Annotation of imach/src/imach.c, revision 1.318
1.318 ! brouard 1: /* $Id: imach.c,v 1.317 2022/05/15 15:06:23 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.318 ! brouard 4: Revision 1.317 2022/05/15 15:06:23 brouard
! 5: * imach.c (Module): Some minor improvements
! 6:
1.317 brouard 7: Revision 1.316 2022/05/11 15:11:31 brouard
8: Summary: r27
9:
1.316 brouard 10: Revision 1.315 2022/05/11 15:06:32 brouard
11: *** empty log message ***
12:
1.315 brouard 13: Revision 1.314 2022/04/13 17:43:09 brouard
14: * imach.c (Module): Adding link to text data files
15:
1.314 brouard 16: Revision 1.313 2022/04/11 15:57:42 brouard
17: * imach.c (Module): Error in rewriting the 'r' file with yearsfproj or yearsbproj fixed
18:
1.313 brouard 19: Revision 1.312 2022/04/05 21:24:39 brouard
20: *** empty log message ***
21:
1.312 brouard 22: Revision 1.311 2022/04/05 21:03:51 brouard
23: Summary: Fixed quantitative covariates
24:
25: Fixed covariates (dummy or quantitative)
26: with missing values have never been allowed but are ERRORS and
27: program quits. Standard deviations of fixed covariates were
28: wrongly computed. Mean and standard deviations of time varying
29: covariates are still not computed.
30:
1.311 brouard 31: Revision 1.310 2022/03/17 08:45:53 brouard
32: Summary: 99r25
33:
34: Improving detection of errors: result lines should be compatible with
35: the model.
36:
1.310 brouard 37: Revision 1.309 2021/05/20 12:39:14 brouard
38: Summary: Version 0.99r24
39:
1.309 brouard 40: Revision 1.308 2021/03/31 13:11:57 brouard
41: Summary: Version 0.99r23
42:
43:
44: * imach.c (Module): Still bugs in the result loop. Thank to Holly Benett
45:
1.308 brouard 46: Revision 1.307 2021/03/08 18:11:32 brouard
47: Summary: 0.99r22 fixed bug on result:
48:
1.307 brouard 49: Revision 1.306 2021/02/20 15:44:02 brouard
50: Summary: Version 0.99r21
51:
52: * imach.c (Module): Fix bug on quitting after result lines!
53: (Module): Version 0.99r21
54:
1.306 brouard 55: Revision 1.305 2021/02/20 15:28:30 brouard
56: * imach.c (Module): Fix bug on quitting after result lines!
57:
1.305 brouard 58: Revision 1.304 2021/02/12 11:34:20 brouard
59: * imach.c (Module): The use of a Windows BOM (huge) file is now an error
60:
1.304 brouard 61: Revision 1.303 2021/02/11 19:50:15 brouard
62: * (Module): imach.c Someone entered 'results:' instead of 'result:'. Now it is an error which is printed.
63:
1.303 brouard 64: Revision 1.302 2020/02/22 21:00:05 brouard
65: * (Module): imach.c Update mle=-3 (for computing Life expectancy
66: and life table from the data without any state)
67:
1.302 brouard 68: Revision 1.301 2019/06/04 13:51:20 brouard
69: Summary: Error in 'r'parameter file backcast yearsbproj instead of yearsfproj
70:
1.301 brouard 71: Revision 1.300 2019/05/22 19:09:45 brouard
72: Summary: version 0.99r19 of May 2019
73:
1.300 brouard 74: Revision 1.299 2019/05/22 18:37:08 brouard
75: Summary: Cleaned 0.99r19
76:
1.299 brouard 77: Revision 1.298 2019/05/22 18:19:56 brouard
78: *** empty log message ***
79:
1.298 brouard 80: Revision 1.297 2019/05/22 17:56:10 brouard
81: Summary: Fix bug by moving date2dmy and nhstepm which gaefin=-1
82:
1.297 brouard 83: Revision 1.296 2019/05/20 13:03:18 brouard
84: Summary: Projection syntax simplified
85:
86:
87: We can now start projections, forward or backward, from the mean date
88: of inteviews up to or down to a number of years of projection:
89: prevforecast=1 yearsfproj=15.3 mobil_average=0
90: or
91: prevforecast=1 starting-proj-date=1/1/2007 final-proj-date=12/31/2017 mobil_average=0
92: or
93: prevbackcast=1 yearsbproj=12.3 mobil_average=1
94: or
95: prevbackcast=1 starting-back-date=1/10/1999 final-back-date=1/1/1985 mobil_average=1
96:
1.296 brouard 97: Revision 1.295 2019/05/18 09:52:50 brouard
98: Summary: doxygen tex bug
99:
1.295 brouard 100: Revision 1.294 2019/05/16 14:54:33 brouard
101: Summary: There was some wrong lines added
102:
1.294 brouard 103: Revision 1.293 2019/05/09 15:17:34 brouard
104: *** empty log message ***
105:
1.293 brouard 106: Revision 1.292 2019/05/09 14:17:20 brouard
107: Summary: Some updates
108:
1.292 brouard 109: Revision 1.291 2019/05/09 13:44:18 brouard
110: Summary: Before ncovmax
111:
1.291 brouard 112: Revision 1.290 2019/05/09 13:39:37 brouard
113: Summary: 0.99r18 unlimited number of individuals
114:
115: 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.
116:
1.290 brouard 117: Revision 1.289 2018/12/13 09:16:26 brouard
118: Summary: Bug for young ages (<-30) will be in r17
119:
1.289 brouard 120: Revision 1.288 2018/05/02 20:58:27 brouard
121: Summary: Some bugs fixed
122:
1.288 brouard 123: Revision 1.287 2018/05/01 17:57:25 brouard
124: Summary: Bug fixed by providing frequencies only for non missing covariates
125:
1.287 brouard 126: Revision 1.286 2018/04/27 14:27:04 brouard
127: Summary: some minor bugs
128:
1.286 brouard 129: Revision 1.285 2018/04/21 21:02:16 brouard
130: Summary: Some bugs fixed, valgrind tested
131:
1.285 brouard 132: Revision 1.284 2018/04/20 05:22:13 brouard
133: Summary: Computing mean and stdeviation of fixed quantitative variables
134:
1.284 brouard 135: Revision 1.283 2018/04/19 14:49:16 brouard
136: Summary: Some minor bugs fixed
137:
1.283 brouard 138: Revision 1.282 2018/02/27 22:50:02 brouard
139: *** empty log message ***
140:
1.282 brouard 141: Revision 1.281 2018/02/27 19:25:23 brouard
142: Summary: Adding second argument for quitting
143:
1.281 brouard 144: Revision 1.280 2018/02/21 07:58:13 brouard
145: Summary: 0.99r15
146:
147: New Makefile with recent VirtualBox 5.26. Bug in sqrt negatve in imach.c
148:
1.280 brouard 149: Revision 1.279 2017/07/20 13:35:01 brouard
150: Summary: temporary working
151:
1.279 brouard 152: Revision 1.278 2017/07/19 14:09:02 brouard
153: Summary: Bug for mobil_average=0 and prevforecast fixed(?)
154:
1.278 brouard 155: Revision 1.277 2017/07/17 08:53:49 brouard
156: Summary: BOM files can be read now
157:
1.277 brouard 158: Revision 1.276 2017/06/30 15:48:31 brouard
159: Summary: Graphs improvements
160:
1.276 brouard 161: Revision 1.275 2017/06/30 13:39:33 brouard
162: Summary: Saito's color
163:
1.275 brouard 164: Revision 1.274 2017/06/29 09:47:08 brouard
165: Summary: Version 0.99r14
166:
1.274 brouard 167: Revision 1.273 2017/06/27 11:06:02 brouard
168: Summary: More documentation on projections
169:
1.273 brouard 170: Revision 1.272 2017/06/27 10:22:40 brouard
171: Summary: Color of backprojection changed from 6 to 5(yellow)
172:
1.272 brouard 173: Revision 1.271 2017/06/27 10:17:50 brouard
174: Summary: Some bug with rint
175:
1.271 brouard 176: Revision 1.270 2017/05/24 05:45:29 brouard
177: *** empty log message ***
178:
1.270 brouard 179: Revision 1.269 2017/05/23 08:39:25 brouard
180: Summary: Code into subroutine, cleanings
181:
1.269 brouard 182: Revision 1.268 2017/05/18 20:09:32 brouard
183: Summary: backprojection and confidence intervals of backprevalence
184:
1.268 brouard 185: Revision 1.267 2017/05/13 10:25:05 brouard
186: Summary: temporary save for backprojection
187:
1.267 brouard 188: Revision 1.266 2017/05/13 07:26:12 brouard
189: Summary: Version 0.99r13 (improvements and bugs fixed)
190:
1.266 brouard 191: Revision 1.265 2017/04/26 16:22:11 brouard
192: Summary: imach 0.99r13 Some bugs fixed
193:
1.265 brouard 194: Revision 1.264 2017/04/26 06:01:29 brouard
195: Summary: Labels in graphs
196:
1.264 brouard 197: Revision 1.263 2017/04/24 15:23:15 brouard
198: Summary: to save
199:
1.263 brouard 200: Revision 1.262 2017/04/18 16:48:12 brouard
201: *** empty log message ***
202:
1.262 brouard 203: Revision 1.261 2017/04/05 10:14:09 brouard
204: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
205:
1.261 brouard 206: Revision 1.260 2017/04/04 17:46:59 brouard
207: Summary: Gnuplot indexations fixed (humm)
208:
1.260 brouard 209: Revision 1.259 2017/04/04 13:01:16 brouard
210: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
211:
1.259 brouard 212: Revision 1.258 2017/04/03 10:17:47 brouard
213: Summary: Version 0.99r12
214:
215: Some cleanings, conformed with updated documentation.
216:
1.258 brouard 217: Revision 1.257 2017/03/29 16:53:30 brouard
218: Summary: Temp
219:
1.257 brouard 220: Revision 1.256 2017/03/27 05:50:23 brouard
221: Summary: Temporary
222:
1.256 brouard 223: Revision 1.255 2017/03/08 16:02:28 brouard
224: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
225:
1.255 brouard 226: Revision 1.254 2017/03/08 07:13:00 brouard
227: Summary: Fixing data parameter line
228:
1.254 brouard 229: Revision 1.253 2016/12/15 11:59:41 brouard
230: Summary: 0.99 in progress
231:
1.253 brouard 232: Revision 1.252 2016/09/15 21:15:37 brouard
233: *** empty log message ***
234:
1.252 brouard 235: Revision 1.251 2016/09/15 15:01:13 brouard
236: Summary: not working
237:
1.251 brouard 238: Revision 1.250 2016/09/08 16:07:27 brouard
239: Summary: continue
240:
1.250 brouard 241: Revision 1.249 2016/09/07 17:14:18 brouard
242: Summary: Starting values from frequencies
243:
1.249 brouard 244: Revision 1.248 2016/09/07 14:10:18 brouard
245: *** empty log message ***
246:
1.248 brouard 247: Revision 1.247 2016/09/02 11:11:21 brouard
248: *** empty log message ***
249:
1.247 brouard 250: Revision 1.246 2016/09/02 08:49:22 brouard
251: *** empty log message ***
252:
1.246 brouard 253: Revision 1.245 2016/09/02 07:25:01 brouard
254: *** empty log message ***
255:
1.245 brouard 256: Revision 1.244 2016/09/02 07:17:34 brouard
257: *** empty log message ***
258:
1.244 brouard 259: Revision 1.243 2016/09/02 06:45:35 brouard
260: *** empty log message ***
261:
1.243 brouard 262: Revision 1.242 2016/08/30 15:01:20 brouard
263: Summary: Fixing a lots
264:
1.242 brouard 265: Revision 1.241 2016/08/29 17:17:25 brouard
266: Summary: gnuplot problem in Back projection to fix
267:
1.241 brouard 268: Revision 1.240 2016/08/29 07:53:18 brouard
269: Summary: Better
270:
1.240 brouard 271: Revision 1.239 2016/08/26 15:51:03 brouard
272: Summary: Improvement in Powell output in order to copy and paste
273:
274: Author:
275:
1.239 brouard 276: Revision 1.238 2016/08/26 14:23:35 brouard
277: Summary: Starting tests of 0.99
278:
1.238 brouard 279: Revision 1.237 2016/08/26 09:20:19 brouard
280: Summary: to valgrind
281:
1.237 brouard 282: Revision 1.236 2016/08/25 10:50:18 brouard
283: *** empty log message ***
284:
1.236 brouard 285: Revision 1.235 2016/08/25 06:59:23 brouard
286: *** empty log message ***
287:
1.235 brouard 288: Revision 1.234 2016/08/23 16:51:20 brouard
289: *** empty log message ***
290:
1.234 brouard 291: Revision 1.233 2016/08/23 07:40:50 brouard
292: Summary: not working
293:
1.233 brouard 294: Revision 1.232 2016/08/22 14:20:21 brouard
295: Summary: not working
296:
1.232 brouard 297: Revision 1.231 2016/08/22 07:17:15 brouard
298: Summary: not working
299:
1.231 brouard 300: Revision 1.230 2016/08/22 06:55:53 brouard
301: Summary: Not working
302:
1.230 brouard 303: Revision 1.229 2016/07/23 09:45:53 brouard
304: Summary: Completing for func too
305:
1.229 brouard 306: Revision 1.228 2016/07/22 17:45:30 brouard
307: Summary: Fixing some arrays, still debugging
308:
1.227 brouard 309: Revision 1.226 2016/07/12 18:42:34 brouard
310: Summary: temp
311:
1.226 brouard 312: Revision 1.225 2016/07/12 08:40:03 brouard
313: Summary: saving but not running
314:
1.225 brouard 315: Revision 1.224 2016/07/01 13:16:01 brouard
316: Summary: Fixes
317:
1.224 brouard 318: Revision 1.223 2016/02/19 09:23:35 brouard
319: Summary: temporary
320:
1.223 brouard 321: Revision 1.222 2016/02/17 08:14:50 brouard
322: Summary: Probably last 0.98 stable version 0.98r6
323:
1.222 brouard 324: Revision 1.221 2016/02/15 23:35:36 brouard
325: Summary: minor bug
326:
1.220 brouard 327: Revision 1.219 2016/02/15 00:48:12 brouard
328: *** empty log message ***
329:
1.219 brouard 330: Revision 1.218 2016/02/12 11:29:23 brouard
331: Summary: 0.99 Back projections
332:
1.218 brouard 333: Revision 1.217 2015/12/23 17:18:31 brouard
334: Summary: Experimental backcast
335:
1.217 brouard 336: Revision 1.216 2015/12/18 17:32:11 brouard
337: Summary: 0.98r4 Warning and status=-2
338:
339: Version 0.98r4 is now:
340: - displaying an error when status is -1, date of interview unknown and date of death known;
341: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
342: Older changes concerning s=-2, dating from 2005 have been supersed.
343:
1.216 brouard 344: Revision 1.215 2015/12/16 08:52:24 brouard
345: Summary: 0.98r4 working
346:
1.215 brouard 347: Revision 1.214 2015/12/16 06:57:54 brouard
348: Summary: temporary not working
349:
1.214 brouard 350: Revision 1.213 2015/12/11 18:22:17 brouard
351: Summary: 0.98r4
352:
1.213 brouard 353: Revision 1.212 2015/11/21 12:47:24 brouard
354: Summary: minor typo
355:
1.212 brouard 356: Revision 1.211 2015/11/21 12:41:11 brouard
357: Summary: 0.98r3 with some graph of projected cross-sectional
358:
359: Author: Nicolas Brouard
360:
1.211 brouard 361: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 362: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 363: Summary: Adding ftolpl parameter
364: Author: N Brouard
365:
366: We had difficulties to get smoothed confidence intervals. It was due
367: to the period prevalence which wasn't computed accurately. The inner
368: parameter ftolpl is now an outer parameter of the .imach parameter
369: file after estepm. If ftolpl is small 1.e-4 and estepm too,
370: computation are long.
371:
1.209 brouard 372: Revision 1.208 2015/11/17 14:31:57 brouard
373: Summary: temporary
374:
1.208 brouard 375: Revision 1.207 2015/10/27 17:36:57 brouard
376: *** empty log message ***
377:
1.207 brouard 378: Revision 1.206 2015/10/24 07:14:11 brouard
379: *** empty log message ***
380:
1.206 brouard 381: Revision 1.205 2015/10/23 15:50:53 brouard
382: Summary: 0.98r3 some clarification for graphs on likelihood contributions
383:
1.205 brouard 384: Revision 1.204 2015/10/01 16:20:26 brouard
385: Summary: Some new graphs of contribution to likelihood
386:
1.204 brouard 387: Revision 1.203 2015/09/30 17:45:14 brouard
388: Summary: looking at better estimation of the hessian
389:
390: Also a better criteria for convergence to the period prevalence And
391: therefore adding the number of years needed to converge. (The
392: prevalence in any alive state shold sum to one
393:
1.203 brouard 394: Revision 1.202 2015/09/22 19:45:16 brouard
395: Summary: Adding some overall graph on contribution to likelihood. Might change
396:
1.202 brouard 397: Revision 1.201 2015/09/15 17:34:58 brouard
398: Summary: 0.98r0
399:
400: - Some new graphs like suvival functions
401: - Some bugs fixed like model=1+age+V2.
402:
1.201 brouard 403: Revision 1.200 2015/09/09 16:53:55 brouard
404: Summary: Big bug thanks to Flavia
405:
406: Even model=1+age+V2. did not work anymore
407:
1.200 brouard 408: Revision 1.199 2015/09/07 14:09:23 brouard
409: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
410:
1.199 brouard 411: Revision 1.198 2015/09/03 07:14:39 brouard
412: Summary: 0.98q5 Flavia
413:
1.198 brouard 414: Revision 1.197 2015/09/01 18:24:39 brouard
415: *** empty log message ***
416:
1.197 brouard 417: Revision 1.196 2015/08/18 23:17:52 brouard
418: Summary: 0.98q5
419:
1.196 brouard 420: Revision 1.195 2015/08/18 16:28:39 brouard
421: Summary: Adding a hack for testing purpose
422:
423: After reading the title, ftol and model lines, if the comment line has
424: a q, starting with #q, the answer at the end of the run is quit. It
425: permits to run test files in batch with ctest. The former workaround was
426: $ echo q | imach foo.imach
427:
1.195 brouard 428: Revision 1.194 2015/08/18 13:32:00 brouard
429: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
430:
1.194 brouard 431: Revision 1.193 2015/08/04 07:17:42 brouard
432: Summary: 0.98q4
433:
1.193 brouard 434: Revision 1.192 2015/07/16 16:49:02 brouard
435: Summary: Fixing some outputs
436:
1.192 brouard 437: Revision 1.191 2015/07/14 10:00:33 brouard
438: Summary: Some fixes
439:
1.191 brouard 440: Revision 1.190 2015/05/05 08:51:13 brouard
441: Summary: Adding digits in output parameters (7 digits instead of 6)
442:
443: Fix 1+age+.
444:
1.190 brouard 445: Revision 1.189 2015/04/30 14:45:16 brouard
446: Summary: 0.98q2
447:
1.189 brouard 448: Revision 1.188 2015/04/30 08:27:53 brouard
449: *** empty log message ***
450:
1.188 brouard 451: Revision 1.187 2015/04/29 09:11:15 brouard
452: *** empty log message ***
453:
1.187 brouard 454: Revision 1.186 2015/04/23 12:01:52 brouard
455: Summary: V1*age is working now, version 0.98q1
456:
457: Some codes had been disabled in order to simplify and Vn*age was
458: working in the optimization phase, ie, giving correct MLE parameters,
459: but, as usual, outputs were not correct and program core dumped.
460:
1.186 brouard 461: Revision 1.185 2015/03/11 13:26:42 brouard
462: Summary: Inclusion of compile and links command line for Intel Compiler
463:
1.185 brouard 464: Revision 1.184 2015/03/11 11:52:39 brouard
465: Summary: Back from Windows 8. Intel Compiler
466:
1.184 brouard 467: Revision 1.183 2015/03/10 20:34:32 brouard
468: Summary: 0.98q0, trying with directest, mnbrak fixed
469:
470: We use directest instead of original Powell test; probably no
471: incidence on the results, but better justifications;
472: We fixed Numerical Recipes mnbrak routine which was wrong and gave
473: wrong results.
474:
1.183 brouard 475: Revision 1.182 2015/02/12 08:19:57 brouard
476: Summary: Trying to keep directest which seems simpler and more general
477: Author: Nicolas Brouard
478:
1.182 brouard 479: Revision 1.181 2015/02/11 23:22:24 brouard
480: Summary: Comments on Powell added
481:
482: Author:
483:
1.181 brouard 484: Revision 1.180 2015/02/11 17:33:45 brouard
485: Summary: Finishing move from main to function (hpijx and prevalence_limit)
486:
1.180 brouard 487: Revision 1.179 2015/01/04 09:57:06 brouard
488: Summary: back to OS/X
489:
1.179 brouard 490: Revision 1.178 2015/01/04 09:35:48 brouard
491: *** empty log message ***
492:
1.178 brouard 493: Revision 1.177 2015/01/03 18:40:56 brouard
494: Summary: Still testing ilc32 on OSX
495:
1.177 brouard 496: Revision 1.176 2015/01/03 16:45:04 brouard
497: *** empty log message ***
498:
1.176 brouard 499: Revision 1.175 2015/01/03 16:33:42 brouard
500: *** empty log message ***
501:
1.175 brouard 502: Revision 1.174 2015/01/03 16:15:49 brouard
503: Summary: Still in cross-compilation
504:
1.174 brouard 505: Revision 1.173 2015/01/03 12:06:26 brouard
506: Summary: trying to detect cross-compilation
507:
1.173 brouard 508: Revision 1.172 2014/12/27 12:07:47 brouard
509: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
510:
1.172 brouard 511: Revision 1.171 2014/12/23 13:26:59 brouard
512: Summary: Back from Visual C
513:
514: Still problem with utsname.h on Windows
515:
1.171 brouard 516: Revision 1.170 2014/12/23 11:17:12 brouard
517: Summary: Cleaning some \%% back to %%
518:
519: The escape was mandatory for a specific compiler (which one?), but too many warnings.
520:
1.170 brouard 521: Revision 1.169 2014/12/22 23:08:31 brouard
522: Summary: 0.98p
523:
524: Outputs some informations on compiler used, OS etc. Testing on different platforms.
525:
1.169 brouard 526: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 527: Summary: update
1.169 brouard 528:
1.168 brouard 529: Revision 1.167 2014/12/22 13:50:56 brouard
530: Summary: Testing uname and compiler version and if compiled 32 or 64
531:
532: Testing on Linux 64
533:
1.167 brouard 534: Revision 1.166 2014/12/22 11:40:47 brouard
535: *** empty log message ***
536:
1.166 brouard 537: Revision 1.165 2014/12/16 11:20:36 brouard
538: Summary: After compiling on Visual C
539:
540: * imach.c (Module): Merging 1.61 to 1.162
541:
1.165 brouard 542: Revision 1.164 2014/12/16 10:52:11 brouard
543: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
544:
545: * imach.c (Module): Merging 1.61 to 1.162
546:
1.164 brouard 547: Revision 1.163 2014/12/16 10:30:11 brouard
548: * imach.c (Module): Merging 1.61 to 1.162
549:
1.163 brouard 550: Revision 1.162 2014/09/25 11:43:39 brouard
551: Summary: temporary backup 0.99!
552:
1.162 brouard 553: Revision 1.1 2014/09/16 11:06:58 brouard
554: Summary: With some code (wrong) for nlopt
555:
556: Author:
557:
558: Revision 1.161 2014/09/15 20:41:41 brouard
559: Summary: Problem with macro SQR on Intel compiler
560:
1.161 brouard 561: Revision 1.160 2014/09/02 09:24:05 brouard
562: *** empty log message ***
563:
1.160 brouard 564: Revision 1.159 2014/09/01 10:34:10 brouard
565: Summary: WIN32
566: Author: Brouard
567:
1.159 brouard 568: Revision 1.158 2014/08/27 17:11:51 brouard
569: *** empty log message ***
570:
1.158 brouard 571: Revision 1.157 2014/08/27 16:26:55 brouard
572: Summary: Preparing windows Visual studio version
573: Author: Brouard
574:
575: In order to compile on Visual studio, time.h is now correct and time_t
576: and tm struct should be used. difftime should be used but sometimes I
577: just make the differences in raw time format (time(&now).
578: Trying to suppress #ifdef LINUX
579: Add xdg-open for __linux in order to open default browser.
580:
1.157 brouard 581: Revision 1.156 2014/08/25 20:10:10 brouard
582: *** empty log message ***
583:
1.156 brouard 584: Revision 1.155 2014/08/25 18:32:34 brouard
585: Summary: New compile, minor changes
586: Author: Brouard
587:
1.155 brouard 588: Revision 1.154 2014/06/20 17:32:08 brouard
589: Summary: Outputs now all graphs of convergence to period prevalence
590:
1.154 brouard 591: Revision 1.153 2014/06/20 16:45:46 brouard
592: Summary: If 3 live state, convergence to period prevalence on same graph
593: Author: Brouard
594:
1.153 brouard 595: Revision 1.152 2014/06/18 17:54:09 brouard
596: Summary: open browser, use gnuplot on same dir than imach if not found in the path
597:
1.152 brouard 598: Revision 1.151 2014/06/18 16:43:30 brouard
599: *** empty log message ***
600:
1.151 brouard 601: Revision 1.150 2014/06/18 16:42:35 brouard
602: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
603: Author: brouard
604:
1.150 brouard 605: Revision 1.149 2014/06/18 15:51:14 brouard
606: Summary: Some fixes in parameter files errors
607: Author: Nicolas Brouard
608:
1.149 brouard 609: Revision 1.148 2014/06/17 17:38:48 brouard
610: Summary: Nothing new
611: Author: Brouard
612:
613: Just a new packaging for OS/X version 0.98nS
614:
1.148 brouard 615: Revision 1.147 2014/06/16 10:33:11 brouard
616: *** empty log message ***
617:
1.147 brouard 618: Revision 1.146 2014/06/16 10:20:28 brouard
619: Summary: Merge
620: Author: Brouard
621:
622: Merge, before building revised version.
