-d",ij);
6276: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
6277: strcat(fileresprobmorprev,digit); /* Tvar to be done */
6278: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
6279: strcat(fileresprobmorprev,fileresu);
6280: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
6281: printf("Problem with resultfile: %s\n", fileresprobmorprev);
6282: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
6283: }
6284: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
6285: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
6286: pstamp(ficresprobmorprev);
6287: 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 6288: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
6289: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
6290: fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
6291: }
6292: for(j=1;j<=cptcoveff;j++)
6293: fprintf(ficresprobmorprev,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,j)]);
6294: fprintf(ficresprobmorprev,"\n");
6295:
1.218 brouard 6296: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
6297: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6298: fprintf(ficresprobmorprev," p.%-d SE",j);
6299: for(i=1; i<=nlstate;i++)
6300: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
6301: }
6302: fprintf(ficresprobmorprev,"\n");
6303:
6304: fprintf(ficgp,"\n# Routine varevsij");
6305: fprintf(ficgp,"\nunset title \n");
6306: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
6307: 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");
6308: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
1.279 brouard 6309:
1.218 brouard 6310: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6311: pstamp(ficresvij);
6312: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
6313: if(popbased==1)
6314: 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);
6315: else
6316: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
6317: fprintf(ficresvij,"# Age");
6318: for(i=1; i<=nlstate;i++)
6319: for(j=1; j<=nlstate;j++)
6320: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
6321: fprintf(ficresvij,"\n");
6322:
6323: xp=vector(1,npar);
6324: dnewm=matrix(1,nlstate,1,npar);
6325: doldm=matrix(1,nlstate,1,nlstate);
6326: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
6327: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6328:
6329: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
6330: gpp=vector(nlstate+1,nlstate+ndeath);
6331: gmp=vector(nlstate+1,nlstate+ndeath);
6332: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 6333:
1.218 brouard 6334: if(estepm < stepm){
6335: printf ("Problem %d lower than %d\n",estepm, stepm);
6336: }
6337: else hstepm=estepm;
6338: /* For example we decided to compute the life expectancy with the smallest unit */
6339: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6340: nhstepm is the number of hstepm from age to agelim
6341: nstepm is the number of stepm from age to agelim.
6342: Look at function hpijx to understand why because of memory size limitations,
6343: we decided (b) to get a life expectancy respecting the most precise curvature of the
6344: survival function given by stepm (the optimization length). Unfortunately it
6345: means that if the survival funtion is printed every two years of age and if
6346: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6347: results. So we changed our mind and took the option of the best precision.
6348: */
6349: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6350: agelim = AGESUP;
6351: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6352: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6353: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6354: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6355: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
6356: gp=matrix(0,nhstepm,1,nlstate);
6357: gm=matrix(0,nhstepm,1,nlstate);
6358:
6359:
6360: for(theta=1; theta <=npar; theta++){
6361: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
6362: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6363: }
1.279 brouard 6364: /**< Computes the prevalence limit with parameter theta shifted of delta up to ftolpl precision and
6365: * returns into prlim .
1.288 brouard 6366: */
1.242 brouard 6367: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.279 brouard 6368:
6369: /* If popbased = 1 we use crossection prevalences. Previous step is useless but prlim is created */
1.218 brouard 6370: if (popbased==1) {
6371: if(mobilav ==0){
6372: for(i=1; i<=nlstate;i++)
6373: prlim[i][i]=probs[(int)age][i][ij];
6374: }else{ /* mobilav */
6375: for(i=1; i<=nlstate;i++)
6376: prlim[i][i]=mobaverage[(int)age][i][ij];
6377: }
6378: }
1.295 brouard 6379: /**< Computes the shifted transition matrix \f$ {}{h}_p^{ij}x\f$ at horizon h.
1.279 brouard 6380: */
6381: 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 6382: /**< 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 6383: * at horizon h in state j including mortality.
6384: */
1.218 brouard 6385: for(j=1; j<= nlstate; j++){
6386: for(h=0; h<=nhstepm; h++){
6387: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
6388: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
6389: }
6390: }
1.279 brouard 6391: /* Next for computing shifted+ probability of death (h=1 means
1.218 brouard 6392: computed over hstepm matrices product = hstepm*stepm months)
1.279 brouard 6393: as a weighted average of prlim(i) * p(i,j) p.3=w1*p13 + w2*p23 .
1.218 brouard 6394: */
6395: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6396: for(i=1,gpp[j]=0.; i<= nlstate; i++)
6397: gpp[j] += prlim[i][i]*p3mat[i][j][1];
1.279 brouard 6398: }
6399:
6400: /* Again with minus shift */
1.218 brouard 6401:
6402: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
6403: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 6404:
1.242 brouard 6405: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 6406:
6407: if (popbased==1) {
6408: if(mobilav ==0){
6409: for(i=1; i<=nlstate;i++)
6410: prlim[i][i]=probs[(int)age][i][ij];
6411: }else{ /* mobilav */
6412: for(i=1; i<=nlstate;i++)
6413: prlim[i][i]=mobaverage[(int)age][i][ij];
6414: }
6415: }
6416:
1.235 brouard 6417: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 6418:
6419: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
6420: for(h=0; h<=nhstepm; h++){
6421: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
6422: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
6423: }
6424: }
6425: /* This for computing probability of death (h=1 means
6426: computed over hstepm matrices product = hstepm*stepm months)
6427: as a weighted average of prlim.
6428: */
6429: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6430: for(i=1,gmp[j]=0.; i<= nlstate; i++)
6431: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6432: }
1.279 brouard 6433: /* end shifting computations */
6434:
6435: /**< Computing gradient matrix at horizon h
6436: */
1.218 brouard 6437: for(j=1; j<= nlstate; j++) /* vareij */
6438: for(h=0; h<=nhstepm; h++){
6439: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
6440: }
1.279 brouard 6441: /**< Gradient of overall mortality p.3 (or p.j)
6442: */
6443: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu mortality from j */
1.218 brouard 6444: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
6445: }
6446:
6447: } /* End theta */
1.279 brouard 6448:
6449: /* We got the gradient matrix for each theta and state j */
1.218 brouard 6450: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
6451:
6452: for(h=0; h<=nhstepm; h++) /* veij */
6453: for(j=1; j<=nlstate;j++)
6454: for(theta=1; theta <=npar; theta++)
6455: trgradg[h][j][theta]=gradg[h][theta][j];
6456:
6457: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
6458: for(theta=1; theta <=npar; theta++)
6459: trgradgp[j][theta]=gradgp[theta][j];
1.279 brouard 6460: /**< as well as its transposed matrix
6461: */
1.218 brouard 6462:
6463: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6464: for(i=1;i<=nlstate;i++)
6465: for(j=1;j<=nlstate;j++)
6466: vareij[i][j][(int)age] =0.;
1.279 brouard 6467:
6468: /* Computing trgradg by matcov by gradg at age and summing over h
6469: * and k (nhstepm) formula 15 of article
6470: * Lievre-Brouard-Heathcote
6471: */
6472:
1.218 brouard 6473: for(h=0;h<=nhstepm;h++){
6474: for(k=0;k<=nhstepm;k++){
6475: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
6476: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
6477: for(i=1;i<=nlstate;i++)
6478: for(j=1;j<=nlstate;j++)
6479: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
6480: }
6481: }
6482:
1.279 brouard 6483: /* pptj is p.3 or p.j = trgradgp by cov by gradgp, variance of
6484: * p.j overall mortality formula 49 but computed directly because
6485: * we compute the grad (wix pijx) instead of grad (pijx),even if
6486: * wix is independent of theta.
6487: */
1.218 brouard 6488: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
6489: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
6490: for(j=nlstate+1;j<=nlstate+ndeath;j++)
6491: for(i=nlstate+1;i<=nlstate+ndeath;i++)
6492: varppt[j][i]=doldmp[j][i];
6493: /* end ppptj */
6494: /* x centered again */
6495:
1.242 brouard 6496: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 6497:
6498: if (popbased==1) {
6499: if(mobilav ==0){
6500: for(i=1; i<=nlstate;i++)
6501: prlim[i][i]=probs[(int)age][i][ij];
6502: }else{ /* mobilav */
6503: for(i=1; i<=nlstate;i++)
6504: prlim[i][i]=mobaverage[(int)age][i][ij];
6505: }
6506: }
6507:
6508: /* This for computing probability of death (h=1 means
6509: computed over hstepm (estepm) matrices product = hstepm*stepm months)
6510: as a weighted average of prlim.
6511: */
1.235 brouard 6512: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 6513: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6514: for(i=1,gmp[j]=0.;i<= nlstate; i++)
6515: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6516: }
6517: /* end probability of death */
6518:
6519: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
6520: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6521: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
6522: for(i=1; i<=nlstate;i++){
6523: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
6524: }
6525: }
6526: fprintf(ficresprobmorprev,"\n");
6527:
6528: fprintf(ficresvij,"%.0f ",age );
6529: for(i=1; i<=nlstate;i++)
6530: for(j=1; j<=nlstate;j++){
6531: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
6532: }
6533: fprintf(ficresvij,"\n");
6534: free_matrix(gp,0,nhstepm,1,nlstate);
6535: free_matrix(gm,0,nhstepm,1,nlstate);
6536: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
6537: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
6538: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6539: } /* End age */
6540: free_vector(gpp,nlstate+1,nlstate+ndeath);
6541: free_vector(gmp,nlstate+1,nlstate+ndeath);
6542: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
6543: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
6544: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
6545: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
6546: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
6547: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
6548: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
6549: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
6550: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
6551: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
6552: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
6553: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
6554: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
6555: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
6556: 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);
6557: /* 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 6558: */
1.218 brouard 6559: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
6560: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 6561:
1.218 brouard 6562: free_vector(xp,1,npar);
6563: free_matrix(doldm,1,nlstate,1,nlstate);
6564: free_matrix(dnewm,1,nlstate,1,npar);
6565: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6566: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
6567: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6568: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6569: fclose(ficresprobmorprev);
6570: fflush(ficgp);
6571: fflush(fichtm);
6572: } /* end varevsij */
1.126 brouard 6573:
6574: /************ Variance of prevlim ******************/
1.269 brouard 6575: 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 6576: {
1.205 brouard 6577: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 6578: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 6579:
1.268 brouard 6580: double **dnewmpar,**doldm;
1.126 brouard 6581: int i, j, nhstepm, hstepm;
6582: double *xp;
6583: double *gp, *gm;
6584: double **gradg, **trgradg;
1.208 brouard 6585: double **mgm, **mgp;
1.126 brouard 6586: double age,agelim;
6587: int theta;
6588:
6589: pstamp(ficresvpl);
1.288 brouard 6590: fprintf(ficresvpl,"# Standard deviation of period (forward stable) prevalences \n");
1.241 brouard 6591: fprintf(ficresvpl,"# Age ");
6592: if(nresult >=1)
6593: fprintf(ficresvpl," Result# ");
1.126 brouard 6594: for(i=1; i<=nlstate;i++)
6595: fprintf(ficresvpl," %1d-%1d",i,i);
6596: fprintf(ficresvpl,"\n");
6597:
6598: xp=vector(1,npar);
1.268 brouard 6599: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 6600: doldm=matrix(1,nlstate,1,nlstate);
6601:
6602: hstepm=1*YEARM; /* Every year of age */
6603: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6604: agelim = AGESUP;
6605: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6606: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6607: if (stepm >= YEARM) hstepm=1;
6608: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6609: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 6610: mgp=matrix(1,npar,1,nlstate);
6611: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 6612: gp=vector(1,nlstate);
6613: gm=vector(1,nlstate);
6614:
6615: for(theta=1; theta <=npar; theta++){
6616: for(i=1; i<=npar; i++){ /* Computes gradient */
6617: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6618: }
1.288 brouard 6619: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
6620: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
6621: /* else */
6622: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6623: for(i=1;i<=nlstate;i++){
1.126 brouard 6624: gp[i] = prlim[i][i];
1.208 brouard 6625: mgp[theta][i] = prlim[i][i];
6626: }
1.126 brouard 6627: for(i=1; i<=npar; i++) /* Computes gradient */
6628: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 6629: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
6630: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
6631: /* else */
6632: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6633: for(i=1;i<=nlstate;i++){
1.126 brouard 6634: gm[i] = prlim[i][i];
1.208 brouard 6635: mgm[theta][i] = prlim[i][i];
6636: }
1.126 brouard 6637: for(i=1;i<=nlstate;i++)
6638: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 6639: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 6640: } /* End theta */
6641:
6642: trgradg =matrix(1,nlstate,1,npar);
6643:
6644: for(j=1; j<=nlstate;j++)
6645: for(theta=1; theta <=npar; theta++)
6646: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 6647: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6648: /* printf("\nmgm mgp %d ",(int)age); */
6649: /* for(j=1; j<=nlstate;j++){ */
6650: /* printf(" %d ",j); */
6651: /* for(theta=1; theta <=npar; theta++) */
6652: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6653: /* printf("\n "); */
6654: /* } */
6655: /* } */
6656: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6657: /* printf("\n gradg %d ",(int)age); */
6658: /* for(j=1; j<=nlstate;j++){ */
6659: /* printf("%d ",j); */
6660: /* for(theta=1; theta <=npar; theta++) */
6661: /* printf("%d %lf ",theta,gradg[theta][j]); */
6662: /* printf("\n "); */
6663: /* } */
6664: /* } */
1.126 brouard 6665:
6666: for(i=1;i<=nlstate;i++)
6667: varpl[i][(int)age] =0.;
1.209 brouard 6668: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 brouard 6669: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6670: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6671: }else{
1.268 brouard 6672: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6673: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6674: }
1.126 brouard 6675: for(i=1;i<=nlstate;i++)
6676: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6677:
6678: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 6679: if(nresult >=1)
6680: fprintf(ficresvpl,"%d ",nres );
1.288 brouard 6681: for(i=1; i<=nlstate;i++){
1.126 brouard 6682: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
1.288 brouard 6683: /* for(j=1;j<=nlstate;j++) */
6684: /* fprintf(ficresvpl," %d %.5f ",j,prlim[j][i]); */
6685: }
1.126 brouard 6686: fprintf(ficresvpl,"\n");
6687: free_vector(gp,1,nlstate);
6688: free_vector(gm,1,nlstate);
1.208 brouard 6689: free_matrix(mgm,1,npar,1,nlstate);
6690: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 6691: free_matrix(gradg,1,npar,1,nlstate);
6692: free_matrix(trgradg,1,nlstate,1,npar);
6693: } /* End age */
6694:
6695: free_vector(xp,1,npar);
6696: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 6697: free_matrix(dnewmpar,1,nlstate,1,nlstate);
6698:
6699: }
6700:
6701:
6702: /************ Variance of backprevalence limit ******************/
1.269 brouard 6703: 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 6704: {
6705: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
6706: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
6707:
6708: double **dnewmpar,**doldm;
6709: int i, j, nhstepm, hstepm;
6710: double *xp;
6711: double *gp, *gm;
6712: double **gradg, **trgradg;
6713: double **mgm, **mgp;
6714: double age,agelim;
6715: int theta;
6716:
6717: pstamp(ficresvbl);
6718: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
6719: fprintf(ficresvbl,"# Age ");
6720: if(nresult >=1)
6721: fprintf(ficresvbl," Result# ");
6722: for(i=1; i<=nlstate;i++)
6723: fprintf(ficresvbl," %1d-%1d",i,i);
6724: fprintf(ficresvbl,"\n");
6725:
6726: xp=vector(1,npar);
6727: dnewmpar=matrix(1,nlstate,1,npar);
6728: doldm=matrix(1,nlstate,1,nlstate);
6729:
6730: hstepm=1*YEARM; /* Every year of age */
6731: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6732: agelim = AGEINF;
6733: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
6734: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6735: if (stepm >= YEARM) hstepm=1;
6736: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6737: gradg=matrix(1,npar,1,nlstate);
6738: mgp=matrix(1,npar,1,nlstate);
6739: mgm=matrix(1,npar,1,nlstate);
6740: gp=vector(1,nlstate);
6741: gm=vector(1,nlstate);
6742:
6743: for(theta=1; theta <=npar; theta++){
6744: for(i=1; i<=npar; i++){ /* Computes gradient */
6745: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6746: }
6747: if(mobilavproj > 0 )
6748: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6749: else
6750: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6751: for(i=1;i<=nlstate;i++){
6752: gp[i] = bprlim[i][i];
6753: mgp[theta][i] = bprlim[i][i];
6754: }
6755: for(i=1; i<=npar; i++) /* Computes gradient */
6756: xp[i] = x[i] - (i==theta ?delti[theta]:0);
6757: if(mobilavproj > 0 )
6758: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6759: else
6760: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6761: for(i=1;i<=nlstate;i++){
6762: gm[i] = bprlim[i][i];
6763: mgm[theta][i] = bprlim[i][i];
6764: }
6765: for(i=1;i<=nlstate;i++)
6766: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
6767: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
6768: } /* End theta */
6769:
6770: trgradg =matrix(1,nlstate,1,npar);
6771:
6772: for(j=1; j<=nlstate;j++)
6773: for(theta=1; theta <=npar; theta++)
6774: trgradg[j][theta]=gradg[theta][j];
6775: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6776: /* printf("\nmgm mgp %d ",(int)age); */
6777: /* for(j=1; j<=nlstate;j++){ */
6778: /* printf(" %d ",j); */
6779: /* for(theta=1; theta <=npar; theta++) */
6780: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6781: /* printf("\n "); */
6782: /* } */
6783: /* } */
6784: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6785: /* printf("\n gradg %d ",(int)age); */
6786: /* for(j=1; j<=nlstate;j++){ */
6787: /* printf("%d ",j); */
6788: /* for(theta=1; theta <=npar; theta++) */
6789: /* printf("%d %lf ",theta,gradg[theta][j]); */
6790: /* printf("\n "); */
6791: /* } */
6792: /* } */
6793:
6794: for(i=1;i<=nlstate;i++)
6795: varbpl[i][(int)age] =0.;
6796: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
6797: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6798: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6799: }else{
6800: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6801: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6802: }
6803: for(i=1;i<=nlstate;i++)
6804: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6805:
6806: fprintf(ficresvbl,"%.0f ",age );
6807: if(nresult >=1)
6808: fprintf(ficresvbl,"%d ",nres );
6809: for(i=1; i<=nlstate;i++)
6810: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
6811: fprintf(ficresvbl,"\n");
6812: free_vector(gp,1,nlstate);
6813: free_vector(gm,1,nlstate);
6814: free_matrix(mgm,1,npar,1,nlstate);
6815: free_matrix(mgp,1,npar,1,nlstate);
6816: free_matrix(gradg,1,npar,1,nlstate);
6817: free_matrix(trgradg,1,nlstate,1,npar);
6818: } /* End age */
6819:
6820: free_vector(xp,1,npar);
6821: free_matrix(doldm,1,nlstate,1,npar);
6822: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 6823:
6824: }
6825:
6826: /************ Variance of one-step probabilities ******************/
6827: 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 6828: {
6829: int i, j=0, k1, l1, tj;
6830: int k2, l2, j1, z1;
6831: int k=0, l;
6832: int first=1, first1, first2;
1.326 brouard 6833: int nres=0; /* New */
1.222 brouard 6834: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
6835: double **dnewm,**doldm;
6836: double *xp;
6837: double *gp, *gm;
6838: double **gradg, **trgradg;
6839: double **mu;
6840: double age, cov[NCOVMAX+1];
6841: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
6842: int theta;
6843: char fileresprob[FILENAMELENGTH];
6844: char fileresprobcov[FILENAMELENGTH];
6845: char fileresprobcor[FILENAMELENGTH];
6846: double ***varpij;
6847:
6848: strcpy(fileresprob,"PROB_");
6849: strcat(fileresprob,fileres);
6850: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
6851: printf("Problem with resultfile: %s\n", fileresprob);
6852: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
6853: }
6854: strcpy(fileresprobcov,"PROBCOV_");
6855: strcat(fileresprobcov,fileresu);
6856: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
6857: printf("Problem with resultfile: %s\n", fileresprobcov);
6858: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
6859: }
6860: strcpy(fileresprobcor,"PROBCOR_");
6861: strcat(fileresprobcor,fileresu);
6862: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
6863: printf("Problem with resultfile: %s\n", fileresprobcor);
6864: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
6865: }
6866: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6867: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6868: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6869: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6870: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6871: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6872: pstamp(ficresprob);
6873: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
6874: fprintf(ficresprob,"# Age");
6875: pstamp(ficresprobcov);
6876: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
6877: fprintf(ficresprobcov,"# Age");
6878: pstamp(ficresprobcor);
6879: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
6880: fprintf(ficresprobcor,"# Age");
1.126 brouard 6881:
6882:
1.222 brouard 6883: for(i=1; i<=nlstate;i++)
6884: for(j=1; j<=(nlstate+ndeath);j++){
6885: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
6886: fprintf(ficresprobcov," p%1d-%1d ",i,j);
6887: fprintf(ficresprobcor," p%1d-%1d ",i,j);
6888: }
6889: /* fprintf(ficresprob,"\n");
6890: fprintf(ficresprobcov,"\n");
6891: fprintf(ficresprobcor,"\n");
6892: */
6893: xp=vector(1,npar);
6894: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6895: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6896: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
6897: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
6898: first=1;
6899: fprintf(ficgp,"\n# Routine varprob");
6900: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
6901: fprintf(fichtm,"\n");
6902:
1.288 brouard 6903: 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 6904: 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);
6905: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 6906: and drawn. It helps understanding how is the covariance between two incidences.\
6907: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 6908: 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 6909: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
6910: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
6911: standard deviations wide on each axis. <br>\
6912: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
6913: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
6914: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
6915:
1.222 brouard 6916: cov[1]=1;
6917: /* tj=cptcoveff; */
1.225 brouard 6918: tj = (int) pow(2,cptcoveff);
1.222 brouard 6919: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
6920: j1=0;
1.224 brouard 6921: for(j1=1; j1<=tj;j1++){ /* For each valid combination of covariates or only once*/
1.326 brouard 6922: for(nres=1;nres <=1; nres++){ /* For each resultline */
6923: /* for(nres=1;nres <=nresult; nres++){ /\* For each resultline *\/ */
1.222 brouard 6924: if (cptcovn>0) {
6925: fprintf(ficresprob, "\n#********** Variable ");
1.225 brouard 6926: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6927: fprintf(ficresprob, "**********\n#\n");
6928: fprintf(ficresprobcov, "\n#********** Variable ");
1.225 brouard 6929: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcov, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6930: fprintf(ficresprobcov, "**********\n#\n");
1.220 brouard 6931:
1.222 brouard 6932: fprintf(ficgp, "\n#********** Variable ");
1.225 brouard 6933: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficgp, " V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6934: fprintf(ficgp, "**********\n#\n");
1.220 brouard 6935:
6936:
1.222 brouard 6937: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
1.319 brouard 6938: /* for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtm, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]); */
6939: for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtmcov, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6940: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 6941:
1.222 brouard 6942: fprintf(ficresprobcor, "\n#********** Variable ");
1.225 brouard 6943: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcor, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6944: fprintf(ficresprobcor, "**********\n#");
6945: if(invalidvarcomb[j1]){
6946: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
6947: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
6948: continue;
6949: }
6950: }
6951: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
6952: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6953: gp=vector(1,(nlstate)*(nlstate+ndeath));
6954: gm=vector(1,(nlstate)*(nlstate+ndeath));
6955: for (age=bage; age<=fage; age ++){
6956: cov[2]=age;
6957: if(nagesqr==1)
6958: cov[3]= age*age;
1.326 brouard 6959: /* for (k=1; k<=cptcovn;k++) { */
6960: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)]; */
6961: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
6962: /* Here comes the value of the covariate 'j1' after renumbering k with single dummy covariates */
6963: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(j1,k)];
1.222 brouard 6964: /*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*//* j1 1 2 3 4
6965: * 1 1 1 1 1
6966: * 2 2 1 1 1
6967: * 3 1 2 1 1
6968: */
6969: /* nbcode[1][1]=0 nbcode[1][2]=1;*/
6970: }
1.319 brouard 6971: /* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1, Tage[1]=2 */
6972: /* ) p nbcode[Tvar[Tage[k]]][(1 & (ij-1) >> (k-1))+1] */
6973: /*for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; */
1.326 brouard 6974: for (k=1; k<=cptcovage;k++){ /* For product with age */
6975: if(Dummy[Tage[k]]==2){ /* dummy with age */
6976: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(j1,k)]*cov[2];
6977: /* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
6978: } else if(Dummy[Tage[k]]==3){ /* quantitative with age */
1.327 brouard 6979: printf("Internal IMaCh error, don't know which value for quantitative covariate with age, Tage[k]%d, k=%d, Tvar[Tage[k]]=V%d, age=%d\n",Tage[k],k ,Tvar[Tage[k]], (int)cov[2]);
6980: exit(1);
6981: /* cov[2+nagesqr+Tage[k]]=meanq[k]/idq[k]*cov[2];/\* Using the mean of quantitative variable Tvar[Tage[k]] /\* Tqresult[nres][k]; *\/ */
1.326 brouard 6982: /* cov[++k1]=Tqresult[nres][k]; */
6983: }
6984: /* cov[2+Tage[k]+nagesqr]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
6985: }
6986: for (k=1; k<=cptcovprod;k++){/* For product without age */
1.329 ! brouard 6987: if(Dummy[Tvard[k][1]]==0){
! 6988: if(Dummy[Tvard[k][2]]==0){
1.326 brouard 6989: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(j1,k)] * nbcode[Tvard[k][2]][codtabm(j1,k)];
6990: /* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */
6991: }else{ /* Should we use the mean of the quantitative variables? */
6992: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(j1,k)] * Tqresult[nres][k];
6993: /* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; */
6994: }
6995: }else{
1.329 ! brouard 6996: if(Dummy[Tvard[k][2]]==0){
1.326 brouard 6997: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(j1,k)] * Tqinvresult[nres][Tvard[k][1]];
6998: /* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; */
6999: }else{
7000: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
7001: /* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
7002: }
7003: }
7004: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
7005: }
7006: /* For each age and combination of dummy covariates we slightly move the parameters of delti in order to get the gradient*/
1.222 brouard 7007: for(theta=1; theta <=npar; theta++){
7008: for(i=1; i<=npar; i++)
7009: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 7010:
1.222 brouard 7011: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 7012:
1.222 brouard 7013: k=0;
7014: for(i=1; i<= (nlstate); i++){
7015: for(j=1; j<=(nlstate+ndeath);j++){
7016: k=k+1;
7017: gp[k]=pmmij[i][j];
7018: }
7019: }
1.220 brouard 7020:
1.222 brouard 7021: for(i=1; i<=npar; i++)
7022: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 7023:
1.222 brouard 7024: pmij(pmmij,cov,ncovmodel,xp,nlstate);
7025: k=0;
7026: for(i=1; i<=(nlstate); i++){
7027: for(j=1; j<=(nlstate+ndeath);j++){
7028: k=k+1;
7029: gm[k]=pmmij[i][j];
7030: }
7031: }
1.220 brouard 7032:
1.222 brouard 7033: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
7034: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
7035: }
1.126 brouard 7036:
1.222 brouard 7037: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
7038: for(theta=1; theta <=npar; theta++)
7039: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 7040:
1.222 brouard 7041: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
7042: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 7043:
1.222 brouard 7044: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 7045:
1.222 brouard 7046: k=0;
7047: for(i=1; i<=(nlstate); i++){
7048: for(j=1; j<=(nlstate+ndeath);j++){
7049: k=k+1;
7050: mu[k][(int) age]=pmmij[i][j];
7051: }
7052: }
7053: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
7054: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
7055: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 7056:
1.222 brouard 7057: /*printf("\n%d ",(int)age);
7058: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
7059: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
7060: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
7061: }*/
1.220 brouard 7062:
1.222 brouard 7063: fprintf(ficresprob,"\n%d ",(int)age);
7064: fprintf(ficresprobcov,"\n%d ",(int)age);
7065: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 7066:
1.222 brouard 7067: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
7068: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
7069: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
7070: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
7071: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
7072: }
7073: i=0;
7074: for (k=1; k<=(nlstate);k++){
7075: for (l=1; l<=(nlstate+ndeath);l++){
7076: i++;
7077: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
7078: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
7079: for (j=1; j<=i;j++){
7080: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
7081: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
7082: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
7083: }
7084: }
7085: }/* end of loop for state */
7086: } /* end of loop for age */
7087: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
7088: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
7089: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7090: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7091:
7092: /* Confidence intervalle of pij */
7093: /*
7094: fprintf(ficgp,"\nunset parametric;unset label");
7095: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
7096: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
7097: 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);
7098: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
7099: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
7100: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
7101: */
7102:
7103: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
7104: first1=1;first2=2;
7105: for (k2=1; k2<=(nlstate);k2++){
7106: for (l2=1; l2<=(nlstate+ndeath);l2++){
7107: if(l2==k2) continue;
7108: j=(k2-1)*(nlstate+ndeath)+l2;
7109: for (k1=1; k1<=(nlstate);k1++){
7110: for (l1=1; l1<=(nlstate+ndeath);l1++){
7111: if(l1==k1) continue;
7112: i=(k1-1)*(nlstate+ndeath)+l1;
7113: if(i<=j) continue;
7114: for (age=bage; age<=fage; age ++){
7115: if ((int)age %5==0){
7116: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
7117: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
7118: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
7119: mu1=mu[i][(int) age]/stepm*YEARM ;
7120: mu2=mu[j][(int) age]/stepm*YEARM;
7121: c12=cv12/sqrt(v1*v2);
7122: /* Computing eigen value of matrix of covariance */
7123: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7124: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7125: if ((lc2 <0) || (lc1 <0) ){
7126: if(first2==1){
7127: first1=0;
7128: 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);
7129: }
7130: 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);
7131: /* lc1=fabs(lc1); */ /* If we want to have them positive */
7132: /* lc2=fabs(lc2); */
7133: }
1.220 brouard 7134:
1.222 brouard 7135: /* Eigen vectors */
1.280 brouard 7136: if(1+(v1-lc1)*(v1-lc1)/cv12/cv12 <1.e-5){
7137: printf(" Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7138: fprintf(ficlog," Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7139: v11=(1./sqrt(fabs(1+(v1-lc1)*(v1-lc1)/cv12/cv12)));
7140: }else
7141: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
1.222 brouard 7142: /*v21=sqrt(1.-v11*v11); *//* error */
7143: v21=(lc1-v1)/cv12*v11;
7144: v12=-v21;
7145: v22=v11;
7146: tnalp=v21/v11;
7147: if(first1==1){
7148: first1=0;
7149: 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);
7150: }
7151: 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);
7152: /*printf(fignu*/
7153: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
7154: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
7155: if(first==1){
7156: first=0;
7157: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
7158: fprintf(ficgp,"\nset parametric;unset label");
7159: 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);
7160: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 7161: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 7162: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 7163: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 7164: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
7165: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7166: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7167: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
7168: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7169: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
7170: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
7171: 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 7172: mu1,std,v11,sqrt(fabs(lc1)),v12,sqrt(fabs(lc2)), \
7173: mu2,std,v21,sqrt(fabs(lc1)),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 7174: }else{
7175: first=0;
7176: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
7177: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
7178: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
7179: 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 7180: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
7181: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 7182: }/* if first */
7183: } /* age mod 5 */
7184: } /* end loop age */
7185: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7186: first=1;
7187: } /*l12 */
7188: } /* k12 */
7189: } /*l1 */
7190: }/* k1 */
1.326 brouard 7191: } /* loop on nres */
1.222 brouard 7192: } /* loop on combination of covariates j1 */
7193: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
7194: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
7195: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
7196: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
7197: free_vector(xp,1,npar);
7198: fclose(ficresprob);
7199: fclose(ficresprobcov);
7200: fclose(ficresprobcor);
7201: fflush(ficgp);
7202: fflush(fichtmcov);
7203: }
1.126 brouard 7204:
7205:
7206: /******************* Printing html file ***********/
1.201 brouard 7207: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 7208: int lastpass, int stepm, int weightopt, char model[],\
7209: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.296 brouard 7210: int popforecast, int mobilav, int prevfcast, int mobilavproj, int prevbcast, int estepm , \
7211: double jprev1, double mprev1,double anprev1, double dateprev1, double dateprojd, double dateback1, \
7212: double jprev2, double mprev2,double anprev2, double dateprev2, double dateprojf, double dateback2){
1.237 brouard 7213: int jj1, k1, i1, cpt, k4, nres;
1.319 brouard 7214: /* In fact some results are already printed in fichtm which is open */
1.126 brouard 7215: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
7216: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
7217: </ul>");
1.319 brouard 7218: /* fprintf(fichtm,"<ul><li> model=1+age+%s\n \ */
7219: /* </ul>", model); */
1.214 brouard 7220: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
7221: 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",
7222: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
7223: 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 7224: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
7225: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 7226: fprintf(fichtm,"\
7227: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 7228: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 7229: fprintf(fichtm,"\
1.217 brouard 7230: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
7231: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
7232: fprintf(fichtm,"\