623:
1.146 brouard 624: Revision 1.145 2014/06/10 21:23:15 brouard
625: Summary: Debugging with valgrind
626: Author: Nicolas Brouard
627:
628: Lot of changes in order to output the results with some covariates
629: After the Edimburgh REVES conference 2014, it seems mandatory to
630: improve the code.
631: No more memory valgrind error but a lot has to be done in order to
632: continue the work of splitting the code into subroutines.
633: Also, decodemodel has been improved. Tricode is still not
634: optimal. nbcode should be improved. Documentation has been added in
635: the source code.
636:
1.144 brouard 637: Revision 1.143 2014/01/26 09:45:38 brouard
638: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
639:
640: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
641: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
642:
1.143 brouard 643: Revision 1.142 2014/01/26 03:57:36 brouard
644: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
645:
646: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
647:
1.142 brouard 648: Revision 1.141 2014/01/26 02:42:01 brouard
649: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
650:
1.141 brouard 651: Revision 1.140 2011/09/02 10:37:54 brouard
652: Summary: times.h is ok with mingw32 now.
653:
1.140 brouard 654: Revision 1.139 2010/06/14 07:50:17 brouard
655: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
656: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
657:
1.139 brouard 658: Revision 1.138 2010/04/30 18:19:40 brouard
659: *** empty log message ***
660:
1.138 brouard 661: Revision 1.137 2010/04/29 18:11:38 brouard
662: (Module): Checking covariates for more complex models
663: than V1+V2. A lot of change to be done. Unstable.
664:
1.137 brouard 665: Revision 1.136 2010/04/26 20:30:53 brouard
666: (Module): merging some libgsl code. Fixing computation
667: of likelione (using inter/intrapolation if mle = 0) in order to
668: get same likelihood as if mle=1.
669: Some cleaning of code and comments added.
670:
1.136 brouard 671: Revision 1.135 2009/10/29 15:33:14 brouard
672: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
673:
1.135 brouard 674: Revision 1.134 2009/10/29 13:18:53 brouard
675: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
676:
1.134 brouard 677: Revision 1.133 2009/07/06 10:21:25 brouard
678: just nforces
679:
1.133 brouard 680: Revision 1.132 2009/07/06 08:22:05 brouard
681: Many tings
682:
1.132 brouard 683: Revision 1.131 2009/06/20 16:22:47 brouard
684: Some dimensions resccaled
685:
1.131 brouard 686: Revision 1.130 2009/05/26 06:44:34 brouard
687: (Module): Max Covariate is now set to 20 instead of 8. A
688: lot of cleaning with variables initialized to 0. Trying to make
689: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
690:
1.130 brouard 691: Revision 1.129 2007/08/31 13:49:27 lievre
692: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
693:
1.129 lievre 694: Revision 1.128 2006/06/30 13:02:05 brouard
695: (Module): Clarifications on computing e.j
696:
1.128 brouard 697: Revision 1.127 2006/04/28 18:11:50 brouard
698: (Module): Yes the sum of survivors was wrong since
699: imach-114 because nhstepm was no more computed in the age
700: loop. Now we define nhstepma in the age loop.
701: (Module): In order to speed up (in case of numerous covariates) we
702: compute health expectancies (without variances) in a first step
703: and then all the health expectancies with variances or standard
704: deviation (needs data from the Hessian matrices) which slows the
705: computation.
706: In the future we should be able to stop the program is only health
707: expectancies and graph are needed without standard deviations.
708:
1.127 brouard 709: Revision 1.126 2006/04/28 17:23:28 brouard
710: (Module): Yes the sum of survivors was wrong since
711: imach-114 because nhstepm was no more computed in the age
712: loop. Now we define nhstepma in the age loop.
713: Version 0.98h
714:
1.126 brouard 715: Revision 1.125 2006/04/04 15:20:31 lievre
716: Errors in calculation of health expectancies. Age was not initialized.
717: Forecasting file added.
718:
719: Revision 1.124 2006/03/22 17:13:53 lievre
720: Parameters are printed with %lf instead of %f (more numbers after the comma).
721: The log-likelihood is printed in the log file
722:
723: Revision 1.123 2006/03/20 10:52:43 brouard
724: * imach.c (Module): <title> changed, corresponds to .htm file
725: name. <head> headers where missing.
726:
727: * imach.c (Module): Weights can have a decimal point as for
728: English (a comma might work with a correct LC_NUMERIC environment,
729: otherwise the weight is truncated).
730: Modification of warning when the covariates values are not 0 or
731: 1.
732: Version 0.98g
733:
734: Revision 1.122 2006/03/20 09:45:41 brouard
735: (Module): Weights can have a decimal point as for
736: English (a comma might work with a correct LC_NUMERIC environment,
737: otherwise the weight is truncated).
738: Modification of warning when the covariates values are not 0 or
739: 1.
740: Version 0.98g
741:
742: Revision 1.121 2006/03/16 17:45:01 lievre
743: * imach.c (Module): Comments concerning covariates added
744:
745: * imach.c (Module): refinements in the computation of lli if
746: status=-2 in order to have more reliable computation if stepm is
747: not 1 month. Version 0.98f
748:
749: Revision 1.120 2006/03/16 15:10:38 lievre
750: (Module): refinements in the computation of lli if
751: status=-2 in order to have more reliable computation if stepm is
752: not 1 month. Version 0.98f
753:
754: Revision 1.119 2006/03/15 17:42:26 brouard
755: (Module): Bug if status = -2, the loglikelihood was
756: computed as likelihood omitting the logarithm. Version O.98e
757:
758: Revision 1.118 2006/03/14 18:20:07 brouard
759: (Module): varevsij Comments added explaining the second
760: table of variances if popbased=1 .
761: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
762: (Module): Function pstamp added
763: (Module): Version 0.98d
764:
765: Revision 1.117 2006/03/14 17:16:22 brouard
766: (Module): varevsij Comments added explaining the second
767: table of variances if popbased=1 .
768: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
769: (Module): Function pstamp added
770: (Module): Version 0.98d
771:
772: Revision 1.116 2006/03/06 10:29:27 brouard
773: (Module): Variance-covariance wrong links and
774: varian-covariance of ej. is needed (Saito).
775:
776: Revision 1.115 2006/02/27 12:17:45 brouard
777: (Module): One freematrix added in mlikeli! 0.98c
778:
779: Revision 1.114 2006/02/26 12:57:58 brouard
780: (Module): Some improvements in processing parameter
781: filename with strsep.
782:
783: Revision 1.113 2006/02/24 14:20:24 brouard
784: (Module): Memory leaks checks with valgrind and:
785: datafile was not closed, some imatrix were not freed and on matrix
786: allocation too.
787:
788: Revision 1.112 2006/01/30 09:55:26 brouard
789: (Module): Back to gnuplot.exe instead of wgnuplot.exe
790:
791: Revision 1.111 2006/01/25 20:38:18 brouard
792: (Module): Lots of cleaning and bugs added (Gompertz)
793: (Module): Comments can be added in data file. Missing date values
794: can be a simple dot '.'.
795:
796: Revision 1.110 2006/01/25 00:51:50 brouard
797: (Module): Lots of cleaning and bugs added (Gompertz)
798:
799: Revision 1.109 2006/01/24 19:37:15 brouard
800: (Module): Comments (lines starting with a #) are allowed in data.
801:
802: Revision 1.108 2006/01/19 18:05:42 lievre
803: Gnuplot problem appeared...
804: To be fixed
805:
806: Revision 1.107 2006/01/19 16:20:37 brouard
807: Test existence of gnuplot in imach path
808:
809: Revision 1.106 2006/01/19 13:24:36 brouard
810: Some cleaning and links added in html output
811:
812: Revision 1.105 2006/01/05 20:23:19 lievre
813: *** empty log message ***
814:
815: Revision 1.104 2005/09/30 16:11:43 lievre
816: (Module): sump fixed, loop imx fixed, and simplifications.
817: (Module): If the status is missing at the last wave but we know
818: that the person is alive, then we can code his/her status as -2
819: (instead of missing=-1 in earlier versions) and his/her
820: contributions to the likelihood is 1 - Prob of dying from last
821: health status (= 1-p13= p11+p12 in the easiest case of somebody in
822: the healthy state at last known wave). Version is 0.98
823:
824: Revision 1.103 2005/09/30 15:54:49 lievre
825: (Module): sump fixed, loop imx fixed, and simplifications.
826:
827: Revision 1.102 2004/09/15 17:31:30 brouard
828: Add the possibility to read data file including tab characters.
829:
830: Revision 1.101 2004/09/15 10:38:38 brouard
831: Fix on curr_time
832:
833: Revision 1.100 2004/07/12 18:29:06 brouard
834: Add version for Mac OS X. Just define UNIX in Makefile
835:
836: Revision 1.99 2004/06/05 08:57:40 brouard
837: *** empty log message ***
838:
839: Revision 1.98 2004/05/16 15:05:56 brouard
840: New version 0.97 . First attempt to estimate force of mortality
841: directly from the data i.e. without the need of knowing the health
842: state at each age, but using a Gompertz model: log u =a + b*age .
843: This is the basic analysis of mortality and should be done before any
844: other analysis, in order to test if the mortality estimated from the
845: cross-longitudinal survey is different from the mortality estimated
846: from other sources like vital statistic data.
847:
848: The same imach parameter file can be used but the option for mle should be -3.
849:
1.133 brouard 850: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 851: former routines in order to include the new code within the former code.
852:
853: The output is very simple: only an estimate of the intercept and of
854: the slope with 95% confident intervals.
855:
856: Current limitations:
857: A) Even if you enter covariates, i.e. with the
858: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
859: B) There is no computation of Life Expectancy nor Life Table.
860:
861: Revision 1.97 2004/02/20 13:25:42 lievre
862: Version 0.96d. Population forecasting command line is (temporarily)
863: suppressed.
864:
865: Revision 1.96 2003/07/15 15:38:55 brouard
866: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
867: rewritten within the same printf. Workaround: many printfs.
868:
869: Revision 1.95 2003/07/08 07:54:34 brouard
870: * imach.c (Repository):
871: (Repository): Using imachwizard code to output a more meaningful covariance
872: matrix (cov(a12,c31) instead of numbers.
873:
874: Revision 1.94 2003/06/27 13:00:02 brouard
875: Just cleaning
876:
877: Revision 1.93 2003/06/25 16:33:55 brouard
878: (Module): On windows (cygwin) function asctime_r doesn't
879: exist so I changed back to asctime which exists.
880: (Module): Version 0.96b
881:
882: Revision 1.92 2003/06/25 16:30:45 brouard
883: (Module): On windows (cygwin) function asctime_r doesn't
884: exist so I changed back to asctime which exists.
885:
886: Revision 1.91 2003/06/25 15:30:29 brouard
887: * imach.c (Repository): Duplicated warning errors corrected.
888: (Repository): Elapsed time after each iteration is now output. It
889: helps to forecast when convergence will be reached. Elapsed time
890: is stamped in powell. We created a new html file for the graphs
891: concerning matrix of covariance. It has extension -cov.htm.
892:
893: Revision 1.90 2003/06/24 12:34:15 brouard
894: (Module): Some bugs corrected for windows. Also, when
895: mle=-1 a template is output in file "or"mypar.txt with the design
896: of the covariance matrix to be input.
897:
898: Revision 1.89 2003/06/24 12:30:52 brouard
899: (Module): Some bugs corrected for windows. Also, when
900: mle=-1 a template is output in file "or"mypar.txt with the design
901: of the covariance matrix to be input.
902:
903: Revision 1.88 2003/06/23 17:54:56 brouard
904: * 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.
905:
906: Revision 1.87 2003/06/18 12:26:01 brouard
907: Version 0.96
908:
909: Revision 1.86 2003/06/17 20:04:08 brouard
910: (Module): Change position of html and gnuplot routines and added
911: routine fileappend.
912:
913: Revision 1.85 2003/06/17 13:12:43 brouard
914: * imach.c (Repository): Check when date of death was earlier that
915: current date of interview. It may happen when the death was just
916: prior to the death. In this case, dh was negative and likelihood
917: was wrong (infinity). We still send an "Error" but patch by
918: assuming that the date of death was just one stepm after the
919: interview.
920: (Repository): Because some people have very long ID (first column)
921: we changed int to long in num[] and we added a new lvector for
922: memory allocation. But we also truncated to 8 characters (left
923: truncation)
924: (Repository): No more line truncation errors.
925:
926: Revision 1.84 2003/06/13 21:44:43 brouard
927: * imach.c (Repository): Replace "freqsummary" at a correct
928: place. It differs from routine "prevalence" which may be called
929: many times. Probs is memory consuming and must be used with
930: parcimony.
931: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
932:
933: Revision 1.83 2003/06/10 13:39:11 lievre
934: *** empty log message ***
935:
936: Revision 1.82 2003/06/05 15:57:20 brouard
937: Add log in imach.c and fullversion number is now printed.
938:
939: */
940: /*
941: Interpolated Markov Chain
942:
943: Short summary of the programme:
944:
1.227 brouard 945: This program computes Healthy Life Expectancies or State-specific
946: (if states aren't health statuses) Expectancies from
947: cross-longitudinal data. Cross-longitudinal data consist in:
948:
949: -1- a first survey ("cross") where individuals from different ages
950: are interviewed on their health status or degree of disability (in
951: the case of a health survey which is our main interest)
952:
953: -2- at least a second wave of interviews ("longitudinal") which
954: measure each change (if any) in individual health status. Health
955: expectancies are computed from the time spent in each health state
956: according to a model. More health states you consider, more time is
957: necessary to reach the Maximum Likelihood of the parameters involved
958: in the model. The simplest model is the multinomial logistic model
959: where pij is the probability to be observed in state j at the second
960: wave conditional to be observed in state i at the first
961: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
962: etc , where 'age' is age and 'sex' is a covariate. If you want to
963: have a more complex model than "constant and age", you should modify
964: the program where the markup *Covariates have to be included here
965: again* invites you to do it. More covariates you add, slower the
1.126 brouard 966: convergence.
967:
968: The advantage of this computer programme, compared to a simple
969: multinomial logistic model, is clear when the delay between waves is not
970: identical for each individual. Also, if a individual missed an
971: intermediate interview, the information is lost, but taken into
972: account using an interpolation or extrapolation.
973:
974: hPijx is the probability to be observed in state i at age x+h
975: conditional to the observed state i at age x. The delay 'h' can be
976: split into an exact number (nh*stepm) of unobserved intermediate
977: states. This elementary transition (by month, quarter,
978: semester or year) is modelled as a multinomial logistic. The hPx
979: matrix is simply the matrix product of nh*stepm elementary matrices
980: and the contribution of each individual to the likelihood is simply
981: hPijx.
982:
983: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 984: of the life expectancies. It also computes the period (stable) prevalence.
985:
986: Back prevalence and projections:
1.227 brouard 987:
988: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
989: double agemaxpar, double ftolpl, int *ncvyearp, double
990: dateprev1,double dateprev2, int firstpass, int lastpass, int
991: mobilavproj)
992:
993: Computes the back prevalence limit for any combination of
994: covariate values k at any age between ageminpar and agemaxpar and
995: returns it in **bprlim. In the loops,
996:
997: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
998: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
999:
1000: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 1001: Computes for any combination of covariates k and any age between bage and fage
1002: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
1003: oldm=oldms;savm=savms;
1.227 brouard 1004:
1.267 brouard 1005: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 1006: Computes the transition matrix starting at age 'age' over
1007: 'nhstepm*hstepm*stepm' months (i.e. until
1008: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 1009: nhstepm*hstepm matrices.
1010:
1011: Returns p3mat[i][j][h] after calling
1012: p3mat[i][j][h]=matprod2(newm,
1013: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
1014: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
1015: oldm);
1.226 brouard 1016:
1017: Important routines
1018:
1019: - func (or funcone), computes logit (pij) distinguishing
1020: o fixed variables (single or product dummies or quantitative);
1021: o varying variables by:
1022: (1) wave (single, product dummies, quantitative),
1023: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
1024: % fixed dummy (treated) or quantitative (not done because time-consuming);
1025: % varying dummy (not done) or quantitative (not done);
1026: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
1027: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
1028: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
1029: o There are 2*cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
1030: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 1031:
1.226 brouard 1032:
1033:
1.133 brouard 1034: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
1035: Institut national d'études démographiques, Paris.
1.126 brouard 1036: This software have been partly granted by Euro-REVES, a concerted action
1037: from the European Union.
1038: It is copyrighted identically to a GNU software product, ie programme and
1039: software can be distributed freely for non commercial use. Latest version
1040: can be accessed at http://euroreves.ined.fr/imach .
1041:
1042: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
1043: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
1044:
1045: **********************************************************************/
1046: /*
1047: main
1048: read parameterfile
1049: read datafile
1050: concatwav
1051: freqsummary
1052: if (mle >= 1)
1053: mlikeli
1054: print results files
1055: if mle==1
1056: computes hessian
1057: read end of parameter file: agemin, agemax, bage, fage, estepm
1058: begin-prev-date,...
1059: open gnuplot file
1060: open html file
1.145 brouard 1061: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
1062: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
1063: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
1064: freexexit2 possible for memory heap.
1065:
1066: h Pij x | pij_nom ficrestpij
1067: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
1068: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
1069: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
1070:
1071: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
1072: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
1073: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
1074: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
1075: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
1076:
1.126 brouard 1077: forecasting if prevfcast==1 prevforecast call prevalence()
1078: health expectancies
1079: Variance-covariance of DFLE
1080: prevalence()
1081: movingaverage()
1082: varevsij()
1083: if popbased==1 varevsij(,popbased)
1084: total life expectancies
1085: Variance of period (stable) prevalence
1086: end
1087: */
1088:
1.187 brouard 1089: /* #define DEBUG */
1090: /* #define DEBUGBRENT */
1.203 brouard 1091: /* #define DEBUGLINMIN */
1092: /* #define DEBUGHESS */
1093: #define DEBUGHESSIJ
1.224 brouard 1094: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 1095: #define POWELL /* Instead of NLOPT */
1.224 brouard 1096: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 1097: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
1098: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.126 brouard 1099:
1100: #include <math.h>
1101: #include <stdio.h>
1102: #include <stdlib.h>
1103: #include <string.h>
1.226 brouard 1104: #include <ctype.h>
1.159 brouard 1105:
1106: #ifdef _WIN32
1107: #include <io.h>
1.172 brouard 1108: #include <windows.h>
1109: #include <tchar.h>
1.159 brouard 1110: #else
1.126 brouard 1111: #include <unistd.h>
1.159 brouard 1112: #endif
1.126 brouard 1113:
1114: #include <limits.h>
1115: #include <sys/types.h>
1.171 brouard 1116:
1117: #if defined(__GNUC__)
1118: #include <sys/utsname.h> /* Doesn't work on Windows */
1119: #endif
1120:
1.126 brouard 1121: #include <sys/stat.h>
1122: #include <errno.h>
1.159 brouard 1123: /* extern int errno; */
1.126 brouard 1124:
1.157 brouard 1125: /* #ifdef LINUX */
1126: /* #include <time.h> */
1127: /* #include "timeval.h" */
1128: /* #else */
1129: /* #include <sys/time.h> */
1130: /* #endif */
1131:
1.126 brouard 1132: #include <time.h>
1133:
1.136 brouard 1134: #ifdef GSL
1135: #include <gsl/gsl_errno.h>
1136: #include <gsl/gsl_multimin.h>
1137: #endif
1138:
1.167 brouard 1139:
1.162 brouard 1140: #ifdef NLOPT
1141: #include <nlopt.h>
1142: typedef struct {
1143: double (* function)(double [] );
1144: } myfunc_data ;
1145: #endif
1146:
1.126 brouard 1147: /* #include <libintl.h> */
1148: /* #define _(String) gettext (String) */
1149:
1.251 brouard 1150: #define MAXLINE 2048 /* Was 256 and 1024. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 1151:
1152: #define GNUPLOTPROGRAM "gnuplot"
1153: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
1154: #define FILENAMELENGTH 132
1155:
1156: #define GLOCK_ERROR_NOPATH -1 /* empty path */
1157: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
1158:
1.144 brouard 1159: #define MAXPARM 128 /**< Maximum number of parameters for the optimization */
1160: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 1161:
1162: #define NINTERVMAX 8
1.144 brouard 1163: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
1164: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
1.318 ! brouard 1165: #define NCOVMAX 30 /**< Maximum number of covariates, including generated covariates V1*V2 */
1.197 brouard 1166: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 1167: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
1168: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.290 brouard 1169: /*#define MAXN 20000 */ /* Should by replaced by nobs, real number of observations and unlimited */
1.144 brouard 1170: #define YEARM 12. /**< Number of months per year */
1.218 brouard 1171: /* #define AGESUP 130 */
1.288 brouard 1172: /* #define AGESUP 150 */
1173: #define AGESUP 200
1.268 brouard 1174: #define AGEINF 0
1.218 brouard 1175: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1176: #define AGEBASE 40
1.194 brouard 1177: #define AGEOVERFLOW 1.e20
1.164 brouard 1178: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1179: #ifdef _WIN32
1180: #define DIRSEPARATOR '\\'
1181: #define CHARSEPARATOR "\\"
1182: #define ODIRSEPARATOR '/'
1183: #else
1.126 brouard 1184: #define DIRSEPARATOR '/'
1185: #define CHARSEPARATOR "/"
1186: #define ODIRSEPARATOR '\\'
1187: #endif
1188:
1.318 ! brouard 1189: /* $Id: imach.c,v 1.317 2022/05/15 15:06:23 brouard Exp $ */
1.126 brouard 1190: /* $State: Exp $ */
1.196 brouard 1191: #include "version.h"
1192: char version[]=__IMACH_VERSION__;
1.316 brouard 1193: char copyright[]="May 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";
1.318 ! brouard 1194: char fullversion[]="$Revision: 1.317 $ $Date: 2022/05/15 15:06:23 $";
1.126 brouard 1195: char strstart[80];
1196: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1197: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.187 brouard 1198: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.145 brouard 1199: /* Number of covariates model=V2+V1+ V3*age+V2*V4 */
1200: int cptcovn=0; /**< cptcovn number of covariates added in the model (excepting constant and age and age*product) */
1201: int cptcovt=0; /**< cptcovt number of covariates added in the model (excepting constant and age) */
1.225 brouard 1202: int cptcovs=0; /**< cptcovs number of simple covariates in the model V2+V1 =2 */
1203: int cptcovsnq=0; /**< cptcovsnq number of simple covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1204: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1205: int cptcovprodnoage=0; /**< Number of covariate products without age */
1206: int cptcoveff=0; /* Total number of covariates to vary for printing results */
1.233 brouard 1207: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1208: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.232 brouard 1209: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (dummy of quantitative) in the model */
1.234 brouard 1210: int nsd=0; /**< Total number of single dummy variables (output) */
1211: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1212: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1213: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1214: int ntveff=0; /**< ntveff number of effective time varying variables */
1215: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1216: int cptcov=0; /* Working variable */
1.290 brouard 1217: int nobs=10; /* Number of observations in the data lastobs-firstobs */
1.218 brouard 1218: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.302 brouard 1219: int npar=NPARMAX; /* Number of parameters (nlstate+ndeath-1)*nlstate*ncovmodel; */
1.126 brouard 1220: int nlstate=2; /* Number of live states */
1221: int ndeath=1; /* Number of dead states */
1.130 brouard 1222: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.223 brouard 1223: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable */
1.126 brouard 1224: int popbased=0;
1225:
1226: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1227: int maxwav=0; /* Maxim number of waves */
1228: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1229: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1230: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 1231: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1232: int mle=1, weightopt=0;
1.126 brouard 1233: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1234: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1235: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1236: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1237: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1238: int selected(int kvar); /* Is covariate kvar selected for printing results */
1239:
1.130 brouard 1240: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1241: double **matprod2(); /* test */
1.126 brouard 1242: double **oldm, **newm, **savm; /* Working pointers to matrices */
1243: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1244: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1245:
1.136 brouard 1246: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1247: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1248: FILE *ficlog, *ficrespow;
1.130 brouard 1249: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1250: double fretone; /* Only one call to likelihood */
1.130 brouard 1251: long ipmx=0; /* Number of contributions */
1.126 brouard 1252: double sw; /* Sum of weights */
1253: char filerespow[FILENAMELENGTH];
1254: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1255: FILE *ficresilk;
1256: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1257: FILE *ficresprobmorprev;
1258: FILE *fichtm, *fichtmcov; /* Html File */
1259: FILE *ficreseij;
1260: char filerese[FILENAMELENGTH];
1261: FILE *ficresstdeij;
1262: char fileresstde[FILENAMELENGTH];
1263: FILE *ficrescveij;
1264: char filerescve[FILENAMELENGTH];
1265: FILE *ficresvij;
1266: char fileresv[FILENAMELENGTH];
1.269 brouard 1267:
1.126 brouard 1268: char title[MAXLINE];
1.234 brouard 1269: char model[MAXLINE]; /**< The model line */
1.217 brouard 1270: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1271: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1272: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1273: char command[FILENAMELENGTH];
1274: int outcmd=0;
1275:
1.217 brouard 1276: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1277: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1278: char filelog[FILENAMELENGTH]; /* Log file */
1279: char filerest[FILENAMELENGTH];
1280: char fileregp[FILENAMELENGTH];
1281: char popfile[FILENAMELENGTH];
1282:
1283: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1284:
1.157 brouard 1285: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1286: /* struct timezone tzp; */
1287: /* extern int gettimeofday(); */
1288: struct tm tml, *gmtime(), *localtime();
1289:
1290: extern time_t time();
1291:
1292: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1293: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1294: struct tm tm;
1295:
1.126 brouard 1296: char strcurr[80], strfor[80];
1297:
1298: char *endptr;
1299: long lval;
1300: double dval;
1301:
1302: #define NR_END 1
1303: #define FREE_ARG char*
1304: #define FTOL 1.0e-10
1305:
1306: #define NRANSI
1.240 brouard 1307: #define ITMAX 200
1308: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1309:
1310: #define TOL 2.0e-4
1311:
1312: #define CGOLD 0.3819660
1313: #define ZEPS 1.0e-10
1314: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1315:
1316: #define GOLD 1.618034
1317: #define GLIMIT 100.0
1318: #define TINY 1.0e-20
1319:
1320: static double maxarg1,maxarg2;
1321: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1322: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1323:
1324: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1325: #define rint(a) floor(a+0.5)
1.166 brouard 1326: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1327: #define mytinydouble 1.0e-16
1.166 brouard 1328: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1329: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1330: /* static double dsqrarg; */
1331: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1332: static double sqrarg;
1333: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1334: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1335: int agegomp= AGEGOMP;
1336:
1337: int imx;
1338: int stepm=1;
1339: /* Stepm, step in month: minimum step interpolation*/
1340:
1341: int estepm;
1342: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1343:
1344: int m,nb;
1345: long *num;
1.197 brouard 1346: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1347: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1348: covariate for which somebody answered excluding
1349: undefined. Usually 2: 0 and 1. */
1350: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1351: covariate for which somebody answered including
1352: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1353: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1354: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1355: double ***mobaverage, ***mobaverages; /* New global variable */
1.126 brouard 1356: double *ageexmed,*agecens;
1357: double dateintmean=0;
1.296 brouard 1358: double anprojd, mprojd, jprojd; /* For eventual projections */
1359: double anprojf, mprojf, jprojf;
1.126 brouard 1360:
1.296 brouard 1361: double anbackd, mbackd, jbackd; /* For eventual backprojections */
1362: double anbackf, mbackf, jbackf;
1363: double jintmean,mintmean,aintmean;
1.126 brouard 1364: double *weight;
1365: int **s; /* Status */
1.141 brouard 1366: double *agedc;
1.145 brouard 1367: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1368: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1369: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1370: double **coqvar; /* Fixed quantitative covariate nqv */
1371: double ***cotvar; /* Time varying covariate ntv */
1.225 brouard 1372: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1373: double idx;
1374: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.318 ! brouard 1375: /* 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
! 1376: # States 1=Coresidence, 2 Living alone, 3 Institution
! 1377: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
! 1378: */
1.234 brouard 1379: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1380: /*k 1 2 3 4 5 6 7 8 9 */
1381: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 */
1382: /* Tndvar[k] 1 2 3 4 5 */
1383: /*TDvar 4 3 6 7 1 */ /* For outputs only; combination of dummies fixed or varying */
1384: /* Tns[k] 1 2 2 4 5 */ /* Number of single cova */
1385: /* TvarsD[k] 1 2 3 */ /* Number of single dummy cova */
1386: /* TvarsDind 2 3 9 */ /* position K of single dummy cova */
1387: /* TvarsQ[k] 1 2 */ /* Number of single quantitative cova */
1388: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1389: /* Tprod[i]=k 4 7 */
1390: /* Tage[i]=k 5 8 */
1391: /* */
1392: /* Type */
1393: /* V 1 2 3 4 5 */
1394: /* F F V V V */
1395: /* D Q D D Q */
1396: /* */
1397: int *TvarsD;
1398: int *TvarsDind;
1399: int *TvarsQ;
1400: int *TvarsQind;
1401:
1.318 ! brouard 1402: #define MAXRESULTLINESPONE 10+1
1.235 brouard 1403: int nresult=0;
1.258 brouard 1404: int parameterline=0; /* # of the parameter (type) line */
1.318 ! brouard 1405: int TKresult[MAXRESULTLINESPONE];
! 1406: int Tresult[MAXRESULTLINESPONE][NCOVMAX];/* For dummy variable , value (output) */
! 1407: int Tinvresult[MAXRESULTLINESPONE][NCOVMAX];/* For dummy variable , value (output) */
! 1408: int Tvresult[MAXRESULTLINESPONE][NCOVMAX]; /* For dummy variable , variable # (output) */
! 1409: double Tqresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , value (output) */
! 1410: double Tqinvresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , value (output) */
! 1411: int Tvqresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , variable # (output) */
! 1412:
! 1413: /* 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
! 1414: # States 1=Coresidence, 2 Living alone, 3 Institution
! 1415: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
! 1416: */
1.234 brouard 1417: /* 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 1418: 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 */
1419: 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 */
1420: 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 */
1421: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1422: 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 */
1423: 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 1424: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1425: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1426: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1427: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1428: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1429: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1430: 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 */
1431: 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 */
1432:
1.230 brouard 1433: int *Tvarsel; /**< Selected covariates for output */
1434: double *Tvalsel; /**< Selected modality value of covariate for output */
1.226 brouard 1435: int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.227 brouard 1436: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1437: 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 1438: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1439: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1440: int *Tage;
1.227 brouard 1441: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1442: 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 1443: 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*/
1444: 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 1445: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1446: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1447: int **Tvard;
1448: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1449: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1450: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1451: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1452: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1453: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1454: double *lsurv, *lpop, *tpop;
1455:
1.231 brouard 1456: #define FD 1; /* Fixed dummy covariate */
1457: #define FQ 2; /* Fixed quantitative covariate */
1458: #define FP 3; /* Fixed product covariate */
1459: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1460: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1461: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1462: #define VD 10; /* Varying dummy covariate */
1463: #define VQ 11; /* Varying quantitative covariate */
1464: #define VP 12; /* Varying product covariate */
1465: #define VPDD 13; /* Varying product dummy*dummy covariate */
1466: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1467: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1468: #define APFD 16; /* Age product * fixed dummy covariate */
1469: #define APFQ 17; /* Age product * fixed quantitative covariate */
1470: #define APVD 18; /* Age product * varying dummy covariate */
1471: #define APVQ 19; /* Age product * varying quantitative covariate */
1472:
1473: #define FTYPE 1; /* Fixed covariate */
1474: #define VTYPE 2; /* Varying covariate (loop in wave) */
1475: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1476:
1477: struct kmodel{
1478: int maintype; /* main type */
1479: int subtype; /* subtype */
1480: };
1481: struct kmodel modell[NCOVMAX];
1482:
1.143 brouard 1483: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1484: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1485:
1486: /**************** split *************************/
1487: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1488: {
1489: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1490: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1491: */
1492: char *ss; /* pointer */
1.186 brouard 1493: int l1=0, l2=0; /* length counters */
1.126 brouard 1494:
1495: l1 = strlen(path ); /* length of path */
1496: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1497: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1498: if ( ss == NULL ) { /* no directory, so determine current directory */
1499: strcpy( name, path ); /* we got the fullname name because no directory */
1500: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1501: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1502: /* get current working directory */
1503: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1504: #ifdef WIN32
1505: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1506: #else
1507: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1508: #endif
1.126 brouard 1509: return( GLOCK_ERROR_GETCWD );
1510: }
1511: /* got dirc from getcwd*/
1512: printf(" DIRC = %s \n",dirc);
1.205 brouard 1513: } else { /* strip directory from path */
1.126 brouard 1514: ss++; /* after this, the filename */
1515: l2 = strlen( ss ); /* length of filename */
1516: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1517: strcpy( name, ss ); /* save file name */
1518: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1519: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1520: printf(" DIRC2 = %s \n",dirc);
1521: }
1522: /* We add a separator at the end of dirc if not exists */
1523: l1 = strlen( dirc ); /* length of directory */
1524: if( dirc[l1-1] != DIRSEPARATOR ){
1525: dirc[l1] = DIRSEPARATOR;
1526: dirc[l1+1] = 0;
1527: printf(" DIRC3 = %s \n",dirc);
1528: }
1529: ss = strrchr( name, '.' ); /* find last / */
1530: if (ss >0){
1531: ss++;
1532: strcpy(ext,ss); /* save extension */
1533: l1= strlen( name);
1534: l2= strlen(ss)+1;
1535: strncpy( finame, name, l1-l2);
1536: finame[l1-l2]= 0;
1537: }
1538:
1539: return( 0 ); /* we're done */
1540: }
1541:
1542:
1543: /******************************************/
1544:
1545: void replace_back_to_slash(char *s, char*t)
1546: {
1547: int i;
1548: int lg=0;
1549: i=0;
1550: lg=strlen(t);
1551: for(i=0; i<= lg; i++) {
1552: (s[i] = t[i]);
1553: if (t[i]== '\\') s[i]='/';
1554: }
1555: }
1556:
1.132 brouard 1557: char *trimbb(char *out, char *in)
1.137 brouard 1558: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1559: char *s;
1560: s=out;
1561: while (*in != '\0'){
1.137 brouard 1562: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1563: in++;
1564: }
1565: *out++ = *in++;
1566: }
1567: *out='\0';
1568: return s;
1569: }
1570:
1.187 brouard 1571: /* char *substrchaine(char *out, char *in, char *chain) */
1572: /* { */
1573: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1574: /* char *s, *t; */
1575: /* t=in;s=out; */
1576: /* while ((*in != *chain) && (*in != '\0')){ */
1577: /* *out++ = *in++; */
1578: /* } */
1579:
1580: /* /\* *in matches *chain *\/ */
1581: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1582: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1583: /* } */
1584: /* in--; chain--; */
1585: /* while ( (*in != '\0')){ */
1586: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1587: /* *out++ = *in++; */
1588: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1589: /* } */
1590: /* *out='\0'; */
1591: /* out=s; */
1592: /* return out; */
1593: /* } */
1594: char *substrchaine(char *out, char *in, char *chain)
1595: {
1596: /* Substract chain 'chain' from 'in', return and output 'out' */
1597: /* in="V1+V1*age+age*age+V2", chain="age*age" */
1598:
1599: char *strloc;
1600:
1601: strcpy (out, in);
1602: strloc = strstr(out, chain); /* strloc points to out at age*age+V2 */
1603: printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out);
1604: if(strloc != NULL){
1605: /* will affect out */ /* strloc+strlenc(chain)=+V2 */ /* Will also work in Unicode */
1606: memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1);
1607: /* strcpy (strloc, strloc +strlen(chain));*/
1608: }
1609: printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out);
1610: return out;
1611: }
1612:
1613:
1.145 brouard 1614: char *cutl(char *blocc, char *alocc, char *in, char occ)
1615: {
1.187 brouard 1616: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.145 brouard 1617: and alocc starts after first occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1.310 brouard 1618: gives alocc="abcdef" and blocc="ghi2j".
1.145 brouard 1619: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1620: */
1.160 brouard 1621: char *s, *t;
1.145 brouard 1622: t=in;s=in;
1623: while ((*in != occ) && (*in != '\0')){
1624: *alocc++ = *in++;
1625: }
1626: if( *in == occ){
1627: *(alocc)='\0';
1628: s=++in;
1629: }
1630:
1631: if (s == t) {/* occ not found */
1632: *(alocc-(in-s))='\0';
1633: in=s;
1634: }
1635: while ( *in != '\0'){
1636: *blocc++ = *in++;
1637: }
1638:
1639: *blocc='\0';
1640: return t;
1641: }
1.137 brouard 1642: char *cutv(char *blocc, char *alocc, char *in, char occ)
1643: {
1.187 brouard 1644: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1645: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1646: gives blocc="abcdef2ghi" and alocc="j".
1647: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1648: */
1649: char *s, *t;
1650: t=in;s=in;
1651: while (*in != '\0'){
1652: while( *in == occ){
1653: *blocc++ = *in++;
1654: s=in;
1655: }
1656: *blocc++ = *in++;
1657: }
1658: if (s == t) /* occ not found */
1659: *(blocc-(in-s))='\0';
1660: else
1661: *(blocc-(in-s)-1)='\0';
1662: in=s;
1663: while ( *in != '\0'){
1664: *alocc++ = *in++;
1665: }
1666:
1667: *alocc='\0';
1668: return s;
1669: }
1670:
1.126 brouard 1671: int nbocc(char *s, char occ)
1672: {
1673: int i,j=0;
1674: int lg=20;
1675: i=0;
1676: lg=strlen(s);
1677: for(i=0; i<= lg; i++) {
1.234 brouard 1678: if (s[i] == occ ) j++;
1.126 brouard 1679: }
1680: return j;
1681: }
1682:
1.137 brouard 1683: /* void cutv(char *u,char *v, char*t, char occ) */
1684: /* { */
1685: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1686: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1687: /* gives u="abcdef2ghi" and v="j" *\/ */
1688: /* int i,lg,j,p=0; */
1689: /* i=0; */
1690: /* lg=strlen(t); */
1691: /* for(j=0; j<=lg-1; j++) { */
1692: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1693: /* } */
1.126 brouard 1694:
1.137 brouard 1695: /* for(j=0; j<p; j++) { */
1696: /* (u[j] = t[j]); */
1697: /* } */
1698: /* u[p]='\0'; */
1.126 brouard 1699:
1.137 brouard 1700: /* for(j=0; j<= lg; j++) { */
1701: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1702: /* } */
1703: /* } */
1.126 brouard 1704:
1.160 brouard 1705: #ifdef _WIN32
1706: char * strsep(char **pp, const char *delim)
1707: {
1708: char *p, *q;
1709:
1710: if ((p = *pp) == NULL)
1711: return 0;
1712: if ((q = strpbrk (p, delim)) != NULL)
1713: {
1714: *pp = q + 1;
1715: *q = '\0';
1716: }
1717: else
1718: *pp = 0;
1719: return p;
1720: }
1721: #endif
1722:
1.126 brouard 1723: /********************** nrerror ********************/
1724:
1725: void nrerror(char error_text[])
1726: {
1727: fprintf(stderr,"ERREUR ...\n");
1728: fprintf(stderr,"%s\n",error_text);
1729: exit(EXIT_FAILURE);
1730: }
1731: /*********************** vector *******************/
1732: double *vector(int nl, int nh)
1733: {
1734: double *v;
1735: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
1736: if (!v) nrerror("allocation failure in vector");
1737: return v-nl+NR_END;
1738: }
1739:
1740: /************************ free vector ******************/
1741: void free_vector(double*v, int nl, int nh)
1742: {
1743: free((FREE_ARG)(v+nl-NR_END));
1744: }
1745:
1746: /************************ivector *******************************/
1747: int *ivector(long nl,long nh)
1748: {
1749: int *v;
1750: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
1751: if (!v) nrerror("allocation failure in ivector");
1752: return v-nl+NR_END;
1753: }
1754:
1755: /******************free ivector **************************/
1756: void free_ivector(int *v, long nl, long nh)
1757: {
1758: free((FREE_ARG)(v+nl-NR_END));
1759: }
1760:
1761: /************************lvector *******************************/
1762: long *lvector(long nl,long nh)
1763: {
1764: long *v;
1765: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
1766: if (!v) nrerror("allocation failure in ivector");
1767: return v-nl+NR_END;
1768: }
1769:
1770: /******************free lvector **************************/
1771: void free_lvector(long *v, long nl, long nh)
1772: {
1773: free((FREE_ARG)(v+nl-NR_END));
1774: }
1775:
1776: /******************* imatrix *******************************/
1777: int **imatrix(long nrl, long nrh, long ncl, long nch)
1778: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
1779: {
1780: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
1781: int **m;
1782:
1783: /* allocate pointers to rows */
1784: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
1785: if (!m) nrerror("allocation failure 1 in matrix()");
1786: m += NR_END;
1787: m -= nrl;
1788:
1789:
1790: /* allocate rows and set pointers to them */
1791: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
1792: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1793: m[nrl] += NR_END;
1794: m[nrl] -= ncl;
1795:
1796: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
1797:
1798: /* return pointer to array of pointers to rows */
1799: return m;
1800: }
1801:
1802: /****************** free_imatrix *************************/
1803: void free_imatrix(m,nrl,nrh,ncl,nch)
1804: int **m;
1805: long nch,ncl,nrh,nrl;
1806: /* free an int matrix allocated by imatrix() */
1807: {
1808: free((FREE_ARG) (m[nrl]+ncl-NR_END));
1809: free((FREE_ARG) (m+nrl-NR_END));
1810: }
1811:
1812: /******************* matrix *******************************/
1813: double **matrix(long nrl, long nrh, long ncl, long nch)
1814: {
1815: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
1816: double **m;
1817:
1818: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1819: if (!m) nrerror("allocation failure 1 in matrix()");
1820: m += NR_END;
1821: m -= nrl;
1822:
1823: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1824: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1825: m[nrl] += NR_END;
1826: m[nrl] -= ncl;
1827:
1828: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1829: return m;
1.145 brouard 1830: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
1831: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
1832: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 1833: */
1834: }
1835:
1836: /*************************free matrix ************************/
1837: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
1838: {
1839: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1840: free((FREE_ARG)(m+nrl-NR_END));
1841: }
1842:
1843: /******************* ma3x *******************************/
1844: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
1845: {
1846: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
1847: double ***m;
1848:
1849: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1850: if (!m) nrerror("allocation failure 1 in matrix()");
1851: m += NR_END;
1852: m -= nrl;
1853:
1854: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1855: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1856: m[nrl] += NR_END;
1857: m[nrl] -= ncl;
1858:
1859: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1860:
1861: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
1862: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
1863: m[nrl][ncl] += NR_END;
1864: m[nrl][ncl] -= nll;
1865: for (j=ncl+1; j<=nch; j++)
1866: m[nrl][j]=m[nrl][j-1]+nlay;
1867:
1868: for (i=nrl+1; i<=nrh; i++) {
1869: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
1870: for (j=ncl+1; j<=nch; j++)
1871: m[i][j]=m[i][j-1]+nlay;
1872: }
1873: return m;
1874: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
1875: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
1876: */
1877: }
1878:
1879: /*************************free ma3x ************************/
1880: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
1881: {
1882: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
1883: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1884: free((FREE_ARG)(m+nrl-NR_END));
1885: }
1886:
1887: /*************** function subdirf ***********/
1888: char *subdirf(char fileres[])
1889: {
1890: /* Caution optionfilefiname is hidden */
1891: strcpy(tmpout,optionfilefiname);
1892: strcat(tmpout,"/"); /* Add to the right */
1893: strcat(tmpout,fileres);
1894: return tmpout;
1895: }
1896:
1897: /*************** function subdirf2 ***********/
1898: char *subdirf2(char fileres[], char *preop)
1899: {
1.314 brouard 1900: /* Example subdirf2(optionfilefiname,"FB_") with optionfilefiname="texte", result="texte/FB_texte"
1901: Errors in subdirf, 2, 3 while printing tmpout is
1.315 brouard 1902: rewritten within the same printf. Workaround: many printfs */
1.126 brouard 1903: /* Caution optionfilefiname is hidden */
1904: strcpy(tmpout,optionfilefiname);
1905: strcat(tmpout,"/");
1906: strcat(tmpout,preop);
1907: strcat(tmpout,fileres);
1908: return tmpout;
1909: }
1910:
1911: /*************** function subdirf3 ***********/
1912: char *subdirf3(char fileres[], char *preop, char *preop2)
1913: {
1914:
1915: /* Caution optionfilefiname is hidden */
1916: strcpy(tmpout,optionfilefiname);
1917: strcat(tmpout,"/");
1918: strcat(tmpout,preop);
1919: strcat(tmpout,preop2);
1920: strcat(tmpout,fileres);
1921: return tmpout;
1922: }
1.213 brouard 1923:
1924: /*************** function subdirfext ***********/
1925: char *subdirfext(char fileres[], char *preop, char *postop)
1926: {
1927:
1928: strcpy(tmpout,preop);
1929: strcat(tmpout,fileres);
1930: strcat(tmpout,postop);
1931: return tmpout;
1932: }
1.126 brouard 1933:
1.213 brouard 1934: /*************** function subdirfext3 ***********/
1935: char *subdirfext3(char fileres[], char *preop, char *postop)
1936: {
1937:
1938: /* Caution optionfilefiname is hidden */
1939: strcpy(tmpout,optionfilefiname);
1940: strcat(tmpout,"/");
1941: strcat(tmpout,preop);
1942: strcat(tmpout,fileres);
1943: strcat(tmpout,postop);
1944: return tmpout;
1945: }
1946:
1.162 brouard 1947: char *asc_diff_time(long time_sec, char ascdiff[])
1948: {
1949: long sec_left, days, hours, minutes;
1950: days = (time_sec) / (60*60*24);
1951: sec_left = (time_sec) % (60*60*24);
1952: hours = (sec_left) / (60*60) ;
1953: sec_left = (sec_left) %(60*60);
1954: minutes = (sec_left) /60;
1955: sec_left = (sec_left) % (60);
1956: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
1957: return ascdiff;
1958: }
1959:
1.126 brouard 1960: /***************** f1dim *************************/
1961: extern int ncom;
1962: extern double *pcom,*xicom;
1963: extern double (*nrfunc)(double []);
1964:
1965: double f1dim(double x)
1966: {
1967: int j;
1968: double f;
1969: double *xt;
1970:
1971: xt=vector(1,ncom);
1972: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
1973: f=(*nrfunc)(xt);
1974: free_vector(xt,1,ncom);
1975: return f;
1976: }
1977:
1978: /*****************brent *************************/
1979: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 1980: {
1981: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
1982: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
1983: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
1984: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
1985: * returned function value.