1.288 brouard 7233: - Period (forward) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 7234: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 7235: fprintf(fichtm,"\
1.288 brouard 7236: - Backward prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.217 brouard 7237: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
7238: fprintf(fichtm,"\
1.211 brouard 7239: - (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 7240: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 7241: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 7242: if(prevfcast==1){
7243: fprintf(fichtm,"\
7244: - Prevalence projections by age and states: \
1.201 brouard 7245: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 7246: }
1.126 brouard 7247:
7248:
1.225 brouard 7249: m=pow(2,cptcoveff);
1.222 brouard 7250: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 7251:
1.317 brouard 7252: fprintf(fichtm," \n<ul><li><b>Graphs (first order)</b></li><p>");
1.264 brouard 7253:
7254: jj1=0;
7255:
7256: fprintf(fichtm," \n<ul>");
7257: for(nres=1; nres <= nresult; nres++) /* For each resultline */
7258: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
7259: if(m != 1 && TKresult[nres]!= k1)
7260: continue;
7261: jj1++;
7262: if (cptcovn > 0) {
7263: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
7264: for (cpt=1; cpt<=cptcoveff;cpt++){
7265: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7266: }
7267: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7268: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
7269: }
7270: fprintf(fichtm,"\">");
7271:
7272: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
7273: fprintf(fichtm,"************ Results for covariates");
7274: for (cpt=1; cpt<=cptcoveff;cpt++){
7275: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7276: }
7277: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7278: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7279: }
7280: if(invalidvarcomb[k1]){
7281: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
7282: continue;
7283: }
7284: fprintf(fichtm,"</a></li>");
7285: } /* cptcovn >0 */
7286: }
1.317 brouard 7287: fprintf(fichtm," \n</ul>");
1.264 brouard 7288:
1.222 brouard 7289: jj1=0;
1.237 brouard 7290:
7291: for(nres=1; nres <= nresult; nres++) /* For each resultline */
1.241 brouard 7292: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
1.253 brouard 7293: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7294: continue;
1.220 brouard 7295:
1.222 brouard 7296: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
7297: jj1++;
7298: if (cptcovn > 0) {
1.264 brouard 7299: fprintf(fichtm,"\n<p><a name=\"rescov");
7300: for (cpt=1; cpt<=cptcoveff;cpt++){
7301: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7302: }
7303: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7304: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
7305: }
7306: fprintf(fichtm,"\"</a>");
7307:
1.222 brouard 7308: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 7309: for (cpt=1; cpt<=cptcoveff;cpt++){
1.237 brouard 7310: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7311: printf(" V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);fflush(stdout);
7312: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
7313: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 7314: }
1.237 brouard 7315: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7316: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7317: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);fflush(stdout);
7318: }
7319:
1.230 brouard 7320: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.321 brouard 7321: fprintf(fichtm," (model=%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.222 brouard 7322: if(invalidvarcomb[k1]){
7323: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
7324: printf("\nCombination (%d) ignored because no cases \n",k1);
7325: continue;
7326: }
7327: }
7328: /* aij, bij */
1.259 brouard 7329: 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 7330: <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 7331: /* Pij */
1.241 brouard 7332: 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> \
7333: <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 7334: /* Quasi-incidences */
7335: 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 7336: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 7337: 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 7338: 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> \
7339: <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 7340: /* Survival functions (period) in state j */
7341: for(cpt=1; cpt<=nlstate;cpt++){
1.329 ! brouard 7342: 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>", cpt, cpt, nlstate, subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres,subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
! 7343: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
! 7344: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.222 brouard 7345: }
7346: /* State specific survival functions (period) */
7347: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 7348: fprintf(fichtm,"<br>\n- Survival functions in state %d and in any other live state (total).\
7349: And probability to be observed in various states (up to %d) being in state %d at different ages. \
1.329 ! brouard 7350: <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br> ", cpt, nlstate, cpt, subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres,subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
! 7351: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
! 7352: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.222 brouard 7353: }
1.288 brouard 7354: /* Period (forward stable) prevalence in each health state */
1.222 brouard 7355: for(cpt=1; cpt<=nlstate;cpt++){
1.329 ! brouard 7356: 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>", cpt, nlstate, cpt, subdirf2(optionfilefiname,"P_"),cpt,k1,nres,subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
! 7357: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"P_"),subdirf2(optionfilefiname,"P_"));
! 7358: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.222 brouard 7359: }
1.296 brouard 7360: if(prevbcast==1){
1.288 brouard 7361: /* Backward prevalence in each health state */
1.222 brouard 7362: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 7363: 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 7364: <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 7365: }
1.217 brouard 7366: }
1.222 brouard 7367: if(prevfcast==1){
1.288 brouard 7368: /* Projection of prevalence up to period (forward stable) prevalence in each health state */
1.222 brouard 7369: for(cpt=1; cpt<=nlstate;cpt++){
1.314 brouard 7370: 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>", dateprev1, dateprev2, mobilavproj, dateprojd, dateprojf, cpt, cpt, nlstate, subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
7371: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"F_"),subdirf2(optionfilefiname,"F_"));
7372: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",
7373: subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.222 brouard 7374: }
7375: }
1.296 brouard 7376: if(prevbcast==1){
1.268 brouard 7377: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
7378: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 7379: fprintf(fichtm,"<br>\n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), \
7380: 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 \
7381: 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) \
1.314 brouard 7382: with weights corresponding to observed prevalence at different ages. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a>", dateprev1, dateprev2, mobilavproj, dateback1, dateback2, cpt, cpt, nlstate, subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
7383: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"FB_"),subdirf2(optionfilefiname,"FB_"));
7384: fprintf(fichtm," <img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
1.268 brouard 7385: }
7386: }
1.220 brouard 7387:
1.222 brouard 7388: for(cpt=1; cpt<=nlstate;cpt++) {
1.314 brouard 7389: 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>",cpt,nlstate,subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres,subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
7390: fprintf(fichtm," (data from text file <a href=\"%s.txt\"> %s.txt</a>)\n<br>",subdirf2(optionfilefiname,"E_"),subdirf2(optionfilefiname,"E_"));
7391: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres );
1.222 brouard 7392: }
7393: /* } /\* end i1 *\/ */
7394: }/* End k1 */
7395: fprintf(fichtm,"</ul>");
1.126 brouard 7396:
1.222 brouard 7397: fprintf(fichtm,"\
1.126 brouard 7398: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 7399: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 7400: - 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 7401: But because parameters are usually highly correlated (a higher incidence of disability \
7402: and a higher incidence of recovery can give very close observed transition) it might \
7403: be very useful to look not only at linear confidence intervals estimated from the \
7404: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
7405: (parameters) of the logistic regression, it might be more meaningful to visualize the \
7406: covariance matrix of the one-step probabilities. \
7407: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 7408:
1.222 brouard 7409: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
7410: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
7411: fprintf(fichtm,"\
1.126 brouard 7412: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 7413: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 7414:
1.222 brouard 7415: fprintf(fichtm,"\
1.126 brouard 7416: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 7417: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
7418: fprintf(fichtm,"\
1.126 brouard 7419: - 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): \
7420: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 7421: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 7422: fprintf(fichtm,"\
1.126 brouard 7423: - (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): \
7424: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 7425: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 7426: fprintf(fichtm,"\
1.288 brouard 7427: - 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 7428: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
7429: fprintf(fichtm,"\
1.128 brouard 7430: - 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 7431: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
7432: fprintf(fichtm,"\
1.288 brouard 7433: - Standard deviation of forward (period) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 7434: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 7435:
7436: /* if(popforecast==1) fprintf(fichtm,"\n */
7437: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
7438: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
7439: /* <br>",fileres,fileres,fileres,fileres); */
7440: /* else */
7441: /* 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 7442: fflush(fichtm);
1.126 brouard 7443:
1.225 brouard 7444: m=pow(2,cptcoveff);
1.222 brouard 7445: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 7446:
1.317 brouard 7447: fprintf(fichtm," <ul><li><b>Graphs (second order)</b></li><p>");
7448:
7449: jj1=0;
7450:
7451: fprintf(fichtm," \n<ul>");
7452: for(nres=1; nres <= nresult; nres++) /* For each resultline */
7453: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
7454: if(m != 1 && TKresult[nres]!= k1)
7455: continue;
7456: jj1++;
7457: if (cptcovn > 0) {
7458: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescovsecond");
7459: for (cpt=1; cpt<=cptcoveff;cpt++){
7460: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7461: }
7462: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7463: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
7464: }
7465: fprintf(fichtm,"\">");
7466:
7467: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
7468: fprintf(fichtm,"************ Results for covariates");
7469: for (cpt=1; cpt<=cptcoveff;cpt++){
7470: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7471: }
7472: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7473: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7474: }
7475: if(invalidvarcomb[k1]){
7476: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
7477: continue;
7478: }
7479: fprintf(fichtm,"</a></li>");
7480: } /* cptcovn >0 */
7481: }
7482: fprintf(fichtm," \n</ul>");
7483:
1.222 brouard 7484: jj1=0;
1.237 brouard 7485:
1.241 brouard 7486: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.222 brouard 7487: for(k1=1; k1<=m;k1++){
1.253 brouard 7488: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7489: continue;
1.222 brouard 7490: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
7491: jj1++;
1.126 brouard 7492: if (cptcovn > 0) {
1.317 brouard 7493: fprintf(fichtm,"\n<p><a name=\"rescovsecond");
7494: for (cpt=1; cpt<=cptcoveff;cpt++){
7495: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7496: }
7497: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7498: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
7499: }
7500: fprintf(fichtm,"\"</a>");
7501:
1.126 brouard 7502: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.317 brouard 7503: for (cpt=1; cpt<=cptcoveff;cpt++){ /**< cptcoveff number of variables */
1.237 brouard 7504: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);
1.317 brouard 7505: printf(" V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);fflush(stdout);
1.237 brouard 7506: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
1.317 brouard 7507: }
1.237 brouard 7508: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7509: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7510: }
7511:
1.321 brouard 7512: fprintf(fichtm," (model=%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.220 brouard 7513:
1.222 brouard 7514: if(invalidvarcomb[k1]){
7515: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
7516: continue;
7517: }
1.126 brouard 7518: }
7519: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 7520: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.314 brouard 7521: prevalence (with 95%% confidence interval) in state (%d): <a href=\"%s_%d-%d-%d.svg\"> %s_%d-%d-%d.svg</a>",mobilav,cpt,subdirf2(optionfilefiname,"V_"),cpt,k1,nres,subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
7522: fprintf(fichtm," (data from text file <a href=\"%s\">%s</a>)\n <br>",subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
7523: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"V_"), cpt,k1,nres);
1.126 brouard 7524: }
7525: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.314 brouard 7526: health expectancies in each live states (1 to %d). If popbased=1 the smooth (due to the model) \
1.128 brouard 7527: true period expectancies (those weighted with period prevalences are also\
7528: drawn in addition to the population based expectancies computed using\
1.314 brouard 7529: observed and cahotic prevalences: <a href=\"%s_%d-%d.svg\">%s_%d-%d.svg</a>",nlstate, subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres);
7530: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>) \n<br>",subdirf2(optionfilefiname,"T_"),subdirf2(optionfilefiname,"T_"));
7531: fprintf(fichtm,"<img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 7532: /* } /\* end i1 *\/ */
7533: }/* End k1 */
1.241 brouard 7534: }/* End nres */
1.222 brouard 7535: fprintf(fichtm,"</ul>");
7536: fflush(fichtm);
1.126 brouard 7537: }
7538:
7539: /******************* Gnuplot file **************/
1.296 brouard 7540: 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 7541:
7542: char dirfileres[132],optfileres[132];
1.264 brouard 7543: char gplotcondition[132], gplotlabel[132];
1.237 brouard 7544: 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 7545: int lv=0, vlv=0, kl=0;
1.130 brouard 7546: int ng=0;
1.201 brouard 7547: int vpopbased;
1.223 brouard 7548: int ioffset; /* variable offset for columns */
1.270 brouard 7549: int iyearc=1; /* variable column for year of projection */
7550: int iagec=1; /* variable column for age of projection */
1.235 brouard 7551: int nres=0; /* Index of resultline */
1.266 brouard 7552: int istart=1; /* For starting graphs in projections */
1.219 brouard 7553:
1.126 brouard 7554: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
7555: /* printf("Problem with file %s",optionfilegnuplot); */
7556: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
7557: /* } */
7558:
7559: /*#ifdef windows */
7560: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 7561: /*#endif */
1.225 brouard 7562: m=pow(2,cptcoveff);
1.126 brouard 7563:
1.274 brouard 7564: /* diagram of the model */
7565: fprintf(ficgp,"\n#Diagram of the model \n");
7566: fprintf(ficgp,"\ndelta=0.03;delta2=0.07;unset arrow;\n");
7567: fprintf(ficgp,"yoff=(%d > 2? 0:1);\n",nlstate);
7568: 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);
7569:
7570: 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);
7571: fprintf(ficgp,"\n#show arrow\nunset label\n");
7572: 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);
7573: fprintf(ficgp,"\nset label %d+1 sprintf(\"State %%d\",%d+1) center at 0.,0. font \"helvetica, 16\" tc rgbcolor \"red\"\n",nlstate,nlstate);
7574: fprintf(ficgp,"\n#show label\nunset border;unset xtics; unset ytics;\n");
7575: fprintf(ficgp,"\n\nset ter svg size 640, 480;set out \"%s_.svg\" \n",subdirf2(optionfilefiname,"D_"));
7576: fprintf(ficgp,"unset log y; plot [-1.2:1.2][yoff-1.2:1.2] 1/0 not; set out;reset;\n");
7577:
1.202 brouard 7578: /* Contribution to likelihood */
7579: /* Plot the probability implied in the likelihood */
1.223 brouard 7580: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
7581: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
7582: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
7583: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 7584: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 7585: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
7586: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 7587: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
7588: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
7589: 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));
7590: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
7591: 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));
7592: for (i=1; i<= nlstate ; i ++) {
7593: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
7594: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
7595: 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);
7596: for (j=2; j<= nlstate+ndeath ; j ++) {
7597: 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);
7598: }
7599: fprintf(ficgp,";\nset out; unset ylabel;\n");
7600: }
7601: /* 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 */
7602: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
7603: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
7604: fprintf(ficgp,"\nset out;unset log\n");
7605: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 7606:
1.126 brouard 7607: strcpy(dirfileres,optionfilefiname);
7608: strcpy(optfileres,"vpl");
1.223 brouard 7609: /* 1eme*/
1.238 brouard 7610: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
7611: for (k1=1; k1<= m ; k1 ++){ /* For each valid combination of covariate */
1.236 brouard 7612: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.238 brouard 7613: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.253 brouard 7614: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7615: continue;
7616: /* We are interested in selected combination by the resultline */
1.246 brouard 7617: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.288 brouard 7618: fprintf(ficgp,"\n# 1st: Forward (stable period) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 7619: strcpy(gplotlabel,"(");
1.238 brouard 7620: for (k=1; k<=cptcoveff; k++){ /* For each covariate k get corresponding value lv for combination k1 */
7621: lv= decodtabm(k1,k,cptcoveff); /* Should be the value of the covariate corresponding to k1 combination */
7622: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7623: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7624: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7625: vlv= nbcode[Tvaraff[k]][lv]; /* vlv is the value of the covariate lv, 0 or 1 */
7626: /* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv */
1.246 brouard 7627: /* printf(" V%d=%d ",Tvaraff[k],vlv); */
1.238 brouard 7628: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7629: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7630: }
7631: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.246 brouard 7632: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 7633: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7634: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7635: }
7636: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 7637: /* printf("\n#\n"); */
1.238 brouard 7638: fprintf(ficgp,"\n#\n");
7639: if(invalidvarcomb[k1]){
1.260 brouard 7640: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 7641: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7642: continue;
7643: }
1.235 brouard 7644:
1.241 brouard 7645: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
7646: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.276 brouard 7647: /* fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel); */
1.321 brouard 7648: fprintf(ficgp,"set title \"Alive state %d %s model=%s\" font \"Helvetica,12\"\n",cpt,gplotlabel,model);
1.260 brouard 7649: 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);
7650: /* 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); */
7651: /* k1-1 error should be nres-1*/
1.238 brouard 7652: for (i=1; i<= nlstate ; i ++) {
7653: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7654: else fprintf(ficgp," %%*lf (%%*lf)");
7655: }
1.288 brouard 7656: 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 7657: for (i=1; i<= nlstate ; i ++) {
7658: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7659: else fprintf(ficgp," %%*lf (%%*lf)");
7660: }
1.260 brouard 7661: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 7662: for (i=1; i<= nlstate ; i ++) {
7663: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7664: else fprintf(ficgp," %%*lf (%%*lf)");
7665: }
1.265 brouard 7666: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
7667:
7668: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
7669: if(cptcoveff ==0){
1.271 brouard 7670: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+3*(cpt-1), cpt );
1.265 brouard 7671: }else{
7672: kl=0;
7673: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7674: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7675: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7676: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7677: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7678: vlv= nbcode[Tvaraff[k]][lv];
7679: kl++;
7680: /* 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 *\/ */
7681: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7682: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7683: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7684: if(k==cptcoveff){
7685: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
7686: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
7687: }else{
7688: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7689: kl++;
7690: }
7691: } /* end covariate */
7692: } /* end if no covariate */
7693:
1.296 brouard 7694: if(prevbcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
1.238 brouard 7695: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 7696: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 7697: if(cptcoveff ==0){
1.245 brouard 7698: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 7699: }else{
7700: kl=0;
7701: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7702: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7703: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7704: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7705: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7706: vlv= nbcode[Tvaraff[k]][lv];
1.223 brouard 7707: kl++;
1.238 brouard 7708: /* 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 *\/ */
7709: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7710: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7711: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7712: if(k==cptcoveff){
1.245 brouard 7713: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 7714: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 7715: }else{
7716: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7717: kl++;
7718: }
7719: } /* end covariate */
7720: } /* end if no covariate */
1.296 brouard 7721: if(prevbcast == 1){
1.268 brouard 7722: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
7723: /* k1-1 error should be nres-1*/
7724: for (i=1; i<= nlstate ; i ++) {
7725: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7726: else fprintf(ficgp," %%*lf (%%*lf)");
7727: }
1.271 brouard 7728: 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 7729: for (i=1; i<= nlstate ; i ++) {
7730: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7731: else fprintf(ficgp," %%*lf (%%*lf)");
7732: }
1.276 brouard 7733: 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 7734: for (i=1; i<= nlstate ; i ++) {
7735: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7736: else fprintf(ficgp," %%*lf (%%*lf)");
7737: }
1.274 brouard 7738: fprintf(ficgp,"\" t\"\" w l lt 4");
1.268 brouard 7739: } /* end if backprojcast */
1.296 brouard 7740: } /* end if prevbcast */
1.276 brouard 7741: /* fprintf(ficgp,"\nset out ;unset label;\n"); */
7742: fprintf(ficgp,"\nset out ;unset title;\n");
1.238 brouard 7743: } /* nres */
1.201 brouard 7744: } /* k1 */
7745: } /* cpt */
1.235 brouard 7746:
7747:
1.126 brouard 7748: /*2 eme*/
1.238 brouard 7749: for (k1=1; k1<= m ; k1 ++){
7750: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7751: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7752: continue;
7753: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 7754: strcpy(gplotlabel,"(");
1.238 brouard 7755: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.225 brouard 7756: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
1.223 brouard 7757: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7758: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7759: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7760: vlv= nbcode[Tvaraff[k]][lv];
7761: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7762: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7763: }
1.237 brouard 7764: /* for(k=1; k <= ncovds; k++){ */
1.236 brouard 7765: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 7766: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.236 brouard 7767: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7768: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7769: }
1.264 brouard 7770: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7771: fprintf(ficgp,"\n#\n");
1.223 brouard 7772: if(invalidvarcomb[k1]){
7773: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7774: continue;
7775: }
1.219 brouard 7776:
1.241 brouard 7777: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 7778: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 7779: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
7780: if(vpopbased==0){
1.238 brouard 7781: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 7782: }else
1.238 brouard 7783: fprintf(ficgp,"\nreplot ");
7784: for (i=1; i<= nlstate+1 ; i ++) {
7785: k=2*i;
1.261 brouard 7786: 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 7787: for (j=1; j<= nlstate+1 ; j ++) {
7788: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7789: else fprintf(ficgp," %%*lf (%%*lf)");
7790: }
7791: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
7792: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
1.261 brouard 7793: 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 7794: for (j=1; j<= nlstate+1 ; j ++) {
7795: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7796: else fprintf(ficgp," %%*lf (%%*lf)");
7797: }
7798: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 7799: 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 7800: for (j=1; j<= nlstate+1 ; j ++) {
7801: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7802: else fprintf(ficgp," %%*lf (%%*lf)");
7803: }
7804: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
7805: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
7806: } /* state */
7807: } /* vpopbased */
1.264 brouard 7808: 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 7809: } /* end nres */
7810: } /* k1 end 2 eme*/
7811:
7812:
7813: /*3eme*/
7814: for (k1=1; k1<= m ; k1 ++){
7815: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7816: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7817: continue;
7818:
7819: for (cpt=1; cpt<= nlstate ; cpt ++) {
1.261 brouard 7820: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 7821: strcpy(gplotlabel,"(");
1.238 brouard 7822: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7823: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7824: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7825: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7826: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7827: vlv= nbcode[Tvaraff[k]][lv];
7828: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7829: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7830: }
7831: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7832: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7833: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7834: }
1.264 brouard 7835: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7836: fprintf(ficgp,"\n#\n");
7837: if(invalidvarcomb[k1]){
7838: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7839: continue;
7840: }
7841:
7842: /* k=2+nlstate*(2*cpt-2); */
7843: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 7844: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 7845: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 7846: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 7847: 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 7848: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7849: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7850: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
7851: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7852: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7853: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 7854:
1.238 brouard 7855: */
7856: for (i=1; i< nlstate ; i ++) {
1.261 brouard 7857: 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 7858: /* 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 7859:
1.238 brouard 7860: }
1.261 brouard 7861: 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 7862: }
1.264 brouard 7863: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 7864: } /* end nres */
7865: } /* end kl 3eme */
1.126 brouard 7866:
1.223 brouard 7867: /* 4eme */
1.201 brouard 7868: /* Survival functions (period) from state i in state j by initial state i */
1.238 brouard 7869: for (k1=1; k1<=m; k1++){ /* For each covariate and each value */
7870: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7871: if(m != 1 && TKresult[nres]!= k1)
1.223 brouard 7872: continue;
1.238 brouard 7873: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 7874: strcpy(gplotlabel,"(");
1.238 brouard 7875: fprintf(ficgp,"\n#\n#\n# Survival functions in state j : 'LIJ_' files, cov=%d state=%d",k1, cpt);
7876: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7877: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7878: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7879: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7880: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7881: vlv= nbcode[Tvaraff[k]][lv];
7882: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7883: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7884: }
7885: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7886: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7887: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7888: }
1.264 brouard 7889: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7890: fprintf(ficgp,"\n#\n");
7891: if(invalidvarcomb[k1]){
7892: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7893: continue;
1.223 brouard 7894: }
1.238 brouard 7895:
1.241 brouard 7896: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 7897: 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 7898: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7899: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7900: k=3;
7901: for (i=1; i<= nlstate ; i ++){
7902: if(i==1){
7903: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7904: }else{
7905: fprintf(ficgp,", '' ");
7906: }
7907: l=(nlstate+ndeath)*(i-1)+1;
7908: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7909: for (j=2; j<= nlstate+ndeath ; j ++)
7910: fprintf(ficgp,"+$%d",k+l+j-1);
7911: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
7912: } /* nlstate */
1.264 brouard 7913: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7914: } /* end cpt state*/
7915: } /* end nres */
7916: } /* end covariate k1 */
7917:
1.220 brouard 7918: /* 5eme */
1.201 brouard 7919: /* Survival functions (period) from state i in state j by final state j */
1.238 brouard 7920: for (k1=1; k1<= m ; k1++){ /* For each covariate combination if any */
7921: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7922: if(m != 1 && TKresult[nres]!= k1)
1.227 brouard 7923: continue;
1.238 brouard 7924: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 7925: strcpy(gplotlabel,"(");
1.238 brouard 7926: 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);
7927: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7928: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7929: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7930: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7931: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7932: vlv= nbcode[Tvaraff[k]][lv];
7933: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7934: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7935: }
7936: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7937: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7938: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7939: }
1.264 brouard 7940: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7941: fprintf(ficgp,"\n#\n");
7942: if(invalidvarcomb[k1]){
7943: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7944: continue;
7945: }
1.227 brouard 7946:
1.241 brouard 7947: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 7948: 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 7949: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7950: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7951: k=3;
7952: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7953: if(j==1)
7954: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7955: else
7956: fprintf(ficgp,", '' ");
7957: l=(nlstate+ndeath)*(cpt-1) +j;
7958: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
7959: /* for (i=2; i<= nlstate+ndeath ; i ++) */
7960: /* fprintf(ficgp,"+$%d",k+l+i-1); */
7961: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
7962: } /* nlstate */
7963: fprintf(ficgp,", '' ");
7964: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
7965: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7966: l=(nlstate+ndeath)*(cpt-1) +j;
7967: if(j < nlstate)
7968: fprintf(ficgp,"$%d +",k+l);
7969: else
7970: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
7971: }
1.264 brouard 7972: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7973: } /* end cpt state*/
7974: } /* end covariate */
7975: } /* end nres */
1.227 brouard 7976:
1.220 brouard 7977: /* 6eme */
1.202 brouard 7978: /* CV preval stable (period) for each covariate */
1.237 brouard 7979: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7980: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7981: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7982: continue;
1.255 brouard 7983: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 7984: strcpy(gplotlabel,"(");
1.288 brouard 7985: fprintf(ficgp,"\n#\n#\n#CV preval stable (forward): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.225 brouard 7986: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.227 brouard 7987: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7988: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7989: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7990: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7991: vlv= nbcode[Tvaraff[k]][lv];
7992: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7993: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7994: }
1.237 brouard 7995: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7996: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7997: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7998: }
1.264 brouard 7999: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 8000: fprintf(ficgp,"\n#\n");
1.223 brouard 8001: if(invalidvarcomb[k1]){
1.227 brouard 8002: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8003: continue;
1.223 brouard 8004: }
1.227 brouard 8005:
1.241 brouard 8006: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 8007: 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 8008: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 8009: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 8010: k=3; /* Offset */
1.255 brouard 8011: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 8012: if(i==1)
8013: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8014: else
8015: fprintf(ficgp,", '' ");
1.255 brouard 8016: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 8017: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
8018: for (j=2; j<= nlstate ; j ++)
8019: fprintf(ficgp,"+$%d",k+l+j-1);
8020: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 8021: } /* nlstate */
1.264 brouard 8022: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 8023: } /* end cpt state*/
8024: } /* end covariate */
1.227 brouard 8025:
8026:
1.220 brouard 8027: /* 7eme */
1.296 brouard 8028: if(prevbcast == 1){
1.288 brouard 8029: /* CV backward prevalence for each covariate */
1.237 brouard 8030: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
8031: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 8032: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 8033: continue;
1.268 brouard 8034: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 8035: strcpy(gplotlabel,"(");
1.288 brouard 8036: fprintf(ficgp,"\n#\n#\n#CV Backward stable prevalence: 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 8037: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
8038: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
8039: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8040: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
1.223 brouard 8041: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.227 brouard 8042: vlv= nbcode[Tvaraff[k]][lv];
8043: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 8044: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 8045: }
1.237 brouard 8046: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8047: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 8048: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 8049: }
1.264 brouard 8050: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 8051: fprintf(ficgp,"\n#\n");
8052: if(invalidvarcomb[k1]){
8053: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8054: continue;
8055: }
8056:
1.241 brouard 8057: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 8058: 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 8059: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 8060: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 8061: k=3; /* Offset */