1986: */
1.126 brouard 1987: int iter;
1988: double a,b,d,etemp;
1.159 brouard 1989: double fu=0,fv,fw,fx;
1.164 brouard 1990: double ftemp=0.;
1.126 brouard 1991: double p,q,r,tol1,tol2,u,v,w,x,xm;
1992: double e=0.0;
1993:
1994: a=(ax < cx ? ax : cx);
1995: b=(ax > cx ? ax : cx);
1996: x=w=v=bx;
1997: fw=fv=fx=(*f)(x);
1998: for (iter=1;iter<=ITMAX;iter++) {
1999: xm=0.5*(a+b);
2000: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
2001: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
2002: printf(".");fflush(stdout);
2003: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 2004: #ifdef DEBUGBRENT
1.126 brouard 2005: 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);
2006: 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);
2007: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
2008: #endif
2009: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
2010: *xmin=x;
2011: return fx;
2012: }
2013: ftemp=fu;
2014: if (fabs(e) > tol1) {
2015: r=(x-w)*(fx-fv);
2016: q=(x-v)*(fx-fw);
2017: p=(x-v)*q-(x-w)*r;
2018: q=2.0*(q-r);
2019: if (q > 0.0) p = -p;
2020: q=fabs(q);
2021: etemp=e;
2022: e=d;
2023: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 2024: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 2025: else {
1.224 brouard 2026: d=p/q;
2027: u=x+d;
2028: if (u-a < tol2 || b-u < tol2)
2029: d=SIGN(tol1,xm-x);
1.126 brouard 2030: }
2031: } else {
2032: d=CGOLD*(e=(x >= xm ? a-x : b-x));
2033: }
2034: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
2035: fu=(*f)(u);
2036: if (fu <= fx) {
2037: if (u >= x) a=x; else b=x;
2038: SHFT(v,w,x,u)
1.183 brouard 2039: SHFT(fv,fw,fx,fu)
2040: } else {
2041: if (u < x) a=u; else b=u;
2042: if (fu <= fw || w == x) {
1.224 brouard 2043: v=w;
2044: w=u;
2045: fv=fw;
2046: fw=fu;
1.183 brouard 2047: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 2048: v=u;
2049: fv=fu;
1.183 brouard 2050: }
2051: }
1.126 brouard 2052: }
2053: nrerror("Too many iterations in brent");
2054: *xmin=x;
2055: return fx;
2056: }
2057:
2058: /****************** mnbrak ***********************/
2059:
2060: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
2061: double (*func)(double))
1.183 brouard 2062: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
2063: the downhill direction (defined by the function as evaluated at the initial points) and returns
2064: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
2065: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
2066: */
1.126 brouard 2067: double ulim,u,r,q, dum;
2068: double fu;
1.187 brouard 2069:
2070: double scale=10.;
2071: int iterscale=0;
2072:
2073: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
2074: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
2075:
2076:
2077: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
2078: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
2079: /* *bx = *ax - (*ax - *bx)/scale; */
2080: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
2081: /* } */
2082:
1.126 brouard 2083: if (*fb > *fa) {
2084: SHFT(dum,*ax,*bx,dum)
1.183 brouard 2085: SHFT(dum,*fb,*fa,dum)
2086: }
1.126 brouard 2087: *cx=(*bx)+GOLD*(*bx-*ax);
2088: *fc=(*func)(*cx);
1.183 brouard 2089: #ifdef DEBUG
1.224 brouard 2090: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
2091: 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 2092: #endif
1.224 brouard 2093: 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 2094: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 2095: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 2096: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 2097: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
2098: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
2099: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 2100: fu=(*func)(u);
1.163 brouard 2101: #ifdef DEBUG
2102: /* f(x)=A(x-u)**2+f(u) */
2103: double A, fparabu;
2104: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2105: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 2106: 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);
2107: 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 2108: /* And thus,it can be that fu > *fc even if fparabu < *fc */
2109: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
2110: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
2111: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 2112: #endif
1.184 brouard 2113: #ifdef MNBRAKORIGINAL
1.183 brouard 2114: #else
1.191 brouard 2115: /* if (fu > *fc) { */
2116: /* #ifdef DEBUG */
2117: /* printf("mnbrak4 fu > fc \n"); */
2118: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
2119: /* #endif */
2120: /* /\* 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 *\\/ *\/ */
2121: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
2122: /* dum=u; /\* Shifting c and u *\/ */
2123: /* u = *cx; */
2124: /* *cx = dum; */
2125: /* dum = fu; */
2126: /* fu = *fc; */
2127: /* *fc =dum; */
2128: /* } else { /\* end *\/ */
2129: /* #ifdef DEBUG */
2130: /* printf("mnbrak3 fu < fc \n"); */
2131: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
2132: /* #endif */
2133: /* dum=u; /\* Shifting c and u *\/ */
2134: /* u = *cx; */
2135: /* *cx = dum; */
2136: /* dum = fu; */
2137: /* fu = *fc; */
2138: /* *fc =dum; */
2139: /* } */
1.224 brouard 2140: #ifdef DEBUGMNBRAK
2141: double A, fparabu;
2142: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2143: fparabu= *fa - A*(*ax-u)*(*ax-u);
2144: 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);
2145: 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 2146: #endif
1.191 brouard 2147: dum=u; /* Shifting c and u */
2148: u = *cx;
2149: *cx = dum;
2150: dum = fu;
2151: fu = *fc;
2152: *fc =dum;
1.183 brouard 2153: #endif
1.162 brouard 2154: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 2155: #ifdef DEBUG
1.224 brouard 2156: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
2157: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 2158: #endif
1.126 brouard 2159: fu=(*func)(u);
2160: if (fu < *fc) {
1.183 brouard 2161: #ifdef DEBUG
1.224 brouard 2162: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2163: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2164: #endif
2165: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
2166: SHFT(*fb,*fc,fu,(*func)(u))
2167: #ifdef DEBUG
2168: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 2169: #endif
2170: }
1.162 brouard 2171: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 2172: #ifdef DEBUG
1.224 brouard 2173: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
2174: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 2175: #endif
1.126 brouard 2176: u=ulim;
2177: fu=(*func)(u);
1.183 brouard 2178: } else { /* u could be left to b (if r > q parabola has a maximum) */
2179: #ifdef DEBUG
1.224 brouard 2180: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
2181: 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 2182: #endif
1.126 brouard 2183: u=(*cx)+GOLD*(*cx-*bx);
2184: fu=(*func)(u);
1.224 brouard 2185: #ifdef DEBUG
2186: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2187: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2188: #endif
1.183 brouard 2189: } /* end tests */
1.126 brouard 2190: SHFT(*ax,*bx,*cx,u)
1.183 brouard 2191: SHFT(*fa,*fb,*fc,fu)
2192: #ifdef DEBUG
1.224 brouard 2193: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2194: 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 2195: #endif
2196: } /* 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 2197: }
2198:
2199: /*************** linmin ************************/
1.162 brouard 2200: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2201: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2202: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2203: the value of func at the returned location p . This is actually all accomplished by calling the
2204: routines mnbrak and brent .*/
1.126 brouard 2205: int ncom;
2206: double *pcom,*xicom;
2207: double (*nrfunc)(double []);
2208:
1.224 brouard 2209: #ifdef LINMINORIGINAL
1.126 brouard 2210: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2211: #else
2212: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2213: #endif
1.126 brouard 2214: {
2215: double brent(double ax, double bx, double cx,
2216: double (*f)(double), double tol, double *xmin);
2217: double f1dim(double x);
2218: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2219: double *fc, double (*func)(double));
2220: int j;
2221: double xx,xmin,bx,ax;
2222: double fx,fb,fa;
1.187 brouard 2223:
1.203 brouard 2224: #ifdef LINMINORIGINAL
2225: #else
2226: double scale=10., axs, xxs; /* Scale added for infinity */
2227: #endif
2228:
1.126 brouard 2229: ncom=n;
2230: pcom=vector(1,n);
2231: xicom=vector(1,n);
2232: nrfunc=func;
2233: for (j=1;j<=n;j++) {
2234: pcom[j]=p[j];
1.202 brouard 2235: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2236: }
1.187 brouard 2237:
1.203 brouard 2238: #ifdef LINMINORIGINAL
2239: xx=1.;
2240: #else
2241: axs=0.0;
2242: xxs=1.;
2243: do{
2244: xx= xxs;
2245: #endif
1.187 brouard 2246: ax=0.;
2247: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2248: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2249: /* 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)) */
2250: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2251: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2252: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2253: /* 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 2254: #ifdef LINMINORIGINAL
2255: #else
2256: if (fx != fx){
1.224 brouard 2257: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2258: printf("|");
2259: fprintf(ficlog,"|");
1.203 brouard 2260: #ifdef DEBUGLINMIN
1.224 brouard 2261: 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 2262: #endif
2263: }
1.224 brouard 2264: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2265: #endif
2266:
1.191 brouard 2267: #ifdef DEBUGLINMIN
2268: 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 2269: 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 2270: #endif
1.224 brouard 2271: #ifdef LINMINORIGINAL
2272: #else
1.317 brouard 2273: if(fb == fx){ /* Flat function in the direction */
2274: xmin=xx;
1.224 brouard 2275: *flat=1;
1.317 brouard 2276: }else{
1.224 brouard 2277: *flat=0;
2278: #endif
2279: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2280: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2281: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2282: /* fmin = f(p[j] + xmin * xi[j]) */
2283: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2284: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2285: #ifdef DEBUG
1.224 brouard 2286: 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);
2287: 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);
2288: #endif
2289: #ifdef LINMINORIGINAL
2290: #else
2291: }
1.126 brouard 2292: #endif
1.191 brouard 2293: #ifdef DEBUGLINMIN
2294: printf("linmin end ");
1.202 brouard 2295: fprintf(ficlog,"linmin end ");
1.191 brouard 2296: #endif
1.126 brouard 2297: for (j=1;j<=n;j++) {
1.203 brouard 2298: #ifdef LINMINORIGINAL
2299: xi[j] *= xmin;
2300: #else
2301: #ifdef DEBUGLINMIN
2302: if(xxs <1.0)
2303: printf(" before xi[%d]=%12.8f", j,xi[j]);
2304: #endif
2305: 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) */
2306: #ifdef DEBUGLINMIN
2307: if(xxs <1.0)
2308: 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 );
2309: #endif
2310: #endif
1.187 brouard 2311: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2312: }
1.191 brouard 2313: #ifdef DEBUGLINMIN
1.203 brouard 2314: printf("\n");
1.191 brouard 2315: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2316: 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 2317: for (j=1;j<=n;j++) {
1.202 brouard 2318: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2319: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2320: if(j % ncovmodel == 0){
1.191 brouard 2321: printf("\n");
1.202 brouard 2322: fprintf(ficlog,"\n");
2323: }
1.191 brouard 2324: }
1.203 brouard 2325: #else
1.191 brouard 2326: #endif
1.126 brouard 2327: free_vector(xicom,1,n);
2328: free_vector(pcom,1,n);
2329: }
2330:
2331:
2332: /*************** powell ************************/
1.162 brouard 2333: /*
1.317 brouard 2334: Minimization of a function func of n variables. Input consists in an initial starting point
2335: p[1..n] ; an initial matrix xi[1..n][1..n] whose columns contain the initial set of di-
2336: rections (usually the n unit vectors); and ftol, the fractional tolerance in the function value
2337: such that failure to decrease by more than this amount in one iteration signals doneness. On
1.162 brouard 2338: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2339: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2340: */
1.224 brouard 2341: #ifdef LINMINORIGINAL
2342: #else
2343: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2344: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2345: #endif
1.126 brouard 2346: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2347: double (*func)(double []))
2348: {
1.224 brouard 2349: #ifdef LINMINORIGINAL
2350: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2351: double (*func)(double []));
1.224 brouard 2352: #else
1.241 brouard 2353: void linmin(double p[], double xi[], int n, double *fret,
2354: double (*func)(double []),int *flat);
1.224 brouard 2355: #endif
1.239 brouard 2356: int i,ibig,j,jk,k;
1.126 brouard 2357: double del,t,*pt,*ptt,*xit;
1.181 brouard 2358: double directest;
1.126 brouard 2359: double fp,fptt;
2360: double *xits;
2361: int niterf, itmp;
1.224 brouard 2362: #ifdef LINMINORIGINAL
2363: #else
2364:
2365: flatdir=ivector(1,n);
2366: for (j=1;j<=n;j++) flatdir[j]=0;
2367: #endif
1.126 brouard 2368:
2369: pt=vector(1,n);
2370: ptt=vector(1,n);
2371: xit=vector(1,n);
2372: xits=vector(1,n);
2373: *fret=(*func)(p);
2374: for (j=1;j<=n;j++) pt[j]=p[j];
1.202 brouard 2375: rcurr_time = time(NULL);
1.126 brouard 2376: for (*iter=1;;++(*iter)) {
1.187 brouard 2377: fp=(*fret); /* From former iteration or initial value */
1.126 brouard 2378: ibig=0;
2379: del=0.0;
1.157 brouard 2380: rlast_time=rcurr_time;
2381: /* (void) gettimeofday(&curr_time,&tzp); */
2382: rcurr_time = time(NULL);
2383: curr_time = *localtime(&rcurr_time);
2384: printf("\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout);
2385: fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog);
2386: /* fprintf(ficrespow,"%d %.12f %ld",*iter,*fret,curr_time.tm_sec-start_time.tm_sec); */
1.192 brouard 2387: for (i=1;i<=n;i++) {
1.126 brouard 2388: fprintf(ficrespow," %.12lf", p[i]);
2389: }
1.239 brouard 2390: fprintf(ficrespow,"\n");fflush(ficrespow);
2391: printf("\n#model= 1 + age ");
2392: fprintf(ficlog,"\n#model= 1 + age ");
2393: if(nagesqr==1){
1.241 brouard 2394: printf(" + age*age ");
2395: fprintf(ficlog," + age*age ");
1.239 brouard 2396: }
2397: for(j=1;j <=ncovmodel-2;j++){
2398: if(Typevar[j]==0) {
2399: printf(" + V%d ",Tvar[j]);
2400: fprintf(ficlog," + V%d ",Tvar[j]);
2401: }else if(Typevar[j]==1) {
2402: printf(" + V%d*age ",Tvar[j]);
2403: fprintf(ficlog," + V%d*age ",Tvar[j]);
2404: }else if(Typevar[j]==2) {
2405: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2406: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2407: }
2408: }
1.126 brouard 2409: printf("\n");
1.239 brouard 2410: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2411: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2412: fprintf(ficlog,"\n");
1.239 brouard 2413: for(i=1,jk=1; i <=nlstate; i++){
2414: for(k=1; k <=(nlstate+ndeath); k++){
2415: if (k != i) {
2416: printf("%d%d ",i,k);
2417: fprintf(ficlog,"%d%d ",i,k);
2418: for(j=1; j <=ncovmodel; j++){
2419: printf("%12.7f ",p[jk]);
2420: fprintf(ficlog,"%12.7f ",p[jk]);
2421: jk++;
2422: }
2423: printf("\n");
2424: fprintf(ficlog,"\n");
2425: }
2426: }
2427: }
1.241 brouard 2428: if(*iter <=3 && *iter >1){
1.157 brouard 2429: tml = *localtime(&rcurr_time);
2430: strcpy(strcurr,asctime(&tml));
2431: rforecast_time=rcurr_time;
1.126 brouard 2432: itmp = strlen(strcurr);
2433: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2434: strcurr[itmp-1]='\0';
1.162 brouard 2435: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2436: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.126 brouard 2437: for(niterf=10;niterf<=30;niterf+=10){
1.241 brouard 2438: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2439: forecast_time = *localtime(&rforecast_time);
2440: strcpy(strfor,asctime(&forecast_time));
2441: itmp = strlen(strfor);
2442: if(strfor[itmp-1]=='\n')
2443: strfor[itmp-1]='\0';
2444: 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);
2445: 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 2446: }
2447: }
1.187 brouard 2448: for (i=1;i<=n;i++) { /* For each direction i */
2449: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2450: fptt=(*fret);
2451: #ifdef DEBUG
1.203 brouard 2452: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2453: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2454: #endif
1.203 brouard 2455: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2456: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2457: #ifdef LINMINORIGINAL
1.188 brouard 2458: linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.224 brouard 2459: #else
2460: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2461: flatdir[i]=flat; /* Function is vanishing in that direction i */
2462: #endif
2463: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2464: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2465: /* because that direction will be replaced unless the gain del is small */
2466: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2467: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2468: /* with the new direction. */
2469: del=fabs(fptt-(*fret));
2470: ibig=i;
1.126 brouard 2471: }
2472: #ifdef DEBUG
2473: printf("%d %.12e",i,(*fret));
2474: fprintf(ficlog,"%d %.12e",i,(*fret));
2475: for (j=1;j<=n;j++) {
1.224 brouard 2476: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2477: printf(" x(%d)=%.12e",j,xit[j]);
2478: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2479: }
2480: for(j=1;j<=n;j++) {
1.225 brouard 2481: printf(" p(%d)=%.12e",j,p[j]);
2482: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2483: }
2484: printf("\n");
2485: fprintf(ficlog,"\n");
2486: #endif
1.187 brouard 2487: } /* end loop on each direction i */
2488: /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
1.188 brouard 2489: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.187 brouard 2490: /* New value of last point Pn is not computed, P(n-1) */
1.224 brouard 2491: for(j=1;j<=n;j++) {
1.302 brouard 2492: if(flatdir[j] >0){
2493: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2494: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2495: }
2496: /* printf("\n"); */
2497: /* fprintf(ficlog,"\n"); */
2498: }
1.243 brouard 2499: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
2500: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2501: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2502: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2503: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2504: /* decreased of more than 3.84 */
2505: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2506: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2507: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2508:
1.188 brouard 2509: /* Starting the program with initial values given by a former maximization will simply change */
2510: /* the scales of the directions and the directions, because the are reset to canonical directions */
2511: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2512: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2513: #ifdef DEBUG
2514: int k[2],l;
2515: k[0]=1;
2516: k[1]=-1;
2517: printf("Max: %.12e",(*func)(p));
2518: fprintf(ficlog,"Max: %.12e",(*func)(p));
2519: for (j=1;j<=n;j++) {
2520: printf(" %.12e",p[j]);
2521: fprintf(ficlog," %.12e",p[j]);
2522: }
2523: printf("\n");
2524: fprintf(ficlog,"\n");
2525: for(l=0;l<=1;l++) {
2526: for (j=1;j<=n;j++) {
2527: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2528: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2529: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2530: }
2531: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2532: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2533: }
2534: #endif
2535:
1.224 brouard 2536: #ifdef LINMINORIGINAL
2537: #else
2538: free_ivector(flatdir,1,n);
2539: #endif
1.126 brouard 2540: free_vector(xit,1,n);
2541: free_vector(xits,1,n);
2542: free_vector(ptt,1,n);
2543: free_vector(pt,1,n);
2544: return;
1.192 brouard 2545: } /* enough precision */
1.240 brouard 2546: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2547: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2548: ptt[j]=2.0*p[j]-pt[j];
2549: xit[j]=p[j]-pt[j];
2550: pt[j]=p[j];
2551: }
1.181 brouard 2552: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2553: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2554: if (*iter <=4) {
1.225 brouard 2555: #else
2556: #endif
1.224 brouard 2557: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2558: #else
1.161 brouard 2559: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2560: #endif
1.162 brouard 2561: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2562: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2563: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2564: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2565: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2566: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2567: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2568: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2569: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2570: /* Even if f3 <f1, directest can be negative and t >0 */
2571: /* mu² and del² are equal when f3=f1 */
2572: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2573: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2574: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2575: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2576: #ifdef NRCORIGINAL
2577: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2578: #else
2579: 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 2580: t= t- del*SQR(fp-fptt);
1.183 brouard 2581: #endif
1.202 brouard 2582: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2583: #ifdef DEBUG
1.181 brouard 2584: 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);
2585: 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 2586: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2587: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2588: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2589: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2590: 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);
2591: 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);
2592: #endif
1.183 brouard 2593: #ifdef POWELLORIGINAL
2594: if (t < 0.0) { /* Then we use it for new direction */
2595: #else
1.182 brouard 2596: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2597: 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 2598: 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 2599: 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 2600: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2601: }
1.181 brouard 2602: if (directest < 0.0) { /* Then we use it for new direction */
2603: #endif
1.191 brouard 2604: #ifdef DEBUGLINMIN
1.234 brouard 2605: printf("Before linmin in direction P%d-P0\n",n);
2606: for (j=1;j<=n;j++) {
2607: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2608: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2609: if(j % ncovmodel == 0){
2610: printf("\n");
2611: fprintf(ficlog,"\n");
2612: }
2613: }
1.224 brouard 2614: #endif
2615: #ifdef LINMINORIGINAL
1.234 brouard 2616: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2617: #else
1.234 brouard 2618: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2619: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2620: #endif
1.234 brouard 2621:
1.191 brouard 2622: #ifdef DEBUGLINMIN
1.234 brouard 2623: for (j=1;j<=n;j++) {
2624: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2625: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2626: if(j % ncovmodel == 0){
2627: printf("\n");
2628: fprintf(ficlog,"\n");
2629: }
2630: }
1.224 brouard 2631: #endif
1.234 brouard 2632: for (j=1;j<=n;j++) {
2633: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2634: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2635: }
1.224 brouard 2636: #ifdef LINMINORIGINAL
2637: #else
1.234 brouard 2638: for (j=1, flatd=0;j<=n;j++) {
2639: if(flatdir[j]>0)
2640: flatd++;
2641: }
2642: if(flatd >0){
1.255 brouard 2643: printf("%d flat directions: ",flatd);
2644: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 2645: for (j=1;j<=n;j++) {
2646: if(flatdir[j]>0){
2647: printf("%d ",j);
2648: fprintf(ficlog,"%d ",j);
2649: }
2650: }
2651: printf("\n");
2652: fprintf(ficlog,"\n");
2653: }
1.191 brouard 2654: #endif
1.234 brouard 2655: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2656: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2657:
1.126 brouard 2658: #ifdef DEBUG
1.234 brouard 2659: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2660: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2661: for(j=1;j<=n;j++){
2662: printf(" %lf",xit[j]);
2663: fprintf(ficlog," %lf",xit[j]);
2664: }
2665: printf("\n");
2666: fprintf(ficlog,"\n");
1.126 brouard 2667: #endif
1.192 brouard 2668: } /* end of t or directest negative */
1.224 brouard 2669: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2670: #else
1.234 brouard 2671: } /* end if (fptt < fp) */
1.192 brouard 2672: #endif
1.225 brouard 2673: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2674: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2675: #else
1.224 brouard 2676: #endif
1.234 brouard 2677: } /* loop iteration */
1.126 brouard 2678: }
1.234 brouard 2679:
1.126 brouard 2680: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 2681:
1.235 brouard 2682: 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 2683: {
1.279 brouard 2684: /**< Computes the prevalence limit in each live state at age x and for covariate combination ij
2685: * (and selected quantitative values in nres)
2686: * by left multiplying the unit
2687: * matrix by transitions matrix until convergence is reached with precision ftolpl
2688: * Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I
2689: * Wx is row vector: population in state 1, population in state 2, population dead
2690: * or prevalence in state 1, prevalence in state 2, 0
2691: * newm is the matrix after multiplications, its rows are identical at a factor.
2692: * Inputs are the parameter, age, a tolerance for the prevalence limit ftolpl.
2693: * Output is prlim.
2694: * Initial matrix pimij
2695: */
1.206 brouard 2696: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2697: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2698: /* 0, 0 , 1} */
2699: /*
2700: * and after some iteration: */
2701: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2702: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2703: /* 0, 0 , 1} */
2704: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2705: /* {0.51571254859325999, 0.4842874514067399, */
2706: /* 0.51326036147820708, 0.48673963852179264} */
2707: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 2708:
1.126 brouard 2709: int i, ii,j,k;
1.209 brouard 2710: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 2711: /* double **matprod2(); */ /* test */
1.218 brouard 2712: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 2713: double **newm;
1.209 brouard 2714: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 2715: int ncvloop=0;
1.288 brouard 2716: int first=0;
1.169 brouard 2717:
1.209 brouard 2718: min=vector(1,nlstate);
2719: max=vector(1,nlstate);
2720: meandiff=vector(1,nlstate);
2721:
1.218 brouard 2722: /* Starting with matrix unity */
1.126 brouard 2723: for (ii=1;ii<=nlstate+ndeath;ii++)
2724: for (j=1;j<=nlstate+ndeath;j++){
2725: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2726: }
1.169 brouard 2727:
2728: cov[1]=1.;
2729:
2730: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 2731: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 2732: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 2733: ncvloop++;
1.126 brouard 2734: newm=savm;
2735: /* Covariates have to be included here again */
1.138 brouard 2736: cov[2]=agefin;
1.187 brouard 2737: if(nagesqr==1)
2738: cov[3]= agefin*agefin;;
1.234 brouard 2739: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2740: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2741: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.235 brouard 2742: /* 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 2743: }
2744: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2745: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
1.235 brouard 2746: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2747: /* 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 2748: }
1.237 brouard 2749: for (k=1; k<=cptcovage;k++){ /* For product with age */
1.234 brouard 2750: if(Dummy[Tvar[Tage[k]]]){
2751: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
2752: } else{
1.235 brouard 2753: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
1.234 brouard 2754: }
1.235 brouard 2755: /* 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 2756: }
1.237 brouard 2757: for (k=1; k<=cptcovprod;k++){ /* For product without age */
1.235 brouard 2758: /* printf("prevalim Prod ij=%d k=%d Tprod[%d]=%d Tvard[%d][1]=V%d, Tvard[%d][2]=V%d\n",ij,k,k,Tprod[k], k,Tvard[k][1], k,Tvard[k][2]); */
1.237 brouard 2759: if(Dummy[Tvard[k][1]==0]){
2760: if(Dummy[Tvard[k][2]==0]){
2761: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2762: }else{
2763: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2764: }
2765: }else{
2766: if(Dummy[Tvard[k][2]==0]){
2767: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2768: }else{
2769: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2770: }
2771: }
1.234 brouard 2772: }
1.138 brouard 2773: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2774: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2775: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 2776: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2777: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2778: /* age and covariate values of ij are in 'cov' */
1.142 brouard 2779: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 2780:
1.126 brouard 2781: savm=oldm;
2782: oldm=newm;
1.209 brouard 2783:
2784: for(j=1; j<=nlstate; j++){
2785: max[j]=0.;
2786: min[j]=1.;
2787: }
2788: for(i=1;i<=nlstate;i++){
2789: sumnew=0;
2790: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
2791: for(j=1; j<=nlstate; j++){
2792: prlim[i][j]= newm[i][j]/(1-sumnew);
2793: max[j]=FMAX(max[j],prlim[i][j]);
2794: min[j]=FMIN(min[j],prlim[i][j]);
2795: }
2796: }
2797:
1.126 brouard 2798: maxmax=0.;
1.209 brouard 2799: for(j=1; j<=nlstate; j++){
2800: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
2801: maxmax=FMAX(maxmax,meandiff[j]);
2802: /* 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 2803: } /* j loop */
1.203 brouard 2804: *ncvyear= (int)age- (int)agefin;
1.208 brouard 2805: /* 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 2806: if(maxmax < ftolpl){
1.209 brouard 2807: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
2808: free_vector(min,1,nlstate);
2809: free_vector(max,1,nlstate);
2810: free_vector(meandiff,1,nlstate);
1.126 brouard 2811: return prlim;
2812: }
1.288 brouard 2813: } /* agefin loop */
1.208 brouard 2814: /* After some age loop it doesn't converge */
1.288 brouard 2815: if(!first){
2816: first=1;
2817: 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 2818: 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);
2819: }else if (first >=1 && first <10){
2820: 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);
2821: first++;
2822: }else if (first ==10){
2823: 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);
2824: 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");
2825: fprintf(ficlog,"Warning: the stable prevalence no convergence; too many cases, giving up noticing, even in log file\n");
2826: first++;
1.288 brouard 2827: }
2828:
1.209 brouard 2829: /* 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); */
2830: free_vector(min,1,nlstate);
2831: free_vector(max,1,nlstate);
2832: free_vector(meandiff,1,nlstate);
1.208 brouard 2833:
1.169 brouard 2834: return prlim; /* should not reach here */
1.126 brouard 2835: }
2836:
1.217 brouard 2837:
2838: /**** Back Prevalence limit (stable or period prevalence) ****************/
2839:
1.218 brouard 2840: /* 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) */
2841: /* 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 2842: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 2843: {
1.264 brouard 2844: /* 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 2845: matrix by transitions matrix until convergence is reached with precision ftolpl */
2846: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
2847: /* Wx is row vector: population in state 1, population in state 2, population dead */
2848: /* or prevalence in state 1, prevalence in state 2, 0 */
2849: /* newm is the matrix after multiplications, its rows are identical at a factor */
2850: /* Initial matrix pimij */
2851: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2852: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2853: /* 0, 0 , 1} */
2854: /*
2855: * and after some iteration: */
2856: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2857: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2858: /* 0, 0 , 1} */
2859: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2860: /* {0.51571254859325999, 0.4842874514067399, */
2861: /* 0.51326036147820708, 0.48673963852179264} */
2862: /* If we start from prlim again, prlim tends to a constant matrix */
2863:
2864: int i, ii,j,k;
1.247 brouard 2865: int first=0;
1.217 brouard 2866: double *min, *max, *meandiff, maxmax,sumnew=0.;
2867: /* double **matprod2(); */ /* test */
2868: double **out, cov[NCOVMAX+1], **bmij();
2869: double **newm;
1.218 brouard 2870: double **dnewm, **doldm, **dsavm; /* for use */
2871: double **oldm, **savm; /* for use */
2872:
1.217 brouard 2873: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
2874: int ncvloop=0;
2875:
2876: min=vector(1,nlstate);
2877: max=vector(1,nlstate);
2878: meandiff=vector(1,nlstate);
2879:
1.266 brouard 2880: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
2881: oldm=oldms; savm=savms;
2882:
2883: /* Starting with matrix unity */
2884: for (ii=1;ii<=nlstate+ndeath;ii++)
2885: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 2886: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2887: }
2888:
2889: cov[1]=1.;
2890:
2891: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
2892: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 2893: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
1.288 brouard 2894: /* for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
2895: for(agefin=age; agefin<FMIN(AGESUP,age+delaymax); agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 2896: ncvloop++;
1.218 brouard 2897: newm=savm; /* oldm should be kept from previous iteration or unity at start */
2898: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 2899: /* Covariates have to be included here again */
2900: cov[2]=agefin;
2901: if(nagesqr==1)
2902: cov[3]= agefin*agefin;;
1.242 brouard 2903: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2904: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2905: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.264 brouard 2906: /* 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 2907: }
2908: /* for (k=1; k<=cptcovn;k++) { */
2909: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
2910: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
2911: /* /\* 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])]); *\/ */
2912: /* } */
2913: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2914: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
2915: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2916: /* 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]); */
2917: }
2918: /* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; */
2919: /* for (k=1; k<=cptcovprod;k++) /\* Useless *\/ */
2920: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\/ */
2921: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */
2922: for (k=1; k<=cptcovage;k++){ /* For product with age */
2923: if(Dummy[Tvar[Tage[k]]]){
2924: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
2925: } else{
2926: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
2927: }
2928: /* 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]); */
2929: }
2930: for (k=1; k<=cptcovprod;k++){ /* For product without age */
2931: /* 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]); */
2932: if(Dummy[Tvard[k][1]==0]){
2933: if(Dummy[Tvard[k][2]==0]){
2934: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2935: }else{
2936: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2937: }
2938: }else{
2939: if(Dummy[Tvard[k][2]==0]){
2940: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2941: }else{
2942: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2943: }
2944: }
1.217 brouard 2945: }
2946:
2947: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2948: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2949: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
2950: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2951: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2952: /* ij should be linked to the correct index of cov */
2953: /* age and covariate values ij are in 'cov', but we need to pass
2954: * ij for the observed prevalence at age and status and covariate
2955: * number: prevacurrent[(int)agefin][ii][ij]
2956: */
2957: /* 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 *\/ */
2958: /* 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 *\/ */
2959: 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 2960: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 2961: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
2962: /* for(i=1; i<=nlstate+ndeath; i++) { */
2963: /* printf("%d newm= ",i); */
2964: /* for(j=1;j<=nlstate+ndeath;j++) { */
2965: /* printf("%f ",newm[i][j]); */
2966: /* } */
2967: /* printf("oldm * "); */
2968: /* for(j=1;j<=nlstate+ndeath;j++) { */
2969: /* printf("%f ",oldm[i][j]); */
2970: /* } */
1.268 brouard 2971: /* printf(" bmmij "); */
1.266 brouard 2972: /* for(j=1;j<=nlstate+ndeath;j++) { */
2973: /* printf("%f ",pmmij[i][j]); */
2974: /* } */
2975: /* printf("\n"); */
2976: /* } */
2977: /* } */
1.217 brouard 2978: savm=oldm;
2979: oldm=newm;
1.266 brouard 2980:
1.217 brouard 2981: for(j=1; j<=nlstate; j++){
2982: max[j]=0.;
2983: min[j]=1.;
2984: }
2985: for(j=1; j<=nlstate; j++){
2986: for(i=1;i<=nlstate;i++){
1.234 brouard 2987: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
2988: bprlim[i][j]= newm[i][j];
2989: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
2990: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 2991: }
2992: }
1.218 brouard 2993:
1.217 brouard 2994: maxmax=0.;
2995: for(i=1; i<=nlstate; i++){
1.318 ! brouard 2996: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column, could be nan! */
1.217 brouard 2997: maxmax=FMAX(maxmax,meandiff[i]);
2998: /* 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 2999: } /* i loop */
1.217 brouard 3000: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 3001: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3002: if(maxmax < ftolpl){
1.220 brouard 3003: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3004: free_vector(min,1,nlstate);
3005: free_vector(max,1,nlstate);
3006: free_vector(meandiff,1,nlstate);
3007: return bprlim;
3008: }
1.288 brouard 3009: } /* agefin loop */
1.217 brouard 3010: /* After some age loop it doesn't converge */
1.288 brouard 3011: if(!first){
1.247 brouard 3012: first=1;
3013: 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\
3014: 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);
3015: }
3016: 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 3017: 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);
3018: /* 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); */
3019: free_vector(min,1,nlstate);
3020: free_vector(max,1,nlstate);
3021: free_vector(meandiff,1,nlstate);
3022:
3023: return bprlim; /* should not reach here */
3024: }
3025:
1.126 brouard 3026: /*************** transition probabilities ***************/
3027:
3028: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
3029: {
1.138 brouard 3030: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 3031: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 3032: model to the ncovmodel covariates (including constant and age).
3033: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3034: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3035: ncth covariate in the global vector x is given by the formula:
3036: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3037: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3038: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3039: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 3040: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 3041: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 3042: Sum on j ps[i][j] should equal to 1.
1.138 brouard 3043: */
3044: double s1, lnpijopii;
1.126 brouard 3045: /*double t34;*/
1.164 brouard 3046: int i,j, nc, ii, jj;
1.126 brouard 3047:
1.223 brouard 3048: for(i=1; i<= nlstate; i++){
3049: for(j=1; j<i;j++){
3050: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3051: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3052: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3053: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3054: }
3055: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3056: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3057: }
3058: for(j=i+1; j<=nlstate+ndeath;j++){
3059: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3060: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3061: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3062: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3063: }
3064: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3065: }
3066: }
1.218 brouard 3067:
1.223 brouard 3068: for(i=1; i<= nlstate; i++){
3069: s1=0;
3070: for(j=1; j<i; j++){
3071: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3072: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3073: }
3074: for(j=i+1; j<=nlstate+ndeath; j++){
3075: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3076: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3077: }
3078: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3079: ps[i][i]=1./(s1+1.);
3080: /* Computing other pijs */
3081: for(j=1; j<i; j++)
3082: ps[i][j]= exp(ps[i][j])*ps[i][i];
3083: for(j=i+1; j<=nlstate+ndeath; j++)
3084: ps[i][j]= exp(ps[i][j])*ps[i][i];
3085: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3086: } /* end i */
1.218 brouard 3087:
1.223 brouard 3088: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3089: for(jj=1; jj<= nlstate+ndeath; jj++){
3090: ps[ii][jj]=0;
3091: ps[ii][ii]=1;
3092: }
3093: }
1.294 brouard 3094:
3095:
1.223 brouard 3096: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3097: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3098: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3099: /* } */
3100: /* printf("\n "); */
3101: /* } */
3102: /* printf("\n ");printf("%lf ",cov[2]);*/
3103: /*
3104: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 3105: goto end;*/
1.266 brouard 3106: return ps; /* Pointer is unchanged since its call */
1.126 brouard 3107: }
3108:
1.218 brouard 3109: /*************** backward transition probabilities ***************/
3110:
3111: /* 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 ) */
3112: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
3113: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
3114: {
1.302 brouard 3115: /* 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 3116: * 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 3117: */
1.218 brouard 3118: int i, ii, j,k;
1.222 brouard 3119:
3120: double **out, **pmij();
3121: double sumnew=0.;
1.218 brouard 3122: double agefin;
1.292 brouard 3123: 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 3124: double **dnewm, **dsavm, **doldm;
3125: double **bbmij;
3126:
1.218 brouard 3127: doldm=ddoldms; /* global pointers */
1.222 brouard 3128: dnewm=ddnewms;
3129: dsavm=ddsavms;
1.318 ! brouard 3130:
! 3131: /* Debug */
! 3132: /* printf("Bmij ij=%d, cov[2}=%f\n", ij, cov[2]); */
1.222 brouard 3133: agefin=cov[2];
1.268 brouard 3134: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 3135: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 3136: the observed prevalence (with this covariate ij) at beginning of transition */
3137: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 3138:
3139: /* P_x */
1.266 brouard 3140: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm */
1.268 brouard 3141: /* outputs pmmij which is a stochastic matrix in row */
3142:
3143: /* Diag(w_x) */
1.292 brouard 3144: /* Rescaling the cross-sectional prevalence: Problem with prevacurrent which can be zero */
1.268 brouard 3145: sumnew=0.;
1.269 brouard 3146: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 3147: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.297 brouard 3148: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 3149: sumnew+=prevacurrent[(int)agefin][ii][ij];
3150: }
3151: if(sumnew >0.01){ /* At least some value in the prevalence */
3152: for (ii=1;ii<=nlstate+ndeath;ii++){
3153: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 3154: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 3155: }
3156: }else{
3157: for (ii=1;ii<=nlstate+ndeath;ii++){
3158: for (j=1;j<=nlstate+ndeath;j++)
3159: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
3160: }
3161: /* if(sumnew <0.9){ */
3162: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
3163: /* } */
3164: }
3165: k3=0.0; /* We put the last diagonal to 0 */
3166: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
3167: doldm[ii][ii]= k3;
3168: }
3169: /* End doldm, At the end doldm is diag[(w_i)] */
3170:
1.292 brouard 3171: /* Left product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm): diag[(w_i)*Px */
3172: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* was a Bug Valgrind */
1.268 brouard 3173:
1.292 brouard 3174: /* Diag(Sum_i w^i_x p^ij_x, should be the prevalence at age x+stepm */
1.268 brouard 3175: /* 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 3176: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 3177: sumnew=0.;
1.222 brouard 3178: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 3179: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 3180: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 3181: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 3182: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 3183: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 3184: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3185: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 3186: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3187: /* }else */
1.268 brouard 3188: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
3189: } /*End ii */
3190: } /* 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 */
3191:
1.292 brouard 3192: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* was a Bug Valgrind */
1.268 brouard 3193: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 3194: /* end bmij */
1.266 brouard 3195: return ps; /*pointer is unchanged */
1.218 brouard 3196: }
1.217 brouard 3197: /*************** transition probabilities ***************/
3198:
1.218 brouard 3199: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 3200: {
3201: /* According to parameters values stored in x and the covariate's values stored in cov,
3202: computes the probability to be observed in state j being in state i by appying the
3203: model to the ncovmodel covariates (including constant and age).
3204: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3205: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3206: ncth covariate in the global vector x is given by the formula:
3207: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3208: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3209: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3210: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
3211: Outputs ps[i][j] the probability to be observed in j being in j according to
3212: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
3213: */
3214: double s1, lnpijopii;
3215: /*double t34;*/
3216: int i,j, nc, ii, jj;
3217:
1.234 brouard 3218: for(i=1; i<= nlstate; i++){
3219: for(j=1; j<i;j++){
3220: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3221: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3222: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3223: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3224: }
3225: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3226: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3227: }
3228: for(j=i+1; j<=nlstate+ndeath;j++){
3229: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3230: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3231: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3232: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3233: }
3234: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3235: }
3236: }
3237:
3238: for(i=1; i<= nlstate; i++){
3239: s1=0;
3240: for(j=1; j<i; j++){
3241: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3242: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3243: }
3244: for(j=i+1; j<=nlstate+ndeath; j++){
3245: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3246: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3247: }
3248: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3249: ps[i][i]=1./(s1+1.);
3250: /* Computing other pijs */
3251: for(j=1; j<i; j++)
3252: ps[i][j]= exp(ps[i][j])*ps[i][i];
3253: for(j=i+1; j<=nlstate+ndeath; j++)
3254: ps[i][j]= exp(ps[i][j])*ps[i][i];
3255: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3256: } /* end i */
3257:
3258: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3259: for(jj=1; jj<= nlstate+ndeath; jj++){
3260: ps[ii][jj]=0;
3261: ps[ii][ii]=1;
3262: }
3263: }
1.296 brouard 3264: /* Added for prevbcast */ /* Transposed matrix too */
1.234 brouard 3265: for(jj=1; jj<= nlstate+ndeath; jj++){
3266: s1=0.;
3267: for(ii=1; ii<= nlstate+ndeath; ii++){
3268: s1+=ps[ii][jj];
3269: }
3270: for(ii=1; ii<= nlstate; ii++){
3271: ps[ii][jj]=ps[ii][jj]/s1;
3272: }
3273: }
3274: /* Transposition */
3275: for(jj=1; jj<= nlstate+ndeath; jj++){
3276: for(ii=jj; ii<= nlstate+ndeath; ii++){
3277: s1=ps[ii][jj];
3278: ps[ii][jj]=ps[jj][ii];
3279: ps[jj][ii]=s1;
3280: }
3281: }
3282: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3283: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3284: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3285: /* } */
3286: /* printf("\n "); */
3287: /* } */
3288: /* printf("\n ");printf("%lf ",cov[2]);*/
3289: /*
3290: for(i=1; i<= npar; i++) printf("%f ",x[i]);
3291: goto end;*/
3292: return ps;
1.217 brouard 3293: }
3294:
3295:
1.126 brouard 3296: /**************** Product of 2 matrices ******************/
3297:
1.145 brouard 3298: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 3299: {
3300: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
3301: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
3302: /* in, b, out are matrice of pointers which should have been initialized
3303: before: only the contents of out is modified. The function returns
3304: a pointer to pointers identical to out */
1.145 brouard 3305: int i, j, k;
1.126 brouard 3306: for(i=nrl; i<= nrh; i++)
1.145 brouard 3307: for(k=ncolol; k<=ncoloh; k++){
3308: out[i][k]=0.;
3309: for(j=ncl; j<=nch; j++)
3310: out[i][k] +=in[i][j]*b[j][k];
3311: }
1.126 brouard 3312: return out;
3313: }
3314:
3315:
3316: /************* Higher Matrix Product ***************/
3317:
1.235 brouard 3318: 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 3319: {
1.218 brouard 3320: /* Computes the transition matrix starting at age 'age' and combination of covariate values corresponding to ij over
1.126 brouard 3321: 'nhstepm*hstepm*stepm' months (i.e. until
3322: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3323: nhstepm*hstepm matrices.
3324: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3325: (typically every 2 years instead of every month which is too big
3326: for the memory).
3327: Model is determined by parameters x and covariates have to be
3328: included manually here.
3329:
3330: */
3331:
3332: int i, j, d, h, k;
1.131 brouard 3333: double **out, cov[NCOVMAX+1];
1.126 brouard 3334: double **newm;
1.187 brouard 3335: double agexact;
1.214 brouard 3336: double agebegin, ageend;
1.126 brouard 3337:
3338: /* Hstepm could be zero and should return the unit matrix */
3339: for (i=1;i<=nlstate+ndeath;i++)
3340: for (j=1;j<=nlstate+ndeath;j++){
3341: oldm[i][j]=(i==j ? 1.0 : 0.0);
3342: po[i][j][0]=(i==j ? 1.0 : 0.0);
3343: }
3344: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3345: for(h=1; h <=nhstepm; h++){
3346: for(d=1; d <=hstepm; d++){
3347: newm=savm;
3348: /* Covariates have to be included here again */
3349: cov[1]=1.;
1.214 brouard 3350: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3351: cov[2]=agexact;
3352: if(nagesqr==1)
1.227 brouard 3353: cov[3]= agexact*agexact;
1.235 brouard 3354: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
3355: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
3356: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3357: /* 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)); */
3358: }
3359: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3360: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3361: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3362: /* 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]); */
3363: }
3364: for (k=1; k<=cptcovage;k++){
3365: if(Dummy[Tvar[Tage[k]]]){
3366: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
3367: } else{
3368: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3369: }
3370: /* 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]); */
3371: }
3372: for (k=1; k<=cptcovprod;k++){ /* */
3373: /* 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]); */
3374: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
3375: }
3376: /* for (k=1; k<=cptcovn;k++) */
3377: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3378: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3379: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3380: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3381: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3382:
3383:
1.126 brouard 3384: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3385: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.218 brouard 3386: /* right multiplication of oldm by the current matrix */
1.126 brouard 3387: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3388: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3389: /* if((int)age == 70){ */
3390: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3391: /* for(i=1; i<=nlstate+ndeath; i++) { */
3392: /* printf("%d pmmij ",i); */
3393: /* for(j=1;j<=nlstate+ndeath;j++) { */
3394: /* printf("%f ",pmmij[i][j]); */
3395: /* } */
3396: /* printf(" oldm "); */
3397: /* for(j=1;j<=nlstate+ndeath;j++) { */
3398: /* printf("%f ",oldm[i][j]); */
3399: /* } */
3400: /* printf("\n"); */
3401: /* } */
3402: /* } */
1.126 brouard 3403: savm=oldm;
3404: oldm=newm;
3405: }
3406: for(i=1; i<=nlstate+ndeath; i++)
3407: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 3408: po[i][j][h]=newm[i][j];
3409: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3410: }
1.128 brouard 3411: /*printf("h=%d ",h);*/
1.126 brouard 3412: } /* end h */
1.267 brouard 3413: /* printf("\n H=%d \n",h); */
1.126 brouard 3414: return po;
3415: }
3416:
1.217 brouard 3417: /************* Higher Back Matrix Product ***************/
1.218 brouard 3418: /* 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 3419: 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 3420: {
1.266 brouard 3421: /* For a combination of dummy covariate ij, computes the transition matrix starting at age 'age' over
1.217 brouard 3422: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3423: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3424: nhstepm*hstepm matrices.
3425: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3426: (typically every 2 years instead of every month which is too big
1.217 brouard 3427: for the memory).
1.218 brouard 3428: Model is determined by parameters x and covariates have to be
1.266 brouard 3429: included manually here. Then we use a call to bmij(x and cov)
3430: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 3431: */
1.217 brouard 3432:
3433: int i, j, d, h, k;
1.266 brouard 3434: double **out, cov[NCOVMAX+1], **bmij();
3435: double **newm, ***newmm;
1.217 brouard 3436: double agexact;
3437: double agebegin, ageend;
1.222 brouard 3438: double **oldm, **savm;
1.217 brouard 3439:
1.266 brouard 3440: newmm=po; /* To be saved */
3441: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 3442: /* Hstepm could be zero and should return the unit matrix */
3443: for (i=1;i<=nlstate+ndeath;i++)
3444: for (j=1;j<=nlstate+ndeath;j++){
3445: oldm[i][j]=(i==j ? 1.0 : 0.0);
3446: po[i][j][0]=(i==j ? 1.0 : 0.0);
3447: }
3448: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3449: for(h=1; h <=nhstepm; h++){
3450: for(d=1; d <=hstepm; d++){
3451: newm=savm;
3452: /* Covariates have to be included here again */
3453: cov[1]=1.;
1.271 brouard 3454: agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 3455: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
1.318 ! brouard 3456: /* Debug */
! 3457: /* printf("hBxij age=%lf, agexact=%lf\n", age, agexact); */
1.217 brouard 3458: cov[2]=agexact;
3459: if(nagesqr==1)
1.222 brouard 3460: cov[3]= agexact*agexact;
1.266 brouard 3461: for (k=1; k<=cptcovn;k++){
3462: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3463: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
3464: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3465: /* 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)); */
3466: }
1.267 brouard 3467: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3468: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3469: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3470: /* 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]); */
3471: }
3472: for (k=1; k<=cptcovage;k++){ /* Should start at cptcovn+1 */
3473: if(Dummy[Tvar[Tage[k]]]){
3474: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
3475: } else{
3476: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3477: }
3478: /* 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]); */
3479: }
3480: for (k=1; k<=cptcovprod;k++){ /* Useless because included in cptcovn */
1.222 brouard 3481: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.267 brouard 3482: }
1.217 brouard 3483: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3484: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.267 brouard 3485:
1.218 brouard 3486: /* Careful transposed matrix */
1.266 brouard 3487: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 3488: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3489: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3490: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.222 brouard 3491: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);
1.217 brouard 3492: /* if((int)age == 70){ */
3493: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3494: /* for(i=1; i<=nlstate+ndeath; i++) { */
3495: /* printf("%d pmmij ",i); */
3496: /* for(j=1;j<=nlstate+ndeath;j++) { */
3497: /* printf("%f ",pmmij[i][j]); */
3498: /* } */
3499: /* printf(" oldm "); */
3500: /* for(j=1;j<=nlstate+ndeath;j++) { */
3501: /* printf("%f ",oldm[i][j]); */
3502: /* } */
3503: /* printf("\n"); */
3504: /* } */
3505: /* } */
3506: savm=oldm;
3507: oldm=newm;
3508: }
3509: for(i=1; i<=nlstate+ndeath; i++)
3510: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 3511: po[i][j][h]=newm[i][j];
1.268 brouard 3512: /* if(h==nhstepm) */
3513: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 3514: }
1.268 brouard 3515: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 3516: } /* end h */
1.268 brouard 3517: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 3518: return po;
3519: }
3520:
3521:
1.162 brouard 3522: #ifdef NLOPT
3523: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
3524: double fret;
3525: double *xt;
3526: int j;
3527: myfunc_data *d2 = (myfunc_data *) pd;
3528: /* xt = (p1-1); */
3529: xt=vector(1,n);
3530: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
3531:
3532: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
3533: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
3534: printf("Function = %.12lf ",fret);
3535: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
3536: printf("\n");
3537: free_vector(xt,1,n);
3538: return fret;
3539: }
3540: #endif
1.126 brouard 3541:
3542: /*************** log-likelihood *************/
3543: double func( double *x)
3544: {
1.226 brouard 3545: int i, ii, j, k, mi, d, kk;
3546: int ioffset=0;
3547: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
3548: double **out;
3549: double lli; /* Individual log likelihood */
3550: int s1, s2;
1.228 brouard 3551: 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 3552: double bbh, survp;
3553: long ipmx;
3554: double agexact;
3555: /*extern weight */
3556: /* We are differentiating ll according to initial status */
3557: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3558: /*for(i=1;i<imx;i++)
3559: printf(" %d\n",s[4][i]);
3560: */
1.162 brouard 3561:
1.226 brouard 3562: ++countcallfunc;
1.162 brouard 3563:
1.226 brouard 3564: cov[1]=1.;
1.126 brouard 3565:
1.226 brouard 3566: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3567: ioffset=0;
1.226 brouard 3568: if(mle==1){
3569: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3570: /* Computes the values of the ncovmodel covariates of the model
3571: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
3572: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
3573: to be observed in j being in i according to the model.
3574: */
1.243 brouard 3575: ioffset=2+nagesqr ;
1.233 brouard 3576: /* Fixed */
1.234 brouard 3577: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */
3578: 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)*/
3579: }
1.226 brouard 3580: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
3581: is 6, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]
3582: has been calculated etc */
3583: /* For an individual i, wav[i] gives the number of effective waves */
3584: /* We compute the contribution to Likelihood of each effective transition
3585: mw[mi][i] is real wave of the mi th effectve wave */
3586: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
3587: s2=s[mw[mi+1][i]][i];
3588: And the iv th varying covariate is the cotvar[mw[mi+1][i]][iv][i]
3589: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
3590: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
3591: */
3592: for(mi=1; mi<= wav[i]-1; mi++){
1.234 brouard 3593: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 3594: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
3595: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
1.234 brouard 3596: }
3597: for (ii=1;ii<=nlstate+ndeath;ii++)
3598: for (j=1;j<=nlstate+ndeath;j++){
3599: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3600: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3601: }
3602: for(d=0; d<dh[mi][i]; d++){
3603: newm=savm;
3604: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3605: cov[2]=agexact;
3606: if(nagesqr==1)
3607: cov[3]= agexact*agexact; /* Should be changed here */
3608: for (kk=1; kk<=cptcovage;kk++) {
1.318 ! brouard 3609: if(!FixedV[Tvar[Tage[kk]]])
! 3610: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
! 3611: else
! 3612: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
1.234 brouard 3613: }
3614: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3615: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3616: savm=oldm;
3617: oldm=newm;
3618: } /* end mult */
3619:
3620: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
3621: /* But now since version 0.9 we anticipate for bias at large stepm.
3622: * If stepm is larger than one month (smallest stepm) and if the exact delay
3623: * (in months) between two waves is not a multiple of stepm, we rounded to
3624: * the nearest (and in case of equal distance, to the lowest) interval but now
3625: * we keep into memory the bias bh[mi][i] and also the previous matrix product
3626: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
3627: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 3628: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
3629: * -stepm/2 to stepm/2 .
3630: * For stepm=1 the results are the same as for previous versions of Imach.
3631: * For stepm > 1 the results are less biased than in previous versions.
3632: */
1.234 brouard 3633: s1=s[mw[mi][i]][i];
3634: s2=s[mw[mi+1][i]][i];
3635: bbh=(double)bh[mi][i]/(double)stepm;
3636: /* bias bh is positive if real duration
3637: * is higher than the multiple of stepm and negative otherwise.
3638: */
3639: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
3640: if( s2 > nlstate){
3641: /* i.e. if s2 is a death state and if the date of death is known
3642: then the contribution to the likelihood is the probability to
3643: die between last step unit time and current step unit time,
3644: which is also equal to probability to die before dh
3645: minus probability to die before dh-stepm .
3646: In version up to 0.92 likelihood was computed
3647: as if date of death was unknown. Death was treated as any other
3648: health state: the date of the interview describes the actual state
3649: and not the date of a change in health state. The former idea was
3650: to consider that at each interview the state was recorded
3651: (healthy, disable or death) and IMaCh was corrected; but when we
3652: introduced the exact date of death then we should have modified
3653: the contribution of an exact death to the likelihood. This new
3654: contribution is smaller and very dependent of the step unit
3655: stepm. It is no more the probability to die between last interview
3656: and month of death but the probability to survive from last
3657: interview up to one month before death multiplied by the
3658: probability to die within a month. Thanks to Chris
3659: Jackson for correcting this bug. Former versions increased
3660: mortality artificially. The bad side is that we add another loop
3661: which slows down the processing. The difference can be up to 10%
3662: lower mortality.
3663: */
3664: /* If, at the beginning of the maximization mostly, the
3665: cumulative probability or probability to be dead is
3666: constant (ie = 1) over time d, the difference is equal to
3667: 0. out[s1][3] = savm[s1][3]: probability, being at state
3668: s1 at precedent wave, to be dead a month before current
3669: wave is equal to probability, being at state s1 at
3670: precedent wave, to be dead at mont of the current
3671: wave. Then the observed probability (that this person died)
3672: is null according to current estimated parameter. In fact,
3673: it should be very low but not zero otherwise the log go to
3674: infinity.