1.268 brouard 8062: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 8063: if(i==1)
8064: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
8065: else
8066: fprintf(ficgp,", '' ");
8067: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 8068: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.324 brouard 8069: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
8070: /* 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 8071: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 8072: /* for (j=2; j<= nlstate ; j ++) */
8073: /* fprintf(ficgp,"+$%d",k+l+j-1); */
8074: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 8075: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 8076: } /* nlstate */
1.264 brouard 8077: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 8078: } /* end cpt state*/
8079: } /* end covariate */
1.296 brouard 8080: } /* End if prevbcast */
1.218 brouard 8081:
1.223 brouard 8082: /* 8eme */
1.218 brouard 8083: if(prevfcast==1){
1.288 brouard 8084: /* Projection from cross-sectional to forward stable (period) prevalence for each covariate */
1.218 brouard 8085:
1.237 brouard 8086: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
8087: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 8088: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 8089: continue;
1.211 brouard 8090: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 8091: strcpy(gplotlabel,"(");
1.288 brouard 8092: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to forward stable prevalence (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 8093: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
8094: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
8095: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8096: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8097: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8098: vlv= nbcode[Tvaraff[k]][lv];
8099: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 8100: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 8101: }
1.237 brouard 8102: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8103: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 8104: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 8105: }
1.264 brouard 8106: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 8107: fprintf(ficgp,"\n#\n");
8108: if(invalidvarcomb[k1]){
8109: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8110: continue;
8111: }
8112:
8113: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 8114: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 8115: 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 8116: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 8117: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 8118:
8119: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
8120: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
8121: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
8122: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 8123: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8124: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8125: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8126: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 8127: if(i==istart){
1.227 brouard 8128: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
8129: }else{
8130: fprintf(ficgp,",\\\n '' ");
8131: }
8132: if(cptcoveff ==0){ /* No covariate */
8133: ioffset=2; /* Age is in 2 */
8134: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8135: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8136: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8137: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8138: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 8139: if(i==nlstate+1){
1.270 brouard 8140: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 8141: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
8142: fprintf(ficgp,",\\\n '' ");
8143: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 8144: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 8145: offyear, \
1.268 brouard 8146: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 8147: }else
1.227 brouard 8148: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
8149: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
8150: }else{ /* more than 2 covariates */
1.270 brouard 8151: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
8152: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8153: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8154: iyearc=ioffset-1;
8155: iagec=ioffset;
1.227 brouard 8156: fprintf(ficgp," u %d:(",ioffset);
8157: kl=0;
8158: strcpy(gplotcondition,"(");
8159: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
8160: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
8161: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8162: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8163: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8164: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
8165: kl++;
8166: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
8167: kl++;
8168: if(k <cptcoveff && cptcoveff>1)
8169: sprintf(gplotcondition+strlen(gplotcondition)," && ");
8170: }
8171: strcpy(gplotcondition+strlen(gplotcondition),")");
8172: /* 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 *\/ */
8173: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8174: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8175: /* '' 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*/
8176: if(i==nlstate+1){
1.270 brouard 8177: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
8178: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 8179: fprintf(ficgp,",\\\n '' ");
1.270 brouard 8180: fprintf(ficgp," u %d:(",iagec);
8181: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
8182: iyearc, iagec, offyear, \
8183: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 8184: /* '' 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 8185: }else{
8186: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
8187: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
8188: }
8189: } /* end if covariate */
8190: } /* nlstate */
1.264 brouard 8191: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 8192: } /* end cpt state*/
8193: } /* end covariate */
8194: } /* End if prevfcast */
1.227 brouard 8195:
1.296 brouard 8196: if(prevbcast==1){
1.268 brouard 8197: /* Back projection from cross-sectional to stable (mixed) for each covariate */
8198:
8199: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
8200: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
8201: if(m != 1 && TKresult[nres]!= k1)
8202: continue;
8203: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
8204: strcpy(gplotlabel,"(");
8205: fprintf(ficgp,"\n#\n#\n#Back projection of prevalence to stable (mixed) back prevalence: 'BPROJ_' files, covariatecombination#=%d originstate=%d",k1, cpt);
8206: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
8207: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
8208: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8209: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8210: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8211: vlv= nbcode[Tvaraff[k]][lv];
8212: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
8213: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
8214: }
8215: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8216: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
8217: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
8218: }
8219: strcpy(gplotlabel+strlen(gplotlabel),")");
8220: fprintf(ficgp,"\n#\n");
8221: if(invalidvarcomb[k1]){
8222: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8223: continue;
8224: }
8225:
8226: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
8227: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
8228: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
8229: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
8230: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8231:
8232: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
8233: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
8234: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
8235: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
8236: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8237: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8238: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8239: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8240: if(i==istart){
8241: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
8242: }else{
8243: fprintf(ficgp,",\\\n '' ");
8244: }
8245: if(cptcoveff ==0){ /* No covariate */
8246: ioffset=2; /* Age is in 2 */
8247: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8248: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8249: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8250: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8251: fprintf(ficgp," u %d:(", ioffset);
8252: if(i==nlstate+1){
1.270 brouard 8253: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 8254: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
8255: fprintf(ficgp,",\\\n '' ");
8256: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 8257: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 8258: offbyear, \
8259: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
8260: }else
8261: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
8262: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
8263: }else{ /* more than 2 covariates */
1.270 brouard 8264: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
8265: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8266: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8267: iyearc=ioffset-1;
8268: iagec=ioffset;
1.268 brouard 8269: fprintf(ficgp," u %d:(",ioffset);
8270: kl=0;
8271: strcpy(gplotcondition,"(");
8272: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
8273: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
8274: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8275: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8276: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8277: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
8278: kl++;
8279: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
8280: kl++;
8281: if(k <cptcoveff && cptcoveff>1)
8282: sprintf(gplotcondition+strlen(gplotcondition)," && ");
8283: }
8284: strcpy(gplotcondition+strlen(gplotcondition),")");
8285: /* 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 *\/ */
8286: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8287: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8288: /* '' 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*/
8289: if(i==nlstate+1){
1.270 brouard 8290: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
8291: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 8292: fprintf(ficgp,",\\\n '' ");
1.270 brouard 8293: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 8294: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 brouard 8295: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
8296: iyearc,iagec,offbyear, \
8297: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 8298: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
8299: }else{
8300: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
8301: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
8302: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
8303: }
8304: } /* end if covariate */
8305: } /* nlstate */
8306: fprintf(ficgp,"\nset out; unset label;\n");
8307: } /* end cpt state*/
8308: } /* end covariate */
1.296 brouard 8309: } /* End if prevbcast */
1.268 brouard 8310:
1.227 brouard 8311:
1.238 brouard 8312: /* 9eme writing MLE parameters */
8313: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 8314: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 8315: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 8316: for(k=1; k <=(nlstate+ndeath); k++){
8317: if (k != i) {
1.227 brouard 8318: fprintf(ficgp,"# current state %d\n",k);
8319: for(j=1; j <=ncovmodel; j++){
8320: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
8321: jk++;
8322: }
8323: fprintf(ficgp,"\n");
1.126 brouard 8324: }
8325: }
1.223 brouard 8326: }
1.187 brouard 8327: fprintf(ficgp,"##############\n#\n");
1.227 brouard 8328:
1.145 brouard 8329: /*goto avoid;*/
1.238 brouard 8330: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
8331: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 8332: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
8333: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
8334: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
8335: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
8336: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
8337: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
8338: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
8339: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
8340: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
8341: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
8342: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
8343: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
8344: fprintf(ficgp,"#\n");
1.223 brouard 8345: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 8346: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.237 brouard 8347: fprintf(ficgp,"#model=%s \n",model);
1.238 brouard 8348: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.264 brouard 8349: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/* to be checked */
8350: for(k1=1; k1 <=m; k1++) /* For each combination of covariate */
1.237 brouard 8351: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.264 brouard 8352: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 8353: continue;
1.264 brouard 8354: fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1);
8355: strcpy(gplotlabel,"(");
1.276 brouard 8356: /*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*/
1.264 brouard 8357: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
8358: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
8359: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8360: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8361: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8362: vlv= nbcode[Tvaraff[k]][lv];
8363: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
8364: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
8365: }
1.237 brouard 8366: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8367: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 8368: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 8369: }
1.264 brouard 8370: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 8371: fprintf(ficgp,"\n#\n");
1.264 brouard 8372: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
1.276 brouard 8373: fprintf(ficgp,"\nset key outside ");
8374: /* fprintf(ficgp,"\nset label \"%s\" at graph 1.2,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel); */
8375: fprintf(ficgp,"\nset title \"%s\" font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 8376: fprintf(ficgp,"\nset ter svg size 640, 480 ");
8377: if (ng==1){
8378: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
8379: fprintf(ficgp,"\nunset log y");
8380: }else if (ng==2){
8381: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
8382: fprintf(ficgp,"\nset log y");
8383: }else if (ng==3){
8384: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
8385: fprintf(ficgp,"\nset log y");
8386: }else
8387: fprintf(ficgp,"\nunset title ");
8388: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
8389: i=1;
8390: for(k2=1; k2<=nlstate; k2++) {
8391: k3=i;
8392: for(k=1; k<=(nlstate+ndeath); k++) {
8393: if (k != k2){
8394: switch( ng) {
8395: case 1:
8396: if(nagesqr==0)
8397: fprintf(ficgp," p%d+p%d*x",i,i+1);
8398: else /* nagesqr =1 */
8399: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
8400: break;
8401: case 2: /* ng=2 */
8402: if(nagesqr==0)
8403: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
8404: else /* nagesqr =1 */
8405: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
8406: break;
8407: case 3:
8408: if(nagesqr==0)
8409: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
8410: else /* nagesqr =1 */
8411: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
8412: break;
8413: }
8414: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 8415: ijp=1; /* product no age */
8416: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
8417: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 8418: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.329 ! brouard 8419: switch(Typevar[j]){
! 8420: case 1:
! 8421: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
! 8422: if(j==Tage[ij]) { /* Product by age To be looked at!!*//* Bug valgrind */
! 8423: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
! 8424: if(DummyV[j]==0){/* Bug valgrind */
! 8425: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
! 8426: }else{ /* quantitative */
! 8427: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
! 8428: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
! 8429: }
! 8430: ij++;
1.268 brouard 8431: }
1.237 brouard 8432: }
1.329 ! brouard 8433: }
! 8434: break;
! 8435: case 2:
! 8436: if(cptcovprod >0){
! 8437: if(j==Tprod[ijp]) { /* */
! 8438: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
! 8439: if(ijp <=cptcovprod) { /* Product */
! 8440: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
! 8441: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
! 8442: /* 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)]); */
! 8443: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
! 8444: }else{ /* Vn is dummy and Vm is quanti */
! 8445: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
! 8446: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
! 8447: }
! 8448: }else{ /* Vn*Vm Vn is quanti */
! 8449: if(DummyV[Tvard[ijp][2]]==0){
! 8450: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
! 8451: }else{ /* Both quanti */
! 8452: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
! 8453: }
1.268 brouard 8454: }
1.329 ! brouard 8455: ijp++;
1.237 brouard 8456: }
1.329 ! brouard 8457: } /* end Tprod */
! 8458: }
! 8459: break;
! 8460: case 0:
! 8461: /* simple covariate */
1.264 brouard 8462: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 8463: if(Dummy[j]==0){
8464: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
8465: }else{ /* quantitative */
8466: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 8467: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 8468: }
1.329 ! brouard 8469: /* end simple */
! 8470: break;
! 8471: default:
! 8472: break;
! 8473: } /* end switch */
1.237 brouard 8474: } /* end j */
1.329 ! brouard 8475: }else{ /* k=k2 */
! 8476: if(ng !=1 ){ /* For logit formula of log p11 is more difficult to get */
! 8477: fprintf(ficgp," (1.");i=i-ncovmodel;
! 8478: }else
! 8479: i=i-ncovmodel;
1.223 brouard 8480: }
1.227 brouard 8481:
1.223 brouard 8482: if(ng != 1){
8483: fprintf(ficgp,")/(1");
1.227 brouard 8484:
1.264 brouard 8485: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 8486: if(nagesqr==0)
1.264 brouard 8487: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 8488: else /* nagesqr =1 */
1.264 brouard 8489: 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 8490:
1.223 brouard 8491: ij=1;
1.329 ! brouard 8492: ijp=1;
! 8493: /* for(j=3; j <=ncovmodel-nagesqr; j++){ */
! 8494: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
! 8495: switch(Typevar[j]){
! 8496: case 1:
! 8497: if(cptcovage >0){
! 8498: if(j==Tage[ij]) { /* Bug valgrind */
! 8499: if(ij <=cptcovage) { /* Bug valgrind */
! 8500: if(DummyV[j]==0){/* Bug valgrind */
! 8501: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]); */
! 8502: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,nbcode[Tvar[j]][codtabm(k1,j)]); */
! 8503: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]);
! 8504: /* fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);; */
! 8505: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
! 8506: }else{ /* quantitative */
! 8507: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
! 8508: fprintf(ficgp,"+p%d*%f*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
! 8509: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
! 8510: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
! 8511: }
! 8512: ij++;
! 8513: }
! 8514: }
! 8515: }
! 8516: break;
! 8517: case 2:
! 8518: if(cptcovprod >0){
! 8519: if(j==Tprod[ijp]) { /* */
! 8520: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
! 8521: if(ijp <=cptcovprod) { /* Product */
! 8522: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
! 8523: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
! 8524: /* 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)]); */
! 8525: fprintf(ficgp,"+p%d*%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
! 8526: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]); */
! 8527: }else{ /* Vn is dummy and Vm is quanti */
! 8528: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
! 8529: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
! 8530: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
! 8531: }
! 8532: }else{ /* Vn*Vm Vn is quanti */
! 8533: if(DummyV[Tvard[ijp][2]]==0){
! 8534: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
! 8535: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]); */
! 8536: }else{ /* Both quanti */
! 8537: fprintf(ficgp,"+p%d*%f*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
! 8538: /* fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
! 8539: }
! 8540: }
! 8541: ijp++;
! 8542: }
! 8543: } /* end Tprod */
! 8544: } /* end if */
! 8545: break;
! 8546: case 0:
! 8547: /* simple covariate */
! 8548: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
! 8549: if(Dummy[j]==0){
! 8550: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
! 8551: fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]); /* */
! 8552: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
! 8553: }else{ /* quantitative */
! 8554: fprintf(ficgp,"+p%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* */
! 8555: /* fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* *\/ */
! 8556: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
! 8557: }
! 8558: /* end simple */
! 8559: /* fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);/\* Valgrind bug nbcode *\/ */
! 8560: break;
! 8561: default:
! 8562: break;
! 8563: } /* end switch */
1.223 brouard 8564: }
8565: fprintf(ficgp,")");
8566: }
8567: fprintf(ficgp,")");
8568: if(ng ==2)
1.276 brouard 8569: 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 8570: else /* ng= 3 */
1.276 brouard 8571: 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);
1.329 ! brouard 8572: }else{ /* end ng <> 1 */
1.223 brouard 8573: if( k !=k2) /* logit p11 is hard to draw */
1.276 brouard 8574: 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 8575: }
8576: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
8577: fprintf(ficgp,",");
8578: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
8579: fprintf(ficgp,",");
8580: i=i+ncovmodel;
8581: } /* end k */
8582: } /* end k2 */
1.276 brouard 8583: /* fprintf(ficgp,"\n set out; unset label;set key default;\n"); */
8584: fprintf(ficgp,"\n set out; unset title;set key default;\n");
1.264 brouard 8585: } /* end k1 */
1.223 brouard 8586: } /* end ng */
8587: /* avoid: */
8588: fflush(ficgp);
1.126 brouard 8589: } /* end gnuplot */
8590:
8591:
8592: /*************** Moving average **************/
1.219 brouard 8593: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 8594: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 8595:
1.222 brouard 8596: int i, cpt, cptcod;
8597: int modcovmax =1;
8598: int mobilavrange, mob;
8599: int iage=0;
1.288 brouard 8600: int firstA1=0, firstA2=0;
1.222 brouard 8601:
1.266 brouard 8602: double sum=0., sumr=0.;
1.222 brouard 8603: double age;
1.266 brouard 8604: double *sumnewp, *sumnewm, *sumnewmr;
8605: double *agemingood, *agemaxgood;
8606: double *agemingoodr, *agemaxgoodr;
1.222 brouard 8607:
8608:
1.278 brouard 8609: /* modcovmax=2*cptcoveff; Max number of modalities. We suppose */
8610: /* a covariate has 2 modalities, should be equal to ncovcombmax */
1.222 brouard 8611:
8612: sumnewp = vector(1,ncovcombmax);
8613: sumnewm = vector(1,ncovcombmax);
1.266 brouard 8614: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 8615: agemingood = vector(1,ncovcombmax);
1.266 brouard 8616: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 8617: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 8618: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 8619:
8620: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 8621: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 8622: sumnewp[cptcod]=0.;
1.266 brouard 8623: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
8624: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 8625: }
8626: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
8627:
1.266 brouard 8628: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
8629: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 8630: else mobilavrange=mobilav;
8631: for (age=bage; age<=fage; age++)
8632: for (i=1; i<=nlstate;i++)
8633: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
8634: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8635: /* We keep the original values on the extreme ages bage, fage and for
8636: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
8637: we use a 5 terms etc. until the borders are no more concerned.
8638: */
8639: for (mob=3;mob <=mobilavrange;mob=mob+2){
8640: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 8641: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
8642: sumnewm[cptcod]=0.;
8643: for (i=1; i<=nlstate;i++){
1.222 brouard 8644: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
8645: for (cpt=1;cpt<=(mob-1)/2;cpt++){
8646: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
8647: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
8648: }
8649: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 8650: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8651: } /* end i */
8652: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
8653: } /* end cptcod */
1.222 brouard 8654: }/* end age */
8655: }/* end mob */
1.266 brouard 8656: }else{
8657: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 8658: return -1;
1.266 brouard 8659: }
8660:
8661: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 8662: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
8663: if(invalidvarcomb[cptcod]){
8664: printf("\nCombination (%d) ignored because no cases \n",cptcod);
8665: continue;
8666: }
1.219 brouard 8667:
1.266 brouard 8668: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
8669: sumnewm[cptcod]=0.;
8670: sumnewmr[cptcod]=0.;
8671: for (i=1; i<=nlstate;i++){
8672: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8673: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8674: }
8675: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8676: agemingoodr[cptcod]=age;
8677: }
8678: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8679: agemingood[cptcod]=age;
8680: }
8681: } /* age */
8682: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 8683: sumnewm[cptcod]=0.;
1.266 brouard 8684: sumnewmr[cptcod]=0.;
1.222 brouard 8685: for (i=1; i<=nlstate;i++){
8686: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8687: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8688: }
8689: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8690: agemaxgoodr[cptcod]=age;
1.222 brouard 8691: }
8692: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 8693: agemaxgood[cptcod]=age;
8694: }
8695: } /* age */
8696: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
8697: /* but they will change */
1.288 brouard 8698: firstA1=0;firstA2=0;
1.266 brouard 8699: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
8700: sumnewm[cptcod]=0.;
8701: sumnewmr[cptcod]=0.;
8702: for (i=1; i<=nlstate;i++){
8703: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8704: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8705: }
8706: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8707: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8708: agemaxgoodr[cptcod]=age; /* age min */
8709: for (i=1; i<=nlstate;i++)
8710: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8711: }else{ /* bad we change the value with the values of good ages */
8712: for (i=1; i<=nlstate;i++){
8713: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
8714: } /* i */
8715: } /* end bad */
8716: }else{
8717: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8718: agemaxgood[cptcod]=age;
8719: }else{ /* bad we change the value with the values of good ages */
8720: for (i=1; i<=nlstate;i++){
8721: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
8722: } /* i */
8723: } /* end bad */
8724: }/* end else */
8725: sum=0.;sumr=0.;
8726: for (i=1; i<=nlstate;i++){
8727: sum+=mobaverage[(int)age][i][cptcod];
8728: sumr+=probs[(int)age][i][cptcod];
8729: }
8730: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.288 brouard 8731: if(!firstA1){
8732: firstA1=1;
8733: 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);
8734: }
8735: 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 8736: } /* end bad */
8737: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8738: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.288 brouard 8739: if(!firstA2){
8740: firstA2=1;
8741: 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);
8742: }
8743: 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 8744: } /* end bad */
8745: }/* age */
1.266 brouard 8746:
8747: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 8748: sumnewm[cptcod]=0.;
1.266 brouard 8749: sumnewmr[cptcod]=0.;
1.222 brouard 8750: for (i=1; i<=nlstate;i++){
8751: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8752: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8753: }
8754: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8755: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
8756: agemingoodr[cptcod]=age;
8757: for (i=1; i<=nlstate;i++)
8758: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8759: }else{ /* bad we change the value with the values of good ages */
8760: for (i=1; i<=nlstate;i++){
8761: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
8762: } /* i */
8763: } /* end bad */
8764: }else{
8765: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8766: agemingood[cptcod]=age;
8767: }else{ /* bad */
8768: for (i=1; i<=nlstate;i++){
8769: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
8770: } /* i */
8771: } /* end bad */
8772: }/* end else */
8773: sum=0.;sumr=0.;
8774: for (i=1; i<=nlstate;i++){
8775: sum+=mobaverage[(int)age][i][cptcod];
8776: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 8777: }
1.266 brouard 8778: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 8779: 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 8780: } /* end bad */
8781: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8782: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 8783: 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 8784: } /* end bad */
8785: }/* age */
1.266 brouard 8786:
1.222 brouard 8787:
8788: for (age=bage; age<=fage; age++){
1.235 brouard 8789: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 8790: sumnewp[cptcod]=0.;
8791: sumnewm[cptcod]=0.;
8792: for (i=1; i<=nlstate;i++){
8793: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
8794: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8795: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
8796: }
8797: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
8798: }
8799: /* printf("\n"); */
8800: /* } */
1.266 brouard 8801:
1.222 brouard 8802: /* brutal averaging */
1.266 brouard 8803: /* for (i=1; i<=nlstate;i++){ */
8804: /* for (age=1; age<=bage; age++){ */
8805: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
8806: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8807: /* } */
8808: /* for (age=fage; age<=AGESUP; age++){ */
8809: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
8810: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8811: /* } */
8812: /* } /\* end i status *\/ */
8813: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
8814: /* for (age=1; age<=AGESUP; age++){ */
8815: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
8816: /* mobaverage[(int)age][i][cptcod]=0.; */
8817: /* } */
8818: /* } */
1.222 brouard 8819: }/* end cptcod */
1.266 brouard 8820: free_vector(agemaxgoodr,1, ncovcombmax);
8821: free_vector(agemaxgood,1, ncovcombmax);
8822: free_vector(agemingood,1, ncovcombmax);
8823: free_vector(agemingoodr,1, ncovcombmax);
8824: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 8825: free_vector(sumnewm,1, ncovcombmax);
8826: free_vector(sumnewp,1, ncovcombmax);
8827: return 0;
8828: }/* End movingaverage */
1.218 brouard 8829:
1.126 brouard 8830:
1.296 brouard 8831:
1.126 brouard 8832: /************** Forecasting ******************/
1.296 brouard 8833: /* 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)*/
8834: 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){
8835: /* dateintemean, mean date of interviews
8836: dateprojd, year, month, day of starting projection
8837: dateprojf date of end of projection;year of end of projection (same day and month as proj1).
1.126 brouard 8838: agemin, agemax range of age
8839: dateprev1 dateprev2 range of dates during which prevalence is computed
8840: */
1.296 brouard 8841: /* double anprojd, mprojd, jprojd; */
8842: /* double anprojf, mprojf, jprojf; */
1.267 brouard 8843: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 8844: double agec; /* generic age */
1.296 brouard 8845: double agelim, ppij, yp,yp1,yp2;
1.126 brouard 8846: double *popeffectif,*popcount;
8847: double ***p3mat;
1.218 brouard 8848: /* double ***mobaverage; */
1.126 brouard 8849: char fileresf[FILENAMELENGTH];
8850:
8851: agelim=AGESUP;
1.211 brouard 8852: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8853: in each health status at the date of interview (if between dateprev1 and dateprev2).
8854: We still use firstpass and lastpass as another selection.
8855: */
1.214 brouard 8856: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8857: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 8858:
1.201 brouard 8859: strcpy(fileresf,"F_");
8860: strcat(fileresf,fileresu);
1.126 brouard 8861: if((ficresf=fopen(fileresf,"w"))==NULL) {
8862: printf("Problem with forecast resultfile: %s\n", fileresf);
8863: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
8864: }
1.235 brouard 8865: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
8866: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 8867:
1.225 brouard 8868: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 8869:
8870:
8871: stepsize=(int) (stepm+YEARM-1)/YEARM;
8872: if (stepm<=12) stepsize=1;
8873: if(estepm < stepm){
8874: printf ("Problem %d lower than %d\n",estepm, stepm);
8875: }
1.270 brouard 8876: else{
8877: hstepm=estepm;
8878: }
8879: if(estepm > stepm){ /* Yes every two year */
8880: stepsize=2;
8881: }
1.296 brouard 8882: hstepm=hstepm/stepm;
1.126 brouard 8883:
1.296 brouard 8884:
8885: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
8886: /* fractional in yp1 *\/ */
8887: /* aintmean=yp; */
8888: /* yp2=modf((yp1*12),&yp); */
8889: /* mintmean=yp; */
8890: /* yp1=modf((yp2*30.5),&yp); */
8891: /* jintmean=yp; */
8892: /* if(jintmean==0) jintmean=1; */
8893: /* if(mintmean==0) mintmean=1; */
1.126 brouard 8894:
1.296 brouard 8895:
8896: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */
8897: /* date2dmy(dateprojd,&jprojd, &mprojd, &anprojd); */
8898: /* date2dmy(dateprojf,&jprojf, &mprojf, &anprojf); */
1.227 brouard 8899: i1=pow(2,cptcoveff);
1.126 brouard 8900: if (cptcovn < 1){i1=1;}
8901:
1.296 brouard 8902: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.126 brouard 8903:
8904: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 8905:
1.126 brouard 8906: /* if (h==(int)(YEARM*yearp)){ */
1.235 brouard 8907: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8908: for(k=1; k<=i1;k++){
1.253 brouard 8909: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 8910: continue;
1.227 brouard 8911: if(invalidvarcomb[k]){
8912: printf("\nCombination (%d) projection ignored because no cases \n",k);
8913: continue;
8914: }
8915: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
8916: for(j=1;j<=cptcoveff;j++) {
8917: fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8918: }
1.235 brouard 8919: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 8920: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.235 brouard 8921: }
1.227 brouard 8922: fprintf(ficresf," yearproj age");
8923: for(j=1; j<=nlstate+ndeath;j++){
8924: for(i=1; i<=nlstate;i++)
8925: fprintf(ficresf," p%d%d",i,j);
8926: fprintf(ficresf," wp.%d",j);
8927: }
1.296 brouard 8928: for (yearp=0; yearp<=(anprojf-anprojd);yearp +=stepsize) {
1.227 brouard 8929: fprintf(ficresf,"\n");
1.296 brouard 8930: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jprojd,mprojd,anprojd+yearp);
1.270 brouard 8931: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
8932: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 8933: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
8934: nhstepm = nhstepm/hstepm;
8935: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8936: oldm=oldms;savm=savms;
1.268 brouard 8937: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 8938: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 8939: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 8940: for (h=0; h<=nhstepm; h++){
8941: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 8942: break;
8943: }
8944: }
8945: fprintf(ficresf,"\n");
8946: for(j=1;j<=cptcoveff;j++)
8947: fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.296 brouard 8948: fprintf(ficresf,"%.f %.f ",anprojd+yearp,agec+h*hstepm/YEARM*stepm);
1.268 brouard 8949:
8950: for(j=1; j<=nlstate+ndeath;j++) {
8951: ppij=0.;
8952: for(i=1; i<=nlstate;i++) {
1.278 brouard 8953: if (mobilav>=1)
8954: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
8955: else { /* even if mobilav==-1 we use mobaverage, probs may not sums to 1 */
8956: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
8957: }
1.268 brouard 8958: fprintf(ficresf," %.3f", p3mat[i][j][h]);
8959: } /* end i */
8960: fprintf(ficresf," %.3f", ppij);
8961: }/* end j */
1.227 brouard 8962: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8963: } /* end agec */
1.266 brouard 8964: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
8965: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 8966: } /* end yearp */
8967: } /* end k */
1.219 brouard 8968:
1.126 brouard 8969: fclose(ficresf);
1.215 brouard 8970: printf("End of Computing forecasting \n");
8971: fprintf(ficlog,"End of Computing forecasting\n");
8972:
1.126 brouard 8973: }
8974:
1.269 brouard 8975: /************** Back Forecasting ******************/
1.296 brouard 8976: /* 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){ */
8977: 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){
8978: /* back1, year, month, day of starting backprojection
1.267 brouard 8979: agemin, agemax range of age
8980: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 8981: anback2 year of end of backprojection (same day and month as back1).
8982: prevacurrent and prev are prevalences.
1.267 brouard 8983: */
8984: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
8985: double agec; /* generic age */
1.302 brouard 8986: double agelim, ppij, ppi, yp,yp1,yp2; /* ,jintmean,mintmean,aintmean;*/
1.267 brouard 8987: double *popeffectif,*popcount;
8988: double ***p3mat;
8989: /* double ***mobaverage; */
8990: char fileresfb[FILENAMELENGTH];
8991:
1.268 brouard 8992: agelim=AGEINF;
1.267 brouard 8993: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8994: in each health status at the date of interview (if between dateprev1 and dateprev2).
8995: We still use firstpass and lastpass as another selection.
8996: */
8997: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8998: /* firstpass, lastpass, stepm, weightopt, model); */
8999:
9000: /*Do we need to compute prevalence again?*/
9001:
9002: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
9003:
9004: strcpy(fileresfb,"FB_");
9005: strcat(fileresfb,fileresu);
9006: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
9007: printf("Problem with back forecast resultfile: %s\n", fileresfb);
9008: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
9009: }
9010: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
9011: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
9012:
9013: if (cptcoveff==0) ncodemax[cptcoveff]=1;
9014:
9015:
9016: stepsize=(int) (stepm+YEARM-1)/YEARM;
9017: if (stepm<=12) stepsize=1;
9018: if(estepm < stepm){
9019: printf ("Problem %d lower than %d\n",estepm, stepm);
9020: }
1.270 brouard 9021: else{
9022: hstepm=estepm;
9023: }
9024: if(estepm >= stepm){ /* Yes every two year */
9025: stepsize=2;
9026: }
1.267 brouard 9027:
9028: hstepm=hstepm/stepm;
1.296 brouard 9029: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
9030: /* fractional in yp1 *\/ */
9031: /* aintmean=yp; */
9032: /* yp2=modf((yp1*12),&yp); */
9033: /* mintmean=yp; */
9034: /* yp1=modf((yp2*30.5),&yp); */
9035: /* jintmean=yp; */
9036: /* if(jintmean==0) jintmean=1; */
9037: /* if(mintmean==0) jintmean=1; */
1.267 brouard 9038:
9039: i1=pow(2,cptcoveff);
9040: if (cptcovn < 1){i1=1;}
9041:
1.296 brouard 9042: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
9043: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 9044:
9045: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
9046:
9047: for(nres=1; nres <= nresult; nres++) /* For each resultline */
9048: for(k=1; k<=i1;k++){
9049: if(i1 != 1 && TKresult[nres]!= k)
9050: continue;
9051: if(invalidvarcomb[k]){
9052: printf("\nCombination (%d) projection ignored because no cases \n",k);
9053: continue;
9054: }
1.268 brouard 9055: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.267 brouard 9056: for(j=1;j<=cptcoveff;j++) {
9057: fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9058: }
9059: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
9060: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
9061: }
9062: fprintf(ficresfb," yearbproj age");
9063: for(j=1; j<=nlstate+ndeath;j++){
9064: for(i=1; i<=nlstate;i++)
1.268 brouard 9065: fprintf(ficresfb," b%d%d",i,j);
9066: fprintf(ficresfb," b.%d",j);
1.267 brouard 9067: }
1.296 brouard 9068: for (yearp=0; yearp>=(anbackf-anbackd);yearp -=stepsize) {
1.267 brouard 9069: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
9070: fprintf(ficresfb,"\n");
1.296 brouard 9071: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jbackd,mbackd,anbackd+yearp);
1.273 brouard 9072: /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
1.270 brouard 9073: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
9074: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 9075: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
1.271 brouard 9076: nhstepm=(int) (agec-agelim) *YEARM/stepm;/* nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
1.267 brouard 9077: nhstepm = nhstepm/hstepm;
9078: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9079: oldm=oldms;savm=savms;
1.268 brouard 9080: /* computes hbxij at age agec over 1 to nhstepm */
1.271 brouard 9081: /* printf("####prevbackforecast debug agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
1.267 brouard 9082: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 9083: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
9084: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
9085: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 9086: for (h=0; h<=nhstepm; h++){
1.268 brouard 9087: if (h*hstepm/YEARM*stepm ==-yearp) {
9088: break;
9089: }
9090: }
9091: fprintf(ficresfb,"\n");
9092: for(j=1;j<=cptcoveff;j++)
9093: fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.296 brouard 9094: fprintf(ficresfb,"%.f %.f ",anbackd+yearp,agec-h*hstepm/YEARM*stepm);
1.268 brouard 9095: for(i=1; i<=nlstate+ndeath;i++) {
9096: ppij=0.;ppi=0.;
9097: for(j=1; j<=nlstate;j++) {
9098: /* if (mobilav==1) */
1.269 brouard 9099: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
9100: ppi=ppi+prevacurrent[(int)agec][j][k];
9101: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
9102: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 9103: /* else { */
9104: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
9105: /* } */
1.268 brouard 9106: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
9107: } /* end j */
9108: if(ppi <0.99){
9109: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
9110: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
9111: }
9112: fprintf(ficresfb," %.3f", ppij);
9113: }/* end j */
1.267 brouard 9114: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9115: } /* end agec */
9116: } /* end yearp */
9117: } /* end k */
1.217 brouard 9118:
1.267 brouard 9119: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 9120:
1.267 brouard 9121: fclose(ficresfb);
9122: printf("End of Computing Back forecasting \n");
9123: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 9124:
1.267 brouard 9125: }
1.217 brouard 9126:
1.269 brouard 9127: /* Variance of prevalence limit: varprlim */
9128: 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 9129: /*------- Variance of forward period (stable) prevalence------*/
1.269 brouard 9130:
9131: char fileresvpl[FILENAMELENGTH];
9132: FILE *ficresvpl;
9133: double **oldm, **savm;
9134: double **varpl; /* Variances of prevalence limits by age */
9135: int i1, k, nres, j ;
9136:
9137: strcpy(fileresvpl,"VPL_");
9138: strcat(fileresvpl,fileresu);
9139: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
1.288 brouard 9140: printf("Problem with variance of forward period (stable) prevalence resultfile: %s\n", fileresvpl);
1.269 brouard 9141: exit(0);
9142: }
1.288 brouard 9143: printf("Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
9144: fprintf(ficlog, "Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
1.269 brouard 9145:
9146: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
9147: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
9148:
9149: i1=pow(2,cptcoveff);
9150: if (cptcovn < 1){i1=1;}
9151:
9152: for(nres=1; nres <= nresult; nres++) /* For each resultline */
9153: for(k=1; k<=i1;k++){
9154: if(i1 != 1 && TKresult[nres]!= k)
9155: continue;
9156: fprintf(ficresvpl,"\n#****** ");
9157: printf("\n#****** ");
9158: fprintf(ficlog,"\n#****** ");
9159: for(j=1;j<=cptcoveff;j++) {
9160: fprintf(ficresvpl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9161: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9162: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9163: }
9164: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
9165: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
9166: fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
9167: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
9168: }
9169: fprintf(ficresvpl,"******\n");
9170: printf("******\n");
9171: fprintf(ficlog,"******\n");
9172:
9173: varpl=matrix(1,nlstate,(int) bage, (int) fage);
9174: oldm=oldms;savm=savms;
9175: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
9176: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
9177: /*}*/
9178: }
9179:
9180: fclose(ficresvpl);
1.288 brouard 9181: printf("done variance-covariance of forward period prevalence\n");fflush(stdout);
9182: fprintf(ficlog,"done variance-covariance of forward period prevalence\n");fflush(ficlog);
1.269 brouard 9183:
9184: }
9185: /* Variance of back prevalence: varbprlim */
9186: 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){
9187: /*------- Variance of back (stable) prevalence------*/
9188:
9189: char fileresvbl[FILENAMELENGTH];
9190: FILE *ficresvbl;
9191:
9192: double **oldm, **savm;
9193: double **varbpl; /* Variances of back prevalence limits by age */
9194: int i1, k, nres, j ;
9195:
9196: strcpy(fileresvbl,"VBL_");
9197: strcat(fileresvbl,fileresu);
9198: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
9199: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
9200: exit(0);
9201: }
9202: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
9203: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
9204:
9205:
9206: i1=pow(2,cptcoveff);
9207: if (cptcovn < 1){i1=1;}
9208:
9209: for(nres=1; nres <= nresult; nres++) /* For each resultline */
9210: for(k=1; k<=i1;k++){
9211: if(i1 != 1 && TKresult[nres]!= k)
9212: continue;
9213: fprintf(ficresvbl,"\n#****** ");
9214: printf("\n#****** ");
9215: fprintf(ficlog,"\n#****** ");
9216: for(j=1;j<=cptcoveff;j++) {
9217: fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9218: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9219: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9220: }
9221: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
9222: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
9223: fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
9224: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
9225: }
9226: fprintf(ficresvbl,"******\n");
9227: printf("******\n");
9228: fprintf(ficlog,"******\n");
9229:
9230: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
9231: oldm=oldms;savm=savms;
9232:
9233: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
9234: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
9235: /*}*/
9236: }
9237:
9238: fclose(ficresvbl);
9239: printf("done variance-covariance of back prevalence\n");fflush(stdout);
9240: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
9241:
9242: } /* End of varbprlim */
9243:
1.126 brouard 9244: /************** Forecasting *****not tested NB*************/
1.227 brouard 9245: /* 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 9246:
1.227 brouard 9247: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
9248: /* int *popage; */
9249: /* double calagedatem, agelim, kk1, kk2; */
9250: /* double *popeffectif,*popcount; */
9251: /* double ***p3mat,***tabpop,***tabpopprev; */
9252: /* /\* double ***mobaverage; *\/ */
9253: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 9254:
1.227 brouard 9255: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9256: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9257: /* agelim=AGESUP; */
9258: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 9259:
1.227 brouard 9260: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 9261:
9262:
1.227 brouard 9263: /* strcpy(filerespop,"POP_"); */
9264: /* strcat(filerespop,fileresu); */
9265: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
9266: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
9267: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
9268: /* } */
9269: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
9270: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 9271:
1.227 brouard 9272: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 9273:
1.227 brouard 9274: /* /\* if (mobilav!=0) { *\/ */
9275: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
9276: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
9277: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
9278: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
9279: /* /\* } *\/ */
9280: /* /\* } *\/ */
1.126 brouard 9281:
1.227 brouard 9282: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
9283: /* if (stepm<=12) stepsize=1; */
1.126 brouard 9284:
1.227 brouard 9285: /* agelim=AGESUP; */
1.126 brouard 9286:
1.227 brouard 9287: /* hstepm=1; */
9288: /* hstepm=hstepm/stepm; */
1.218 brouard 9289:
1.227 brouard 9290: /* if (popforecast==1) { */
9291: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
9292: /* printf("Problem with population file : %s\n",popfile);exit(0); */
9293: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
9294: /* } */
9295: /* popage=ivector(0,AGESUP); */
9296: /* popeffectif=vector(0,AGESUP); */
9297: /* popcount=vector(0,AGESUP); */
1.126 brouard 9298:
1.227 brouard 9299: /* i=1; */
9300: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 9301:
1.227 brouard 9302: /* imx=i; */
9303: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
9304: /* } */
1.218 brouard 9305:
1.227 brouard 9306: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
9307: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
9308: /* k=k+1; */
9309: /* fprintf(ficrespop,"\n#******"); */
9310: /* for(j=1;j<=cptcoveff;j++) { */
9311: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
9312: /* } */
9313: /* fprintf(ficrespop,"******\n"); */
9314: /* fprintf(ficrespop,"# Age"); */
9315: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
9316: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 9317:
1.227 brouard 9318: /* for (cpt=0; cpt<=0;cpt++) { */
9319: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 9320:
1.227 brouard 9321: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
9322: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
9323: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 9324:
1.227 brouard 9325: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9326: /* oldm=oldms;savm=savms; */
9327: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 9328:
1.227 brouard 9329: /* for (h=0; h<=nhstepm; h++){ */
9330: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
9331: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
9332: /* } */
9333: /* for(j=1; j<=nlstate+ndeath;j++) { */
9334: /* kk1=0.;kk2=0; */
9335: /* for(i=1; i<=nlstate;i++) { */
9336: /* if (mobilav==1) */
9337: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
9338: /* else { */
9339: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
9340: /* } */
9341: /* } */
9342: /* if (h==(int)(calagedatem+12*cpt)){ */
9343: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
9344: /* /\*fprintf(ficrespop," %.3f", kk1); */
9345: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
9346: /* } */
9347: /* } */
9348: /* for(i=1; i<=nlstate;i++){ */
9349: /* kk1=0.; */
9350: /* for(j=1; j<=nlstate;j++){ */
9351: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
9352: /* } */
9353: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
9354: /* } */
1.218 brouard 9355:
1.227 brouard 9356: /* if (h==(int)(calagedatem+12*cpt)) */
9357: /* for(j=1; j<=nlstate;j++) */
9358: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
9359: /* } */
9360: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9361: /* } */
9362: /* } */
1.218 brouard 9363:
1.227 brouard 9364: /* /\******\/ */
1.218 brouard 9365:
1.227 brouard 9366: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
9367: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
9368: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
9369: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
9370: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 9371:
1.227 brouard 9372: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9373: /* oldm=oldms;savm=savms; */
9374: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
9375: /* for (h=0; h<=nhstepm; h++){ */
9376: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
9377: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
9378: /* } */
9379: /* for(j=1; j<=nlstate+ndeath;j++) { */
9380: /* kk1=0.;kk2=0; */
9381: /* for(i=1; i<=nlstate;i++) { */
9382: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
9383: /* } */
9384: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
9385: /* } */
9386: /* } */
9387: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9388: /* } */
9389: /* } */
9390: /* } */
9391: /* } */
1.218 brouard 9392:
1.227 brouard 9393: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 9394:
1.227 brouard 9395: /* if (popforecast==1) { */
9396: /* free_ivector(popage,0,AGESUP); */
9397: /* free_vector(popeffectif,0,AGESUP); */
9398: /* free_vector(popcount,0,AGESUP); */
9399: /* } */
9400: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9401: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9402: /* fclose(ficrespop); */
9403: /* } /\* End of popforecast *\/ */
1.218 brouard 9404:
1.126 brouard 9405: int fileappend(FILE *fichier, char *optionfich)
9406: {
9407: if((fichier=fopen(optionfich,"a"))==NULL) {
9408: printf("Problem with file: %s\n", optionfich);
9409: fprintf(ficlog,"Problem with file: %s\n", optionfich);
9410: return (0);
9411: }
9412: fflush(fichier);
9413: return (1);
9414: }
9415:
9416:
9417: /**************** function prwizard **********************/
9418: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
9419: {
9420:
9421: /* Wizard to print covariance matrix template */
9422:
1.164 brouard 9423: char ca[32], cb[32];
9424: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 9425: int numlinepar;
9426:
9427: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
9428: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
9429: for(i=1; i <=nlstate; i++){
9430: jj=0;
9431: for(j=1; j <=nlstate+ndeath; j++){
9432: if(j==i) continue;
9433: jj++;
9434: /*ca[0]= k+'a'-1;ca[1]='\0';*/
9435: printf("%1d%1d",i,j);
9436: fprintf(ficparo,"%1d%1d",i,j);
9437: for(k=1; k<=ncovmodel;k++){
9438: /* printf(" %lf",param[i][j][k]); */
9439: /* fprintf(ficparo," %lf",param[i][j][k]); */
9440: printf(" 0.");
9441: fprintf(ficparo," 0.");
9442: }
9443: printf("\n");
9444: fprintf(ficparo,"\n");
9445: }
9446: }
9447: printf("# Scales (for hessian or gradient estimation)\n");
9448: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
9449: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
9450: for(i=1; i <=nlstate; i++){
9451: jj=0;
9452: for(j=1; j <=nlstate+ndeath; j++){
9453: if(j==i) continue;
9454: jj++;
9455: fprintf(ficparo,"%1d%1d",i,j);
9456: printf("%1d%1d",i,j);
9457: fflush(stdout);
9458: for(k=1; k<=ncovmodel;k++){
9459: /* printf(" %le",delti3[i][j][k]); */
9460: /* fprintf(ficparo," %le",delti3[i][j][k]); */
9461: printf(" 0.");
9462: fprintf(ficparo," 0.");
9463: }
9464: numlinepar++;
9465: printf("\n");
9466: fprintf(ficparo,"\n");
9467: }
9468: }
9469: printf("# Covariance matrix\n");
9470: /* # 121 Var(a12)\n\ */
9471: /* # 122 Cov(b12,a12) Var(b12)\n\ */
9472: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
9473: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
9474: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
9475: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
9476: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
9477: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
9478: fflush(stdout);
9479: fprintf(ficparo,"# Covariance matrix\n");
9480: /* # 121 Var(a12)\n\ */
9481: /* # 122 Cov(b12,a12) Var(b12)\n\ */
9482: /* # ...\n\ */
9483: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
9484:
9485: for(itimes=1;itimes<=2;itimes++){
9486: jj=0;
9487: for(i=1; i <=nlstate; i++){
9488: for(j=1; j <=nlstate+ndeath; j++){
9489: if(j==i) continue;
9490: for(k=1; k<=ncovmodel;k++){
9491: jj++;
9492: ca[0]= k+'a'-1;ca[1]='\0';
9493: if(itimes==1){
9494: printf("#%1d%1d%d",i,j,k);
9495: fprintf(ficparo,"#%1d%1d%d",i,j,k);
9496: }else{
9497: printf("%1d%1d%d",i,j,k);
9498: fprintf(ficparo,"%1d%1d%d",i,j,k);
9499: /* printf(" %.5le",matcov[i][j]); */
9500: }
9501: ll=0;
9502: for(li=1;li <=nlstate; li++){
9503: for(lj=1;lj <=nlstate+ndeath; lj++){
9504: if(lj==li) continue;
9505: for(lk=1;lk<=ncovmodel;lk++){
9506: ll++;
9507: if(ll<=jj){
9508: cb[0]= lk +'a'-1;cb[1]='\0';
9509: if(ll<jj){
9510: if(itimes==1){
9511: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
9512: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
9513: }else{
9514: printf(" 0.");
9515: fprintf(ficparo," 0.");
9516: }
9517: }else{
9518: if(itimes==1){
9519: printf(" Var(%s%1d%1d)",ca,i,j);
9520: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
9521: }else{
9522: printf(" 0.");
9523: fprintf(ficparo," 0.");
9524: }
9525: }
9526: }
9527: } /* end lk */
9528: } /* end lj */
9529: } /* end li */
9530: printf("\n");
9531: fprintf(ficparo,"\n");
9532: numlinepar++;
9533: } /* end k*/
9534: } /*end j */
9535: } /* end i */
9536: } /* end itimes */
9537:
9538: } /* end of prwizard */
9539: /******************* Gompertz Likelihood ******************************/
9540: double gompertz(double x[])
9541: {
1.302 brouard 9542: double A=0.0,B=0.,L=0.0,sump=0.,num=0.;
1.126 brouard 9543: int i,n=0; /* n is the size of the sample */
9544:
1.220 brouard 9545: for (i=1;i<=imx ; i++) {
1.126 brouard 9546: sump=sump+weight[i];
9547: /* sump=sump+1;*/
9548: num=num+1;
9549: }
1.302 brouard 9550: L=0.0;
9551: /* agegomp=AGEGOMP; */
1.126 brouard 9552: /* for (i=0; i<=imx; i++)
9553: 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]);*/
9554:
1.302 brouard 9555: for (i=1;i<=imx ; i++) {
9556: /* mu(a)=mu(agecomp)*exp(teta*(age-agegomp))
9557: mu(a)=x[1]*exp(x[2]*(age-agegomp)); x[1] and x[2] are per year.
9558: * L= Product mu(agedeces)exp(-\int_ageexam^agedc mu(u) du ) for a death between agedc (in month)
9559: * and agedc +1 month, cens[i]=0: log(x[1]/YEARM)
9560: * +
9561: * exp(-\int_ageexam^agecens mu(u) du ) when censored, cens[i]=1
9562: */
9563: if (wav[i] > 1 || agedc[i] < AGESUP) {
9564: if (cens[i] == 1){
9565: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
9566: } else if (cens[i] == 0){
1.126 brouard 9567: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
1.302 brouard 9568: +log(x[1]/YEARM) +x[2]*(agedc[i]-agegomp)+log(YEARM);
9569: } else
9570: printf("Gompertz cens[%d] neither 1 nor 0\n",i);
1.126 brouard 9571: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
1.302 brouard 9572: L=L+A*weight[i];
1.126 brouard 9573: /* printf("\ni=%d A=%f L=%lf x[1]=%lf x[2]=%lf ageex=%lf agecens=%lf cens=%d agedc=%lf weight=%lf\n",i,A,L,x[1],x[2],ageexmed[i]*12,agecens[i]*12,cens[i],agedc[i]*12,weight[i]);*/
1.302 brouard 9574: }
9575: }
1.126 brouard 9576:
1.302 brouard 9577: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
1.126 brouard 9578:
9579: return -2*L*num/sump;
9580: }
9581:
1.136 brouard 9582: #ifdef GSL
9583: /******************* Gompertz_f Likelihood ******************************/
9584: double gompertz_f(const gsl_vector *v, void *params)
9585: {
1.302 brouard 9586: double A=0.,B=0.,LL=0.0,sump=0.,num=0.;
1.136 brouard 9587: double *x= (double *) v->data;
9588: int i,n=0; /* n is the size of the sample */
9589:
9590: for (i=0;i<=imx-1 ; i++) {
9591: sump=sump+weight[i];
9592: /* sump=sump+1;*/
9593: num=num+1;
9594: }
9595:
9596:
9597: /* for (i=0; i<=imx; i++)
9598: 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]);*/
9599: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
9600: for (i=1;i<=imx ; i++)
9601: {
9602: if (cens[i] == 1 && wav[i]>1)
9603: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
9604:
9605: if (cens[i] == 0 && wav[i]>1)
9606: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
9607: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
9608:
9609: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
9610: if (wav[i] > 1 ) { /* ??? */
9611: LL=LL+A*weight[i];
9612: /* 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]);*/
9613: }
9614: }
9615:
9616: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
9617: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
9618:
9619: return -2*LL*num/sump;
9620: }
9621: #endif
9622:
1.126 brouard 9623: /******************* Printing html file ***********/
1.201 brouard 9624: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 9625: int lastpass, int stepm, int weightopt, char model[],\
9626: int imx, double p[],double **matcov,double agemortsup){
9627: int i,k;
9628:
9629: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
9630: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
9631: for (i=1;i<=2;i++)
9632: 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 9633: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 9634: fprintf(fichtm,"</ul>");
9635:
9636: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
9637:
9638: 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>");
9639:
9640: for (k=agegomp;k<(agemortsup-2);k++)
9641: 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]);
9642:
9643:
9644: fflush(fichtm);
9645: }
9646:
9647: /******************* Gnuplot file **************/
1.201 brouard 9648: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 9649:
9650: char dirfileres[132],optfileres[132];
1.164 brouard 9651:
1.126 brouard 9652: int ng;
9653:
9654:
9655: /*#ifdef windows */
9656: fprintf(ficgp,"cd \"%s\" \n",pathc);
9657: /*#endif */
9658:
9659:
9660: strcpy(dirfileres,optionfilefiname);
9661: strcpy(optfileres,"vpl");
1.199 brouard 9662: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 9663: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 9664: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 9665: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 9666: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
9667:
9668: }
9669:
1.136 brouard 9670: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
9671: {
1.126 brouard 9672:
1.136 brouard 9673: /*-------- data file ----------*/
9674: FILE *fic;
9675: char dummy[]=" ";
1.240 brouard 9676: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 9677: int lstra;
1.136 brouard 9678: int linei, month, year,iout;
1.302 brouard 9679: int noffset=0; /* This is the offset if BOM data file */
1.136 brouard 9680: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 9681: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 9682: char *stratrunc;
1.223 brouard 9683:
1.240 brouard 9684: DummyV=ivector(1,NCOVMAX); /* 1 to 3 */
9685: FixedV=ivector(1,NCOVMAX); /* 1 to 3 */
1.328 brouard 9686: for(v=1;v<NCOVMAX;v++){
9687: DummyV[v]=0;
9688: FixedV[v]=0;
9689: }
1.126 brouard 9690:
1.240 brouard 9691: for(v=1; v <=ncovcol;v++){
9692: DummyV[v]=0;
9693: FixedV[v]=0;
9694: }
9695: for(v=ncovcol+1; v <=ncovcol+nqv;v++){
9696: DummyV[v]=1;
9697: FixedV[v]=0;
9698: }
9699: for(v=ncovcol+nqv+1; v <=ncovcol+nqv+ntv;v++){
9700: DummyV[v]=0;
9701: FixedV[v]=1;
9702: }
9703: for(v=ncovcol+nqv+ntv+1; v <=ncovcol+nqv+ntv+nqtv;v++){
9704: DummyV[v]=1;
9705: FixedV[v]=1;
9706: }
9707: for(v=1; v <=ncovcol+nqv+ntv+nqtv;v++){
9708: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",v,v,DummyV[v],v,FixedV[v]);
9709: 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]);
9710: }
1.126 brouard 9711:
1.136 brouard 9712: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 9713: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
9714: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 9715: }
1.126 brouard 9716:
1.302 brouard 9717: /* Is it a BOM UTF-8 Windows file? */
9718: /* First data line */
9719: linei=0;
9720: while(fgets(line, MAXLINE, fic)) {
9721: noffset=0;
9722: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
9723: {
9724: noffset=noffset+3;
9725: printf("# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);fflush(stdout);
9726: fprintf(ficlog,"# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);
9727: fflush(ficlog); return 1;
9728: }
9729: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
9730: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
9731: {
9732: noffset=noffset+2;
1.304 brouard 9733: printf("# Error Data file '%s' is a huge UTF16BE BOM file, please convert to UTF8 or ascii file (for example with dos2unix) and rerun.\n",datafile);fflush(stdout);
9734: fprintf(ficlog,"# Error Data file '%s' is a huge UTF16BE BOM file, please convert to UTF8 or ascii file (for example with dos2unix) and rerun.\n",datafile);
1.302 brouard 9735: fflush(ficlog); return 1;
9736: }
9737: else if( line[0] == 0 && line[1] == 0)
9738: {
9739: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
9740: noffset=noffset+4;
1.304 brouard 9741: printf("# Error Data file '%s' is a huge UTF16BE BOM file, please convert to UTF8 or ascii file (for example with dos2unix) and rerun.\n",datafile);fflush(stdout);
9742: fprintf(ficlog,"# Error Data file '%s' is a huge UTF16BE BOM file, please convert to UTF8 or ascii file (for example with dos2unix) and rerun.\n",datafile);
1.302 brouard 9743: fflush(ficlog); return 1;
9744: }
9745: } else{
9746: ;/*printf(" Not a BOM file\n");*/
9747: }
9748: /* If line starts with a # it is a comment */
9749: if (line[noffset] == '#') {
9750: linei=linei+1;
9751: break;
9752: }else{
9753: break;
9754: }
9755: }
9756: fclose(fic);
9757: if((fic=fopen(datafile,"r"))==NULL) {
9758: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
9759: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
9760: }
9761: /* Not a Bom file */
9762:
1.136 brouard 9763: i=1;
9764: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
9765: linei=linei+1;
9766: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
9767: if(line[j] == '\t')
9768: line[j] = ' ';
9769: }
9770: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
9771: ;
9772: };
9773: line[j+1]=0; /* Trims blanks at end of line */
9774: if(line[0]=='#'){
9775: fprintf(ficlog,"Comment line\n%s\n",line);
9776: printf("Comment line\n%s\n",line);
9777: continue;
9778: }
9779: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 9780: strcpy(line, linetmp);
1.223 brouard 9781:
9782: /* Loops on waves */
9783: for (j=maxwav;j>=1;j--){
9784: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 9785: cutv(stra, strb, line, ' ');
9786: if(strb[0]=='.') { /* Missing value */
9787: lval=-1;
9788: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
9789: cotvar[j][ntv+iv][i]=-1; /* For performance reasons */
9790: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
9791: 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);
9792: 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);
9793: return 1;
9794: }
9795: }else{
9796: errno=0;
9797: /* what_kind_of_number(strb); */
9798: dval=strtod(strb,&endptr);
9799: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
9800: /* if(strb != endptr && *endptr == '\0') */
9801: /* dval=dlval; */
9802: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9803: if( strb[0]=='\0' || (*endptr != '\0')){
9804: 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);
9805: 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);
9806: return 1;
9807: }
9808: cotqvar[j][iv][i]=dval;
9809: cotvar[j][ntv+iv][i]=dval;
9810: }
9811: strcpy(line,stra);
1.223 brouard 9812: }/* end loop ntqv */
1.225 brouard 9813:
1.223 brouard 9814: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 9815: cutv(stra, strb, line, ' ');
9816: if(strb[0]=='.') { /* Missing value */
9817: lval=-1;
9818: }else{
9819: errno=0;
9820: lval=strtol(strb,&endptr,10);
9821: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9822: if( strb[0]=='\0' || (*endptr != '\0')){
9823: 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);
9824: 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);
9825: return 1;
9826: }
9827: }
9828: if(lval <-1 || lval >1){
9829: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 9830: Should be a value of %d(nth) covariate of wave %d (0 should be the value for the reference and 1\n \
1.223 brouard 9831: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9832: For example, for multinomial values like 1, 2 and 3,\n \
9833: build V1=0 V2=0 for the reference value (1),\n \
9834: V1=1 V2=0 for (2) \n \
1.223 brouard 9835: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9836: output of IMaCh is often meaningless.\n \
1.319 brouard 9837: Exiting.\n",lval,linei, i,line,iv,j);
1.238 brouard 9838: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 9839: Should be a value of %d(nth) covariate of wave %d (0 should be the value for the reference and 1\n \
1.223 brouard 9840: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9841: For example, for multinomial values like 1, 2 and 3,\n \
9842: build V1=0 V2=0 for the reference value (1),\n \
9843: V1=1 V2=0 for (2) \n \
1.223 brouard 9844: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9845: output of IMaCh is often meaningless.\n \
1.319 brouard 9846: Exiting.\n",lval,linei, i,line,iv,j);fflush(ficlog);
1.238 brouard 9847: return 1;
9848: }
9849: cotvar[j][iv][i]=(double)(lval);
9850: strcpy(line,stra);
1.223 brouard 9851: }/* end loop ntv */
1.225 brouard 9852:
1.223 brouard 9853: /* Statuses at wave */
1.137 brouard 9854: cutv(stra, strb, line, ' ');
1.223 brouard 9855: if(strb[0]=='.') { /* Missing value */
1.238 brouard 9856: lval=-1;
1.136 brouard 9857: }else{
1.238 brouard 9858: errno=0;
9859: lval=strtol(strb,&endptr,10);
9860: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9861: if( strb[0]=='\0' || (*endptr != '\0')){
9862: 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);
9863: 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);
9864: return 1;
9865: }
1.136 brouard 9866: }
1.225 brouard 9867:
1.136 brouard 9868: s[j][i]=lval;
1.225 brouard 9869:
1.223 brouard 9870: /* Date of Interview */
1.136 brouard 9871: strcpy(line,stra);
9872: cutv(stra, strb,line,' ');
1.169 brouard 9873: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9874: }
1.169 brouard 9875: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 9876: month=99;
9877: year=9999;
1.136 brouard 9878: }else{
1.225 brouard 9879: 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);
9880: 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);
9881: return 1;
1.136 brouard 9882: }
9883: anint[j][i]= (double) year;
1.302 brouard 9884: mint[j][i]= (double)month;
9885: /* if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){ */
9886: /* printf("Warning reading data around '%s' at line number %d for individual %d, '%s'\nThe date of interview (%2d/%4d) at wave %d occurred before the date of birth (%2d/%4d).\n",strb, linei,i, line, mint[j][i],anint[j][i], moisnais[i],annais[i]); */
9887: /* fprintf(ficlog,"Warning reading data around '%s' at line number %d for individual %d, '%s'\nThe date of interview (%2d/%4d) at wave %d occurred before the date of birth (%2d/%4d).\n",strb, linei,i, line, mint[j][i],anint[j][i], moisnais[i],annais[i]); */
9888: /* } */
1.136 brouard 9889: strcpy(line,stra);
1.223 brouard 9890: } /* End loop on waves */
1.225 brouard 9891:
1.223 brouard 9892: /* Date of death */
1.136 brouard 9893: cutv(stra, strb,line,' ');
1.169 brouard 9894: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9895: }
1.169 brouard 9896: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 9897: month=99;
9898: year=9999;
9899: }else{
1.141 brouard 9900: 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 9901: 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);
9902: return 1;
1.136 brouard 9903: }
9904: andc[i]=(double) year;
9905: moisdc[i]=(double) month;
9906: strcpy(line,stra);
9907:
1.223 brouard 9908: /* Date of birth */
1.136 brouard 9909: cutv(stra, strb,line,' ');
1.169 brouard 9910: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9911: }
1.169 brouard 9912: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 9913: month=99;
9914: year=9999;
9915: }else{
1.141 brouard 9916: 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);
9917: 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 9918: return 1;
1.136 brouard 9919: }
9920: if (year==9999) {
1.141 brouard 9921: 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);
9922: 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 9923: return 1;
9924:
1.136 brouard 9925: }
9926: annais[i]=(double)(year);
1.302 brouard 9927: moisnais[i]=(double)(month);
9928: for (j=1;j<=maxwav;j++){
9929: if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){
9930: printf("Warning reading data around '%s' at line number %d for individual %d, '%s'\nThe date of interview (%2d/%4d) at wave %d occurred before the date of birth (%2d/%4d).\n",strb, linei,i, line, (int)mint[j][i],(int)anint[j][i], j,(int)moisnais[i],(int)annais[i]);
9931: fprintf(ficlog,"Warning reading data around '%s' at line number %d for individual %d, '%s'\nThe date of interview (%2d/%4d) at wave %d occurred before the date of birth (%2d/%4d).\n",strb, linei,i, line, (int)mint[j][i],(int)anint[j][i], j, (int)moisnais[i],(int)annais[i]);
9932: }
9933: }
9934:
1.136 brouard 9935: strcpy(line,stra);
1.225 brouard 9936:
1.223 brouard 9937: /* Sample weight */
1.136 brouard 9938: cutv(stra, strb,line,' ');
9939: errno=0;
9940: dval=strtod(strb,&endptr);
9941: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 9942: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
9943: 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 9944: fflush(ficlog);
9945: return 1;
9946: }
9947: weight[i]=dval;
9948: strcpy(line,stra);
1.225 brouard 9949:
1.223 brouard 9950: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
9951: cutv(stra, strb, line, ' ');
9952: if(strb[0]=='.') { /* Missing value */
1.225 brouard 9953: lval=-1;
1.311 brouard 9954: coqvar[iv][i]=NAN;
9955: covar[ncovcol+iv][i]=NAN; /* including qvar in standard covar for performance reasons */
1.223 brouard 9956: }else{
1.225 brouard 9957: errno=0;
9958: /* what_kind_of_number(strb); */
9959: dval=strtod(strb,&endptr);
9960: /* if(strb != endptr && *endptr == '\0') */
9961: /* dval=dlval; */
9962: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9963: if( strb[0]=='\0' || (*endptr != '\0')){
9964: 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);
9965: 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);
9966: return 1;
9967: }
9968: coqvar[iv][i]=dval;
1.226 brouard 9969: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 9970: }
9971: strcpy(line,stra);
9972: }/* end loop nqv */
1.136 brouard 9973:
1.223 brouard 9974: /* Covariate values */
1.136 brouard 9975: for (j=ncovcol;j>=1;j--){
9976: cutv(stra, strb,line,' ');
1.223 brouard 9977: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 9978: lval=-1;
1.136 brouard 9979: }else{
1.225 brouard 9980: errno=0;
9981: lval=strtol(strb,&endptr,10);
9982: if( strb[0]=='\0' || (*endptr != '\0')){
9983: 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);
9984: 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);
9985: return 1;
9986: }
1.136 brouard 9987: }
9988: if(lval <-1 || lval >1){
1.225 brouard 9989: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9990: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9991: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9992: For example, for multinomial values like 1, 2 and 3,\n \
9993: build V1=0 V2=0 for the reference value (1),\n \
9994: V1=1 V2=0 for (2) \n \
1.136 brouard 9995: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9996: output of IMaCh is often meaningless.\n \
1.136 brouard 9997: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 9998: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9999: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
10000: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 10001: For example, for multinomial values like 1, 2 and 3,\n \
10002: build V1=0 V2=0 for the reference value (1),\n \
10003: V1=1 V2=0 for (2) \n \
1.136 brouard 10004: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 10005: output of IMaCh is often meaningless.\n \
1.136 brouard 10006: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 10007: return 1;
1.136 brouard 10008: }
10009: covar[j][i]=(double)(lval);
10010: strcpy(line,stra);
10011: }
10012: lstra=strlen(stra);
1.225 brouard 10013:
1.136 brouard 10014: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
10015: stratrunc = &(stra[lstra-9]);
10016: num[i]=atol(stratrunc);
10017: }
10018: else
10019: num[i]=atol(stra);
10020: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
10021: 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;}*/
10022:
10023: i=i+1;
10024: } /* End loop reading data */
1.225 brouard 10025:
1.136 brouard 10026: *imax=i-1; /* Number of individuals */
10027: fclose(fic);
1.225 brouard 10028:
1.136 brouard 10029: return (0);
1.164 brouard 10030: /* endread: */
1.225 brouard 10031: printf("Exiting readdata: ");
10032: fclose(fic);
10033: return (1);
1.223 brouard 10034: }
1.126 brouard 10035:
1.234 brouard 10036: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 10037: char *p1 = *stri, *p2 = *stri;
1.235 brouard 10038: while (*p2 == ' ')
1.234 brouard 10039: p2++;
10040: /* while ((*p1++ = *p2++) !=0) */
10041: /* ; */
10042: /* do */
10043: /* while (*p2 == ' ') */
10044: /* p2++; */
10045: /* while (*p1++ == *p2++); */
10046: *stri=p2;
1.145 brouard 10047: }
10048:
1.235 brouard 10049: int decoderesult ( char resultline[], int nres)
1.230 brouard 10050: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
10051: {
1.235 brouard 10052: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 10053: char resultsav[MAXLINE];
1.234 brouard 10054: int resultmodel[MAXLINE];
10055: int modelresult[MAXLINE];
1.230 brouard 10056: char stra[80], strb[80], strc[80], strd[80],stre[80];
10057:
1.234 brouard 10058: removefirstspace(&resultline);
1.230 brouard 10059:
10060: if (strstr(resultline,"v") !=0){
10061: printf("Error. 'v' must be in upper case 'V' result: %s ",resultline);
10062: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultline);fflush(ficlog);
10063: return 1;
10064: }
10065: trimbb(resultsav, resultline);
10066: if (strlen(resultsav) >1){
10067: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' */
10068: }
1.253 brouard 10069: if(j == 0){ /* Resultline but no = */
10070: TKresult[nres]=0; /* Combination for the nresult and the model */
10071: return (0);
10072: }
1.234 brouard 10073: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
1.318 brouard 10074: printf("ERROR: the number of variables in this result line, %d, differs from the number of variables used in the model line, %d.\n",j, cptcovs);
1.310 brouard 10075: fprintf(ficlog,"ERROR: the number of variables in the resultline, %d, differs from the number of variables used in the model line, %d.\n",j, cptcovs);
1.234 brouard 10076: }
10077: for(k=1; k<=j;k++){ /* Loop on any covariate of the result line */
10078: if(nbocc(resultsav,'=') >1){
1.318 brouard 10079: cutl(stra,strb,resultsav,' '); /* keeps in strb after the first ' ' (stra is the rest of the resultline to be analyzed in the next loop *//* resultsav= "V4=1 V5=25.1 V3=0" stra= "V5=25.1 V3=0" strb= "V4=1" */
10080: cutl(strc,strd,strb,'='); /* strb:"V4=1" strc="1" strd="V4" */
1.234 brouard 10081: }else
10082: cutl(strc,strd,resultsav,'=');
1.318 brouard 10083: Tvalsel[k]=atof(strc); /* 1 */ /* Tvalsel of k is the float value of the kth covariate appearing in this result line */
1.234 brouard 10084:
1.230 brouard 10085: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
1.318 brouard 10086: Tvarsel[k]=atoi(strc); /* 4 */ /* Tvarsel is the id of the kth covariate in the result line Tvarsel[1] in "V4=1.." is 4.*/
1.230 brouard 10087: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
10088: /* cptcovsel++; */
10089: if (nbocc(stra,'=') >0)
10090: strcpy(resultsav,stra); /* and analyzes it */
10091: }
1.235 brouard 10092: /* Checking for missing or useless values in comparison of current model needs */
1.318 brouard 10093: for(k1=1; k1<= cptcovt ;k1++){ /* Loop on model. model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
10094: if(Typevar[k1]==0){ /* Single covariate in model *//*0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.234 brouard 10095: match=0;
1.318 brouard 10096: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
10097: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.236 brouard 10098: modelresult[k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.318 brouard 10099: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
1.234 brouard 10100: break;
10101: }
10102: }
10103: if(match == 0){
1.310 brouard 10104: printf("Error in result line: V%d is missing in result: %s according to model=%s\n",k1, resultline, model);
10105: fprintf(ficlog,"Error in result line: V%d is missing in result: %s according to model=%s\n",k1, resultline, model);
10106: return 1;
1.234 brouard 10107: }
10108: }
10109: }
1.235 brouard 10110: /* Checking for missing or useless values in comparison of current model needs */
1.318 brouard 10111: for(k2=1; k2 <=j;k2++){ /* Loop on resultline variables: result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 10112: match=0;
1.318 brouard 10113: for(k1=1; k1<= cptcovt ;k1++){ /* loop on model: model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.235 brouard 10114: if(Typevar[k1]==0){ /* Single */
1.237 brouard 10115: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 */
1.318 brouard 10116: resultmodel[k1]=k2; /* k2th variable of the model corresponds to k1 variable of the model. resultmodel[2]=1 resultmodel[1]=2 resultmodel[3]=3 resultmodel[6]=4 resultmodel[9]=5 */
1.234 brouard 10117: ++match;
10118: }
10119: }
10120: }
10121: if(match == 0){
10122: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
1.310 brouard 10123: fprintf(ficlog,"Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
10124: return 1;
1.234 brouard 10125: }else if(match > 1){
10126: printf("Error in result line: %d doubled; result: %s, model=%s\n",k2, resultline, model);
1.310 brouard 10127: fprintf(ficlog,"Error in result line: %d doubled; result: %s, model=%s\n",k2, resultline, model);
10128: return 1;
1.234 brouard 10129: }
10130: }
1.235 brouard 10131:
1.234 brouard 10132: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 10133: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
10134: /* result line V4=1 V5=25.1 V3=0 V2=8 V1=1 */
10135: /* should give a combination of dummy V4=1, V3=0, V1=1 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 5 + (1offset) = 6*/
10136: /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
10137: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
10138: /* 1 0 0 0 */
10139: /* 2 1 0 0 */
10140: /* 3 0 1 0 */
10141: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 */
10142: /* 5 0 0 1 */
10143: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 */
10144: /* 7 0 1 1 */
10145: /* 8 1 1 1 */
1.237 brouard 10146: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
10147: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
10148: /* V5*age V5 known which value for nres? */
10149: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.318 brouard 10150: for(k1=1, k=0, k4=0, k4q=0; k1 <=cptcovt;k1++){ /* loop on model line */
1.235 brouard 10151: if( Dummy[k1]==0 && Typevar[k1]==0 ){ /* Single dummy */
1.237 brouard 10152: k3= resultmodel[k1]; /* resultmodel[2(V4)] = 1=k3 */
1.235 brouard 10153: k2=(int)Tvarsel[k3]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
10154: k+=Tvalsel[k3]*pow(2,k4); /* Tvalsel[1]=1 */
1.237 brouard 10155: Tresult[nres][k4+1]=Tvalsel[k3];/* Tresult[nres][1]=1(V4=1) Tresult[nres][2]=0(V3=0) */
10156: Tvresult[nres][k4+1]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
10157: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.235 brouard 10158: printf("Decoderesult Dummy k=%d, V(k2=V%d)= Tvalsel[%d]=%d, 2**(%d)\n",k, k2, k3, (int)Tvalsel[k3], k4);
10159: k4++;;
10160: } else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Single quantitative */
1.318 brouard 10161: k3q= resultmodel[k1]; /* resultmodel[1(V5)] = 25.1=k3q */
10162: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
1.237 brouard 10163: Tqresult[nres][k4q+1]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
10164: Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
10165: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.235 brouard 10166: printf("Decoderesult Quantitative nres=%d, V(k2q=V%d)= Tvalsel[%d]=%d, Tvarsel[%d]=%f\n",nres, k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]);
10167: k4q++;;
10168: }
10169: }
1.234 brouard 10170:
1.235 brouard 10171: TKresult[nres]=++k; /* Combination for the nresult and the model */
1.230 brouard 10172: return (0);
10173: }
1.235 brouard 10174:
1.230 brouard 10175: int decodemodel( char model[], int lastobs)
10176: /**< This routine decodes the model and returns:
1.224 brouard 10177: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
10178: * - nagesqr = 1 if age*age in the model, otherwise 0.