3675: */
1.183 brouard 3676: /* #ifdef INFINITYORIGINAL */
3677: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3678: /* #else */
3679: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
3680: /* lli=log(mytinydouble); */
3681: /* else */
3682: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3683: /* #endif */
1.226 brouard 3684: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3685:
1.226 brouard 3686: } else if ( s2==-1 ) { /* alive */
3687: for (j=1,survp=0. ; j<=nlstate; j++)
3688: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3689: /*survp += out[s1][j]; */
3690: lli= log(survp);
3691: }
3692: else if (s2==-4) {
3693: for (j=3,survp=0. ; j<=nlstate; j++)
3694: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3695: lli= log(survp);
3696: }
3697: else if (s2==-5) {
3698: for (j=1,survp=0. ; j<=2; j++)
3699: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3700: lli= log(survp);
3701: }
3702: else{
3703: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3704: /* 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 */
3705: }
3706: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
3707: /*if(lli ==000.0)*/
3708: /*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); */
3709: ipmx +=1;
3710: sw += weight[i];
3711: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3712: /* if (lli < log(mytinydouble)){ */
3713: /* 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); */
3714: /* 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]); */
3715: /* } */
3716: } /* end of wave */
3717: } /* end of individual */
3718: } else if(mle==2){
3719: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3720: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3721: for(mi=1; mi<= wav[i]-1; mi++){
3722: for (ii=1;ii<=nlstate+ndeath;ii++)
3723: for (j=1;j<=nlstate+ndeath;j++){
3724: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3725: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3726: }
3727: for(d=0; d<=dh[mi][i]; d++){
3728: newm=savm;
3729: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3730: cov[2]=agexact;
3731: if(nagesqr==1)
3732: cov[3]= agexact*agexact;
3733: for (kk=1; kk<=cptcovage;kk++) {
3734: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3735: }
3736: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3737: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3738: savm=oldm;
3739: oldm=newm;
3740: } /* end mult */
3741:
3742: s1=s[mw[mi][i]][i];
3743: s2=s[mw[mi+1][i]][i];
3744: bbh=(double)bh[mi][i]/(double)stepm;
3745: 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 */
3746: ipmx +=1;
3747: sw += weight[i];
3748: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3749: } /* end of wave */
3750: } /* end of individual */
3751: } else if(mle==3){ /* exponential inter-extrapolation */
3752: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3753: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3754: for(mi=1; mi<= wav[i]-1; mi++){
3755: for (ii=1;ii<=nlstate+ndeath;ii++)
3756: for (j=1;j<=nlstate+ndeath;j++){
3757: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3758: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3759: }
3760: for(d=0; d<dh[mi][i]; d++){
3761: newm=savm;
3762: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3763: cov[2]=agexact;
3764: if(nagesqr==1)
3765: cov[3]= agexact*agexact;
3766: for (kk=1; kk<=cptcovage;kk++) {
3767: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3768: }
3769: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3770: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3771: savm=oldm;
3772: oldm=newm;
3773: } /* end mult */
3774:
3775: s1=s[mw[mi][i]][i];
3776: s2=s[mw[mi+1][i]][i];
3777: bbh=(double)bh[mi][i]/(double)stepm;
3778: 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 */
3779: ipmx +=1;
3780: sw += weight[i];
3781: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3782: } /* end of wave */
3783: } /* end of individual */
3784: }else if (mle==4){ /* ml=4 no inter-extrapolation */
3785: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3786: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3787: for(mi=1; mi<= wav[i]-1; mi++){
3788: for (ii=1;ii<=nlstate+ndeath;ii++)
3789: for (j=1;j<=nlstate+ndeath;j++){
3790: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3791: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3792: }
3793: for(d=0; d<dh[mi][i]; d++){
3794: newm=savm;
3795: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3796: cov[2]=agexact;
3797: if(nagesqr==1)
3798: cov[3]= agexact*agexact;
3799: for (kk=1; kk<=cptcovage;kk++) {
3800: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3801: }
1.126 brouard 3802:
1.226 brouard 3803: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3804: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3805: savm=oldm;
3806: oldm=newm;
3807: } /* end mult */
3808:
3809: s1=s[mw[mi][i]][i];
3810: s2=s[mw[mi+1][i]][i];
3811: if( s2 > nlstate){
3812: lli=log(out[s1][s2] - savm[s1][s2]);
3813: } else if ( s2==-1 ) { /* alive */
3814: for (j=1,survp=0. ; j<=nlstate; j++)
3815: survp += out[s1][j];
3816: lli= log(survp);
3817: }else{
3818: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3819: }
3820: ipmx +=1;
3821: sw += weight[i];
3822: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.126 brouard 3823: /* 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 3824: } /* end of wave */
3825: } /* end of individual */
3826: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
3827: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3828: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3829: for(mi=1; mi<= wav[i]-1; mi++){
3830: for (ii=1;ii<=nlstate+ndeath;ii++)
3831: for (j=1;j<=nlstate+ndeath;j++){
3832: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3833: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3834: }
3835: for(d=0; d<dh[mi][i]; d++){
3836: newm=savm;
3837: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3838: cov[2]=agexact;
3839: if(nagesqr==1)
3840: cov[3]= agexact*agexact;
3841: for (kk=1; kk<=cptcovage;kk++) {
3842: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3843: }
1.126 brouard 3844:
1.226 brouard 3845: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3846: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3847: savm=oldm;
3848: oldm=newm;
3849: } /* end mult */
3850:
3851: s1=s[mw[mi][i]][i];
3852: s2=s[mw[mi+1][i]][i];
3853: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3854: ipmx +=1;
3855: sw += weight[i];
3856: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3857: /*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]);*/
3858: } /* end of wave */
3859: } /* end of individual */
3860: } /* End of if */
3861: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3862: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3863: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3864: return -l;
1.126 brouard 3865: }
3866:
3867: /*************** log-likelihood *************/
3868: double funcone( double *x)
3869: {
1.228 brouard 3870: /* Same as func but slower because of a lot of printf and if */
1.126 brouard 3871: int i, ii, j, k, mi, d, kk;
1.228 brouard 3872: int ioffset=0;
1.131 brouard 3873: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 3874: double **out;
3875: double lli; /* Individual log likelihood */
3876: double llt;
3877: int s1, s2;
1.228 brouard 3878: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
3879:
1.126 brouard 3880: double bbh, survp;
1.187 brouard 3881: double agexact;
1.214 brouard 3882: double agebegin, ageend;
1.126 brouard 3883: /*extern weight */
3884: /* We are differentiating ll according to initial status */
3885: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3886: /*for(i=1;i<imx;i++)
3887: printf(" %d\n",s[4][i]);
3888: */
3889: cov[1]=1.;
3890:
3891: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3892: ioffset=0;
3893: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.243 brouard 3894: /* ioffset=2+nagesqr+cptcovage; */
3895: ioffset=2+nagesqr;
1.232 brouard 3896: /* Fixed */
1.224 brouard 3897: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 3898: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
1.311 brouard 3899: 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 3900: 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)*/
3901: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
3902: /* cov[2+6]=covar[Tvar[6]][i]; */
3903: /* cov[2+6]=covar[2][i]; V2 */
3904: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
3905: /* cov[2+7]=covar[Tvar[7]][i]; */
3906: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
3907: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
3908: /* cov[2+9]=covar[Tvar[9]][i]; */
3909: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 3910: }
1.232 brouard 3911: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
3912: /* 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?)*\/ */
3913: /* } */
1.231 brouard 3914: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
3915: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
3916: /* } */
1.225 brouard 3917:
1.233 brouard 3918:
3919: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.232 brouard 3920: /* Wave varying (but not age varying) */
3921: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 3922: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
3923: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
3924: }
1.232 brouard 3925: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates (single??)*\/ */
1.242 brouard 3926: /* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3927: /* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; */
3928: /* k=ioffset-2-nagesqr-cptcovage+itv; /\* position in simple model *\/ */
3929: /* cov[ioffset+itv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; */
3930: /* 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 3931: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 3932: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3933: /* /\* 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]); *\/ */
3934: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 3935: /* } */
1.126 brouard 3936: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 3937: for (j=1;j<=nlstate+ndeath;j++){
3938: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3939: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3940: }
1.214 brouard 3941:
3942: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
3943: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
3944: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 3945: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 3946: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
3947: and mw[mi+1][i]. dh depends on stepm.*/
3948: newm=savm;
1.247 brouard 3949: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 3950: cov[2]=agexact;
3951: if(nagesqr==1)
3952: cov[3]= agexact*agexact;
3953: for (kk=1; kk<=cptcovage;kk++) {
3954: if(!FixedV[Tvar[Tage[kk]]])
3955: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3956: else
3957: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
3958: }
3959: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
3960: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3961: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3962: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3963: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
3964: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
3965: savm=oldm;
3966: oldm=newm;
1.126 brouard 3967: } /* end mult */
3968:
3969: s1=s[mw[mi][i]][i];
3970: s2=s[mw[mi+1][i]][i];
1.217 brouard 3971: /* if(s2==-1){ */
1.268 brouard 3972: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 3973: /* /\* exit(1); *\/ */
3974: /* } */
1.126 brouard 3975: bbh=(double)bh[mi][i]/(double)stepm;
3976: /* bias is positive if real duration
3977: * is higher than the multiple of stepm and negative otherwise.
3978: */
3979: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 3980: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3981: } else if ( s2==-1 ) { /* alive */
1.242 brouard 3982: for (j=1,survp=0. ; j<=nlstate; j++)
3983: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3984: lli= log(survp);
1.126 brouard 3985: }else if (mle==1){
1.242 brouard 3986: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 3987: } else if(mle==2){
1.242 brouard 3988: 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 3989: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 3990: 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 3991: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 3992: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 3993: } else{ /* mle=0 back to 1 */
1.242 brouard 3994: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3995: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 3996: } /* End of if */
3997: ipmx +=1;
3998: sw += weight[i];
3999: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.132 brouard 4000: /*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 4001: if(globpr){
1.246 brouard 4002: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 4003: %11.6f %11.6f %11.6f ", \
1.242 brouard 4004: 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 4005: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.242 brouard 4006: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
4007: llt +=ll[k]*gipmx/gsw;
4008: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
4009: }
4010: fprintf(ficresilk," %10.6f\n", -llt);
1.126 brouard 4011: }
1.232 brouard 4012: } /* end of wave */
4013: } /* end of individual */
4014: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
4015: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
4016: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
4017: if(globpr==0){ /* First time we count the contributions and weights */
4018: gipmx=ipmx;
4019: gsw=sw;
4020: }
4021: return -l;
1.126 brouard 4022: }
4023:
4024:
4025: /*************** function likelione ***********/
1.292 brouard 4026: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*func)(double []))
1.126 brouard 4027: {
4028: /* This routine should help understanding what is done with
4029: the selection of individuals/waves and
4030: to check the exact contribution to the likelihood.
4031: Plotting could be done.
4032: */
4033: int k;
4034:
4035: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 4036: strcpy(fileresilk,"ILK_");
1.202 brouard 4037: strcat(fileresilk,fileresu);
1.126 brouard 4038: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
4039: printf("Problem with resultfile: %s\n", fileresilk);
4040: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
4041: }
1.214 brouard 4042: 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");
4043: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 4044: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
4045: for(k=1; k<=nlstate; k++)
4046: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
4047: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total)\n");
4048: }
4049:
1.292 brouard 4050: *fretone=(*func)(p);
1.126 brouard 4051: if(*globpri !=0){
4052: fclose(ficresilk);
1.205 brouard 4053: if (mle ==0)
4054: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
4055: else if(mle >=1)
4056: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
4057: 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 4058: fprintf(fichtm,"\n<br>Equation of the model: <b>model=1+age+%s</b><br>\n",model);
1.208 brouard 4059:
4060: for (k=1; k<= nlstate ; k++) {
1.211 brouard 4061: 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 4062: <img src=\"%s-p%dj.png\">",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
4063: }
1.207 brouard 4064: 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 4065: <img src=\"%s-ori.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 4066: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.204 brouard 4067: <img src=\"%s-dest.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 4068: fflush(fichtm);
1.205 brouard 4069: }
1.126 brouard 4070: return;
4071: }
4072:
4073:
4074: /*********** Maximum Likelihood Estimation ***************/
4075:
4076: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
4077: {
1.165 brouard 4078: int i,j, iter=0;
1.126 brouard 4079: double **xi;
4080: double fret;
4081: double fretone; /* Only one call to likelihood */
4082: /* char filerespow[FILENAMELENGTH];*/
1.162 brouard 4083:
4084: #ifdef NLOPT
4085: int creturn;
4086: nlopt_opt opt;
4087: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
4088: double *lb;
4089: double minf; /* the minimum objective value, upon return */
4090: double * p1; /* Shifted parameters from 0 instead of 1 */
4091: myfunc_data dinst, *d = &dinst;
4092: #endif
4093:
4094:
1.126 brouard 4095: xi=matrix(1,npar,1,npar);
4096: for (i=1;i<=npar;i++)
4097: for (j=1;j<=npar;j++)
4098: xi[i][j]=(i==j ? 1.0 : 0.0);
4099: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 4100: strcpy(filerespow,"POW_");
1.126 brouard 4101: strcat(filerespow,fileres);
4102: if((ficrespow=fopen(filerespow,"w"))==NULL) {
4103: printf("Problem with resultfile: %s\n", filerespow);
4104: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
4105: }
4106: fprintf(ficrespow,"# Powell\n# iter -2*LL");
4107: for (i=1;i<=nlstate;i++)
4108: for(j=1;j<=nlstate+ndeath;j++)
4109: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
4110: fprintf(ficrespow,"\n");
1.162 brouard 4111: #ifdef POWELL
1.126 brouard 4112: powell(p,xi,npar,ftol,&iter,&fret,func);
1.162 brouard 4113: #endif
1.126 brouard 4114:
1.162 brouard 4115: #ifdef NLOPT
4116: #ifdef NEWUOA
4117: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
4118: #else
4119: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
4120: #endif
4121: lb=vector(0,npar-1);
4122: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
4123: nlopt_set_lower_bounds(opt, lb);
4124: nlopt_set_initial_step1(opt, 0.1);
4125:
4126: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
4127: d->function = func;
4128: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
4129: nlopt_set_min_objective(opt, myfunc, d);
4130: nlopt_set_xtol_rel(opt, ftol);
4131: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
4132: printf("nlopt failed! %d\n",creturn);
4133: }
4134: else {
4135: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
4136: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
4137: iter=1; /* not equal */
4138: }
4139: nlopt_destroy(opt);
4140: #endif
1.126 brouard 4141: free_matrix(xi,1,npar,1,npar);
4142: fclose(ficrespow);
1.203 brouard 4143: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
4144: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 4145: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 4146:
4147: }
4148:
4149: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 4150: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 4151: {
4152: double **a,**y,*x,pd;
1.203 brouard 4153: /* double **hess; */
1.164 brouard 4154: int i, j;
1.126 brouard 4155: int *indx;
4156:
4157: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 4158: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 4159: void lubksb(double **a, int npar, int *indx, double b[]) ;
4160: void ludcmp(double **a, int npar, int *indx, double *d) ;
4161: double gompertz(double p[]);
1.203 brouard 4162: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 4163:
4164: printf("\nCalculation of the hessian matrix. Wait...\n");
4165: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
4166: for (i=1;i<=npar;i++){
1.203 brouard 4167: printf("%d-",i);fflush(stdout);
4168: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 4169:
4170: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
4171:
4172: /* printf(" %f ",p[i]);
4173: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
4174: }
4175:
4176: for (i=1;i<=npar;i++) {
4177: for (j=1;j<=npar;j++) {
4178: if (j>i) {
1.203 brouard 4179: printf(".%d-%d",i,j);fflush(stdout);
4180: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
4181: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 4182:
4183: hess[j][i]=hess[i][j];
4184: /*printf(" %lf ",hess[i][j]);*/
4185: }
4186: }
4187: }
4188: printf("\n");
4189: fprintf(ficlog,"\n");
4190:
4191: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
4192: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
4193:
4194: a=matrix(1,npar,1,npar);
4195: y=matrix(1,npar,1,npar);
4196: x=vector(1,npar);
4197: indx=ivector(1,npar);
4198: for (i=1;i<=npar;i++)
4199: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
4200: ludcmp(a,npar,indx,&pd);
4201:
4202: for (j=1;j<=npar;j++) {
4203: for (i=1;i<=npar;i++) x[i]=0;
4204: x[j]=1;
4205: lubksb(a,npar,indx,x);
4206: for (i=1;i<=npar;i++){
4207: matcov[i][j]=x[i];
4208: }
4209: }
4210:
4211: printf("\n#Hessian matrix#\n");
4212: fprintf(ficlog,"\n#Hessian matrix#\n");
4213: for (i=1;i<=npar;i++) {
4214: for (j=1;j<=npar;j++) {
1.203 brouard 4215: printf("%.6e ",hess[i][j]);
4216: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 4217: }
4218: printf("\n");
4219: fprintf(ficlog,"\n");
4220: }
4221:
1.203 brouard 4222: /* printf("\n#Covariance matrix#\n"); */
4223: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
4224: /* for (i=1;i<=npar;i++) { */
4225: /* for (j=1;j<=npar;j++) { */
4226: /* printf("%.6e ",matcov[i][j]); */
4227: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
4228: /* } */
4229: /* printf("\n"); */
4230: /* fprintf(ficlog,"\n"); */
4231: /* } */
4232:
1.126 brouard 4233: /* Recompute Inverse */
1.203 brouard 4234: /* for (i=1;i<=npar;i++) */
4235: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
4236: /* ludcmp(a,npar,indx,&pd); */
4237:
4238: /* printf("\n#Hessian matrix recomputed#\n"); */
4239:
4240: /* for (j=1;j<=npar;j++) { */
4241: /* for (i=1;i<=npar;i++) x[i]=0; */
4242: /* x[j]=1; */
4243: /* lubksb(a,npar,indx,x); */
4244: /* for (i=1;i<=npar;i++){ */
4245: /* y[i][j]=x[i]; */
4246: /* printf("%.3e ",y[i][j]); */
4247: /* fprintf(ficlog,"%.3e ",y[i][j]); */
4248: /* } */
4249: /* printf("\n"); */
4250: /* fprintf(ficlog,"\n"); */
4251: /* } */
4252:
4253: /* Verifying the inverse matrix */
4254: #ifdef DEBUGHESS
4255: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 4256:
1.203 brouard 4257: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
4258: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 4259:
4260: for (j=1;j<=npar;j++) {
4261: for (i=1;i<=npar;i++){
1.203 brouard 4262: printf("%.2f ",y[i][j]);
4263: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 4264: }
4265: printf("\n");
4266: fprintf(ficlog,"\n");
4267: }
1.203 brouard 4268: #endif
1.126 brouard 4269:
4270: free_matrix(a,1,npar,1,npar);
4271: free_matrix(y,1,npar,1,npar);
4272: free_vector(x,1,npar);
4273: free_ivector(indx,1,npar);
1.203 brouard 4274: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 4275:
4276:
4277: }
4278:
4279: /*************** hessian matrix ****************/
4280: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 4281: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 4282: int i;
4283: int l=1, lmax=20;
1.203 brouard 4284: double k1,k2, res, fx;
1.132 brouard 4285: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 4286: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
4287: int k=0,kmax=10;
4288: double l1;
4289:
4290: fx=func(x);
4291: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 4292: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 4293: l1=pow(10,l);
4294: delts=delt;
4295: for(k=1 ; k <kmax; k=k+1){
4296: delt = delta*(l1*k);
4297: p2[theta]=x[theta] +delt;
1.145 brouard 4298: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 4299: p2[theta]=x[theta]-delt;
4300: k2=func(p2)-fx;
4301: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 4302: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 4303:
1.203 brouard 4304: #ifdef DEBUGHESSII
1.126 brouard 4305: 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);
4306: 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);
4307: #endif
4308: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
4309: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
4310: k=kmax;
4311: }
4312: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 4313: k=kmax; l=lmax*10;
1.126 brouard 4314: }
4315: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
4316: delts=delt;
4317: }
1.203 brouard 4318: } /* End loop k */
1.126 brouard 4319: }
4320: delti[theta]=delts;
4321: return res;
4322:
4323: }
4324:
1.203 brouard 4325: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 4326: {
4327: int i;
1.164 brouard 4328: int l=1, lmax=20;
1.126 brouard 4329: double k1,k2,k3,k4,res,fx;
1.132 brouard 4330: double p2[MAXPARM+1];
1.203 brouard 4331: int k, kmax=1;
4332: double v1, v2, cv12, lc1, lc2;
1.208 brouard 4333:
4334: int firstime=0;
1.203 brouard 4335:
1.126 brouard 4336: fx=func(x);
1.203 brouard 4337: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 4338: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 4339: p2[thetai]=x[thetai]+delti[thetai]*k;
4340: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4341: k1=func(p2)-fx;
4342:
1.203 brouard 4343: p2[thetai]=x[thetai]+delti[thetai]*k;
4344: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4345: k2=func(p2)-fx;
4346:
1.203 brouard 4347: p2[thetai]=x[thetai]-delti[thetai]*k;
4348: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4349: k3=func(p2)-fx;
4350:
1.203 brouard 4351: p2[thetai]=x[thetai]-delti[thetai]*k;
4352: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4353: k4=func(p2)-fx;
1.203 brouard 4354: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
4355: if(k1*k2*k3*k4 <0.){
1.208 brouard 4356: firstime=1;
1.203 brouard 4357: kmax=kmax+10;
1.208 brouard 4358: }
4359: if(kmax >=10 || firstime ==1){
1.246 brouard 4360: 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);
4361: 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 4362: 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);
4363: 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);
4364: }
4365: #ifdef DEBUGHESSIJ
4366: v1=hess[thetai][thetai];
4367: v2=hess[thetaj][thetaj];
4368: cv12=res;
4369: /* Computing eigen value of Hessian matrix */
4370: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4371: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4372: if ((lc2 <0) || (lc1 <0) ){
4373: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4374: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4375: 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);
4376: 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);
4377: }
1.126 brouard 4378: #endif
4379: }
4380: return res;
4381: }
4382:
1.203 brouard 4383: /* Not done yet: Was supposed to fix if not exactly at the maximum */
4384: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
4385: /* { */
4386: /* int i; */
4387: /* int l=1, lmax=20; */
4388: /* double k1,k2,k3,k4,res,fx; */
4389: /* double p2[MAXPARM+1]; */
4390: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
4391: /* int k=0,kmax=10; */
4392: /* double l1; */
4393:
4394: /* fx=func(x); */
4395: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
4396: /* l1=pow(10,l); */
4397: /* delts=delt; */
4398: /* for(k=1 ; k <kmax; k=k+1){ */
4399: /* delt = delti*(l1*k); */
4400: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
4401: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4402: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4403: /* k1=func(p2)-fx; */
4404:
4405: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4406: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4407: /* k2=func(p2)-fx; */
4408:
4409: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4410: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4411: /* k3=func(p2)-fx; */
4412:
4413: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4414: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4415: /* k4=func(p2)-fx; */
4416: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
4417: /* #ifdef DEBUGHESSIJ */
4418: /* 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); */
4419: /* 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); */
4420: /* #endif */
4421: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
4422: /* k=kmax; */
4423: /* } */
4424: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
4425: /* k=kmax; l=lmax*10; */
4426: /* } */
4427: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
4428: /* delts=delt; */
4429: /* } */
4430: /* } /\* End loop k *\/ */
4431: /* } */
4432: /* delti[theta]=delts; */
4433: /* return res; */
4434: /* } */
4435:
4436:
1.126 brouard 4437: /************** Inverse of matrix **************/
4438: void ludcmp(double **a, int n, int *indx, double *d)
4439: {
4440: int i,imax,j,k;
4441: double big,dum,sum,temp;
4442: double *vv;
4443:
4444: vv=vector(1,n);
4445: *d=1.0;
4446: for (i=1;i<=n;i++) {
4447: big=0.0;
4448: for (j=1;j<=n;j++)
4449: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 4450: if (big == 0.0){
4451: printf(" Singular Hessian matrix at row %d:\n",i);
4452: for (j=1;j<=n;j++) {
4453: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
4454: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
4455: }
4456: fflush(ficlog);
4457: fclose(ficlog);
4458: nrerror("Singular matrix in routine ludcmp");
4459: }
1.126 brouard 4460: vv[i]=1.0/big;
4461: }
4462: for (j=1;j<=n;j++) {
4463: for (i=1;i<j;i++) {
4464: sum=a[i][j];
4465: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
4466: a[i][j]=sum;
4467: }
4468: big=0.0;
4469: for (i=j;i<=n;i++) {
4470: sum=a[i][j];
4471: for (k=1;k<j;k++)
4472: sum -= a[i][k]*a[k][j];
4473: a[i][j]=sum;
4474: if ( (dum=vv[i]*fabs(sum)) >= big) {
4475: big=dum;
4476: imax=i;
4477: }
4478: }
4479: if (j != imax) {
4480: for (k=1;k<=n;k++) {
4481: dum=a[imax][k];
4482: a[imax][k]=a[j][k];
4483: a[j][k]=dum;
4484: }
4485: *d = -(*d);
4486: vv[imax]=vv[j];
4487: }
4488: indx[j]=imax;
4489: if (a[j][j] == 0.0) a[j][j]=TINY;
4490: if (j != n) {
4491: dum=1.0/(a[j][j]);
4492: for (i=j+1;i<=n;i++) a[i][j] *= dum;
4493: }
4494: }
4495: free_vector(vv,1,n); /* Doesn't work */
4496: ;
4497: }
4498:
4499: void lubksb(double **a, int n, int *indx, double b[])
4500: {
4501: int i,ii=0,ip,j;
4502: double sum;
4503:
4504: for (i=1;i<=n;i++) {
4505: ip=indx[i];
4506: sum=b[ip];
4507: b[ip]=b[i];
4508: if (ii)
4509: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
4510: else if (sum) ii=i;
4511: b[i]=sum;
4512: }
4513: for (i=n;i>=1;i--) {
4514: sum=b[i];
4515: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
4516: b[i]=sum/a[i][i];
4517: }
4518: }
4519:
4520: void pstamp(FILE *fichier)
4521: {
1.196 brouard 4522: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 4523: }
4524:
1.297 brouard 4525: void date2dmy(double date,double *day, double *month, double *year){
4526: double yp=0., yp1=0., yp2=0.;
4527:
4528: yp1=modf(date,&yp);/* extracts integral of date in yp and
4529: fractional in yp1 */
4530: *year=yp;
4531: yp2=modf((yp1*12),&yp);
4532: *month=yp;
4533: yp1=modf((yp2*30.5),&yp);
4534: *day=yp;
4535: if(*day==0) *day=1;
4536: if(*month==0) *month=1;
4537: }
4538:
1.253 brouard 4539:
4540:
1.126 brouard 4541: /************ Frequencies ********************/
1.251 brouard 4542: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 4543: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
4544: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 4545: { /* Some frequencies as well as proposing some starting values */
1.226 brouard 4546:
1.265 brouard 4547: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 4548: int iind=0, iage=0;
4549: int mi; /* Effective wave */
4550: int first;
4551: double ***freq; /* Frequencies */
1.268 brouard 4552: 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 */
4553: 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 4554: double *meanq, *stdq, *idq;
1.226 brouard 4555: double **meanqt;
4556: double *pp, **prop, *posprop, *pospropt;
4557: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
4558: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
4559: double agebegin, ageend;
4560:
4561: pp=vector(1,nlstate);
1.251 brouard 4562: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4563: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
4564: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
4565: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
4566: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.284 brouard 4567: stdq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.283 brouard 4568: idq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.226 brouard 4569: meanqt=matrix(1,lastpass,1,nqtveff);
4570: strcpy(fileresp,"P_");
4571: strcat(fileresp,fileresu);
4572: /*strcat(fileresphtm,fileresu);*/
4573: if((ficresp=fopen(fileresp,"w"))==NULL) {
4574: printf("Problem with prevalence resultfile: %s\n", fileresp);
4575: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
4576: exit(0);
4577: }
1.240 brouard 4578:
1.226 brouard 4579: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
4580: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
4581: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4582: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4583: fflush(ficlog);
4584: exit(70);
4585: }
4586: else{
4587: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 4588: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4589: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4590: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4591: }
1.237 brouard 4592: fprintf(ficresphtm,"Current page is file <a href=\"%s\">%s</a><br>\n\n<h4>Frequencies and prevalence by age at begin of transition and dummy covariate value at beginning of transition</h4>\n",fileresphtm, fileresphtm);
1.240 brouard 4593:
1.226 brouard 4594: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
4595: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
4596: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4597: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4598: fflush(ficlog);
4599: exit(70);
1.240 brouard 4600: } else{
1.226 brouard 4601: fprintf(ficresphtmfr,"<html><head>\n<title>IMaCh PHTM_Frequency table %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 4602: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4603: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4604: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4605: }
1.240 brouard 4606: fprintf(ficresphtmfr,"Current page is file <a href=\"%s\">%s</a><br>\n\n<h4>Frequencies of all effective transitions of the model, by age at begin of transition, and covariate value at the begin of transition (if the covariate is a varying covariate) </h4>Unknown status is -1<br/>\n",fileresphtmfr, fileresphtmfr);
4607:
1.253 brouard 4608: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
4609: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 4610: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4611: j1=0;
1.126 brouard 4612:
1.227 brouard 4613: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
4614: j=cptcoveff; /* Only dummy covariates of the model */
1.226 brouard 4615: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 4616:
4617:
1.226 brouard 4618: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
4619: reference=low_education V1=0,V2=0
4620: med_educ V1=1 V2=0,
4621: high_educ V1=0 V2=1
4622: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcoveff
4623: */
1.249 brouard 4624: dateintsum=0;
4625: k2cpt=0;
4626:
1.253 brouard 4627: if(cptcoveff == 0 )
1.265 brouard 4628: nl=1; /* Constant and age model only */
1.253 brouard 4629: else
4630: nl=2;
1.265 brouard 4631:
4632: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
4633: /* Loop on nj=1 or 2 if dummy covariates j!=0
4634: * Loop on j1(1 to 2**cptcoveff) covariate combination
4635: * freq[s1][s2][iage] =0.
4636: * Loop on iind
4637: * ++freq[s1][s2][iage] weighted
4638: * end iind
4639: * if covariate and j!0
4640: * headers Variable on one line
4641: * endif cov j!=0
4642: * header of frequency table by age
4643: * Loop on age
4644: * pp[s1]+=freq[s1][s2][iage] weighted
4645: * pos+=freq[s1][s2][iage] weighted
4646: * Loop on s1 initial state
4647: * fprintf(ficresp
4648: * end s1
4649: * end age
4650: * if j!=0 computes starting values
4651: * end compute starting values
4652: * end j1
4653: * end nl
4654: */
1.253 brouard 4655: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
4656: if(nj==1)
4657: j=0; /* First pass for the constant */
1.265 brouard 4658: else{
1.253 brouard 4659: j=cptcoveff; /* Other passes for the covariate values */
1.265 brouard 4660: }
1.251 brouard 4661: first=1;
1.265 brouard 4662: 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 4663: posproptt=0.;
4664: /*printf("cptcoveff=%d Tvaraff=%d", cptcoveff,Tvaraff[1]);
4665: scanf("%d", i);*/
4666: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 4667: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 4668: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 4669: freq[i][s2][m]=0;
1.251 brouard 4670:
4671: for (i=1; i<=nlstate; i++) {
1.240 brouard 4672: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 4673: prop[i][m]=0;
4674: posprop[i]=0;
4675: pospropt[i]=0;
4676: }
1.283 brouard 4677: for (z1=1; z1<= nqfveff; z1++) { /* zeroing for each combination j1 as well as for the total */
1.284 brouard 4678: idq[z1]=0.;
4679: meanq[z1]=0.;
4680: stdq[z1]=0.;
1.283 brouard 4681: }
4682: /* for (z1=1; z1<= nqtveff; z1++) { */
1.251 brouard 4683: /* for(m=1;m<=lastpass;m++){ */
1.283 brouard 4684: /* meanqt[m][z1]=0.; */
4685: /* } */
4686: /* } */
1.251 brouard 4687: /* dateintsum=0; */
4688: /* k2cpt=0; */
4689:
1.265 brouard 4690: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 4691: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
4692: bool=1;
4693: if(j !=0){
4694: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
4695: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
4696: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
4697: /* if(Tvaraff[z1] ==-20){ */
4698: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
4699: /* }else if(Tvaraff[z1] ==-10){ */
4700: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
4701: /* }else */
4702: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]){ /* for combination j1 of covariates */
1.265 brouard 4703: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 4704: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
4705: /* 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",
4706: bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),
4707: j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
4708: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
4709: } /* Onlyf fixed */
4710: } /* end z1 */
4711: } /* cptcovn > 0 */
4712: } /* end any */
4713: }/* end j==0 */
1.265 brouard 4714: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 4715: /* for(m=firstpass; m<=lastpass; m++){ */
1.284 brouard 4716: for(mi=1; mi<wav[iind];mi++){ /* For each wave */
1.251 brouard 4717: m=mw[mi][iind];
4718: if(j!=0){
4719: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
4720: for (z1=1; z1<=cptcoveff; z1++) {
4721: if( Fixed[Tmodelind[z1]]==1){
4722: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
4723: if (cotvar[m][iv][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality. If covariate's
4724: value is -1, we don't select. It differs from the
4725: constant and age model which counts them. */
4726: bool=0; /* not selected */
4727: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
4728: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
4729: bool=0;
4730: }
4731: }
4732: }
4733: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
4734: } /* end j==0 */
4735: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
1.284 brouard 4736: if(bool==1){ /*Selected */
1.251 brouard 4737: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
4738: and mw[mi+1][iind]. dh depends on stepm. */
4739: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
4740: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
4741: if(m >=firstpass && m <=lastpass){
4742: k2=anint[m][iind]+(mint[m][iind]/12.);
4743: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
4744: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
4745: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
4746: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
4747: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
4748: if (m<lastpass) {
4749: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
4750: /* 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]); */
4751: if(s[m][iind]==-1)
4752: 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.));
4753: 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 4754: for (z1=1; z1<= nqfveff; z1++) { /* Quantitative variables, calculating mean on known values only */
4755: if(!isnan(covar[ncovcol+z1][iind])){
4756: idq[z1]=idq[z1]+weight[iind];
4757: meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /* Computes mean of quantitative with selected filter */
4758: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; *//*error*/
4759: stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]; /* *weight[iind];*/ /* Computes mean of quantitative with selected filter */
4760: }
1.284 brouard 4761: }
1.251 brouard 4762: /* if((int)agev[m][iind] == 55) */
4763: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
4764: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
4765: 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 4766: }
1.251 brouard 4767: } /* end if between passes */
4768: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
4769: dateintsum=dateintsum+k2; /* on all covariates ?*/
4770: k2cpt++;
4771: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 4772: }
1.251 brouard 4773: }else{
4774: bool=1;
4775: }/* end bool 2 */
4776: } /* end m */
1.284 brouard 4777: /* for (z1=1; z1<= nqfveff; z1++) { /\* Quantitative variables, calculating mean *\/ */
4778: /* idq[z1]=idq[z1]+weight[iind]; */
4779: /* meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /\* Computes mean of quantitative with selected filter *\/ */
4780: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /\* *weight[iind];*\/ /\* Computes mean of quantitative with selected filter *\/ */
4781: /* } */
1.251 brouard 4782: } /* end bool */
4783: } /* end iind = 1 to imx */
4784: /* prop[s][age] is feeded for any initial and valid live state as well as
4785: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
4786:
4787:
4788: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.265 brouard 4789: if(cptcoveff==0 && nj==1) /* no covariate and first pass */
4790: pstamp(ficresp);
1.251 brouard 4791: if (cptcoveff>0 && j!=0){
1.265 brouard 4792: pstamp(ficresp);
1.251 brouard 4793: printf( "\n#********** Variable ");
4794: fprintf(ficresp, "\n#********** Variable ");
4795: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
4796: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
4797: fprintf(ficlog, "\n#********** Variable ");
4798: for (z1=1; z1<=cptcoveff; z1++){
4799: if(!FixedV[Tvaraff[z1]]){
4800: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4801: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4802: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4803: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4804: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.250 brouard 4805: }else{
1.251 brouard 4806: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4807: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4808: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4809: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4810: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4811: }
4812: }
4813: printf( "**********\n#");
4814: fprintf(ficresp, "**********\n#");
4815: fprintf(ficresphtm, "**********</h3>\n");
4816: fprintf(ficresphtmfr, "**********</h3>\n");
4817: fprintf(ficlog, "**********\n");
4818: }
1.284 brouard 4819: /*
4820: Printing means of quantitative variables if any
4821: */
4822: for (z1=1; z1<= nqfveff; z1++) {
1.311 brouard 4823: fprintf(ficlog,"Mean of fixed quantitative variable V%d on %.3g (weighted) individuals sum=%f", ncovcol+z1, idq[z1], meanq[z1]);
1.312 brouard 4824: fprintf(ficlog,", mean=%.3g\n",meanq[z1]/idq[z1]);
1.284 brouard 4825: if(weightopt==1){
4826: printf(" Weighted mean and standard deviation of");
4827: fprintf(ficlog," Weighted mean and standard deviation of");
4828: fprintf(ficresphtmfr," Weighted mean and standard deviation of");
4829: }
1.311 brouard 4830: /* mu = \frac{w x}{\sum w}
4831: var = \frac{\sum w (x-mu)^2}{\sum w} = \frac{w x^2}{\sum w} - mu^2
4832: */
4833: 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]));
4834: 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]));
4835: 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 4836: }
4837: /* for (z1=1; z1<= nqtveff; z1++) { */
4838: /* for(m=1;m<=lastpass;m++){ */
4839: /* fprintf(ficresphtmfr,"V quantitative id %d, pass id=%d, mean=%f<p>\n", z1, m, meanqt[m][z1]); */
4840: /* } */
4841: /* } */
1.283 brouard 4842:
1.251 brouard 4843: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.265 brouard 4844: if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
4845: fprintf(ficresp, " Age");
4846: 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 4847: for(i=1; i<=nlstate;i++) {
1.265 brouard 4848: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 4849: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
4850: }
1.265 brouard 4851: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 4852: fprintf(ficresphtm, "\n");
4853:
4854: /* Header of frequency table by age */
4855: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
4856: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 4857: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 4858: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 4859: if(s2!=0 && m!=0)
4860: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 4861: }
1.226 brouard 4862: }
1.251 brouard 4863: fprintf(ficresphtmfr, "\n");
4864:
4865: /* For each age */
4866: for(iage=iagemin; iage <= iagemax+3; iage++){
4867: fprintf(ficresphtm,"<tr>");
4868: if(iage==iagemax+1){
4869: fprintf(ficlog,"1");
4870: fprintf(ficresphtmfr,"<tr><th>0</th> ");
4871: }else if(iage==iagemax+2){
4872: fprintf(ficlog,"0");
4873: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
4874: }else if(iage==iagemax+3){
4875: fprintf(ficlog,"Total");
4876: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
4877: }else{
1.240 brouard 4878: if(first==1){
1.251 brouard 4879: first=0;
4880: printf("See log file for details...\n");
4881: }
4882: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
4883: fprintf(ficlog,"Age %d", iage);
4884: }
1.265 brouard 4885: for(s1=1; s1 <=nlstate ; s1++){
4886: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
4887: pp[s1] += freq[s1][m][iage];
1.251 brouard 4888: }
1.265 brouard 4889: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 4890: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 4891: pos += freq[s1][m][iage];
4892: if(pp[s1]>=1.e-10){
1.251 brouard 4893: if(first==1){
1.265 brouard 4894: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 4895: }
1.265 brouard 4896: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 4897: }else{
4898: if(first==1)
1.265 brouard 4899: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
4900: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 4901: }
4902: }
4903:
1.265 brouard 4904: for(s1=1; s1 <=nlstate ; s1++){
4905: /* posprop[s1]=0; */
4906: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
4907: pp[s1] += freq[s1][m][iage];
4908: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
4909:
4910: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
4911: pos += pp[s1]; /* pos is the total number of transitions until this age */
4912: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
4913: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
4914: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
4915: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
4916: }
4917:
4918: /* Writing ficresp */
4919: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
4920: if( iage <= iagemax){
4921: fprintf(ficresp," %d",iage);
4922: }
4923: }else if( nj==2){
4924: if( iage <= iagemax){
4925: fprintf(ficresp," %d",iage);
4926: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4927: }
1.240 brouard 4928: }
1.265 brouard 4929: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 4930: if(pos>=1.e-5){
1.251 brouard 4931: if(first==1)
1.265 brouard 4932: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
4933: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 4934: }else{
4935: if(first==1)
1.265 brouard 4936: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
4937: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 4938: }
4939: if( iage <= iagemax){
4940: if(pos>=1.e-5){
1.265 brouard 4941: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
4942: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4943: }else if( nj==2){
4944: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4945: }
4946: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4947: /*probs[iage][s1][j1]= pp[s1]/pos;*/
4948: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
4949: } else{
4950: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
4951: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 4952: }
1.240 brouard 4953: }
1.265 brouard 4954: pospropt[s1] +=posprop[s1];
4955: } /* end loop s1 */
1.251 brouard 4956: /* pospropt=0.; */
1.265 brouard 4957: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 4958: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 4959: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 4960: if(first==1){
1.265 brouard 4961: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 4962: }
1.265 brouard 4963: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
4964: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 4965: }
1.265 brouard 4966: if(s1!=0 && m!=0)
4967: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 4968: }
1.265 brouard 4969: } /* end loop s1 */
1.251 brouard 4970: posproptt=0.;
1.265 brouard 4971: for(s1=1; s1 <=nlstate; s1++){
4972: posproptt += pospropt[s1];
1.251 brouard 4973: }
4974: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 4975: fprintf(ficresphtm,"</tr>\n");
4976: if((cptcoveff==0 && nj==1)|| nj==2 ) {
4977: if(iage <= iagemax)
4978: fprintf(ficresp,"\n");
1.240 brouard 4979: }
1.251 brouard 4980: if(first==1)
4981: printf("Others in log...\n");
4982: fprintf(ficlog,"\n");
4983: } /* end loop age iage */
1.265 brouard 4984:
1.251 brouard 4985: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 4986: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 4987: if(posproptt < 1.e-5){
1.265 brouard 4988: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 4989: }else{
1.265 brouard 4990: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 4991: }
1.226 brouard 4992: }
1.251 brouard 4993: fprintf(ficresphtm,"</tr>\n");
4994: fprintf(ficresphtm,"</table>\n");
4995: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 4996: if(posproptt < 1.e-5){
1.251 brouard 4997: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
4998: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 4999: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
5000: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 5001: invalidvarcomb[j1]=1;
1.226 brouard 5002: }else{
1.251 brouard 5003: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced.</p>",j1);
5004: invalidvarcomb[j1]=0;
1.226 brouard 5005: }
1.251 brouard 5006: fprintf(ficresphtmfr,"</table>\n");
5007: fprintf(ficlog,"\n");
5008: if(j!=0){
5009: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 5010: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5011: for(k=1; k <=(nlstate+ndeath); k++){
5012: if (k != i) {
1.265 brouard 5013: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 5014: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 5015: if(j1==1){ /* All dummy covariates to zero */
5016: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
5017: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 5018: printf("%d%d ",i,k);
5019: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5020: 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]));
5021: 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]));
5022: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 5023: }
1.253 brouard 5024: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
5025: for(iage=iagemin; iage <= iagemax+3; iage++){
5026: x[iage]= (double)iage;
5027: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 5028: /* 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 5029: }
1.268 brouard 5030: /* Some are not finite, but linreg will ignore these ages */
5031: no=0;
1.253 brouard 5032: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 5033: pstart[s1]=b;
5034: pstart[s1-1]=a;
1.252 brouard 5035: }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 */
5036: 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]);
5037: 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 5038: 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 5039: printf("%d%d ",i,k);
5040: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5041: 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 5042: }else{ /* Other cases, like quantitative fixed or varying covariates */
5043: ;
5044: }
5045: /* printf("%12.7f )", param[i][jj][k]); */
5046: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5047: s1++;
1.251 brouard 5048: } /* end jj */
5049: } /* end k!= i */
5050: } /* end k */
1.265 brouard 5051: } /* end i, s1 */
1.251 brouard 5052: } /* end j !=0 */
5053: } /* end selected combination of covariate j1 */
5054: if(j==0){ /* We can estimate starting values from the occurences in each case */
5055: printf("#Freqsummary: Starting values for the constants:\n");
5056: fprintf(ficlog,"\n");
1.265 brouard 5057: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5058: for(k=1; k <=(nlstate+ndeath); k++){
5059: if (k != i) {
5060: printf("%d%d ",i,k);
5061: fprintf(ficlog,"%d%d ",i,k);
5062: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 5063: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 5064: if(jj==1){ /* Age has to be done */
1.265 brouard 5065: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
5066: 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]));
5067: 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 5068: }
5069: /* printf("%12.7f )", param[i][jj][k]); */
5070: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5071: s1++;
1.250 brouard 5072: }
1.251 brouard 5073: printf("\n");
5074: fprintf(ficlog,"\n");
1.250 brouard 5075: }
5076: }
1.284 brouard 5077: } /* end of state i */
1.251 brouard 5078: printf("#Freqsummary\n");
5079: fprintf(ficlog,"\n");
1.265 brouard 5080: for(s1=-1; s1 <=nlstate+ndeath; s1++){
5081: for(s2=-1; s2 <=nlstate+ndeath; s2++){
5082: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
5083: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
5084: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
5085: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
5086: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
5087: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 5088: /* } */
5089: }
1.265 brouard 5090: } /* end loop s1 */
1.251 brouard 5091:
5092: printf("\n");
5093: fprintf(ficlog,"\n");
5094: } /* end j=0 */
1.249 brouard 5095: } /* end j */
1.252 brouard 5096:
1.253 brouard 5097: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 5098: for(i=1, jk=1; i <=nlstate; i++){
5099: for(j=1; j <=nlstate+ndeath; j++){
5100: if(j!=i){
5101: /*ca[0]= k+'a'-1;ca[1]='\0';*/
5102: printf("%1d%1d",i,j);
5103: fprintf(ficparo,"%1d%1d",i,j);
5104: for(k=1; k<=ncovmodel;k++){
5105: /* printf(" %lf",param[i][j][k]); */
5106: /* fprintf(ficparo," %lf",param[i][j][k]); */
5107: p[jk]=pstart[jk];
5108: printf(" %f ",pstart[jk]);
5109: fprintf(ficparo," %f ",pstart[jk]);
5110: jk++;
5111: }
5112: printf("\n");
5113: fprintf(ficparo,"\n");
5114: }
5115: }
5116: }
5117: } /* end mle=-2 */
1.226 brouard 5118: dateintmean=dateintsum/k2cpt;
1.296 brouard 5119: date2dmy(dateintmean,&jintmean,&mintmean,&aintmean);
1.240 brouard 5120:
1.226 brouard 5121: fclose(ficresp);
5122: fclose(ficresphtm);
5123: fclose(ficresphtmfr);
1.283 brouard 5124: free_vector(idq,1,nqfveff);
1.226 brouard 5125: free_vector(meanq,1,nqfveff);
1.284 brouard 5126: free_vector(stdq,1,nqfveff);
1.226 brouard 5127: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 5128: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
5129: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 5130: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 5131: free_vector(pospropt,1,nlstate);
5132: free_vector(posprop,1,nlstate);
1.251 brouard 5133: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 5134: free_vector(pp,1,nlstate);
5135: /* End of freqsummary */
5136: }
1.126 brouard 5137:
1.268 brouard 5138: /* Simple linear regression */
5139: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
5140:
5141: /* y=a+bx regression */
5142: double sumx = 0.0; /* sum of x */
5143: double sumx2 = 0.0; /* sum of x**2 */
5144: double sumxy = 0.0; /* sum of x * y */
5145: double sumy = 0.0; /* sum of y */
5146: double sumy2 = 0.0; /* sum of y**2 */
5147: double sume2 = 0.0; /* sum of square or residuals */
5148: double yhat;
5149:
5150: double denom=0;
5151: int i;
5152: int ne=*no;
5153:
5154: for ( i=ifi, ne=0;i<=ila;i++) {
5155: if(!isfinite(x[i]) || !isfinite(y[i])){
5156: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5157: continue;
5158: }
5159: ne=ne+1;
5160: sumx += x[i];
5161: sumx2 += x[i]*x[i];
5162: sumxy += x[i] * y[i];
5163: sumy += y[i];
5164: sumy2 += y[i]*y[i];
5165: denom = (ne * sumx2 - sumx*sumx);
5166: /* 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); */
5167: }
5168:
5169: denom = (ne * sumx2 - sumx*sumx);
5170: if (denom == 0) {
5171: // vertical, slope m is infinity
5172: *b = INFINITY;
5173: *a = 0;
5174: if (r) *r = 0;
5175: return 1;
5176: }
5177:
5178: *b = (ne * sumxy - sumx * sumy) / denom;
5179: *a = (sumy * sumx2 - sumx * sumxy) / denom;
5180: if (r!=NULL) {
5181: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
5182: sqrt((sumx2 - sumx*sumx/ne) *
5183: (sumy2 - sumy*sumy/ne));
5184: }
5185: *no=ne;
5186: for ( i=ifi, ne=0;i<=ila;i++) {
5187: if(!isfinite(x[i]) || !isfinite(y[i])){
5188: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5189: continue;
5190: }
5191: ne=ne+1;
5192: yhat = y[i] - *a -*b* x[i];
5193: sume2 += yhat * yhat ;
5194:
5195: denom = (ne * sumx2 - sumx*sumx);
5196: /* 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); */
5197: }
5198: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
5199: *sa= *sb * sqrt(sumx2/ne);
5200:
5201: return 0;
5202: }
5203:
1.126 brouard 5204: /************ Prevalence ********************/
1.227 brouard 5205: 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)
5206: {
5207: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
5208: in each health status at the date of interview (if between dateprev1 and dateprev2).
5209: We still use firstpass and lastpass as another selection.
5210: */
1.126 brouard 5211:
1.227 brouard 5212: int i, m, jk, j1, bool, z1,j, iv;
5213: int mi; /* Effective wave */
5214: int iage;
5215: double agebegin, ageend;
5216:
5217: double **prop;
5218: double posprop;
5219: double y2; /* in fractional years */
5220: int iagemin, iagemax;
5221: int first; /** to stop verbosity which is redirected to log file */
5222:
5223: iagemin= (int) agemin;
5224: iagemax= (int) agemax;
5225: /*pp=vector(1,nlstate);*/
1.251 brouard 5226: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5227: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
5228: j1=0;
1.222 brouard 5229:
1.227 brouard 5230: /*j=cptcoveff;*/
5231: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 5232:
1.288 brouard 5233: first=0;
1.227 brouard 5234: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of covariate */
5235: for (i=1; i<=nlstate; i++)
1.251 brouard 5236: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 5237: prop[i][iage]=0.0;
5238: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
5239: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
5240: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
5241:
5242: for (i=1; i<=imx; i++) { /* Each individual */
5243: bool=1;
5244: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
5245: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
5246: m=mw[mi][i];
5247: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
5248: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
5249: for (z1=1; z1<=cptcoveff; z1++){
5250: if( Fixed[Tmodelind[z1]]==1){
5251: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
5252: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality */
5253: bool=0;
5254: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
5255: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
5256: bool=0;
5257: }
5258: }
5259: if(bool==1){ /* Otherwise we skip that wave/person */
5260: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
5261: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
5262: if(m >=firstpass && m <=lastpass){
5263: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
5264: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
5265: if(agev[m][i]==0) agev[m][i]=iagemax+1;
5266: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 5267: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 5268: 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);
5269: exit(1);
5270: }
5271: if (s[m][i]>0 && s[m][i]<=nlstate) {
5272: /*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]]);*/
5273: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
5274: prop[s[m][i]][iagemax+3] += weight[i];
5275: } /* end valid statuses */
5276: } /* end selection of dates */
5277: } /* end selection of waves */
5278: } /* end bool */
5279: } /* end wave */
5280: } /* end individual */
5281: for(i=iagemin; i <= iagemax+3; i++){
5282: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
5283: posprop += prop[jk][i];
5284: }
5285:
5286: for(jk=1; jk <=nlstate ; jk++){
5287: if( i <= iagemax){
5288: if(posprop>=1.e-5){
5289: probs[i][jk][j1]= prop[jk][i]/posprop;
5290: } else{
1.288 brouard 5291: if(!first){
5292: first=1;
1.266 brouard 5293: 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]);
5294: }else{
1.288 brouard 5295: 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 5296: }
5297: }
5298: }
5299: }/* end jk */
5300: }/* end i */
1.222 brouard 5301: /*} *//* end i1 */
1.227 brouard 5302: } /* end j1 */
1.222 brouard 5303:
1.227 brouard 5304: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
5305: /*free_vector(pp,1,nlstate);*/
1.251 brouard 5306: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5307: } /* End of prevalence */
1.126 brouard 5308:
5309: /************* Waves Concatenation ***************/
5310:
5311: 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)
5312: {
1.298 brouard 5313: /* 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 5314: Death is a valid wave (if date is known).