10179: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
10180: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
10181: * - cptcovage number of covariates with age*products =2
10182: * - cptcovs number of simple covariates
10183: * - 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
10184: * which is a new column after the 9 (ncovcol) variables.
1.319 brouard 10185: * - if k is a product Vn*Vm, covar[k][i] is filled with correct values for each individual
1.224 brouard 10186: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
10187: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
10188: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
10189: */
1.319 brouard 10190: /* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1, Tage[1]=2 */
1.136 brouard 10191: {
1.238 brouard 10192: int i, j, k, ks, v;
1.227 brouard 10193: int j1, k1, k2, k3, k4;
1.136 brouard 10194: char modelsav[80];
1.145 brouard 10195: char stra[80], strb[80], strc[80], strd[80],stre[80];
1.187 brouard 10196: char *strpt;
1.136 brouard 10197:
1.145 brouard 10198: /*removespace(model);*/
1.136 brouard 10199: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.145 brouard 10200: j=0, j1=0, k1=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 10201: if (strstr(model,"AGE") !=0){
1.192 brouard 10202: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
10203: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 10204: return 1;
10205: }
1.141 brouard 10206: if (strstr(model,"v") !=0){
10207: printf("Error. 'v' must be in upper case 'V' model=%s ",model);
10208: fprintf(ficlog,"Error. 'v' must be in upper case model=%s ",model);fflush(ficlog);
10209: return 1;
10210: }
1.187 brouard 10211: strcpy(modelsav,model);
10212: if ((strpt=strstr(model,"age*age")) !=0){
10213: printf(" strpt=%s, model=%s\n",strpt, model);
10214: if(strpt != model){
1.234 brouard 10215: printf("Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 10216: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 10217: corresponding column of parameters.\n",model);
1.234 brouard 10218: fprintf(ficlog,"Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 10219: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 10220: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 10221: return 1;
1.225 brouard 10222: }
1.187 brouard 10223: nagesqr=1;
10224: if (strstr(model,"+age*age") !=0)
1.234 brouard 10225: substrchaine(modelsav, model, "+age*age");
1.187 brouard 10226: else if (strstr(model,"age*age+") !=0)
1.234 brouard 10227: substrchaine(modelsav, model, "age*age+");
1.187 brouard 10228: else
1.234 brouard 10229: substrchaine(modelsav, model, "age*age");
1.187 brouard 10230: }else
10231: nagesqr=0;
10232: if (strlen(modelsav) >1){
10233: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
10234: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.224 brouard 10235: cptcovs=j+1-j1; /**< Number of simple covariates V1+V1*age+V3 +V3*V4+age*age=> V1 + V3 =5-3=2 */
1.187 brouard 10236: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 10237: * cst, age and age*age
10238: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
10239: /* including age products which are counted in cptcovage.
10240: * but the covariates which are products must be treated
10241: * separately: ncovn=4- 2=2 (V1+V3). */
1.187 brouard 10242: cptcovprod=j1; /**< Number of products V1*V2 +v3*age = 2 */
10243: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.225 brouard 10244:
10245:
1.187 brouard 10246: /* Design
10247: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
10248: * < ncovcol=8 >
10249: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
10250: * k= 1 2 3 4 5 6 7 8
10251: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
10252: * covar[k,i], value of kth covariate if not including age for individual i:
1.224 brouard 10253: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
10254: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 10255: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
10256: * Tage[++cptcovage]=k
10257: * if products, new covar are created after ncovcol with k1
10258: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
10259: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
10260: * 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
10261: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
10262: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
10263: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
10264: * < ncovcol=8 >
10265: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
10266: * k= 1 2 3 4 5 6 7 8 9 10 11 12
10267: * Tvar[k]= 2 1 3 3 10 11 8 8 5 6 7 8
1.319 brouard 10268: * p Tvar[1]@12={2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
1.187 brouard 10269: * p Tprod[1]@2={ 6, 5}
10270: *p Tvard[1][1]@4= {7, 8, 5, 6}
10271: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
10272: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
1.319 brouard 10273: *How to reorganize? Tvars(orted)
1.187 brouard 10274: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
10275: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
10276: * {2, 1, 4, 8, 5, 6, 3, 7}
10277: * Struct []
10278: */
1.225 brouard 10279:
1.187 brouard 10280: /* This loop fills the array Tvar from the string 'model'.*/
10281: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
10282: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
10283: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
10284: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
10285: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
10286: /* k=1 Tvar[1]=2 (from V2) */
10287: /* k=5 Tvar[5] */
10288: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 10289: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 10290: /* } */
1.198 brouard 10291: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 10292: /*
10293: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 10294: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
10295: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
10296: }
1.187 brouard 10297: cptcovage=0;
1.319 brouard 10298: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model line */
10299: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+' cutl from left to right
10300: modelsav==V2+V1+V5*age+V4+V3*age strb=V3*age stra=V2+V1V5*age+V4 */ /* <model> "V5+V4+V3+V4*V3+V5*age+V1*age+V1" strb="V5" stra="V4+V3+V4*V3+V5*age+V1*age+V1" */
10301: if (nbocc(modelsav,'+')==0)
10302: strcpy(strb,modelsav); /* and analyzes it */
1.234 brouard 10303: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
10304: /*scanf("%d",i);*/
1.319 brouard 10305: if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V5*age+ V4+V3*age strb=V3*age */
10306: cutl(strc,strd,strb,'*'); /**< k=1 strd*strc Vm*Vn: strb=V3*age(input) strc=age strd=V3 ; V3*V2 strc=V2, strd=V3 */
1.234 brouard 10307: if (strcmp(strc,"age")==0) { /**< Model includes age: Vn*age */
10308: /* covar is not filled and then is empty */
10309: cptcovprod--;
10310: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
1.319 brouard 10311: Tvar[k]=atoi(stre); /* V2+V1+V5*age+V4+V3*age Tvar[5]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1 */
1.234 brouard 10312: Typevar[k]=1; /* 1 for age product */
1.319 brouard 10313: cptcovage++; /* Counts the number of covariates which include age as a product */
10314: Tage[cptcovage]=k; /* V2+V1+V4+V3*age Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */
1.234 brouard 10315: /*printf("stre=%s ", stre);*/
10316: } else if (strcmp(strd,"age")==0) { /* or age*Vn */
10317: cptcovprod--;
10318: cutl(stre,strb,strc,'V');
10319: Tvar[k]=atoi(stre);
10320: Typevar[k]=1; /* 1 for age product */
10321: cptcovage++;
10322: Tage[cptcovage]=k;
10323: } else { /* Age is not in the model product V2+V1+V1*V4+V3*age+V3*V2 strb=V3*V2*/
10324: /* loops on k1=1 (V3*V2) and k1=2 V4*V3 */
10325: cptcovn++;
10326: cptcovprodnoage++;k1++;
10327: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
10328: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* For model-covariate k tells which data-covariate to use but
10329: because this model-covariate is a construction we invent a new column
10330: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
1.319 brouard 10331: If already ncovcol=4 and model=V2 + V1 +V1*V4 +age*V3 +V3*V2
10332: thus after V4 we invent V5 and V6 because age*V3 will be computed in 4
10333: Tvar[3=V1*V4]=4+1=5 Tvar[5=V3*V2]=4 + 2= 6, Tvar[4=age*V3]=4 etc */
1.234 brouard 10334: Typevar[k]=2; /* 2 for double fixed dummy covariates */
10335: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
10336: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 */
1.319 brouard 10337: Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 */
1.234 brouard 10338: Tvard[k1][1] =atoi(strc); /* m 1 for V1*/
10339: Tvard[k1][2] =atoi(stre); /* n 4 for V4*/
10340: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
10341: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
10342: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
1.225 brouard 10343: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
1.234 brouard 10344: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
10345: for (i=1; i<=lastobs;i++){
10346: /* Computes the new covariate which is a product of
10347: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
10348: covar[ncovcol+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
10349: }
10350: } /* End age is not in the model */
10351: } /* End if model includes a product */
1.319 brouard 10352: else { /* not a product */
1.234 brouard 10353: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
10354: /* scanf("%d",i);*/
10355: cutl(strd,strc,strb,'V');
10356: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
10357: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
10358: Tvar[k]=atoi(strd);
10359: Typevar[k]=0; /* 0 for simple covariates */
10360: }
10361: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 10362: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 10363: scanf("%d",i);*/
1.187 brouard 10364: } /* end of loop + on total covariates */
10365: } /* end if strlen(modelsave == 0) age*age might exist */
10366: } /* end if strlen(model == 0) */
1.136 brouard 10367:
10368: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
10369: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 10370:
1.136 brouard 10371: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 10372: printf("cptcovprod=%d ", cptcovprod);
10373: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
10374: scanf("%d ",i);*/
10375:
10376:
1.230 brouard 10377: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
10378: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 10379: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
10380: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
10381: k = 1 2 3 4 5 6 7 8 9
10382: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
1.319 brouard 10383: Typevar[k]= 0 0 0 2 1 0 2 1 0
1.227 brouard 10384: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
10385: Dummy[k] 1 0 0 0 3 1 1 2 3
10386: Tmodelind[combination of covar]=k;
1.225 brouard 10387: */
10388: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 10389: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 10390: /* 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 10391: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.318 brouard 10392: printf("Model=1+age+%s\n\
1.227 brouard 10393: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
10394: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
10395: 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);
1.318 brouard 10396: fprintf(ficlog,"Model=1+age+%s\n\
1.227 brouard 10397: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
10398: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
10399: 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 10400: for(k=-1;k<=cptcovt; k++){ Fixed[k]=0; Dummy[k]=0;}
1.234 brouard 10401: 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 */
10402: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 10403: Fixed[k]= 0;
10404: Dummy[k]= 0;
1.225 brouard 10405: ncoveff++;
1.232 brouard 10406: ncovf++;
1.234 brouard 10407: nsd++;
10408: modell[k].maintype= FTYPE;
10409: TvarsD[nsd]=Tvar[k];
10410: TvarsDind[nsd]=k;
10411: TvarF[ncovf]=Tvar[k];
10412: TvarFind[ncovf]=k;
10413: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
10414: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
10415: }else if( Tvar[k] <=ncovcol && Typevar[k]==2){ /* Product of fixed dummy (<=ncovcol) covariates */
10416: Fixed[k]= 0;
10417: Dummy[k]= 0;
10418: ncoveff++;
10419: ncovf++;
10420: modell[k].maintype= FTYPE;
10421: TvarF[ncovf]=Tvar[k];
10422: TvarFind[ncovf]=k;
1.230 brouard 10423: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.231 brouard 10424: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.240 brouard 10425: }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 10426: Fixed[k]= 0;
10427: Dummy[k]= 1;
1.230 brouard 10428: nqfveff++;
1.234 brouard 10429: modell[k].maintype= FTYPE;
10430: modell[k].subtype= FQ;
10431: nsq++;
10432: TvarsQ[nsq]=Tvar[k];
10433: TvarsQind[nsq]=k;
1.232 brouard 10434: ncovf++;
1.234 brouard 10435: TvarF[ncovf]=Tvar[k];
10436: TvarFind[ncovf]=k;
1.231 brouard 10437: 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 10438: 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 10439: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.227 brouard 10440: Fixed[k]= 1;
10441: Dummy[k]= 0;
1.225 brouard 10442: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 10443: modell[k].maintype= VTYPE;
10444: modell[k].subtype= VD;
10445: nsd++;
10446: TvarsD[nsd]=Tvar[k];
10447: TvarsDind[nsd]=k;
10448: ncovv++; /* Only simple time varying variables */
10449: TvarV[ncovv]=Tvar[k];
1.242 brouard 10450: 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 10451: 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 */
10452: 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 10453: 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);
10454: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 10455: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.234 brouard 10456: Fixed[k]= 1;
10457: Dummy[k]= 1;
10458: nqtveff++;
10459: modell[k].maintype= VTYPE;
10460: modell[k].subtype= VQ;
10461: ncovv++; /* Only simple time varying variables */
10462: nsq++;
1.319 brouard 10463: TvarsQ[nsq]=Tvar[k]; /* k=1 Tvar=5 nsq=1 TvarsQ[1]=5 */
1.234 brouard 10464: TvarsQind[nsq]=k;
10465: TvarV[ncovv]=Tvar[k];
1.242 brouard 10466: 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 10467: 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 */
10468: 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 10469: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
10470: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
10471: 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 10472: printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv);
1.227 brouard 10473: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 10474: ncova++;
10475: TvarA[ncova]=Tvar[k];
10476: TvarAind[ncova]=k;
1.231 brouard 10477: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 10478: Fixed[k]= 2;
10479: Dummy[k]= 2;
10480: modell[k].maintype= ATYPE;
10481: modell[k].subtype= APFD;
10482: /* ncoveff++; */
1.227 brouard 10483: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 10484: Fixed[k]= 2;
10485: Dummy[k]= 3;
10486: modell[k].maintype= ATYPE;
10487: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
10488: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 10489: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 10490: Fixed[k]= 3;
10491: Dummy[k]= 2;
10492: modell[k].maintype= ATYPE;
10493: modell[k].subtype= APVD; /* Product age * varying dummy */
10494: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 10495: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 10496: Fixed[k]= 3;
10497: Dummy[k]= 3;
10498: modell[k].maintype= ATYPE;
10499: modell[k].subtype= APVQ; /* Product age * varying quantitative */
10500: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 10501: }
10502: }else if (Typevar[k] == 2) { /* product without age */
10503: k1=Tposprod[k];
10504: if(Tvard[k1][1] <=ncovcol){
1.240 brouard 10505: if(Tvard[k1][2] <=ncovcol){
10506: Fixed[k]= 1;
10507: Dummy[k]= 0;
10508: modell[k].maintype= FTYPE;
10509: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
10510: ncovf++; /* Fixed variables without age */
10511: TvarF[ncovf]=Tvar[k];
10512: TvarFind[ncovf]=k;
10513: }else if(Tvard[k1][2] <=ncovcol+nqv){
10514: Fixed[k]= 0; /* or 2 ?*/
10515: Dummy[k]= 1;
10516: modell[k].maintype= FTYPE;
10517: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
10518: ncovf++; /* Varying variables without age */
10519: TvarF[ncovf]=Tvar[k];
10520: TvarFind[ncovf]=k;
10521: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10522: Fixed[k]= 1;
10523: Dummy[k]= 0;
10524: modell[k].maintype= VTYPE;
10525: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
10526: ncovv++; /* Varying variables without age */
10527: TvarV[ncovv]=Tvar[k];
10528: TvarVind[ncovv]=k;
10529: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10530: Fixed[k]= 1;
10531: Dummy[k]= 1;
10532: modell[k].maintype= VTYPE;
10533: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
10534: ncovv++; /* Varying variables without age */
10535: TvarV[ncovv]=Tvar[k];
10536: TvarVind[ncovv]=k;
10537: }
1.227 brouard 10538: }else if(Tvard[k1][1] <=ncovcol+nqv){
1.240 brouard 10539: if(Tvard[k1][2] <=ncovcol){
10540: Fixed[k]= 0; /* or 2 ?*/
10541: Dummy[k]= 1;
10542: modell[k].maintype= FTYPE;
10543: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
10544: ncovf++; /* Fixed variables without age */
10545: TvarF[ncovf]=Tvar[k];
10546: TvarFind[ncovf]=k;
10547: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10548: Fixed[k]= 1;
10549: Dummy[k]= 1;
10550: modell[k].maintype= VTYPE;
10551: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
10552: ncovv++; /* Varying variables without age */
10553: TvarV[ncovv]=Tvar[k];
10554: TvarVind[ncovv]=k;
10555: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10556: Fixed[k]= 1;
10557: Dummy[k]= 1;
10558: modell[k].maintype= VTYPE;
10559: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
10560: ncovv++; /* Varying variables without age */
10561: TvarV[ncovv]=Tvar[k];
10562: TvarVind[ncovv]=k;
10563: ncovv++; /* Varying variables without age */
10564: TvarV[ncovv]=Tvar[k];
10565: TvarVind[ncovv]=k;
10566: }
1.227 brouard 10567: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){
1.240 brouard 10568: if(Tvard[k1][2] <=ncovcol){
10569: Fixed[k]= 1;
10570: Dummy[k]= 1;
10571: modell[k].maintype= VTYPE;
10572: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
10573: ncovv++; /* Varying variables without age */
10574: TvarV[ncovv]=Tvar[k];
10575: TvarVind[ncovv]=k;
10576: }else if(Tvard[k1][2] <=ncovcol+nqv){
10577: Fixed[k]= 1;
10578: Dummy[k]= 1;
10579: modell[k].maintype= VTYPE;
10580: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
10581: ncovv++; /* Varying variables without age */
10582: TvarV[ncovv]=Tvar[k];
10583: TvarVind[ncovv]=k;
10584: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10585: Fixed[k]= 1;
10586: Dummy[k]= 0;
10587: modell[k].maintype= VTYPE;
10588: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
10589: ncovv++; /* Varying variables without age */
10590: TvarV[ncovv]=Tvar[k];
10591: TvarVind[ncovv]=k;
10592: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10593: Fixed[k]= 1;
10594: Dummy[k]= 1;
10595: modell[k].maintype= VTYPE;
10596: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
10597: ncovv++; /* Varying variables without age */
10598: TvarV[ncovv]=Tvar[k];
10599: TvarVind[ncovv]=k;
10600: }
1.227 brouard 10601: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 10602: if(Tvard[k1][2] <=ncovcol){
10603: Fixed[k]= 1;
10604: Dummy[k]= 1;
10605: modell[k].maintype= VTYPE;
10606: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
10607: ncovv++; /* Varying variables without age */
10608: TvarV[ncovv]=Tvar[k];
10609: TvarVind[ncovv]=k;
10610: }else if(Tvard[k1][2] <=ncovcol+nqv){
10611: Fixed[k]= 1;
10612: Dummy[k]= 1;
10613: modell[k].maintype= VTYPE;
10614: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
10615: ncovv++; /* Varying variables without age */
10616: TvarV[ncovv]=Tvar[k];
10617: TvarVind[ncovv]=k;
10618: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10619: Fixed[k]= 1;
10620: Dummy[k]= 1;
10621: modell[k].maintype= VTYPE;
10622: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
10623: ncovv++; /* Varying variables without age */
10624: TvarV[ncovv]=Tvar[k];
10625: TvarVind[ncovv]=k;
10626: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10627: Fixed[k]= 1;
10628: Dummy[k]= 1;
10629: modell[k].maintype= VTYPE;
10630: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
10631: ncovv++; /* Varying variables without age */
10632: TvarV[ncovv]=Tvar[k];
10633: TvarVind[ncovv]=k;
10634: }
1.227 brouard 10635: }else{
1.240 brouard 10636: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
10637: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
10638: } /*end k1*/
1.225 brouard 10639: }else{
1.226 brouard 10640: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
10641: 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 10642: }
1.227 brouard 10643: 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 10644: printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype);
1.227 brouard 10645: 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]);
10646: }
10647: /* Searching for doublons in the model */
10648: for(k1=1; k1<= cptcovt;k1++){
10649: for(k2=1; k2 <k1;k2++){
1.285 brouard 10650: /* if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){ */
10651: if((Typevar[k1]==Typevar[k2]) && (Fixed[k1]==Fixed[k2]) && (Dummy[k1]==Dummy[k2] )){
1.234 brouard 10652: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
10653: if(Tvar[k1]==Tvar[k2]){
1.285 brouard 10654: 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]);
10655: 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 10656: return(1);
10657: }
10658: }else if (Typevar[k1] ==2){
10659: k3=Tposprod[k1];
10660: k4=Tposprod[k2];
10661: 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])) ){
10662: 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]]);
10663: 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);
10664: return(1);
10665: }
10666: }
1.227 brouard 10667: }
10668: }
1.225 brouard 10669: }
10670: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
10671: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 10672: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
10673: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.137 brouard 10674: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 10675: /*endread:*/
1.225 brouard 10676: printf("Exiting decodemodel: ");
10677: return (1);
1.136 brouard 10678: }
10679:
1.169 brouard 10680: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 10681: {/* Check ages at death */
1.136 brouard 10682: int i, m;
1.218 brouard 10683: int firstone=0;
10684:
1.136 brouard 10685: for (i=1; i<=imx; i++) {
10686: for(m=2; (m<= maxwav); m++) {
10687: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
10688: anint[m][i]=9999;
1.216 brouard 10689: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
10690: s[m][i]=-1;
1.136 brouard 10691: }
10692: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 10693: *nberr = *nberr + 1;
1.218 brouard 10694: if(firstone == 0){
10695: firstone=1;
1.260 brouard 10696: 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 10697: }
1.262 brouard 10698: 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 10699: s[m][i]=-1; /* Droping the death status */
1.136 brouard 10700: }
10701: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 10702: (*nberr)++;
1.259 brouard 10703: 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 10704: 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 10705: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 10706: }
10707: }
10708: }
10709:
10710: for (i=1; i<=imx; i++) {
10711: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
10712: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 10713: 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 10714: if (s[m][i] >= nlstate+1) {
1.169 brouard 10715: if(agedc[i]>0){
10716: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 10717: agev[m][i]=agedc[i];
1.214 brouard 10718: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 10719: }else {
1.136 brouard 10720: if ((int)andc[i]!=9999){
10721: nbwarn++;
10722: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
10723: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
10724: agev[m][i]=-1;
10725: }
10726: }
1.169 brouard 10727: } /* agedc > 0 */
1.214 brouard 10728: } /* end if */
1.136 brouard 10729: else if(s[m][i] !=9){ /* Standard case, age in fractional
10730: years but with the precision of a month */
10731: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
10732: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
10733: agev[m][i]=1;
10734: else if(agev[m][i] < *agemin){
10735: *agemin=agev[m][i];
10736: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
10737: }
10738: else if(agev[m][i] >*agemax){
10739: *agemax=agev[m][i];
1.156 brouard 10740: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 10741: }
10742: /*agev[m][i]=anint[m][i]-annais[i];*/
10743: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 10744: } /* en if 9*/
1.136 brouard 10745: else { /* =9 */
1.214 brouard 10746: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 10747: agev[m][i]=1;
10748: s[m][i]=-1;
10749: }
10750: }
1.214 brouard 10751: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 10752: agev[m][i]=1;
1.214 brouard 10753: else{
10754: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
10755: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
10756: agev[m][i]=0;
10757: }
10758: } /* End for lastpass */
10759: }
1.136 brouard 10760:
10761: for (i=1; i<=imx; i++) {
10762: for(m=firstpass; (m<=lastpass); m++){
10763: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 10764: (*nberr)++;
1.136 brouard 10765: 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);
10766: 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);
10767: return 1;
10768: }
10769: }
10770: }
10771:
10772: /*for (i=1; i<=imx; i++){
10773: for (m=firstpass; (m<lastpass); m++){
10774: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
10775: }
10776:
10777: }*/
10778:
10779:
1.139 brouard 10780: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
10781: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 10782:
10783: return (0);
1.164 brouard 10784: /* endread:*/
1.136 brouard 10785: printf("Exiting calandcheckages: ");
10786: return (1);
10787: }
10788:
1.172 brouard 10789: #if defined(_MSC_VER)
10790: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
10791: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
10792: //#include "stdafx.h"
10793: //#include <stdio.h>
10794: //#include <tchar.h>
10795: //#include <windows.h>
10796: //#include <iostream>
10797: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
10798:
10799: LPFN_ISWOW64PROCESS fnIsWow64Process;
10800:
10801: BOOL IsWow64()
10802: {
10803: BOOL bIsWow64 = FALSE;
10804:
10805: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
10806: // (HANDLE, PBOOL);
10807:
10808: //LPFN_ISWOW64PROCESS fnIsWow64Process;
10809:
10810: HMODULE module = GetModuleHandle(_T("kernel32"));
10811: const char funcName[] = "IsWow64Process";
10812: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
10813: GetProcAddress(module, funcName);
10814:
10815: if (NULL != fnIsWow64Process)
10816: {
10817: if (!fnIsWow64Process(GetCurrentProcess(),
10818: &bIsWow64))
10819: //throw std::exception("Unknown error");
10820: printf("Unknown error\n");
10821: }
10822: return bIsWow64 != FALSE;
10823: }
10824: #endif
1.177 brouard 10825:
1.191 brouard 10826: void syscompilerinfo(int logged)
1.292 brouard 10827: {
10828: #include <stdint.h>
10829:
10830: /* #include "syscompilerinfo.h"*/
1.185 brouard 10831: /* command line Intel compiler 32bit windows, XP compatible:*/
10832: /* /GS /W3 /Gy
10833: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
10834: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
10835: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 10836: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
10837: */
10838: /* 64 bits */
1.185 brouard 10839: /*
10840: /GS /W3 /Gy
10841: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
10842: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
10843: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
10844: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
10845: /* Optimization are useless and O3 is slower than O2 */
10846: /*
10847: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
10848: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
10849: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
10850: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
10851: */
1.186 brouard 10852: /* Link is */ /* /OUT:"visual studio
1.185 brouard 10853: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
10854: /PDB:"visual studio
10855: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
10856: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
10857: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
10858: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
10859: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
10860: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
10861: uiAccess='false'"
10862: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
10863: /NOLOGO /TLBID:1
10864: */
1.292 brouard 10865:
10866:
1.177 brouard 10867: #if defined __INTEL_COMPILER
1.178 brouard 10868: #if defined(__GNUC__)
10869: struct utsname sysInfo; /* For Intel on Linux and OS/X */
10870: #endif
1.177 brouard 10871: #elif defined(__GNUC__)
1.179 brouard 10872: #ifndef __APPLE__
1.174 brouard 10873: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 10874: #endif
1.177 brouard 10875: struct utsname sysInfo;
1.178 brouard 10876: int cross = CROSS;
10877: if (cross){
10878: printf("Cross-");
1.191 brouard 10879: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 10880: }
1.174 brouard 10881: #endif
10882:
1.191 brouard 10883: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 10884: #if defined(__clang__)
1.191 brouard 10885: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 10886: #endif
10887: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 10888: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 10889: #endif
10890: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 10891: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 10892: #endif
10893: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 10894: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 10895: #endif
10896: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 10897: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 10898: #endif
10899: #if defined(_MSC_VER)
1.191 brouard 10900: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 10901: #endif
10902: #if defined(__PGI)
1.191 brouard 10903: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 10904: #endif
10905: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 10906: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 10907: #endif
1.191 brouard 10908: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 10909:
1.167 brouard 10910: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
10911: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
10912: // Windows (x64 and x86)
1.191 brouard 10913: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 10914: #elif __unix__ // all unices, not all compilers
10915: // Unix
1.191 brouard 10916: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 10917: #elif __linux__
10918: // linux
1.191 brouard 10919: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 10920: #elif __APPLE__
1.174 brouard 10921: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 10922: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 10923: #endif
10924:
10925: /* __MINGW32__ */
10926: /* __CYGWIN__ */
10927: /* __MINGW64__ */
10928: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
10929: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
10930: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
10931: /* _WIN64 // Defined for applications for Win64. */
10932: /* _M_X64 // Defined for compilations that target x64 processors. */
10933: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 10934:
1.167 brouard 10935: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 10936: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 10937: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 10938: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 10939: #else
1.191 brouard 10940: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 10941: #endif
10942:
1.169 brouard 10943: #if defined(__GNUC__)
10944: # if defined(__GNUC_PATCHLEVEL__)
10945: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10946: + __GNUC_MINOR__ * 100 \
10947: + __GNUC_PATCHLEVEL__)
10948: # else
10949: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10950: + __GNUC_MINOR__ * 100)
10951: # endif
1.174 brouard 10952: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 10953: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 10954:
10955: if (uname(&sysInfo) != -1) {
10956: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 10957: 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 10958: }
10959: else
10960: perror("uname() error");
1.179 brouard 10961: //#ifndef __INTEL_COMPILER
10962: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 10963: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 10964: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 10965: #endif
1.169 brouard 10966: #endif
1.172 brouard 10967:
1.286 brouard 10968: // void main ()
1.172 brouard 10969: // {
1.169 brouard 10970: #if defined(_MSC_VER)
1.174 brouard 10971: if (IsWow64()){
1.191 brouard 10972: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
10973: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 10974: }
10975: else{
1.191 brouard 10976: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
10977: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 10978: }
1.172 brouard 10979: // printf("\nPress Enter to continue...");
10980: // getchar();
10981: // }
10982:
1.169 brouard 10983: #endif
10984:
1.167 brouard 10985:
1.219 brouard 10986: }
1.136 brouard 10987:
1.219 brouard 10988: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.288 brouard 10989: /*--------------- Prevalence limit (forward period or forward stable prevalence) --------------*/
1.235 brouard 10990: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 10991: /* double ftolpl = 1.e-10; */
1.180 brouard 10992: double age, agebase, agelim;
1.203 brouard 10993: double tot;
1.180 brouard 10994:
1.202 brouard 10995: strcpy(filerespl,"PL_");
10996: strcat(filerespl,fileresu);
10997: if((ficrespl=fopen(filerespl,"w"))==NULL) {
1.288 brouard 10998: printf("Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
10999: fprintf(ficlog,"Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
1.202 brouard 11000: }
1.288 brouard 11001: printf("\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
11002: fprintf(ficlog,"\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 11003: pstamp(ficrespl);
1.288 brouard 11004: fprintf(ficrespl,"# Forward period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 11005: fprintf(ficrespl,"#Age ");
11006: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
11007: fprintf(ficrespl,"\n");
1.180 brouard 11008:
1.219 brouard 11009: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 11010:
1.219 brouard 11011: agebase=ageminpar;
11012: agelim=agemaxpar;
1.180 brouard 11013:
1.227 brouard 11014: /* i1=pow(2,ncoveff); */
1.234 brouard 11015: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 11016: if (cptcovn < 1){i1=1;}
1.180 brouard 11017:
1.238 brouard 11018: for(k=1; k<=i1;k++){ /* For each combination k of dummy covariates in the model */
11019: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 11020: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 11021: continue;
1.235 brouard 11022:
1.238 brouard 11023: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
11024: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
11025: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
11026: /* k=k+1; */
11027: /* to clean */
11028: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
11029: fprintf(ficrespl,"#******");
11030: printf("#******");
11031: fprintf(ficlog,"#******");
11032: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
11033: fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); /* Here problem for varying dummy*/
11034: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
11035: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
11036: }
11037: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
11038: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
11039: fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
11040: fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
11041: }
11042: fprintf(ficrespl,"******\n");
11043: printf("******\n");
11044: fprintf(ficlog,"******\n");
11045: if(invalidvarcomb[k]){
11046: printf("\nCombination (%d) ignored because no case \n",k);
11047: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
11048: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
11049: continue;
11050: }
1.219 brouard 11051:
1.238 brouard 11052: fprintf(ficrespl,"#Age ");
11053: for(j=1;j<=cptcoveff;j++) {
11054: fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
11055: }
11056: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
11057: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 11058:
1.238 brouard 11059: for (age=agebase; age<=agelim; age++){
11060: /* for (age=agebase; age<=agebase; age++){ */
11061: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres);
11062: fprintf(ficrespl,"%.0f ",age );
11063: for(j=1;j<=cptcoveff;j++)
11064: fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
11065: tot=0.;
11066: for(i=1; i<=nlstate;i++){
11067: tot += prlim[i][i];
11068: fprintf(ficrespl," %.5f", prlim[i][i]);
11069: }
11070: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
11071: } /* Age */
11072: /* was end of cptcod */
11073: } /* cptcov */
11074: } /* nres */
1.219 brouard 11075: return 0;
1.180 brouard 11076: }
11077:
1.218 brouard 11078: 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 11079: /*--------------- Back Prevalence limit (backward stable prevalence) --------------*/
1.218 brouard 11080:
11081: /* Computes the back prevalence limit for any combination of covariate values
11082: * at any age between ageminpar and agemaxpar
11083: */
1.235 brouard 11084: int i, j, k, i1, nres=0 ;
1.217 brouard 11085: /* double ftolpl = 1.e-10; */
11086: double age, agebase, agelim;
11087: double tot;
1.218 brouard 11088: /* double ***mobaverage; */
11089: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 11090:
11091: strcpy(fileresplb,"PLB_");
11092: strcat(fileresplb,fileresu);
11093: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
1.288 brouard 11094: printf("Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
11095: fprintf(ficlog,"Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
1.217 brouard 11096: }
1.288 brouard 11097: printf("Computing backward prevalence: result on file '%s' \n", fileresplb);
11098: fprintf(ficlog,"Computing backward prevalence: result on file '%s' \n", fileresplb);
1.217 brouard 11099: pstamp(ficresplb);
1.288 brouard 11100: fprintf(ficresplb,"# Backward prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.217 brouard 11101: fprintf(ficresplb,"#Age ");
11102: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
11103: fprintf(ficresplb,"\n");
11104:
1.218 brouard 11105:
11106: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
11107:
11108: agebase=ageminpar;
11109: agelim=agemaxpar;
11110:
11111:
1.227 brouard 11112: i1=pow(2,cptcoveff);
1.218 brouard 11113: if (cptcovn < 1){i1=1;}
1.227 brouard 11114:
1.238 brouard 11115: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
11116: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 11117: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 11118: continue;
11119: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
11120: fprintf(ficresplb,"#******");
11121: printf("#******");
11122: fprintf(ficlog,"#******");
11123: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
11124: fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
11125: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
11126: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
11127: }
11128: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
11129: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
11130: fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
11131: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
11132: }
11133: fprintf(ficresplb,"******\n");
11134: printf("******\n");
11135: fprintf(ficlog,"******\n");
11136: if(invalidvarcomb[k]){
11137: printf("\nCombination (%d) ignored because no cases \n",k);
11138: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
11139: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
11140: continue;
11141: }
1.218 brouard 11142:
1.238 brouard 11143: fprintf(ficresplb,"#Age ");
11144: for(j=1;j<=cptcoveff;j++) {
11145: fprintf(ficresplb,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
11146: }
11147: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
11148: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 11149:
11150:
1.238 brouard 11151: for (age=agebase; age<=agelim; age++){
11152: /* for (age=agebase; age<=agebase; age++){ */
11153: if(mobilavproj > 0){
11154: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
11155: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 11156: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 11157: }else if (mobilavproj == 0){
11158: 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);
11159: 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);
11160: exit(1);
11161: }else{
11162: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 11163: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 11164: /* printf("TOTOT\n"); */
11165: /* exit(1); */
1.238 brouard 11166: }
11167: fprintf(ficresplb,"%.0f ",age );
11168: for(j=1;j<=cptcoveff;j++)
11169: fprintf(ficresplb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
11170: tot=0.;
11171: for(i=1; i<=nlstate;i++){
11172: tot += bprlim[i][i];
11173: fprintf(ficresplb," %.5f", bprlim[i][i]);
11174: }
11175: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
11176: } /* Age */
11177: /* was end of cptcod */
1.255 brouard 11178: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.238 brouard 11179: } /* end of any combination */
11180: } /* end of nres */
1.218 brouard 11181: /* hBijx(p, bage, fage); */
11182: /* fclose(ficrespijb); */
11183:
11184: return 0;
1.217 brouard 11185: }
1.218 brouard 11186:
1.180 brouard 11187: int hPijx(double *p, int bage, int fage){
11188: /*------------- h Pij x at various ages ------------*/
11189:
11190: int stepsize;
11191: int agelim;
11192: int hstepm;
11193: int nhstepm;
1.235 brouard 11194: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 11195:
11196: double agedeb;
11197: double ***p3mat;
11198:
1.201 brouard 11199: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
1.180 brouard 11200: if((ficrespij=fopen(filerespij,"w"))==NULL) {
11201: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
11202: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
11203: }
11204: printf("Computing pij: result on file '%s' \n", filerespij);
11205: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
11206:
11207: stepsize=(int) (stepm+YEARM-1)/YEARM;
11208: /*if (stepm<=24) stepsize=2;*/
11209:
11210: agelim=AGESUP;
11211: hstepm=stepsize*YEARM; /* Every year of age */
11212: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
1.218 brouard 11213:
1.180 brouard 11214: /* hstepm=1; aff par mois*/
11215: pstamp(ficrespij);
11216: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
1.227 brouard 11217: i1= pow(2,cptcoveff);
1.218 brouard 11218: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
11219: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
11220: /* k=k+1; */
1.235 brouard 11221: for(nres=1; nres <= nresult; nres++) /* For each resultline */
11222: for(k=1; k<=i1;k++){
1.253 brouard 11223: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 11224: continue;
1.183 brouard 11225: fprintf(ficrespij,"\n#****** ");
1.227 brouard 11226: for(j=1;j<=cptcoveff;j++)
1.198 brouard 11227: fprintf(ficrespij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 11228: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
11229: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
11230: fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
11231: }
1.183 brouard 11232: fprintf(ficrespij,"******\n");
11233:
11234: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
11235: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
11236: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
11237:
11238: /* nhstepm=nhstepm*YEARM; aff par mois*/
1.180 brouard 11239:
1.183 brouard 11240: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11241: oldm=oldms;savm=savms;
1.235 brouard 11242: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.183 brouard 11243: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
11244: for(i=1; i<=nlstate;i++)
11245: for(j=1; j<=nlstate+ndeath;j++)
11246: fprintf(ficrespij," %1d-%1d",i,j);
11247: fprintf(ficrespij,"\n");
11248: for (h=0; h<=nhstepm; h++){
11249: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
11250: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.180 brouard 11251: for(i=1; i<=nlstate;i++)
11252: for(j=1; j<=nlstate+ndeath;j++)
1.183 brouard 11253: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.180 brouard 11254: fprintf(ficrespij,"\n");
11255: }
1.183 brouard 11256: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11257: fprintf(ficrespij,"\n");
11258: }
1.180 brouard 11259: /*}*/
11260: }
1.218 brouard 11261: return 0;
1.180 brouard 11262: }
1.218 brouard 11263:
11264: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 11265: /*------------- h Bij x at various ages ------------*/
11266:
11267: int stepsize;
1.218 brouard 11268: /* int agelim; */
11269: int ageminl;
1.217 brouard 11270: int hstepm;
11271: int nhstepm;
1.238 brouard 11272: int h, i, i1, j, k, nres;
1.218 brouard 11273:
1.217 brouard 11274: double agedeb;
11275: double ***p3mat;
1.218 brouard 11276:
11277: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
11278: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
11279: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
11280: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
11281: }
11282: printf("Computing pij back: result on file '%s' \n", filerespijb);
11283: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
11284:
11285: stepsize=(int) (stepm+YEARM-1)/YEARM;
11286: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 11287:
1.218 brouard 11288: /* agelim=AGESUP; */
1.289 brouard 11289: ageminl=AGEINF; /* was 30 */
1.218 brouard 11290: hstepm=stepsize*YEARM; /* Every year of age */
11291: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
11292:
11293: /* hstepm=1; aff par mois*/
11294: pstamp(ficrespijb);
1.255 brouard 11295: 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 11296: i1= pow(2,cptcoveff);
1.218 brouard 11297: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
11298: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
11299: /* k=k+1; */
1.238 brouard 11300: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
11301: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 11302: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 11303: continue;
11304: fprintf(ficrespijb,"\n#****** ");
11305: for(j=1;j<=cptcoveff;j++)
11306: fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
11307: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
11308: fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
11309: }
11310: fprintf(ficrespijb,"******\n");
1.264 brouard 11311: if(invalidvarcomb[k]){ /* Is it necessary here? */
1.238 brouard 11312: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
11313: continue;
11314: }
11315:
11316: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
11317: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
11318: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
1.297 brouard 11319: 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 */
11320: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 or 28*/
1.238 brouard 11321:
11322: /* nhstepm=nhstepm*YEARM; aff par mois*/
11323:
1.266 brouard 11324: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
11325: /* and memory limitations if stepm is small */
11326:
1.238 brouard 11327: /* oldm=oldms;savm=savms; */
11328: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.325 brouard 11329: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);/* Bug valgrind */
1.238 brouard 11330: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
1.255 brouard 11331: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
1.217 brouard 11332: for(i=1; i<=nlstate;i++)
11333: for(j=1; j<=nlstate+ndeath;j++)
1.238 brouard 11334: fprintf(ficrespijb," %1d-%1d",i,j);
1.217 brouard 11335: fprintf(ficrespijb,"\n");
1.238 brouard 11336: for (h=0; h<=nhstepm; h++){
11337: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
11338: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
11339: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
11340: for(i=1; i<=nlstate;i++)
11341: for(j=1; j<=nlstate+ndeath;j++)
1.325 brouard 11342: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);/* Bug valgrind */
1.238 brouard 11343: fprintf(ficrespijb,"\n");
11344: }
11345: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11346: fprintf(ficrespijb,"\n");
11347: } /* end age deb */
11348: } /* end combination */
11349: } /* end nres */
1.218 brouard 11350: return 0;
11351: } /* hBijx */
1.217 brouard 11352:
1.180 brouard 11353:
1.136 brouard 11354: /***********************************************/
11355: /**************** Main Program *****************/
11356: /***********************************************/
11357:
11358: int main(int argc, char *argv[])
11359: {
11360: #ifdef GSL
11361: const gsl_multimin_fminimizer_type *T;
11362: size_t iteri = 0, it;
11363: int rval = GSL_CONTINUE;
11364: int status = GSL_SUCCESS;
11365: double ssval;
11366: #endif
11367: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.290 brouard 11368: int i,j, k, iter=0,m,size=100, cptcod; /* Suppressing because nobs */
11369: /* int i,j, k, n=MAXN,iter=0,m,size=100, cptcod; */
1.209 brouard 11370: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 11371: int jj, ll, li, lj, lk;
1.136 brouard 11372: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 11373: int num_filled;
1.136 brouard 11374: int itimes;
11375: int NDIM=2;
11376: int vpopbased=0;
1.235 brouard 11377: int nres=0;
1.258 brouard 11378: int endishere=0;
1.277 brouard 11379: int noffset=0;
1.274 brouard 11380: int ncurrv=0; /* Temporary variable */
11381:
1.164 brouard 11382: char ca[32], cb[32];
1.136 brouard 11383: /* FILE *fichtm; *//* Html File */
11384: /* FILE *ficgp;*/ /*Gnuplot File */
11385: struct stat info;
1.191 brouard 11386: double agedeb=0.;
1.194 brouard 11387:
11388: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 11389: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 11390:
1.165 brouard 11391: double fret;
1.191 brouard 11392: double dum=0.; /* Dummy variable */
1.136 brouard 11393: double ***p3mat;
1.218 brouard 11394: /* double ***mobaverage; */
1.319 brouard 11395: double wald;
1.164 brouard 11396:
11397: char line[MAXLINE];
1.197 brouard 11398: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
11399:
1.234 brouard 11400: char modeltemp[MAXLINE];
1.230 brouard 11401: char resultline[MAXLINE];
11402:
1.136 brouard 11403: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 11404: char *tok, *val; /* pathtot */
1.290 brouard 11405: int firstobs=1, lastobs=10; /* nobs = lastobs-firstobs declared globally ;*/
1.195 brouard 11406: int c, h , cpt, c2;
1.191 brouard 11407: int jl=0;
11408: int i1, j1, jk, stepsize=0;
1.194 brouard 11409: int count=0;
11410:
1.164 brouard 11411: int *tab;
1.136 brouard 11412: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.296 brouard 11413: /* double anprojd, mprojd, jprojd; /\* For eventual projections *\/ */
11414: /* double anprojf, mprojf, jprojf; */
11415: /* double jintmean,mintmean,aintmean; */
11416: int prvforecast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
11417: int prvbackcast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
11418: double yrfproj= 10.0; /* Number of years of forward projections */
11419: double yrbproj= 10.0; /* Number of years of backward projections */
11420: int prevbcast=0; /* defined as global for mlikeli and mle, replacing backcast */
1.136 brouard 11421: int mobilav=0,popforecast=0;
1.191 brouard 11422: int hstepm=0, nhstepm=0;
1.136 brouard 11423: int agemortsup;
11424: float sumlpop=0.;
11425: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
11426: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
11427:
1.191 brouard 11428: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 11429: double ftolpl=FTOL;
11430: double **prlim;
1.217 brouard 11431: double **bprlim;
1.317 brouard 11432: double ***param; /* Matrix of parameters, param[i][j][k] param=ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel)
11433: state of origin, state of destination including death, for each covariate: constante, age, and V1 V2 etc. */
1.251 brouard 11434: double ***paramstart; /* Matrix of starting parameter values */
11435: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 11436: double **matcov; /* Matrix of covariance */
1.203 brouard 11437: double **hess; /* Hessian matrix */
1.136 brouard 11438: double ***delti3; /* Scale */
11439: double *delti; /* Scale */
11440: double ***eij, ***vareij;
11441: double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 11442:
1.136 brouard 11443: double *epj, vepp;
1.164 brouard 11444:
1.273 brouard 11445: double dateprev1, dateprev2;
1.296 brouard 11446: double jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000, dateproj1=0, dateproj2=0, dateprojd=0, dateprojf=0;
11447: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000, dateback1=0, dateback2=0, datebackd=0, datebackf=0;
11448:
1.217 brouard 11449:
1.136 brouard 11450: double **ximort;
1.145 brouard 11451: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 11452: int *dcwave;
11453:
1.164 brouard 11454: char z[1]="c";
1.136 brouard 11455:
11456: /*char *strt;*/
11457: char strtend[80];
1.126 brouard 11458:
1.164 brouard 11459:
1.126 brouard 11460: /* setlocale (LC_ALL, ""); */
11461: /* bindtextdomain (PACKAGE, LOCALEDIR); */
11462: /* textdomain (PACKAGE); */
11463: /* setlocale (LC_CTYPE, ""); */
11464: /* setlocale (LC_MESSAGES, ""); */
11465:
11466: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 11467: rstart_time = time(NULL);
11468: /* (void) gettimeofday(&start_time,&tzp);*/
11469: start_time = *localtime(&rstart_time);
1.126 brouard 11470: curr_time=start_time;
1.157 brouard 11471: /*tml = *localtime(&start_time.tm_sec);*/
11472: /* strcpy(strstart,asctime(&tml)); */
11473: strcpy(strstart,asctime(&start_time));
1.126 brouard 11474:
11475: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 11476: /* tp.tm_sec = tp.tm_sec +86400; */
11477: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 11478: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
11479: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
11480: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 11481: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 11482: /* strt=asctime(&tmg); */
11483: /* printf("Time(after) =%s",strstart); */
11484: /* (void) time (&time_value);
11485: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
11486: * tm = *localtime(&time_value);
11487: * strstart=asctime(&tm);
11488: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
11489: */
11490:
11491: nberr=0; /* Number of errors and warnings */
11492: nbwarn=0;
1.184 brouard 11493: #ifdef WIN32
11494: _getcwd(pathcd, size);
11495: #else
1.126 brouard 11496: getcwd(pathcd, size);
1.184 brouard 11497: #endif
1.191 brouard 11498: syscompilerinfo(0);
1.196 brouard 11499: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 11500: if(argc <=1){
11501: printf("\nEnter the parameter file name: ");
1.205 brouard 11502: if(!fgets(pathr,FILENAMELENGTH,stdin)){
11503: printf("ERROR Empty parameter file name\n");
11504: goto end;
11505: }
1.126 brouard 11506: i=strlen(pathr);
11507: if(pathr[i-1]=='\n')
11508: pathr[i-1]='\0';
1.156 brouard 11509: i=strlen(pathr);
1.205 brouard 11510: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 11511: pathr[i-1]='\0';
1.205 brouard 11512: }
11513: i=strlen(pathr);
11514: if( i==0 ){
11515: printf("ERROR Empty parameter file name\n");
11516: goto end;
11517: }
11518: for (tok = pathr; tok != NULL; ){
1.126 brouard 11519: printf("Pathr |%s|\n",pathr);
11520: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
11521: printf("val= |%s| pathr=%s\n",val,pathr);
11522: strcpy (pathtot, val);
11523: if(pathr[0] == '\0') break; /* Dirty */
11524: }
11525: }
1.281 brouard 11526: else if (argc<=2){
11527: strcpy(pathtot,argv[1]);
11528: }
1.126 brouard 11529: else{
11530: strcpy(pathtot,argv[1]);
1.281 brouard 11531: strcpy(z,argv[2]);
11532: printf("\nargv[2]=%s z=%c\n",argv[2],z[0]);
1.126 brouard 11533: }
11534: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
11535: /*cygwin_split_path(pathtot,path,optionfile);
11536: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
11537: /* cutv(path,optionfile,pathtot,'\\');*/
11538:
11539: /* Split argv[0], imach program to get pathimach */
11540: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
11541: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
11542: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
11543: /* strcpy(pathimach,argv[0]); */
11544: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
11545: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
11546: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 11547: #ifdef WIN32
11548: _chdir(path); /* Can be a relative path */
11549: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
11550: #else
1.126 brouard 11551: chdir(path); /* Can be a relative path */
1.184 brouard 11552: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
11553: #endif
11554: printf("Current directory %s!\n",pathcd);
1.126 brouard 11555: strcpy(command,"mkdir ");
11556: strcat(command,optionfilefiname);
11557: if((outcmd=system(command)) != 0){
1.169 brouard 11558: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 11559: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
11560: /* fclose(ficlog); */
11561: /* exit(1); */
11562: }
11563: /* if((imk=mkdir(optionfilefiname))<0){ */
11564: /* perror("mkdir"); */
11565: /* } */
11566:
11567: /*-------- arguments in the command line --------*/
11568:
1.186 brouard 11569: /* Main Log file */
1.126 brouard 11570: strcat(filelog, optionfilefiname);
11571: strcat(filelog,".log"); /* */
11572: if((ficlog=fopen(filelog,"w"))==NULL) {
11573: printf("Problem with logfile %s\n",filelog);
11574: goto end;
11575: }
11576: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 11577: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 11578: fprintf(ficlog,"\nEnter the parameter file name: \n");
11579: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
11580: path=%s \n\
11581: optionfile=%s\n\
11582: optionfilext=%s\n\
1.156 brouard 11583: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 11584:
1.197 brouard 11585: syscompilerinfo(1);
1.167 brouard 11586:
1.126 brouard 11587: printf("Local time (at start):%s",strstart);
11588: fprintf(ficlog,"Local time (at start): %s",strstart);
11589: fflush(ficlog);
11590: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 11591: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 11592:
11593: /* */
11594: strcpy(fileres,"r");
11595: strcat(fileres, optionfilefiname);
1.201 brouard 11596: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 11597: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 11598: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 11599:
1.186 brouard 11600: /* Main ---------arguments file --------*/
1.126 brouard 11601:
11602: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 11603: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
11604: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 11605: fflush(ficlog);
1.149 brouard 11606: /* goto end; */
11607: exit(70);
1.126 brouard 11608: }
11609:
11610: strcpy(filereso,"o");
1.201 brouard 11611: strcat(filereso,fileresu);
1.126 brouard 11612: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
11613: printf("Problem with Output resultfile: %s\n", filereso);
11614: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
11615: fflush(ficlog);
11616: goto end;
11617: }
1.278 brouard 11618: /*-------- Rewriting parameter file ----------*/
11619: strcpy(rfileres,"r"); /* "Rparameterfile */
11620: strcat(rfileres,optionfilefiname); /* Parameter file first name */
11621: strcat(rfileres,"."); /* */
11622: strcat(rfileres,optionfilext); /* Other files have txt extension */
11623: if((ficres =fopen(rfileres,"w"))==NULL) {
11624: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
11625: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
11626: fflush(ficlog);
11627: goto end;
11628: }
11629: fprintf(ficres,"#IMaCh %s\n",version);
1.126 brouard 11630:
1.278 brouard 11631:
1.126 brouard 11632: /* Reads comments: lines beginning with '#' */
11633: numlinepar=0;
1.277 brouard 11634: /* Is it a BOM UTF-8 Windows file? */
11635: /* First parameter line */
1.197 brouard 11636: while(fgets(line, MAXLINE, ficpar)) {
1.277 brouard 11637: noffset=0;
11638: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
11639: {
11640: noffset=noffset+3;
11641: printf("# File is an UTF8 Bom.\n"); // 0xBF
11642: }
1.302 brouard 11643: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
11644: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
1.277 brouard 11645: {
11646: noffset=noffset+2;
11647: printf("# File is an UTF16BE BOM file\n");
11648: }
11649: else if( line[0] == 0 && line[1] == 0)
11650: {
11651: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
11652: noffset=noffset+4;
11653: printf("# File is an UTF16BE BOM file\n");
11654: }
11655: } else{
11656: ;/*printf(" Not a BOM file\n");*/
11657: }
11658:
1.197 brouard 11659: /* If line starts with a # it is a comment */
1.277 brouard 11660: if (line[noffset] == '#') {
1.197 brouard 11661: numlinepar++;
11662: fputs(line,stdout);
11663: fputs(line,ficparo);
1.278 brouard 11664: fputs(line,ficres);
1.197 brouard 11665: fputs(line,ficlog);
11666: continue;
11667: }else
11668: break;
11669: }
11670: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
11671: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
11672: if (num_filled != 5) {
11673: printf("Should be 5 parameters\n");
1.283 brouard 11674: fprintf(ficlog,"Should be 5 parameters\n");
1.197 brouard 11675: }
1.126 brouard 11676: numlinepar++;
1.197 brouard 11677: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.283 brouard 11678: fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
11679: fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
11680: fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.197 brouard 11681: }
11682: /* Second parameter line */
11683: while(fgets(line, MAXLINE, ficpar)) {
1.283 brouard 11684: /* while(fscanf(ficpar,"%[^\n]", line)) { */
11685: /* If line starts with a # it is a comment. Strangely fgets reads the EOL and fputs doesn't */
1.197 brouard 11686: if (line[0] == '#') {
11687: numlinepar++;
1.283 brouard 11688: printf("%s",line);
11689: fprintf(ficres,"%s",line);
11690: fprintf(ficparo,"%s",line);
11691: fprintf(ficlog,"%s",line);
1.197 brouard 11692: continue;
11693: }else
11694: break;
11695: }
1.223 brouard 11696: 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", \
11697: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
11698: if (num_filled != 11) {
11699: 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 11700: printf("but line=%s\n",line);
1.283 brouard 11701: 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");
11702: fprintf(ficlog,"but line=%s\n",line);
1.197 brouard 11703: }
1.286 brouard 11704: if( lastpass > maxwav){
11705: printf("Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
11706: fprintf(ficlog,"Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
11707: fflush(ficlog);
11708: goto end;
11709: }
11710: 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 11711: 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 11712: 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 11713: 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 11714: }
1.203 brouard 11715: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 11716: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 11717: /* Third parameter line */
11718: while(fgets(line, MAXLINE, ficpar)) {
11719: /* If line starts with a # it is a comment */
11720: if (line[0] == '#') {
11721: numlinepar++;
1.283 brouard 11722: printf("%s",line);
11723: fprintf(ficres,"%s",line);
11724: fprintf(ficparo,"%s",line);
11725: fprintf(ficlog,"%s",line);
1.197 brouard 11726: continue;
11727: }else
11728: break;
11729: }
1.201 brouard 11730: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){
1.279 brouard 11731: if (num_filled != 1){
1.302 brouard 11732: printf("ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
11733: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
1.197 brouard 11734: model[0]='\0';
11735: goto end;
11736: }
11737: else{
11738: if (model[0]=='+'){
11739: for(i=1; i<=strlen(model);i++)
11740: modeltemp[i-1]=model[i];
1.201 brouard 11741: strcpy(model,modeltemp);
1.197 brouard 11742: }
11743: }
1.199 brouard 11744: /* printf(" model=1+age%s modeltemp= %s, model=%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 11745: printf("model=1+age+%s\n",model);fflush(stdout);
1.283 brouard 11746: fprintf(ficparo,"model=1+age+%s\n",model);fflush(stdout);
11747: fprintf(ficres,"model=1+age+%s\n",model);fflush(stdout);
11748: fprintf(ficlog,"model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 11749: }
11750: /* 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); */
11751: /* numlinepar=numlinepar+3; /\* In general *\/ */
11752: /* 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 11753: /* 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); */
11754: /* 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 11755: fflush(ficlog);
1.190 brouard 11756: /* if(model[0]=='#'|| model[0]== '\0'){ */
11757: if(model[0]=='#'){
1.279 brouard 11758: printf("Error in 'model' line: model should start with 'model=1+age+' and end without space \n \
11759: 'model=1+age+' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age' or \n \
11760: 'model=1+age+V1+V2' or 'model=1+age+V1+V2+V1*V2' etc. \n"); \
1.187 brouard 11761: if(mle != -1){
1.279 brouard 11762: 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 11763: exit(1);
11764: }
11765: }
1.126 brouard 11766: while((c=getc(ficpar))=='#' && c!= EOF){
11767: ungetc(c,ficpar);
11768: fgets(line, MAXLINE, ficpar);
11769: numlinepar++;
1.195 brouard 11770: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
11771: z[0]=line[1];
11772: }
11773: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 11774: fputs(line, stdout);
11775: //puts(line);
1.126 brouard 11776: fputs(line,ficparo);
11777: fputs(line,ficlog);
11778: }
11779: ungetc(c,ficpar);
11780:
11781:
1.290 brouard 11782: covar=matrix(0,NCOVMAX,firstobs,lastobs); /**< used in readdata */
11783: if(nqv>=1)coqvar=matrix(1,nqv,firstobs,lastobs); /**< Fixed quantitative covariate */
11784: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,firstobs,lastobs); /**< Time varying quantitative covariate */
11785: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,firstobs,lastobs); /**< Time varying covariate (dummy and quantitative)*/
1.136 brouard 11786: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
11787: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
11788: v1+v2*age+v2*v3 makes cptcovn = 3
11789: */
11790: if (strlen(model)>1)
1.187 brouard 11791: 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 11792: else
1.187 brouard 11793: ncovmodel=2; /* Constant and age */
1.133 brouard 11794: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
11795: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 11796: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
11797: 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);
11798: 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);
11799: fflush(stdout);
11800: fclose (ficlog);
11801: goto end;
11802: }
1.126 brouard 11803: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
11804: delti=delti3[1][1];
11805: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
11806: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 11807: /* We could also provide initial parameters values giving by simple logistic regression
11808: * only one way, that is without matrix product. We will have nlstate maximizations */
11809: /* for(i=1;i<nlstate;i++){ */
11810: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
11811: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
11812: /* } */
1.126 brouard 11813: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 11814: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
11815: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 11816: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
11817: fclose (ficparo);
11818: fclose (ficlog);
11819: goto end;
11820: exit(0);
1.220 brouard 11821: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 11822: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 11823: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
11824: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 11825: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
11826: matcov=matrix(1,npar,1,npar);
1.203 brouard 11827: hess=matrix(1,npar,1,npar);
1.220 brouard 11828: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 11829: /* Read guessed parameters */
1.126 brouard 11830: /* Reads comments: lines beginning with '#' */
11831: while((c=getc(ficpar))=='#' && c!= EOF){
11832: ungetc(c,ficpar);
11833: fgets(line, MAXLINE, ficpar);
11834: numlinepar++;
1.141 brouard 11835: fputs(line,stdout);
1.126 brouard 11836: fputs(line,ficparo);
11837: fputs(line,ficlog);
11838: }
11839: ungetc(c,ficpar);
11840:
11841: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 11842: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 11843: for(i=1; i <=nlstate; i++){
1.234 brouard 11844: j=0;
1.126 brouard 11845: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 11846: if(jj==i) continue;
11847: j++;
1.292 brouard 11848: while((c=getc(ficpar))=='#' && c!= EOF){
11849: ungetc(c,ficpar);
11850: fgets(line, MAXLINE, ficpar);
11851: numlinepar++;
11852: fputs(line,stdout);
11853: fputs(line,ficparo);
11854: fputs(line,ficlog);
11855: }
11856: ungetc(c,ficpar);
1.234 brouard 11857: fscanf(ficpar,"%1d%1d",&i1,&j1);
11858: if ((i1 != i) || (j1 != jj)){
11859: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 11860: It might be a problem of design; if ncovcol and the model are correct\n \
11861: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 11862: exit(1);
11863: }
11864: fprintf(ficparo,"%1d%1d",i1,j1);
11865: if(mle==1)
11866: printf("%1d%1d",i,jj);
11867: fprintf(ficlog,"%1d%1d",i,jj);
11868: for(k=1; k<=ncovmodel;k++){
11869: fscanf(ficpar," %lf",¶m[i][j][k]);
11870: if(mle==1){
11871: printf(" %lf",param[i][j][k]);
11872: fprintf(ficlog," %lf",param[i][j][k]);
11873: }
11874: else
11875: fprintf(ficlog," %lf",param[i][j][k]);
11876: fprintf(ficparo," %lf",param[i][j][k]);
11877: }
11878: fscanf(ficpar,"\n");
11879: numlinepar++;
11880: if(mle==1)
11881: printf("\n");
11882: fprintf(ficlog,"\n");
11883: fprintf(ficparo,"\n");
1.126 brouard 11884: }
11885: }
11886: fflush(ficlog);
1.234 brouard 11887:
1.251 brouard 11888: /* Reads parameters values */
1.126 brouard 11889: p=param[1][1];
1.251 brouard 11890: pstart=paramstart[1][1];
1.126 brouard 11891:
11892: /* Reads comments: lines beginning with '#' */
11893: while((c=getc(ficpar))=='#' && c!= EOF){
11894: ungetc(c,ficpar);
11895: fgets(line, MAXLINE, ficpar);
11896: numlinepar++;
1.141 brouard 11897: fputs(line,stdout);
1.126 brouard 11898: fputs(line,ficparo);
11899: fputs(line,ficlog);
11900: }
11901: ungetc(c,ficpar);
11902:
11903: for(i=1; i <=nlstate; i++){
11904: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 11905: fscanf(ficpar,"%1d%1d",&i1,&j1);
11906: if ( (i1-i) * (j1-j) != 0){
11907: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
11908: exit(1);
11909: }
11910: printf("%1d%1d",i,j);
11911: fprintf(ficparo,"%1d%1d",i1,j1);
11912: fprintf(ficlog,"%1d%1d",i1,j1);
11913: for(k=1; k<=ncovmodel;k++){
11914: fscanf(ficpar,"%le",&delti3[i][j][k]);
11915: printf(" %le",delti3[i][j][k]);
11916: fprintf(ficparo," %le",delti3[i][j][k]);
11917: fprintf(ficlog," %le",delti3[i][j][k]);
11918: }
11919: fscanf(ficpar,"\n");
11920: numlinepar++;
11921: printf("\n");
11922: fprintf(ficparo,"\n");
11923: fprintf(ficlog,"\n");
1.126 brouard 11924: }
11925: }
11926: fflush(ficlog);
1.234 brouard 11927:
1.145 brouard 11928: /* Reads covariance matrix */
1.126 brouard 11929: delti=delti3[1][1];
1.220 brouard 11930:
11931:
1.126 brouard 11932: /* 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 11933:
1.126 brouard 11934: /* Reads comments: lines beginning with '#' */
11935: while((c=getc(ficpar))=='#' && c!= EOF){
11936: ungetc(c,ficpar);
11937: fgets(line, MAXLINE, ficpar);
11938: numlinepar++;
1.141 brouard 11939: fputs(line,stdout);
1.126 brouard 11940: fputs(line,ficparo);
11941: fputs(line,ficlog);
11942: }
11943: ungetc(c,ficpar);
1.220 brouard 11944:
1.126 brouard 11945: matcov=matrix(1,npar,1,npar);
1.203 brouard 11946: hess=matrix(1,npar,1,npar);
1.131 brouard 11947: for(i=1; i <=npar; i++)
11948: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 11949:
1.194 brouard 11950: /* Scans npar lines */
1.126 brouard 11951: for(i=1; i <=npar; i++){
1.226 brouard 11952: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 11953: if(count != 3){
1.226 brouard 11954: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11955: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11956: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11957: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11958: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11959: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11960: exit(1);
1.220 brouard 11961: }else{
1.226 brouard 11962: if(mle==1)
11963: printf("%1d%1d%d",i1,j1,jk);
11964: }
11965: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
11966: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 11967: for(j=1; j <=i; j++){
1.226 brouard 11968: fscanf(ficpar," %le",&matcov[i][j]);
11969: if(mle==1){
11970: printf(" %.5le",matcov[i][j]);
11971: }
11972: fprintf(ficlog," %.5le",matcov[i][j]);
11973: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 11974: }
11975: fscanf(ficpar,"\n");
11976: numlinepar++;
11977: if(mle==1)
1.220 brouard 11978: printf("\n");
1.126 brouard 11979: fprintf(ficlog,"\n");
11980: fprintf(ficparo,"\n");
11981: }
1.194 brouard 11982: /* End of read covariance matrix npar lines */
1.126 brouard 11983: for(i=1; i <=npar; i++)
11984: for(j=i+1;j<=npar;j++)
1.226 brouard 11985: matcov[i][j]=matcov[j][i];
1.126 brouard 11986:
11987: if(mle==1)
11988: printf("\n");
11989: fprintf(ficlog,"\n");
11990:
11991: fflush(ficlog);
11992:
11993: } /* End of mle != -3 */
1.218 brouard 11994:
1.186 brouard 11995: /* Main data
11996: */
1.290 brouard 11997: nobs=lastobs-firstobs+1; /* was = lastobs;*/
11998: /* num=lvector(1,n); */
11999: /* moisnais=vector(1,n); */
12000: /* annais=vector(1,n); */
12001: /* moisdc=vector(1,n); */
12002: /* andc=vector(1,n); */
12003: /* weight=vector(1,n); */
12004: /* agedc=vector(1,n); */
12005: /* cod=ivector(1,n); */
12006: /* for(i=1;i<=n;i++){ */
12007: num=lvector(firstobs,lastobs);
12008: moisnais=vector(firstobs,lastobs);
12009: annais=vector(firstobs,lastobs);
12010: moisdc=vector(firstobs,lastobs);
12011: andc=vector(firstobs,lastobs);
12012: weight=vector(firstobs,lastobs);
12013: agedc=vector(firstobs,lastobs);
12014: cod=ivector(firstobs,lastobs);
12015: for(i=firstobs;i<=lastobs;i++){
1.234 brouard 12016: num[i]=0;
12017: moisnais[i]=0;
12018: annais[i]=0;
12019: moisdc[i]=0;
12020: andc[i]=0;
12021: agedc[i]=0;
12022: cod[i]=0;
12023: weight[i]=1.0; /* Equal weights, 1 by default */
12024: }
1.290 brouard 12025: mint=matrix(1,maxwav,firstobs,lastobs);
12026: anint=matrix(1,maxwav,firstobs,lastobs);
1.325 brouard 12027: s=imatrix(1,maxwav+1,firstobs,lastobs); /* s[i][j] health state for wave i and individual j */
12028: printf("BUG ncovmodel=%d NCOVMAX=%d 2**ncovmodel=%f BUG\n",ncovmodel,NCOVMAX,pow(2,ncovmodel));
1.126 brouard 12029: tab=ivector(1,NCOVMAX);
1.144 brouard 12030: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 12031: 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 12032:
1.136 brouard 12033: /* Reads data from file datafile */
12034: if (readdata(datafile, firstobs, lastobs, &imx)==1)
12035: goto end;
12036:
12037: /* Calculation of the number of parameters from char model */
1.234 brouard 12038: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 12039: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
12040: k=3 V4 Tvar[k=3]= 4 (from V4)
12041: k=2 V1 Tvar[k=2]= 1 (from V1)
12042: k=1 Tvar[1]=2 (from V2)
1.234 brouard 12043: */
12044:
12045: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
12046: TvarsDind=ivector(1,NCOVMAX); /* */
12047: TvarsD=ivector(1,NCOVMAX); /* */
12048: TvarsQind=ivector(1,NCOVMAX); /* */
12049: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 12050: TvarF=ivector(1,NCOVMAX); /* */
12051: TvarFind=ivector(1,NCOVMAX); /* */
12052: TvarV=ivector(1,NCOVMAX); /* */
12053: TvarVind=ivector(1,NCOVMAX); /* */
12054: TvarA=ivector(1,NCOVMAX); /* */
12055: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 12056: TvarFD=ivector(1,NCOVMAX); /* */
12057: TvarFDind=ivector(1,NCOVMAX); /* */
12058: TvarFQ=ivector(1,NCOVMAX); /* */
12059: TvarFQind=ivector(1,NCOVMAX); /* */
12060: TvarVD=ivector(1,NCOVMAX); /* */
12061: TvarVDind=ivector(1,NCOVMAX); /* */
12062: TvarVQ=ivector(1,NCOVMAX); /* */
12063: TvarVQind=ivector(1,NCOVMAX); /* */
12064:
1.230 brouard 12065: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 12066: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 12067: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
12068: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
12069: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.137 brouard 12070: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
12071: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
12072: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
12073: */
12074: /* For model-covariate k tells which data-covariate to use but
12075: because this model-covariate is a construction we invent a new column
12076: ncovcol + k1
12077: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
12078: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 12079: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
12080: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 12081: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
12082: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 12083: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 12084: */
1.145 brouard 12085: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
12086: 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 12087: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
12088: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.145 brouard 12089: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 12090: 4 covariates (3 plus signs)
12091: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
1.328 brouard 12092: */
12093: for(i=1;i<NCOVMAX;i++)
12094: Tage[i]=0;
1.230 brouard 12095: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 12096: * individual dummy, fixed or varying:
12097: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
12098: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 12099: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
12100: * V1 df, V2 qf, V3 & V4 dv, V5 qv
12101: * Tmodelind[1]@9={9,0,3,2,}*/
12102: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
12103: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 12104: * individual quantitative, fixed or varying:
12105: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
12106: * 3, 1, 0, 0, 0, 0, 0, 0},
12107: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.186 brouard 12108: /* Main decodemodel */
12109:
1.187 brouard 12110:
1.223 brouard 12111: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 12112: goto end;
12113:
1.137 brouard 12114: if((double)(lastobs-imx)/(double)imx > 1.10){
12115: nbwarn++;
12116: 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);
12117: 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);
12118: }
1.136 brouard 12119: /* if(mle==1){*/
1.137 brouard 12120: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
12121: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 12122: }
12123:
12124: /*-calculation of age at interview from date of interview and age at death -*/
12125: agev=matrix(1,maxwav,1,imx);
12126:
12127: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
12128: goto end;
12129:
1.126 brouard 12130:
1.136 brouard 12131: agegomp=(int)agemin;
1.290 brouard 12132: free_vector(moisnais,firstobs,lastobs);
12133: free_vector(annais,firstobs,lastobs);
1.126 brouard 12134: /* free_matrix(mint,1,maxwav,1,n);
12135: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 12136: /* free_vector(moisdc,1,n); */
12137: /* free_vector(andc,1,n); */
1.145 brouard 12138: /* */
12139:
1.126 brouard 12140: wav=ivector(1,imx);
1.214 brouard 12141: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
12142: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
12143: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
12144: 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.*/
12145: bh=imatrix(1,lastpass-firstpass+2,1,imx);
12146: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 12147:
12148: /* Concatenates waves */
1.214 brouard 12149: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
12150: Death is a valid wave (if date is known).
12151: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
12152: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
12153: and mw[mi+1][i]. dh depends on stepm.
12154: */
12155:
1.126 brouard 12156: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 12157: /* Concatenates waves */
1.145 brouard 12158:
1.290 brouard 12159: free_vector(moisdc,firstobs,lastobs);
12160: free_vector(andc,firstobs,lastobs);
1.215 brouard 12161:
1.126 brouard 12162: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
12163: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
12164: ncodemax[1]=1;
1.145 brouard 12165: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 12166: cptcoveff=0;
1.220 brouard 12167: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
12168: tricode(&cptcoveff,Tvar,nbcode,imx, Ndum); /**< Fills nbcode[Tvar[j]][l]; */
1.227 brouard 12169: }
12170:
12171: ncovcombmax=pow(2,cptcoveff);
12172: invalidvarcomb=ivector(1, ncovcombmax);
12173: for(i=1;i<ncovcombmax;i++)
12174: invalidvarcomb[i]=0;
12175:
1.211 brouard 12176: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 12177: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 12178: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 12179:
1.200 brouard 12180: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 12181: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 12182: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 12183: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
12184: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
12185: * (currently 0 or 1) in the data.
12186: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
12187: * corresponding modality (h,j).
12188: */
12189:
1.145 brouard 12190: h=0;
12191: /*if (cptcovn > 0) */
1.126 brouard 12192: m=pow(2,cptcoveff);
12193:
1.144 brouard 12194: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 12195: * For k=4 covariates, h goes from 1 to m=2**k
12196: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
12197: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.329 ! brouard 12198: * h\k 1 2 3 4 * h-1\k-1 4 3 2 1
! 12199: *______________________________ *______________________
! 12200: * 1 i=1 1 i=1 1 i=1 1 i=1 1 * 0 0 0 0 0
! 12201: * 2 2 1 1 1 * 1 0 0 0 1
! 12202: * 3 i=2 1 2 1 1 * 2 0 0 1 0
! 12203: * 4 2 2 1 1 * 3 0 0 1 1
! 12204: * 5 i=3 1 i=2 1 2 1 * 4 0 1 0 0
! 12205: * 6 2 1 2 1 * 5 0 1 0 1
! 12206: * 7 i=4 1 2 2 1 * 6 0 1 1 0
! 12207: * 8 2 2 2 1 * 7 0 1 1 1
! 12208: * 9 i=5 1 i=3 1 i=2 1 2 * 8 1 0 0 0
! 12209: * 10 2 1 1 2 * 9 1 0 0 1
! 12210: * 11 i=6 1 2 1 2 * 10 1 0 1 0
! 12211: * 12 2 2 1 2 * 11 1 0 1 1
! 12212: * 13 i=7 1 i=4 1 2 2 * 12 1 1 0 0
! 12213: * 14 2 1 2 2 * 13 1 1 0 1
! 12214: * 15 i=8 1 2 2 2 * 14 1 1 1 0
! 12215: * 16 2 2 2 2 * 15 1 1 1 1
! 12216: */
1.212 brouard 12217: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 12218: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
12219: * and the value of each covariate?
12220: * V1=1, V2=1, V3=2, V4=1 ?
12221: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
12222: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
12223: * In order to get the real value in the data, we use nbcode
12224: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
12225: * We are keeping this crazy system in order to be able (in the future?)
12226: * to have more than 2 values (0 or 1) for a covariate.
12227: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
12228: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
12229: * bbbbbbbb
12230: * 76543210
12231: * h-1 00000101 (6-1=5)
1.219 brouard 12232: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 12233: * &
12234: * 1 00000001 (1)
1.219 brouard 12235: * 00000000 = 1 & ((h-1) >> (k-1))
12236: * +1= 00000001 =1
1.211 brouard 12237: *
12238: * h=14, k=3 => h'=h-1=13, k'=k-1=2
12239: * h' 1101 =2^3+2^2+0x2^1+2^0
12240: * >>k' 11
12241: * & 00000001
12242: * = 00000001
12243: * +1 = 00000010=2 = codtabm(14,3)
12244: * Reverse h=6 and m=16?
12245: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
12246: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
12247: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
12248: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
12249: * V3=decodtabm(14,3,2**4)=2
12250: * h'=13 1101 =2^3+2^2+0x2^1+2^0
12251: *(h-1) >> (j-1) 0011 =13 >> 2
12252: * &1 000000001
12253: * = 000000001
12254: * +1= 000000010 =2
12255: * 2211
12256: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
12257: * V3=2
1.220 brouard 12258: * codtabm and decodtabm are identical
1.211 brouard 12259: */
12260:
1.145 brouard 12261:
12262: free_ivector(Ndum,-1,NCOVMAX);
12263:
12264:
1.126 brouard 12265:
1.186 brouard 12266: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 12267: strcpy(optionfilegnuplot,optionfilefiname);
12268: if(mle==-3)
1.201 brouard 12269: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 12270: strcat(optionfilegnuplot,".gp");
12271:
12272: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
12273: printf("Problem with file %s",optionfilegnuplot);
12274: }
12275: else{
1.204 brouard 12276: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 12277: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 12278: //fprintf(ficgp,"set missing 'NaNq'\n");
12279: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 12280: }
12281: /* fclose(ficgp);*/
1.186 brouard 12282:
12283:
12284: /* Initialisation of --------- index.htm --------*/
1.126 brouard 12285:
12286: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
12287: if(mle==-3)
1.201 brouard 12288: strcat(optionfilehtm,"-MORT_");
1.126 brouard 12289: strcat(optionfilehtm,".htm");
12290: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 12291: printf("Problem with %s \n",optionfilehtm);
12292: exit(0);
1.126 brouard 12293: }
12294:
12295: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
12296: strcat(optionfilehtmcov,"-cov.htm");
12297: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
12298: printf("Problem with %s \n",optionfilehtmcov), exit(0);
12299: }
12300: else{
12301: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
12302: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 12303: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 12304: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
12305: }
12306:
1.324 brouard 12307: 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 12308: <hr size=\"2\" color=\"#EC5E5E\"> \n\
12309: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 12310: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 12311: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n\
1.126 brouard 12312: \n\
12313: <hr size=\"2\" color=\"#EC5E5E\">\
12314: <ul><li><h4>Parameter files</h4>\n\
12315: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
12316: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
12317: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
12318: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
12319: - Date and time at start: %s</ul>\n",\
12320: optionfilehtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model,\
12321: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
12322: fileres,fileres,\
12323: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
12324: fflush(fichtm);
12325:
12326: strcpy(pathr,path);
12327: strcat(pathr,optionfilefiname);
1.184 brouard 12328: #ifdef WIN32
12329: _chdir(optionfilefiname); /* Move to directory named optionfile */
12330: #else
1.126 brouard 12331: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 12332: #endif
12333:
1.126 brouard 12334:
1.220 brouard 12335: /* Calculates basic frequencies. Computes observed prevalence at single age
12336: and for any valid combination of covariates
1.126 brouard 12337: and prints on file fileres'p'. */
1.251 brouard 12338: freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 12339: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 12340:
12341: fprintf(fichtm,"\n");
1.286 brouard 12342: 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 12343: ftol, stepm);
12344: fprintf(fichtm,"\n<li>Number of fixed dummy covariates: ncovcol=%d ", ncovcol);
12345: ncurrv=1;
12346: for(i=ncurrv; i <=ncovcol; i++) fprintf(fichtm,"V%d ", i);
12347: fprintf(fichtm,"\n<li> Number of fixed quantitative variables: nqv=%d ", nqv);
12348: ncurrv=i;
12349: for(i=ncurrv; i <=ncurrv-1+nqv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 12350: fprintf(fichtm,"\n<li> Number of time varying (wave varying) dummy covariates: ntv=%d ", ntv);
1.274 brouard 12351: ncurrv=i;
12352: for(i=ncurrv; i <=ncurrv-1+ntv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 12353: fprintf(fichtm,"\n<li>Number of time varying quantitative covariates: nqtv=%d ", nqtv);
1.274 brouard 12354: ncurrv=i;
12355: for(i=ncurrv; i <=ncurrv-1+nqtv; i++) fprintf(fichtm,"V%d ", i);
12356: 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", \
12357: nlstate, ndeath, maxwav, mle, weightopt);
12358:
12359: fprintf(fichtm,"<h4> Diagram of states <a href=\"%s_.svg\">%s_.svg</a></h4> \n\
12360: <img src=\"%s_.svg\">", subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"));
12361:
12362:
1.317 brouard 12363: fprintf(fichtm,"\n<h4>Some descriptive statistics </h4>\n<br>Number of (used) observations=%d <br>\n\
1.126 brouard 12364: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
12365: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
1.274 brouard 12366: imx,agemin,agemax,jmin,jmax,jmean);
1.126 brouard 12367: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 12368: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
12369: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
12370: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
12371: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 12372:
1.126 brouard 12373: /* For Powell, parameters are in a vector p[] starting at p[1]
12374: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
12375: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
12376:
12377: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 12378: /* For mortality only */
1.126 brouard 12379: if (mle==-3){
1.136 brouard 12380: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 12381: for(i=1;i<=NDIM;i++)
12382: for(j=1;j<=NDIM;j++)
12383: ximort[i][j]=0.;
1.186 brouard 12384: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.290 brouard 12385: cens=ivector(firstobs,lastobs);
12386: ageexmed=vector(firstobs,lastobs);
12387: agecens=vector(firstobs,lastobs);
12388: dcwave=ivector(firstobs,lastobs);
1.223 brouard 12389:
1.126 brouard 12390: for (i=1; i<=imx; i++){
12391: dcwave[i]=-1;
12392: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 12393: if (s[m][i]>nlstate) {
12394: dcwave[i]=m;
12395: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
12396: break;
12397: }
1.126 brouard 12398: }
1.226 brouard 12399:
1.126 brouard 12400: for (i=1; i<=imx; i++) {
12401: if (wav[i]>0){
1.226 brouard 12402: ageexmed[i]=agev[mw[1][i]][i];
12403: j=wav[i];
12404: agecens[i]=1.;
12405:
12406: if (ageexmed[i]> 1 && wav[i] > 0){
12407: agecens[i]=agev[mw[j][i]][i];
12408: cens[i]= 1;
12409: }else if (ageexmed[i]< 1)
12410: cens[i]= -1;
12411: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
12412: cens[i]=0 ;
1.126 brouard 12413: }
12414: else cens[i]=-1;
12415: }
12416:
12417: for (i=1;i<=NDIM;i++) {
12418: for (j=1;j<=NDIM;j++)
1.226 brouard 12419: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 12420: }
12421:
1.302 brouard 12422: p[1]=0.0268; p[NDIM]=0.083;
12423: /* printf("%lf %lf", p[1], p[2]); */
1.126 brouard 12424:
12425:
1.136 brouard 12426: #ifdef GSL
12427: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 12428: #else
1.126 brouard 12429: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 12430: #endif
1.201 brouard 12431: strcpy(filerespow,"POW-MORT_");
12432: strcat(filerespow,fileresu);
1.126 brouard 12433: if((ficrespow=fopen(filerespow,"w"))==NULL) {
12434: printf("Problem with resultfile: %s\n", filerespow);
12435: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
12436: }
1.136 brouard 12437: #ifdef GSL
12438: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 12439: #else
1.126 brouard 12440: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 12441: #endif
1.126 brouard 12442: /* for (i=1;i<=nlstate;i++)
12443: for(j=1;j<=nlstate+ndeath;j++)
12444: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
12445: */
12446: fprintf(ficrespow,"\n");
1.136 brouard 12447: #ifdef GSL
12448: /* gsl starts here */
12449: T = gsl_multimin_fminimizer_nmsimplex;
12450: gsl_multimin_fminimizer *sfm = NULL;
12451: gsl_vector *ss, *x;
12452: gsl_multimin_function minex_func;
12453:
12454: /* Initial vertex size vector */
12455: ss = gsl_vector_alloc (NDIM);
12456:
12457: if (ss == NULL){
12458: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
12459: }
12460: /* Set all step sizes to 1 */
12461: gsl_vector_set_all (ss, 0.001);
12462:
12463: /* Starting point */
1.126 brouard 12464:
1.136 brouard 12465: x = gsl_vector_alloc (NDIM);
12466:
12467: if (x == NULL){
12468: gsl_vector_free(ss);
12469: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
12470: }
12471:
12472: /* Initialize method and iterate */
12473: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 12474: /* gsl_vector_set(x, 0, 0.0268); */
12475: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 12476: gsl_vector_set(x, 0, p[1]);
12477: gsl_vector_set(x, 1, p[2]);
12478:
12479: minex_func.f = &gompertz_f;
12480: minex_func.n = NDIM;
12481: minex_func.params = (void *)&p; /* ??? */
12482:
12483: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
12484: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
12485:
12486: printf("Iterations beginning .....\n\n");
12487: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
12488:
12489: iteri=0;
12490: while (rval == GSL_CONTINUE){
12491: iteri++;
12492: status = gsl_multimin_fminimizer_iterate(sfm);
12493:
12494: if (status) printf("error: %s\n", gsl_strerror (status));
12495: fflush(0);
12496:
12497: if (status)
12498: break;
12499:
12500: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
12501: ssval = gsl_multimin_fminimizer_size (sfm);
12502:
12503: if (rval == GSL_SUCCESS)
12504: printf ("converged to a local maximum at\n");
12505:
12506: printf("%5d ", iteri);
12507: for (it = 0; it < NDIM; it++){
12508: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
12509: }
12510: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
12511: }
12512:
12513: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
12514:
12515: gsl_vector_free(x); /* initial values */
12516: gsl_vector_free(ss); /* inital step size */
12517: for (it=0; it<NDIM; it++){
12518: p[it+1]=gsl_vector_get(sfm->x,it);
12519: fprintf(ficrespow," %.12lf", p[it]);
12520: }
12521: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
12522: #endif
12523: #ifdef POWELL
12524: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
12525: #endif
1.126 brouard 12526: fclose(ficrespow);
12527:
1.203 brouard 12528: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 12529:
12530: for(i=1; i <=NDIM; i++)
12531: for(j=i+1;j<=NDIM;j++)
1.220 brouard 12532: matcov[i][j]=matcov[j][i];
1.126 brouard 12533:
12534: printf("\nCovariance matrix\n ");
1.203 brouard 12535: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 12536: for(i=1; i <=NDIM; i++) {
12537: for(j=1;j<=NDIM;j++){
1.220 brouard 12538: printf("%f ",matcov[i][j]);
12539: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 12540: }
1.203 brouard 12541: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 12542: }
12543:
12544: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 12545: for (i=1;i<=NDIM;i++) {
1.126 brouard 12546: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 12547: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
12548: }
1.302 brouard 12549: lsurv=vector(agegomp,AGESUP);
12550: lpop=vector(agegomp,AGESUP);
12551: tpop=vector(agegomp,AGESUP);
1.126 brouard 12552: lsurv[agegomp]=100000;
12553:
12554: for (k=agegomp;k<=AGESUP;k++) {
12555: agemortsup=k;
12556: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
12557: }
12558:
12559: for (k=agegomp;k<agemortsup;k++)
12560: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
12561:
12562: for (k=agegomp;k<agemortsup;k++){
12563: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
12564: sumlpop=sumlpop+lpop[k];
12565: }
12566:
12567: tpop[agegomp]=sumlpop;
12568: for (k=agegomp;k<(agemortsup-3);k++){
12569: /* tpop[k+1]=2;*/
12570: tpop[k+1]=tpop[k]-lpop[k];
12571: }
12572:
12573:
12574: printf("\nAge lx qx dx Lx Tx e(x)\n");
12575: for (k=agegomp;k<(agemortsup-2);k++)
12576: 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]);
12577:
12578:
12579: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 12580: ageminpar=50;
12581: agemaxpar=100;
1.194 brouard 12582: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
12583: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
12584: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12585: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
12586: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
12587: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12588: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 12589: }else{
12590: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
12591: 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 12592: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 12593: }
1.201 brouard 12594: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 12595: stepm, weightopt,\
12596: model,imx,p,matcov,agemortsup);
12597:
1.302 brouard 12598: free_vector(lsurv,agegomp,AGESUP);
12599: free_vector(lpop,agegomp,AGESUP);
12600: free_vector(tpop,agegomp,AGESUP);
1.220 brouard 12601: free_matrix(ximort,1,NDIM,1,NDIM);
1.290 brouard 12602: free_ivector(dcwave,firstobs,lastobs);
12603: free_vector(agecens,firstobs,lastobs);
12604: free_vector(ageexmed,firstobs,lastobs);
12605: free_ivector(cens,firstobs,lastobs);
1.220 brouard 12606: #ifdef GSL
1.136 brouard 12607: #endif
1.186 brouard 12608: } /* Endof if mle==-3 mortality only */
1.205 brouard 12609: /* Standard */
12610: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
12611: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
12612: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 12613: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 12614: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
12615: for (k=1; k<=npar;k++)
12616: printf(" %d %8.5f",k,p[k]);
12617: printf("\n");
1.205 brouard 12618: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
12619: /* mlikeli uses func not funcone */
1.247 brouard 12620: /* for(i=1;i<nlstate;i++){ */
12621: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
12622: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
12623: /* } */
1.205 brouard 12624: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
12625: }
12626: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
12627: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
12628: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
12629: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
12630: }
12631: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 12632: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
12633: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
12634: for (k=1; k<=npar;k++)
12635: printf(" %d %8.5f",k,p[k]);
12636: printf("\n");
12637:
12638: /*--------- results files --------------*/
1.283 brouard 12639: /* 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 12640:
12641:
12642: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 12643: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n"); /* Printing model equation */
1.126 brouard 12644: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 12645:
12646: printf("#model= 1 + age ");
12647: fprintf(ficres,"#model= 1 + age ");
12648: fprintf(ficlog,"#model= 1 + age ");
12649: fprintf(fichtm,"\n<ul><li> model=1+age+%s\n \
12650: </ul>", model);
12651:
12652: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">\n");
12653: fprintf(fichtm, "<tr><th>Model=</th><th>1</th><th>+ age</th>");
12654: if(nagesqr==1){
12655: printf(" + age*age ");
12656: fprintf(ficres," + age*age ");
12657: fprintf(ficlog," + age*age ");
12658: fprintf(fichtm, "<th>+ age*age</th>");
12659: }
12660: for(j=1;j <=ncovmodel-2;j++){
12661: if(Typevar[j]==0) {
12662: printf(" + V%d ",Tvar[j]);
12663: fprintf(ficres," + V%d ",Tvar[j]);
12664: fprintf(ficlog," + V%d ",Tvar[j]);
12665: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
12666: }else if(Typevar[j]==1) {
12667: printf(" + V%d*age ",Tvar[j]);
12668: fprintf(ficres," + V%d*age ",Tvar[j]);
12669: fprintf(ficlog," + V%d*age ",Tvar[j]);
12670: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
12671: }else if(Typevar[j]==2) {
12672: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
12673: fprintf(ficres," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
12674: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
12675: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
12676: }
12677: }
12678: printf("\n");
12679: fprintf(ficres,"\n");
12680: fprintf(ficlog,"\n");
12681: fprintf(fichtm, "</tr>");
12682: fprintf(fichtm, "\n");
12683:
12684:
1.126 brouard 12685: for(i=1,jk=1; i <=nlstate; i++){
12686: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 12687: if (k != i) {
1.319 brouard 12688: fprintf(fichtm, "<tr>");
1.225 brouard 12689: printf("%d%d ",i,k);
12690: fprintf(ficlog,"%d%d ",i,k);
12691: fprintf(ficres,"%1d%1d ",i,k);
1.319 brouard 12692: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 12693: for(j=1; j <=ncovmodel; j++){
12694: printf("%12.7f ",p[jk]);
12695: fprintf(ficlog,"%12.7f ",p[jk]);
12696: fprintf(ficres,"%12.7f ",p[jk]);
1.319 brouard 12697: fprintf(fichtm, "<td>%12.7f</td>",p[jk]);
1.225 brouard 12698: jk++;
12699: }
12700: printf("\n");
12701: fprintf(ficlog,"\n");
12702: fprintf(ficres,"\n");
1.319 brouard 12703: fprintf(fichtm, "</tr>\n");
1.225 brouard 12704: }
1.126 brouard 12705: }
12706: }
1.319 brouard 12707: /* fprintf(fichtm,"</tr>\n"); */
12708: fprintf(fichtm,"</table>\n");
12709: fprintf(fichtm, "\n");
12710:
1.203 brouard 12711: if(mle != 0){
12712: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 12713: ftolhess=ftol; /* Usually correct */
1.203 brouard 12714: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
12715: 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");
12716: 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");
1.322 brouard 12717: fprintf(fichtm, "\n<p>The Wald test results are output only if the maximimzation of the Likelihood is performed (mle=1)\n</br>Parameters, Wald tests and Wald-based confidence intervals\n</br> W is simply the result of the division of the parameter by the square root of covariance of the parameter.\n</br> And Wald-based confidence intervals plus and minus 1.96 * W \n </br> It might be better to visualize the covariance matrix. See the page '<a href=\"%s\">Matrix of variance-covariance of one-step probabilities and its graphs</a>'.\n</br>",optionfilehtmcov);
1.319 brouard 12718: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">");
12719: fprintf(fichtm, "\n<tr><th>Model=</th><th>1</th><th>+ age</th>");
12720: if(nagesqr==1){
12721: printf(" + age*age ");
12722: fprintf(ficres," + age*age ");
12723: fprintf(ficlog," + age*age ");
12724: fprintf(fichtm, "<th>+ age*age</th>");
12725: }
12726: for(j=1;j <=ncovmodel-2;j++){
12727: if(Typevar[j]==0) {
12728: printf(" + V%d ",Tvar[j]);
12729: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
12730: }else if(Typevar[j]==1) {
12731: printf(" + V%d*age ",Tvar[j]);
12732: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
12733: }else if(Typevar[j]==2) {
12734: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
12735: }
12736: }
12737: fprintf(fichtm, "</tr>\n");
12738:
1.203 brouard 12739: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 12740: for(k=1; k <=(nlstate+ndeath); k++){
12741: if (k != i) {
1.319 brouard 12742: fprintf(fichtm, "<tr valign=top>");
1.225 brouard 12743: printf("%d%d ",i,k);
12744: fprintf(ficlog,"%d%d ",i,k);
1.319 brouard 12745: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 12746: for(j=1; j <=ncovmodel; j++){
1.319 brouard 12747: wald=p[jk]/sqrt(matcov[jk][jk]);
1.324 brouard 12748: printf("%12.7f(%12.7f) W=%8.3f CI=[%12.7f ; %12.7f] ",p[jk],sqrt(matcov[jk][jk]), p[jk]/sqrt(matcov[jk][jk]), p[jk]-1.96*sqrt(matcov[jk][jk]),p[jk]+1.96*sqrt(matcov[jk][jk]));
12749: fprintf(ficlog,"%12.7f(%12.7f) W=%8.3f CI=[%12.7f ; %12.7f] ",p[jk],sqrt(matcov[jk][jk]), p[jk]/sqrt(matcov[jk][jk]), p[jk]-1.96*sqrt(matcov[jk][jk]),p[jk]+1.96*sqrt(matcov[jk][jk]));
1.319 brouard 12750: if(fabs(wald) > 1.96){
1.321 brouard 12751: fprintf(fichtm, "<td><b>%12.7f</b></br> (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
1.319 brouard 12752: }else{
12753: fprintf(fichtm, "<td>%12.7f (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
12754: }
1.324 brouard 12755: fprintf(fichtm,"W=%8.3f</br>",wald);
1.319 brouard 12756: fprintf(fichtm,"[%12.7f;%12.7f]</br></td>", p[jk]-1.96*sqrt(matcov[jk][jk]),p[jk]+1.96*sqrt(matcov[jk][jk]));
1.225 brouard 12757: jk++;
12758: }
12759: printf("\n");
12760: fprintf(ficlog,"\n");
1.319 brouard 12761: fprintf(fichtm, "</tr>\n");
1.225 brouard 12762: }
12763: }
1.193 brouard 12764: }
1.203 brouard 12765: } /* end of hesscov and Wald tests */
1.319 brouard 12766: fprintf(fichtm,"</table>\n");
1.225 brouard 12767:
1.203 brouard 12768: /* */
1.126 brouard 12769: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
12770: printf("# Scales (for hessian or gradient estimation)\n");
12771: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
12772: for(i=1,jk=1; i <=nlstate; i++){
12773: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 12774: if (j!=i) {
12775: fprintf(ficres,"%1d%1d",i,j);
12776: printf("%1d%1d",i,j);
12777: fprintf(ficlog,"%1d%1d",i,j);
12778: for(k=1; k<=ncovmodel;k++){
12779: printf(" %.5e",delti[jk]);
12780: fprintf(ficlog," %.5e",delti[jk]);
12781: fprintf(ficres," %.5e",delti[jk]);
12782: jk++;
12783: }
12784: printf("\n");
12785: fprintf(ficlog,"\n");
12786: fprintf(ficres,"\n");
12787: }
1.126 brouard 12788: }
12789: }
12790:
12791: 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 12792: if(mle >= 1) /* To big for the screen */
1.126 brouard 12793: 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");
12794: 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");
12795: /* # 121 Var(a12)\n\ */
12796: /* # 122 Cov(b12,a12) Var(b12)\n\ */
12797: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
12798: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
12799: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
12800: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
12801: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
12802: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
12803:
12804:
12805: /* Just to have a covariance matrix which will be more understandable
12806: even is we still don't want to manage dictionary of variables
12807: */
12808: for(itimes=1;itimes<=2;itimes++){
12809: jj=0;
12810: for(i=1; i <=nlstate; i++){
1.225 brouard 12811: for(j=1; j <=nlstate+ndeath; j++){
12812: if(j==i) continue;
12813: for(k=1; k<=ncovmodel;k++){
12814: jj++;
12815: ca[0]= k+'a'-1;ca[1]='\0';
12816: if(itimes==1){
12817: if(mle>=1)
12818: printf("#%1d%1d%d",i,j,k);
12819: fprintf(ficlog,"#%1d%1d%d",i,j,k);
12820: fprintf(ficres,"#%1d%1d%d",i,j,k);
12821: }else{
12822: if(mle>=1)
12823: printf("%1d%1d%d",i,j,k);
12824: fprintf(ficlog,"%1d%1d%d",i,j,k);
12825: fprintf(ficres,"%1d%1d%d",i,j,k);
12826: }
12827: ll=0;
12828: for(li=1;li <=nlstate; li++){
12829: for(lj=1;lj <=nlstate+ndeath; lj++){
12830: if(lj==li) continue;
12831: for(lk=1;lk<=ncovmodel;lk++){
12832: ll++;
12833: if(ll<=jj){
12834: cb[0]= lk +'a'-1;cb[1]='\0';
12835: if(ll<jj){
12836: if(itimes==1){
12837: if(mle>=1)
12838: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12839: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12840: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12841: }else{
12842: if(mle>=1)
12843: printf(" %.5e",matcov[jj][ll]);
12844: fprintf(ficlog," %.5e",matcov[jj][ll]);
12845: fprintf(ficres," %.5e",matcov[jj][ll]);
12846: }
12847: }else{
12848: if(itimes==1){
12849: if(mle>=1)
12850: printf(" Var(%s%1d%1d)",ca,i,j);
12851: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
12852: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
12853: }else{
12854: if(mle>=1)
12855: printf(" %.7e",matcov[jj][ll]);
12856: fprintf(ficlog," %.7e",matcov[jj][ll]);
12857: fprintf(ficres," %.7e",matcov[jj][ll]);
12858: }
12859: }
12860: }
12861: } /* end lk */
12862: } /* end lj */
12863: } /* end li */
12864: if(mle>=1)
12865: printf("\n");
12866: fprintf(ficlog,"\n");
12867: fprintf(ficres,"\n");
12868: numlinepar++;
12869: } /* end k*/
12870: } /*end j */
1.126 brouard 12871: } /* end i */
12872: } /* end itimes */
12873:
12874: fflush(ficlog);
12875: fflush(ficres);
1.225 brouard 12876: while(fgets(line, MAXLINE, ficpar)) {
12877: /* If line starts with a # it is a comment */
12878: if (line[0] == '#') {
12879: numlinepar++;
12880: fputs(line,stdout);
12881: fputs(line,ficparo);
12882: fputs(line,ficlog);
1.299 brouard 12883: fputs(line,ficres);
1.225 brouard 12884: continue;
12885: }else
12886: break;
12887: }
12888:
1.209 brouard 12889: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
12890: /* ungetc(c,ficpar); */
12891: /* fgets(line, MAXLINE, ficpar); */
12892: /* fputs(line,stdout); */
12893: /* fputs(line,ficparo); */
12894: /* } */
12895: /* ungetc(c,ficpar); */
1.126 brouard 12896:
12897: estepm=0;
1.209 brouard 12898: 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 12899:
12900: if (num_filled != 6) {
12901: 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);
12902: 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);
12903: goto end;
12904: }
12905: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
12906: }
12907: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
12908: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
12909:
1.209 brouard 12910: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 12911: if (estepm==0 || estepm < stepm) estepm=stepm;
12912: if (fage <= 2) {
12913: bage = ageminpar;
12914: fage = agemaxpar;
12915: }
12916:
12917: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 12918: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
12919: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 12920:
1.186 brouard 12921: /* Other stuffs, more or less useful */
1.254 brouard 12922: while(fgets(line, MAXLINE, ficpar)) {
12923: /* If line starts with a # it is a comment */
12924: if (line[0] == '#') {
12925: numlinepar++;
12926: fputs(line,stdout);
12927: fputs(line,ficparo);
12928: fputs(line,ficlog);
1.299 brouard 12929: fputs(line,ficres);
1.254 brouard 12930: continue;
12931: }else
12932: break;
12933: }
12934:
12935: 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){
12936:
12937: if (num_filled != 7) {
12938: 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);
12939: 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);
12940: goto end;
12941: }
12942: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
12943: 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);
12944: 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);
12945: 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 12946: }
1.254 brouard 12947:
12948: while(fgets(line, MAXLINE, ficpar)) {
12949: /* If line starts with a # it is a comment */
12950: if (line[0] == '#') {
12951: numlinepar++;
12952: fputs(line,stdout);
12953: fputs(line,ficparo);
12954: fputs(line,ficlog);
1.299 brouard 12955: fputs(line,ficres);
1.254 brouard 12956: continue;
12957: }else
12958: break;
1.126 brouard 12959: }
12960:
12961:
12962: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
12963: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
12964:
1.254 brouard 12965: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
12966: if (num_filled != 1) {
12967: 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);
12968: 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);
12969: goto end;
12970: }
12971: printf("pop_based=%d\n",popbased);
12972: fprintf(ficlog,"pop_based=%d\n",popbased);
12973: fprintf(ficparo,"pop_based=%d\n",popbased);
12974: fprintf(ficres,"pop_based=%d\n",popbased);
12975: }
12976:
1.258 brouard 12977: /* Results */
1.307 brouard 12978: endishere=0;
1.258 brouard 12979: nresult=0;
1.308 brouard 12980: parameterline=0;
1.258 brouard 12981: do{
12982: if(!fgets(line, MAXLINE, ficpar)){
12983: endishere=1;
1.308 brouard 12984: parameterline=15;
1.258 brouard 12985: }else if (line[0] == '#') {
12986: /* If line starts with a # it is a comment */
1.254 brouard 12987: numlinepar++;
12988: fputs(line,stdout);
12989: fputs(line,ficparo);
12990: fputs(line,ficlog);
1.299 brouard 12991: fputs(line,ficres);
1.254 brouard 12992: continue;
1.258 brouard 12993: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
12994: parameterline=11;
1.296 brouard 12995: else if(sscanf(line,"prevbackcast=%[^\n]\n",modeltemp))
1.258 brouard 12996: parameterline=12;
1.307 brouard 12997: else if(sscanf(line,"result:%[^\n]\n",modeltemp)){
1.258 brouard 12998: parameterline=13;
1.307 brouard 12999: }
1.258 brouard 13000: else{
13001: parameterline=14;
1.254 brouard 13002: }
1.308 brouard 13003: switch (parameterline){ /* =0 only if only comments */
1.258 brouard 13004: case 11:
1.296 brouard 13005: 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)){
13006: 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 13007: 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);
13008: 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);
13009: 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);
13010: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 13011: dateproj1=anproj1+(mproj1-1)/12.+(jproj1-1)/365.;
13012: dateproj2=anproj2+(mproj2-1)/12.+(jproj2-1)/365.;
1.296 brouard 13013: prvforecast = 1;
13014: }
13015: else if((num_filled=sscanf(line,"prevforecast=%d yearsfproj=%lf mobil_average=%d\n",&prevfcast,&yrfproj,&mobilavproj)) !=EOF){/* && (num_filled == 3))*/
1.313 brouard 13016: printf("prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
13017: fprintf(ficlog,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
13018: fprintf(ficres,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
1.296 brouard 13019: prvforecast = 2;
13020: }
13021: else {
13022: 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);
13023: 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);
13024: goto end;
1.258 brouard 13025: }
1.254 brouard 13026: break;
1.258 brouard 13027: case 12:
1.296 brouard 13028: 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)){
13029: 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);
13030: 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);
13031: 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);
13032: 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);
13033: /* day and month of back2 are not used but only year anback2.*/
1.273 brouard 13034: dateback1=anback1+(mback1-1)/12.+(jback1-1)/365.;
13035: dateback2=anback2+(mback2-1)/12.+(jback2-1)/365.;
1.296 brouard 13036: prvbackcast = 1;
13037: }
13038: else if((num_filled=sscanf(line,"prevbackcast=%d yearsbproj=%lf mobil_average=%d\n",&prevbcast,&yrbproj,&mobilavproj)) ==3){/* && (num_filled == 3))*/
1.313 brouard 13039: printf("prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
13040: fprintf(ficlog,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
13041: fprintf(ficres,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
1.296 brouard 13042: prvbackcast = 2;
13043: }
13044: else {
13045: 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);
13046: 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);
13047: goto end;
1.258 brouard 13048: }
1.230 brouard 13049: break;
1.258 brouard 13050: case 13:
1.307 brouard 13051: num_filled=sscanf(line,"result:%[^\n]\n",resultline);
13052: nresult++; /* Sum of resultlines */
13053: printf("Result %d: result:%s\n",nresult, resultline);
1.318 brouard 13054: if(nresult > MAXRESULTLINESPONE-1){
13055: printf("ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\nYou can use the 'r' parameter file '%s' which uses option mle=0 to get other results. ",MAXRESULTLINESPONE-1,nresult,rfileres);
13056: fprintf(ficlog,"ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\nYou can use the 'r' parameter file '%s' which uses option mle=0 to get other results. ",MAXRESULTLINESPONE-1,nresult,rfileres);
1.307 brouard 13057: goto end;
13058: }
1.310 brouard 13059: if(!decoderesult(resultline, nresult)){ /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
1.314 brouard 13060: fprintf(ficparo,"result: %s\n",resultline);
13061: fprintf(ficres,"result: %s\n",resultline);
13062: fprintf(ficlog,"result: %s\n",resultline);
1.310 brouard 13063: } else
13064: goto end;
1.307 brouard 13065: break;
13066: case 14:
13067: printf("Error: Unknown command '%s'\n",line);
13068: fprintf(ficlog,"Error: Unknown command '%s'\n",line);
1.314 brouard 13069: if(line[0] == ' ' || line[0] == '\n'){
13070: printf("It should not be an empty line '%s'\n",line);
13071: fprintf(ficlog,"It should not be an empty line '%s'\n",line);
13072: }
1.307 brouard 13073: if(ncovmodel >=2 && nresult==0 ){
13074: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
13075: fprintf(ficlog,"ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 13076: }
1.307 brouard 13077: /* goto end; */
13078: break;
1.308 brouard 13079: case 15:
13080: printf("End of resultlines.\n");
13081: fprintf(ficlog,"End of resultlines.\n");
13082: break;
13083: default: /* parameterline =0 */
1.307 brouard 13084: nresult=1;
13085: decoderesult(".",nresult ); /* No covariate */
1.258 brouard 13086: } /* End switch parameterline */
13087: }while(endishere==0); /* End do */
1.126 brouard 13088:
1.230 brouard 13089: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 13090: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 13091:
13092: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 13093: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 13094: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 13095: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
13096: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 13097: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 13098: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
13099: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 13100: }else{
1.270 brouard 13101: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
1.296 brouard 13102: /* It seems that anprojd which is computed from the mean year at interview which is known yet because of freqsummary */
13103: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */ /* Done in freqsummary */
13104: if(prvforecast==1){
13105: dateprojd=(jproj1+12*mproj1+365*anproj1)/365;
13106: jprojd=jproj1;
13107: mprojd=mproj1;
13108: anprojd=anproj1;
13109: dateprojf=(jproj2+12*mproj2+365*anproj2)/365;
13110: jprojf=jproj2;
13111: mprojf=mproj2;
13112: anprojf=anproj2;
13113: } else if(prvforecast == 2){
13114: dateprojd=dateintmean;
13115: date2dmy(dateprojd,&jprojd, &mprojd, &anprojd);
13116: dateprojf=dateintmean+yrfproj;
13117: date2dmy(dateprojf,&jprojf, &mprojf, &anprojf);
13118: }
13119: if(prvbackcast==1){
13120: datebackd=(jback1+12*mback1+365*anback1)/365;
13121: jbackd=jback1;
13122: mbackd=mback1;
13123: anbackd=anback1;
13124: datebackf=(jback2+12*mback2+365*anback2)/365;
13125: jbackf=jback2;
13126: mbackf=mback2;
13127: anbackf=anback2;
13128: } else if(prvbackcast == 2){
13129: datebackd=dateintmean;
13130: date2dmy(datebackd,&jbackd, &mbackd, &anbackd);
13131: datebackf=dateintmean-yrbproj;
13132: date2dmy(datebackf,&jbackf, &mbackf, &anbackf);
13133: }
13134:
13135: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, prevbcast, pathc,p, (int)anprojd-bage, (int)anbackd-fage);
1.220 brouard 13136: }
13137: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.296 brouard 13138: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,prevbcast, estepm, \
13139: jprev1,mprev1,anprev1,dateprev1, dateprojd, datebackd,jprev2,mprev2,anprev2,dateprev2,dateprojf, datebackf);
1.220 brouard 13140:
1.225 brouard 13141: /*------------ free_vector -------------*/
13142: /* chdir(path); */
1.220 brouard 13143:
1.215 brouard 13144: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
13145: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
13146: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
13147: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.290 brouard 13148: free_lvector(num,firstobs,lastobs);
13149: free_vector(agedc,firstobs,lastobs);
1.126 brouard 13150: /*free_matrix(covar,0,NCOVMAX,1,n);*/
13151: /*free_matrix(covar,1,NCOVMAX,1,n);*/
13152: fclose(ficparo);
13153: fclose(ficres);
1.220 brouard 13154:
13155:
1.186 brouard 13156: /* Other results (useful)*/
1.220 brouard 13157:
13158:
1.126 brouard 13159: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 13160: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
13161: prlim=matrix(1,nlstate,1,nlstate);
1.209 brouard 13162: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 13163: fclose(ficrespl);
13164:
13165: /*------------- h Pij x at various ages ------------*/
1.180 brouard 13166: /*#include "hpijx.h"*/
13167: hPijx(p, bage, fage);
1.145 brouard 13168: fclose(ficrespij);
1.227 brouard 13169:
1.220 brouard 13170: /* ncovcombmax= pow(2,cptcoveff); */
1.219 brouard 13171: /*-------------- Variance of one-step probabilities---*/
1.145 brouard 13172: k=1;
1.126 brouard 13173: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 13174:
1.269 brouard 13175: /* Prevalence for each covariate combination in probs[age][status][cov] */
13176: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
13177: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 13178: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 13179: for(k=1;k<=ncovcombmax;k++)
13180: probs[i][j][k]=0.;
1.269 brouard 13181: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
13182: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 13183: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 13184: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
13185: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 13186: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 13187: for(k=1;k<=ncovcombmax;k++)
13188: mobaverages[i][j][k]=0.;
1.219 brouard 13189: mobaverage=mobaverages;
13190: if (mobilav!=0) {
1.235 brouard 13191: printf("Movingaveraging observed prevalence\n");
1.258 brouard 13192: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 13193: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
13194: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
13195: printf(" Error in movingaverage mobilav=%d\n",mobilav);
13196: }
1.269 brouard 13197: } else if (mobilavproj !=0) {
1.235 brouard 13198: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 13199: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 13200: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
13201: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
13202: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
13203: }
1.269 brouard 13204: }else{
13205: printf("Internal error moving average\n");
13206: fflush(stdout);
13207: exit(1);
1.219 brouard 13208: }
13209: }/* end if moving average */
1.227 brouard 13210:
1.126 brouard 13211: /*---------- Forecasting ------------------*/
1.296 brouard 13212: if(prevfcast==1){
13213: /* /\* if(stepm ==1){*\/ */
13214: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
13215: /*This done previously after freqsummary.*/
13216: /* dateprojd=(jproj1+12*mproj1+365*anproj1)/365; */
13217: /* dateprojf=(jproj2+12*mproj2+365*anproj2)/365; */
13218:
13219: /* } else if (prvforecast==2){ */
13220: /* /\* if(stepm ==1){*\/ */
13221: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
13222: /* } */
13223: /*prevforecast(fileresu, dateintmean, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);*/
13224: prevforecast(fileresu,dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, p, cptcoveff);
1.126 brouard 13225: }
1.269 brouard 13226:
1.296 brouard 13227: /* Prevbcasting */
13228: if(prevbcast==1){
1.219 brouard 13229: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
13230: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
13231: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
13232:
13233: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
13234:
13235: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 13236:
1.219 brouard 13237: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
13238: fclose(ficresplb);
13239:
1.222 brouard 13240: hBijx(p, bage, fage, mobaverage);
13241: fclose(ficrespijb);
1.219 brouard 13242:
1.296 brouard 13243: /* /\* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, *\/ */
13244: /* /\* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); *\/ */
13245: /* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, */
13246: /* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); */
13247: prevbackforecast(fileresu, mobaverage, dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2,
13248: mobilavproj, bage, fage, firstpass, lastpass, p, cptcoveff);
13249:
13250:
1.269 brouard 13251: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 13252:
13253:
1.269 brouard 13254: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 13255: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
13256: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
13257: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.296 brouard 13258: } /* end Prevbcasting */
1.268 brouard 13259:
1.186 brouard 13260:
13261: /* ------ Other prevalence ratios------------ */
1.126 brouard 13262:
1.215 brouard 13263: free_ivector(wav,1,imx);
13264: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
13265: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
13266: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 13267:
13268:
1.127 brouard 13269: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 13270:
1.201 brouard 13271: strcpy(filerese,"E_");
13272: strcat(filerese,fileresu);
1.126 brouard 13273: if((ficreseij=fopen(filerese,"w"))==NULL) {
13274: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
13275: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
13276: }
1.208 brouard 13277: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
13278: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 13279:
13280: pstamp(ficreseij);
1.219 brouard 13281:
1.235 brouard 13282: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
13283: if (cptcovn < 1){i1=1;}
13284:
13285: for(nres=1; nres <= nresult; nres++) /* For each resultline */
13286: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 13287: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 13288: continue;
1.219 brouard 13289: fprintf(ficreseij,"\n#****** ");
1.235 brouard 13290: printf("\n#****** ");
1.225 brouard 13291: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 13292: fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 13293: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
13294: }
13295: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
13296: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
13297: fprintf(ficreseij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
1.219 brouard 13298: }
13299: fprintf(ficreseij,"******\n");
1.235 brouard 13300: printf("******\n");
1.219 brouard 13301:
13302: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
13303: oldm=oldms;savm=savms;
1.235 brouard 13304: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 13305:
1.219 brouard 13306: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 13307: }
13308: fclose(ficreseij);
1.208 brouard 13309: printf("done evsij\n");fflush(stdout);
13310: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 13311:
1.218 brouard 13312:
1.227 brouard 13313: /*---------- State-specific expectancies and variances ------------*/
1.218 brouard 13314:
1.201 brouard 13315: strcpy(filerest,"T_");
13316: strcat(filerest,fileresu);
1.127 brouard 13317: if((ficrest=fopen(filerest,"w"))==NULL) {
13318: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
13319: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
13320: }
1.208 brouard 13321: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
13322: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 13323: strcpy(fileresstde,"STDE_");
13324: strcat(fileresstde,fileresu);
1.126 brouard 13325: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 13326: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
13327: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 13328: }
1.227 brouard 13329: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
13330: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 13331:
1.201 brouard 13332: strcpy(filerescve,"CVE_");
13333: strcat(filerescve,fileresu);
1.126 brouard 13334: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 13335: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
13336: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 13337: }
1.227 brouard 13338: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
13339: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 13340:
1.201 brouard 13341: strcpy(fileresv,"V_");
13342: strcat(fileresv,fileresu);
1.126 brouard 13343: if((ficresvij=fopen(fileresv,"w"))==NULL) {
13344: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
13345: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
13346: }
1.227 brouard 13347: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
13348: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 13349:
1.235 brouard 13350: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
13351: if (cptcovn < 1){i1=1;}
13352:
13353: for(nres=1; nres <= nresult; nres++) /* For each resultline */
13354: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 13355: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 13356: continue;
1.321 brouard 13357: printf("\n# model %s \n#****** Result for:", model);
13358: fprintf(ficrest,"\n# model %s \n#****** Result for:", model);
13359: fprintf(ficlog,"\n# model %s \n#****** Result for:", model);
1.227 brouard 13360: for(j=1;j<=cptcoveff;j++){
13361: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
13362: fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
13363: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
13364: }
1.235 brouard 13365: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
13366: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
13367: fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
13368: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
13369: }
1.208 brouard 13370: fprintf(ficrest,"******\n");
1.227 brouard 13371: fprintf(ficlog,"******\n");
13372: printf("******\n");
1.208 brouard 13373:
13374: fprintf(ficresstdeij,"\n#****** ");
13375: fprintf(ficrescveij,"\n#****** ");
1.225 brouard 13376: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 13377: fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
13378: fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.208 brouard 13379: }
1.235 brouard 13380: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
13381: fprintf(ficresstdeij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
13382: fprintf(ficrescveij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
13383: }
1.208 brouard 13384: fprintf(ficresstdeij,"******\n");
13385: fprintf(ficrescveij,"******\n");
13386:
13387: fprintf(ficresvij,"\n#****** ");
1.238 brouard 13388: /* pstamp(ficresvij); */
1.225 brouard 13389: for(j=1;j<=cptcoveff;j++)
1.227 brouard 13390: fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 13391: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
13392: fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
13393: }
1.208 brouard 13394: fprintf(ficresvij,"******\n");
13395:
13396: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
13397: oldm=oldms;savm=savms;
1.235 brouard 13398: printf(" cvevsij ");
13399: fprintf(ficlog, " cvevsij ");
13400: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 13401: printf(" end cvevsij \n ");
13402: fprintf(ficlog, " end cvevsij \n ");
13403:
13404: /*
13405: */
13406: /* goto endfree; */
13407:
13408: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
13409: pstamp(ficrest);
13410:
1.269 brouard 13411: epj=vector(1,nlstate+1);
1.208 brouard 13412: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 13413: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
13414: cptcod= 0; /* To be deleted */
13415: printf("varevsij vpopbased=%d \n",vpopbased);
13416: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 13417: 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 13418: 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 ");
13419: if(vpopbased==1)
13420: 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);
13421: else
1.288 brouard 13422: fprintf(ficrest,"the age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 13423: fprintf(ficrest,"# Age popbased mobilav e.. (std) ");
13424: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
13425: fprintf(ficrest,"\n");
13426: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
1.288 brouard 13427: printf("Computing age specific forward period (stable) prevalences in each health state \n");
13428: fprintf(ficlog,"Computing age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 13429: for(age=bage; age <=fage ;age++){
1.235 brouard 13430: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 13431: if (vpopbased==1) {
13432: if(mobilav ==0){
13433: for(i=1; i<=nlstate;i++)
13434: prlim[i][i]=probs[(int)age][i][k];
13435: }else{ /* mobilav */
13436: for(i=1; i<=nlstate;i++)
13437: prlim[i][i]=mobaverage[(int)age][i][k];
13438: }
13439: }
1.219 brouard 13440:
1.227 brouard 13441: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
13442: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
13443: /* printf(" age %4.0f ",age); */
13444: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
13445: for(i=1, epj[j]=0.;i <=nlstate;i++) {
13446: epj[j] += prlim[i][i]*eij[i][j][(int)age];
13447: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
13448: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
13449: }
13450: epj[nlstate+1] +=epj[j];
13451: }
13452: /* printf(" age %4.0f \n",age); */
1.219 brouard 13453:
1.227 brouard 13454: for(i=1, vepp=0.;i <=nlstate;i++)
13455: for(j=1;j <=nlstate;j++)
13456: vepp += vareij[i][j][(int)age];
13457: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
13458: for(j=1;j <=nlstate;j++){
13459: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
13460: }
13461: fprintf(ficrest,"\n");
13462: }
1.208 brouard 13463: } /* End vpopbased */
1.269 brouard 13464: free_vector(epj,1,nlstate+1);
1.208 brouard 13465: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
13466: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 13467: printf("done selection\n");fflush(stdout);
13468: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 13469:
1.235 brouard 13470: } /* End k selection */
1.227 brouard 13471:
13472: printf("done State-specific expectancies\n");fflush(stdout);
13473: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
13474:
1.288 brouard 13475: /* variance-covariance of forward period prevalence*/
1.269 brouard 13476: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 13477:
1.227 brouard 13478:
1.290 brouard 13479: free_vector(weight,firstobs,lastobs);
1.227 brouard 13480: free_imatrix(Tvard,1,NCOVMAX,1,2);
1.290 brouard 13481: free_imatrix(s,1,maxwav+1,firstobs,lastobs);
13482: free_matrix(anint,1,maxwav,firstobs,lastobs);
13483: free_matrix(mint,1,maxwav,firstobs,lastobs);
13484: free_ivector(cod,firstobs,lastobs);
1.227 brouard 13485: free_ivector(tab,1,NCOVMAX);
13486: fclose(ficresstdeij);
13487: fclose(ficrescveij);
13488: fclose(ficresvij);
13489: fclose(ficrest);
13490: fclose(ficpar);
13491:
13492:
1.126 brouard 13493: /*---------- End : free ----------------*/
1.219 brouard 13494: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 13495: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
13496: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 13497: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
13498: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 13499: } /* mle==-3 arrives here for freeing */
1.227 brouard 13500: /* endfree:*/
13501: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
13502: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
13503: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.290 brouard 13504: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,firstobs,lastobs);
13505: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,firstobs,lastobs);
13506: if(nqv>=1)free_matrix(coqvar,1,nqv,firstobs,lastobs);
13507: free_matrix(covar,0,NCOVMAX,firstobs,lastobs);
1.227 brouard 13508: free_matrix(matcov,1,npar,1,npar);
13509: free_matrix(hess,1,npar,1,npar);
13510: /*free_vector(delti,1,npar);*/
13511: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
13512: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 13513: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 13514: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
13515:
13516: free_ivector(ncodemax,1,NCOVMAX);
13517: free_ivector(ncodemaxwundef,1,NCOVMAX);
13518: free_ivector(Dummy,-1,NCOVMAX);
13519: free_ivector(Fixed,-1,NCOVMAX);
1.238 brouard 13520: free_ivector(DummyV,1,NCOVMAX);
13521: free_ivector(FixedV,1,NCOVMAX);
1.227 brouard 13522: free_ivector(Typevar,-1,NCOVMAX);
13523: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 13524: free_ivector(TvarsQ,1,NCOVMAX);
13525: free_ivector(TvarsQind,1,NCOVMAX);
13526: free_ivector(TvarsD,1,NCOVMAX);
13527: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 13528: free_ivector(TvarFD,1,NCOVMAX);
13529: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 13530: free_ivector(TvarF,1,NCOVMAX);
13531: free_ivector(TvarFind,1,NCOVMAX);
13532: free_ivector(TvarV,1,NCOVMAX);
13533: free_ivector(TvarVind,1,NCOVMAX);
13534: free_ivector(TvarA,1,NCOVMAX);
13535: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 13536: free_ivector(TvarFQ,1,NCOVMAX);
13537: free_ivector(TvarFQind,1,NCOVMAX);
13538: free_ivector(TvarVD,1,NCOVMAX);
13539: free_ivector(TvarVDind,1,NCOVMAX);
13540: free_ivector(TvarVQ,1,NCOVMAX);
13541: free_ivector(TvarVQind,1,NCOVMAX);
1.230 brouard 13542: free_ivector(Tvarsel,1,NCOVMAX);
13543: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 13544: free_ivector(Tposprod,1,NCOVMAX);
13545: free_ivector(Tprod,1,NCOVMAX);
13546: free_ivector(Tvaraff,1,NCOVMAX);
13547: free_ivector(invalidvarcomb,1,ncovcombmax);
13548: free_ivector(Tage,1,NCOVMAX);
13549: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 13550: free_ivector(TmodelInvind,1,NCOVMAX);
13551: free_ivector(TmodelInvQind,1,NCOVMAX);
1.227 brouard 13552:
13553: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
13554: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 13555: fflush(fichtm);
13556: fflush(ficgp);
13557:
1.227 brouard 13558:
1.126 brouard 13559: if((nberr >0) || (nbwarn>0)){
1.216 brouard 13560: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
13561: 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 13562: }else{
13563: printf("End of Imach\n");
13564: fprintf(ficlog,"End of Imach\n");
13565: }
13566: printf("See log file on %s\n",filelog);
13567: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 13568: /*(void) gettimeofday(&end_time,&tzp);*/
13569: rend_time = time(NULL);
13570: end_time = *localtime(&rend_time);
13571: /* tml = *localtime(&end_time.tm_sec); */
13572: strcpy(strtend,asctime(&end_time));
1.126 brouard 13573: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
13574: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 13575: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 13576:
1.157 brouard 13577: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
13578: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
13579: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 13580: /* printf("Total time was %d uSec.\n", total_usecs);*/
13581: /* if(fileappend(fichtm,optionfilehtm)){ */
13582: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
13583: fclose(fichtm);
13584: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
13585: fclose(fichtmcov);
13586: fclose(ficgp);
13587: fclose(ficlog);
13588: /*------ End -----------*/
1.227 brouard 13589:
1.281 brouard 13590:
13591: /* Executes gnuplot */
1.227 brouard 13592:
13593: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 13594: #ifdef WIN32
1.227 brouard 13595: if (_chdir(pathcd) != 0)
13596: printf("Can't move to directory %s!\n",path);
13597: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 13598: #else
1.227 brouard 13599: if(chdir(pathcd) != 0)
13600: printf("Can't move to directory %s!\n", path);
13601: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 13602: #endif
1.126 brouard 13603: printf("Current directory %s!\n",pathcd);
13604: /*strcat(plotcmd,CHARSEPARATOR);*/
13605: sprintf(plotcmd,"gnuplot");
1.157 brouard 13606: #ifdef _WIN32
1.126 brouard 13607: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
13608: #endif
13609: if(!stat(plotcmd,&info)){
1.158 brouard 13610: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 13611: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 13612: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 13613: }else
13614: strcpy(pplotcmd,plotcmd);
1.157 brouard 13615: #ifdef __unix
1.126 brouard 13616: strcpy(plotcmd,GNUPLOTPROGRAM);
13617: if(!stat(plotcmd,&info)){
1.158 brouard 13618: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 13619: }else
13620: strcpy(pplotcmd,plotcmd);
13621: #endif
13622: }else
13623: strcpy(pplotcmd,plotcmd);
13624:
13625: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 13626: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.292 brouard 13627: strcpy(pplotcmd,plotcmd);
1.227 brouard 13628:
1.126 brouard 13629: if((outcmd=system(plotcmd)) != 0){
1.292 brouard 13630: printf("Error in gnuplot, command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 13631: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 13632: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.292 brouard 13633: if((outcmd=system(plotcmd)) != 0){
1.153 brouard 13634: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.292 brouard 13635: strcpy(plotcmd,pplotcmd);
13636: }
1.126 brouard 13637: }
1.158 brouard 13638: printf(" Successful, please wait...");
1.126 brouard 13639: while (z[0] != 'q') {
13640: /* chdir(path); */
1.154 brouard 13641: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 13642: scanf("%s",z);
13643: /* if (z[0] == 'c') system("./imach"); */
13644: if (z[0] == 'e') {
1.158 brouard 13645: #ifdef __APPLE__
1.152 brouard 13646: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 13647: #elif __linux
13648: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 13649: #else
1.152 brouard 13650: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 13651: #endif
13652: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
13653: system(pplotcmd);
1.126 brouard 13654: }
13655: else if (z[0] == 'g') system(plotcmd);
13656: else if (z[0] == 'q') exit(0);
13657: }
1.227 brouard 13658: end:
1.126 brouard 13659: while (z[0] != 'q') {
1.195 brouard 13660: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 13661: scanf("%s",z);
13662: }
1.283 brouard 13663: printf("End\n");
1.282 brouard 13664: exit(0);
1.126 brouard 13665: }
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