5315: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
5316: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
1.298 brouard 5317: and mw[mi+1][i]. dh depends on stepm. s[m][i] exists for any wave from firstpass to lastpass
1.227 brouard 5318: */
1.126 brouard 5319:
1.224 brouard 5320: int i=0, mi=0, m=0, mli=0;
1.126 brouard 5321: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
5322: double sum=0., jmean=0.;*/
1.224 brouard 5323: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 5324: int j, k=0,jk, ju, jl;
5325: double sum=0.;
5326: first=0;
1.214 brouard 5327: firstwo=0;
1.217 brouard 5328: firsthree=0;
1.218 brouard 5329: firstfour=0;
1.164 brouard 5330: jmin=100000;
1.126 brouard 5331: jmax=-1;
5332: jmean=0.;
1.224 brouard 5333:
5334: /* Treating live states */
1.214 brouard 5335: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 5336: mi=0; /* First valid wave */
1.227 brouard 5337: mli=0; /* Last valid wave */
1.309 brouard 5338: m=firstpass; /* Loop on waves */
5339: while(s[m][i] <= nlstate){ /* a live state or unknown state */
1.227 brouard 5340: 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 */
5341: mli=m-1;/* mw[++mi][i]=m-1; */
5342: }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 5343: 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 5344: mli=m;
1.224 brouard 5345: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
5346: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 5347: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 5348: }
1.309 brouard 5349: else{ /* m = lastpass, eventual special issue with warning */
1.224 brouard 5350: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 5351: break;
1.224 brouard 5352: #else
1.317 brouard 5353: 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 5354: if(firsthree == 0){
1.302 brouard 5355: 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 5356: firsthree=1;
1.317 brouard 5357: }else if(firsthree >=1 && firsthree < 10){
5358: 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);
5359: firsthree++;
5360: }else if(firsthree == 10){
5361: printf("Information, too many Information flags: no more reported to log either\n");
5362: fprintf(ficlog,"Information, too many Information flags: no more reported to log either\n");
5363: firsthree++;
5364: }else{
5365: firsthree++;
1.227 brouard 5366: }
1.309 brouard 5367: mw[++mi][i]=m; /* Valid transition with unknown status */
1.227 brouard 5368: mli=m;
5369: }
5370: if(s[m][i]==-2){ /* Vital status is really unknown */
5371: nbwarn++;
1.309 brouard 5372: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified?not a transition */
1.227 brouard 5373: 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);
5374: 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);
5375: }
5376: break;
5377: }
5378: break;
1.224 brouard 5379: #endif
1.227 brouard 5380: }/* End m >= lastpass */
1.126 brouard 5381: }/* end while */
1.224 brouard 5382:
1.227 brouard 5383: /* 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 5384: /* After last pass */
1.224 brouard 5385: /* Treating death states */
1.214 brouard 5386: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 5387: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
5388: /* } */
1.126 brouard 5389: mi++; /* Death is another wave */
5390: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 5391: /* Only death is a correct wave */
1.126 brouard 5392: mw[mi][i]=m;
1.257 brouard 5393: } /* else not in a death state */
1.224 brouard 5394: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 5395: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 5396: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.309 brouard 5397: 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 5398: nbwarn++;
5399: if(firstfiv==0){
1.309 brouard 5400: 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 5401: firstfiv=1;
5402: }else{
1.309 brouard 5403: 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 5404: }
1.309 brouard 5405: s[m][i]=nlstate+1; /* Fixing the status as death. Be careful if multiple death states */
5406: }else{ /* Month of Death occured afer last wave month, potential bias */
1.227 brouard 5407: nberr++;
5408: if(firstwo==0){
1.309 brouard 5409: 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 5410: firstwo=1;
5411: }
1.309 brouard 5412: 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 5413: }
1.257 brouard 5414: }else{ /* if date of interview is unknown */
1.227 brouard 5415: /* death is known but not confirmed by death status at any wave */
5416: if(firstfour==0){
1.309 brouard 5417: 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 5418: firstfour=1;
5419: }
1.309 brouard 5420: 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 5421: }
1.224 brouard 5422: } /* end if date of death is known */
5423: #endif
1.309 brouard 5424: wav[i]=mi; /* mi should be the last effective wave (or mli), */
5425: /* wav[i]=mw[mi][i]; */
1.126 brouard 5426: if(mi==0){
5427: nbwarn++;
5428: if(first==0){
1.227 brouard 5429: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
5430: first=1;
1.126 brouard 5431: }
5432: if(first==1){
1.227 brouard 5433: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 5434: }
5435: } /* end mi==0 */
5436: } /* End individuals */
1.214 brouard 5437: /* wav and mw are no more changed */
1.223 brouard 5438:
1.317 brouard 5439: printf("Information, you have to check %d informations which haven't been logged!\n",firsthree);
5440: fprintf(ficlog,"Information, you have to check %d informations which haven't been logged!\n",firsthree);
5441:
5442:
1.126 brouard 5443: for(i=1; i<=imx; i++){
5444: for(mi=1; mi<wav[i];mi++){
5445: if (stepm <=0)
1.227 brouard 5446: dh[mi][i]=1;
1.126 brouard 5447: else{
1.260 brouard 5448: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 5449: if (agedc[i] < 2*AGESUP) {
5450: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
5451: if(j==0) j=1; /* Survives at least one month after exam */
5452: else if(j<0){
5453: nberr++;
5454: 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]);
5455: j=1; /* Temporary Dangerous patch */
5456: 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);
5457: 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]);
5458: 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);
5459: }
5460: k=k+1;
5461: if (j >= jmax){
5462: jmax=j;
5463: ijmax=i;
5464: }
5465: if (j <= jmin){
5466: jmin=j;
5467: ijmin=i;
5468: }
5469: sum=sum+j;
5470: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
5471: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
5472: }
5473: }
5474: else{
5475: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 5476: /* 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 5477:
1.227 brouard 5478: k=k+1;
5479: if (j >= jmax) {
5480: jmax=j;
5481: ijmax=i;
5482: }
5483: else if (j <= jmin){
5484: jmin=j;
5485: ijmin=i;
5486: }
5487: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
5488: /*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]);*/
5489: if(j<0){
5490: nberr++;
5491: 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]);
5492: 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]);
5493: }
5494: sum=sum+j;
5495: }
5496: jk= j/stepm;
5497: jl= j -jk*stepm;
5498: ju= j -(jk+1)*stepm;
5499: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
5500: if(jl==0){
5501: dh[mi][i]=jk;
5502: bh[mi][i]=0;
5503: }else{ /* We want a negative bias in order to only have interpolation ie
5504: * to avoid the price of an extra matrix product in likelihood */
5505: dh[mi][i]=jk+1;
5506: bh[mi][i]=ju;
5507: }
5508: }else{
5509: if(jl <= -ju){
5510: dh[mi][i]=jk;
5511: bh[mi][i]=jl; /* bias is positive if real duration
5512: * is higher than the multiple of stepm and negative otherwise.
5513: */
5514: }
5515: else{
5516: dh[mi][i]=jk+1;
5517: bh[mi][i]=ju;
5518: }
5519: if(dh[mi][i]==0){
5520: dh[mi][i]=1; /* At least one step */
5521: bh[mi][i]=ju; /* At least one step */
5522: /* 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);*/
5523: }
5524: } /* end if mle */
1.126 brouard 5525: }
5526: } /* end wave */
5527: }
5528: jmean=sum/k;
5529: 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 5530: 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 5531: }
1.126 brouard 5532:
5533: /*********** Tricode ****************************/
1.220 brouard 5534: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 5535: {
5536: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
5537: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
5538: * Boring subroutine which should only output nbcode[Tvar[j]][k]
5539: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
5540: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
5541: */
1.130 brouard 5542:
1.242 brouard 5543: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
5544: int modmaxcovj=0; /* Modality max of covariates j */
5545: int cptcode=0; /* Modality max of covariates j */
5546: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 5547:
5548:
1.242 brouard 5549: /* cptcoveff=0; */
5550: /* *cptcov=0; */
1.126 brouard 5551:
1.242 brouard 5552: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.285 brouard 5553: for (k=1; k <= maxncov; k++)
5554: for(j=1; j<=2; j++)
5555: nbcode[k][j]=0; /* Valgrind */
1.126 brouard 5556:
1.242 brouard 5557: /* Loop on covariates without age and products and no quantitative variable */
5558: for (k=1; k<=cptcovt; k++) { /* From model V1 + V2*age + V3 + V3*V4 keeps V1 + V3 = 2 only */
5559: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
5560: if(Dummy[k]==0 && Typevar[k] !=1){ /* Dummy covariate and not age product */
5561: switch(Fixed[k]) {
5562: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
1.311 brouard 5563: modmaxcovj=0;
5564: modmincovj=0;
1.242 brouard 5565: 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*/
5566: ij=(int)(covar[Tvar[k]][i]);
5567: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
5568: * If product of Vn*Vm, still boolean *:
5569: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
5570: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
5571: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
5572: modality of the nth covariate of individual i. */
5573: if (ij > modmaxcovj)
5574: modmaxcovj=ij;
5575: else if (ij < modmincovj)
5576: modmincovj=ij;
1.287 brouard 5577: if (ij <0 || ij >1 ){
1.311 brouard 5578: printf("ERROR, IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
5579: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
5580: fflush(ficlog);
5581: exit(1);
1.287 brouard 5582: }
5583: if ((ij < -1) || (ij > NCOVMAX)){
1.242 brouard 5584: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
5585: exit(1);
5586: }else
5587: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
5588: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
5589: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
5590: /* getting the maximum value of the modality of the covariate
5591: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
5592: female ies 1, then modmaxcovj=1.
5593: */
5594: } /* end for loop on individuals i */
5595: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5596: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5597: cptcode=modmaxcovj;
5598: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
5599: /*for (i=0; i<=cptcode; i++) {*/
5600: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
5601: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5602: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5603: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
5604: if( j != -1){
5605: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
5606: covariate for which somebody answered excluding
5607: undefined. Usually 2: 0 and 1. */
5608: }
5609: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
5610: covariate for which somebody answered including
5611: undefined. Usually 3: -1, 0 and 1. */
5612: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
5613: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
5614: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 5615:
1.242 brouard 5616: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
5617: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
5618: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
5619: /* modmincovj=3; modmaxcovj = 7; */
5620: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
5621: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
5622: /* defining two dummy variables: variables V1_1 and V1_2.*/
5623: /* nbcode[Tvar[j]][ij]=k; */
5624: /* nbcode[Tvar[j]][1]=0; */
5625: /* nbcode[Tvar[j]][2]=1; */
5626: /* nbcode[Tvar[j]][3]=2; */
5627: /* To be continued (not working yet). */
5628: ij=0; /* ij is similar to i but can jump over null modalities */
1.287 brouard 5629:
5630: /* 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*/
5631: /* Skipping the case of missing values by reducing nbcode to 0 and 1 and not -1, 0, 1 */
5632: /* model=V1+V2+V3, if V2=-1, 0 or 1, then nbcode[2][1]=0 and nbcode[2][2]=1 instead of
5633: * nbcode[2][1]=-1, nbcode[2][2]=0 and nbcode[2][3]=1 */
5634: /*, could be restored in the future */
5635: 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 5636: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
5637: break;
5638: }
5639: ij++;
1.287 brouard 5640: 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 5641: cptcode = ij; /* New max modality for covar j */
5642: } /* end of loop on modality i=-1 to 1 or more */
5643: break;
5644: case 1: /* Testing on varying covariate, could be simple and
5645: * should look at waves or product of fixed *
5646: * varying. No time to test -1, assuming 0 and 1 only */
5647: ij=0;
5648: for(i=0; i<=1;i++){
5649: nbcode[Tvar[k]][++ij]=i;
5650: }
5651: break;
5652: default:
5653: break;
5654: } /* end switch */
5655: } /* end dummy test */
1.311 brouard 5656: if(Dummy[k]==1 && Typevar[k] !=1){ /* Dummy covariate and not age product */
5657: 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*/
5658: if(isnan(covar[Tvar[k]][i])){
5659: printf("ERROR, IMaCh doesn't treat fixed quantitative covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
5660: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
5661: fflush(ficlog);
5662: exit(1);
5663: }
5664: }
5665: }
1.287 brouard 5666: } /* 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 5667:
5668: for (k=-1; k< maxncov; k++) Ndum[k]=0;
5669: /* Look at fixed dummy (single or product) covariates to check empty modalities */
5670: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
5671: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
5672: 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 */
5673: 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 */
5674: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
5675: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
5676:
5677: ij=0;
5678: /* for (i=0; i<= maxncov-1; i++) { /\* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) *\/ */
5679: for (k=1; k<= cptcovt; k++) { /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
5680: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
5681: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
5682: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy and non empty in the model */
5683: /* If product not in single variable we don't print results */
5684: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
5685: ++ij;/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, */
5686: 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*/
5687: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
5688: 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 */
5689: if(Fixed[k]!=0)
5690: anyvaryingduminmodel=1;
5691: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
5692: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
5693: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
5694: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
5695: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
5696: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
5697: }
5698: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
5699: /* ij--; */
5700: /* cptcoveff=ij; /\*Number of total covariates*\/ */
5701: *cptcov=ij; /*Number of total real effective covariates: effective
5702: * because they can be excluded from the model and real
5703: * if in the model but excluded because missing values, but how to get k from ij?*/
5704: for(j=ij+1; j<= cptcovt; j++){
5705: Tvaraff[j]=0;
5706: Tmodelind[j]=0;
5707: }
5708: for(j=ntveff+1; j<= cptcovt; j++){
5709: TmodelInvind[j]=0;
5710: }
5711: /* To be sorted */
5712: ;
5713: }
1.126 brouard 5714:
1.145 brouard 5715:
1.126 brouard 5716: /*********** Health Expectancies ****************/
5717:
1.235 brouard 5718: 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 5719:
5720: {
5721: /* Health expectancies, no variances */
1.164 brouard 5722: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 5723: int nhstepma, nstepma; /* Decreasing with age */
5724: double age, agelim, hf;
5725: double ***p3mat;
5726: double eip;
5727:
1.238 brouard 5728: /* pstamp(ficreseij); */
1.126 brouard 5729: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
5730: fprintf(ficreseij,"# Age");
5731: for(i=1; i<=nlstate;i++){
5732: for(j=1; j<=nlstate;j++){
5733: fprintf(ficreseij," e%1d%1d ",i,j);
5734: }
5735: fprintf(ficreseij," e%1d. ",i);
5736: }
5737: fprintf(ficreseij,"\n");
5738:
5739:
5740: if(estepm < stepm){
5741: printf ("Problem %d lower than %d\n",estepm, stepm);
5742: }
5743: else hstepm=estepm;
5744: /* We compute the life expectancy from trapezoids spaced every estepm months
5745: * This is mainly to measure the difference between two models: for example
5746: * if stepm=24 months pijx are given only every 2 years and by summing them
5747: * we are calculating an estimate of the Life Expectancy assuming a linear
5748: * progression in between and thus overestimating or underestimating according
5749: * to the curvature of the survival function. If, for the same date, we
5750: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5751: * to compare the new estimate of Life expectancy with the same linear
5752: * hypothesis. A more precise result, taking into account a more precise
5753: * curvature will be obtained if estepm is as small as stepm. */
5754:
5755: /* For example we decided to compute the life expectancy with the smallest unit */
5756: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5757: nhstepm is the number of hstepm from age to agelim
5758: nstepm is the number of stepm from age to agelin.
1.270 brouard 5759: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 5760: and note for a fixed period like estepm months */
5761: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5762: survival function given by stepm (the optimization length). Unfortunately it
5763: means that if the survival funtion is printed only each two years of age and if
5764: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5765: results. So we changed our mind and took the option of the best precision.
5766: */
5767: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5768:
5769: agelim=AGESUP;
5770: /* If stepm=6 months */
5771: /* Computed by stepm unit matrices, product of hstepm matrices, stored
5772: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
5773:
5774: /* nhstepm age range expressed in number of stepm */
5775: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5776: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5777: /* if (stepm >= YEARM) hstepm=1;*/
5778: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5779: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5780:
5781: for (age=bage; age<=fage; age ++){
5782: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5783: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5784: /* if (stepm >= YEARM) hstepm=1;*/
5785: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
5786:
5787: /* If stepm=6 months */
5788: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5789: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5790:
1.235 brouard 5791: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 5792:
5793: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
5794:
5795: printf("%d|",(int)age);fflush(stdout);
5796: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5797:
5798: /* Computing expectancies */
5799: for(i=1; i<=nlstate;i++)
5800: for(j=1; j<=nlstate;j++)
5801: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5802: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
5803:
5804: /* 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]);*/
5805:
5806: }
5807:
5808: fprintf(ficreseij,"%3.0f",age );
5809: for(i=1; i<=nlstate;i++){
5810: eip=0;
5811: for(j=1; j<=nlstate;j++){
5812: eip +=eij[i][j][(int)age];
5813: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
5814: }
5815: fprintf(ficreseij,"%9.4f", eip );
5816: }
5817: fprintf(ficreseij,"\n");
5818:
5819: }
5820: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5821: printf("\n");
5822: fprintf(ficlog,"\n");
5823:
5824: }
5825:
1.235 brouard 5826: 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 5827:
5828: {
5829: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 5830: to initial status i, ei. .
1.126 brouard 5831: */
5832: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
5833: int nhstepma, nstepma; /* Decreasing with age */
5834: double age, agelim, hf;
5835: double ***p3matp, ***p3matm, ***varhe;
5836: double **dnewm,**doldm;
5837: double *xp, *xm;
5838: double **gp, **gm;
5839: double ***gradg, ***trgradg;
5840: int theta;
5841:
5842: double eip, vip;
5843:
5844: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
5845: xp=vector(1,npar);
5846: xm=vector(1,npar);
5847: dnewm=matrix(1,nlstate*nlstate,1,npar);
5848: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
5849:
5850: pstamp(ficresstdeij);
5851: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
5852: fprintf(ficresstdeij,"# Age");
5853: for(i=1; i<=nlstate;i++){
5854: for(j=1; j<=nlstate;j++)
5855: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
5856: fprintf(ficresstdeij," e%1d. ",i);
5857: }
5858: fprintf(ficresstdeij,"\n");
5859:
5860: pstamp(ficrescveij);
5861: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
5862: fprintf(ficrescveij,"# Age");
5863: for(i=1; i<=nlstate;i++)
5864: for(j=1; j<=nlstate;j++){
5865: cptj= (j-1)*nlstate+i;
5866: for(i2=1; i2<=nlstate;i2++)
5867: for(j2=1; j2<=nlstate;j2++){
5868: cptj2= (j2-1)*nlstate+i2;
5869: if(cptj2 <= cptj)
5870: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
5871: }
5872: }
5873: fprintf(ficrescveij,"\n");
5874:
5875: if(estepm < stepm){
5876: printf ("Problem %d lower than %d\n",estepm, stepm);
5877: }
5878: else hstepm=estepm;
5879: /* We compute the life expectancy from trapezoids spaced every estepm months
5880: * This is mainly to measure the difference between two models: for example
5881: * if stepm=24 months pijx are given only every 2 years and by summing them
5882: * we are calculating an estimate of the Life Expectancy assuming a linear
5883: * progression in between and thus overestimating or underestimating according
5884: * to the curvature of the survival function. If, for the same date, we
5885: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5886: * to compare the new estimate of Life expectancy with the same linear
5887: * hypothesis. A more precise result, taking into account a more precise
5888: * curvature will be obtained if estepm is as small as stepm. */
5889:
5890: /* For example we decided to compute the life expectancy with the smallest unit */
5891: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5892: nhstepm is the number of hstepm from age to agelim
5893: nstepm is the number of stepm from age to agelin.
5894: Look at hpijx to understand the reason of that which relies in memory size
5895: and note for a fixed period like estepm months */
5896: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5897: survival function given by stepm (the optimization length). Unfortunately it
5898: means that if the survival funtion is printed only each two years of age and if
5899: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5900: results. So we changed our mind and took the option of the best precision.
5901: */
5902: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5903:
5904: /* If stepm=6 months */
5905: /* nhstepm age range expressed in number of stepm */
5906: agelim=AGESUP;
5907: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
5908: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5909: /* if (stepm >= YEARM) hstepm=1;*/
5910: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5911:
5912: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5913: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5914: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
5915: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
5916: gp=matrix(0,nhstepm,1,nlstate*nlstate);
5917: gm=matrix(0,nhstepm,1,nlstate*nlstate);
5918:
5919: for (age=bage; age<=fage; age ++){
5920: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5921: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5922: /* if (stepm >= YEARM) hstepm=1;*/
5923: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 5924:
1.126 brouard 5925: /* If stepm=6 months */
5926: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5927: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5928:
5929: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 5930:
1.126 brouard 5931: /* Computing Variances of health expectancies */
5932: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
5933: decrease memory allocation */
5934: for(theta=1; theta <=npar; theta++){
5935: for(i=1; i<=npar; i++){
1.222 brouard 5936: xp[i] = x[i] + (i==theta ?delti[theta]:0);
5937: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 5938: }
1.235 brouard 5939: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
5940: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 5941:
1.126 brouard 5942: for(j=1; j<= nlstate; j++){
1.222 brouard 5943: for(i=1; i<=nlstate; i++){
5944: for(h=0; h<=nhstepm-1; h++){
5945: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
5946: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
5947: }
5948: }
1.126 brouard 5949: }
1.218 brouard 5950:
1.126 brouard 5951: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 5952: for(h=0; h<=nhstepm-1; h++){
5953: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
5954: }
1.126 brouard 5955: }/* End theta */
5956:
5957:
5958: for(h=0; h<=nhstepm-1; h++)
5959: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 5960: for(theta=1; theta <=npar; theta++)
5961: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 5962:
1.218 brouard 5963:
1.222 brouard 5964: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 5965: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 5966: varhe[ij][ji][(int)age] =0.;
1.218 brouard 5967:
1.222 brouard 5968: printf("%d|",(int)age);fflush(stdout);
5969: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5970: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 5971: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 5972: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
5973: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
5974: for(ij=1;ij<=nlstate*nlstate;ij++)
5975: for(ji=1;ji<=nlstate*nlstate;ji++)
5976: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 5977: }
5978: }
1.218 brouard 5979:
1.126 brouard 5980: /* Computing expectancies */
1.235 brouard 5981: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 5982: for(i=1; i<=nlstate;i++)
5983: for(j=1; j<=nlstate;j++)
1.222 brouard 5984: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5985: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 5986:
1.222 brouard 5987: /* 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 5988:
1.222 brouard 5989: }
1.269 brouard 5990:
5991: /* Standard deviation of expectancies ij */
1.126 brouard 5992: fprintf(ficresstdeij,"%3.0f",age );
5993: for(i=1; i<=nlstate;i++){
5994: eip=0.;
5995: vip=0.;
5996: for(j=1; j<=nlstate;j++){
1.222 brouard 5997: eip += eij[i][j][(int)age];
5998: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
5999: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
6000: 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 6001: }
6002: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
6003: }
6004: fprintf(ficresstdeij,"\n");
1.218 brouard 6005:
1.269 brouard 6006: /* Variance of expectancies ij */
1.126 brouard 6007: fprintf(ficrescveij,"%3.0f",age );
6008: for(i=1; i<=nlstate;i++)
6009: for(j=1; j<=nlstate;j++){
1.222 brouard 6010: cptj= (j-1)*nlstate+i;
6011: for(i2=1; i2<=nlstate;i2++)
6012: for(j2=1; j2<=nlstate;j2++){
6013: cptj2= (j2-1)*nlstate+i2;
6014: if(cptj2 <= cptj)
6015: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
6016: }
1.126 brouard 6017: }
6018: fprintf(ficrescveij,"\n");
1.218 brouard 6019:
1.126 brouard 6020: }
6021: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
6022: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
6023: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
6024: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
6025: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6026: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6027: printf("\n");
6028: fprintf(ficlog,"\n");
1.218 brouard 6029:
1.126 brouard 6030: free_vector(xm,1,npar);
6031: free_vector(xp,1,npar);
6032: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
6033: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
6034: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
6035: }
1.218 brouard 6036:
1.126 brouard 6037: /************ Variance ******************/
1.235 brouard 6038: 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 6039: {
1.279 brouard 6040: /** Variance of health expectancies
6041: * double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);
6042: * double **newm;
6043: * int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)
6044: */
1.218 brouard 6045:
6046: /* int movingaverage(); */
6047: double **dnewm,**doldm;
6048: double **dnewmp,**doldmp;
6049: int i, j, nhstepm, hstepm, h, nstepm ;
1.288 brouard 6050: int first=0;
1.218 brouard 6051: int k;
6052: double *xp;
1.279 brouard 6053: double **gp, **gm; /**< for var eij */
6054: double ***gradg, ***trgradg; /**< for var eij */
6055: double **gradgp, **trgradgp; /**< for var p point j */
6056: double *gpp, *gmp; /**< for var p point j */
6057: double **varppt; /**< for var p point j nlstate to nlstate+ndeath */
1.218 brouard 6058: double ***p3mat;
6059: double age,agelim, hf;
6060: /* double ***mobaverage; */
6061: int theta;
6062: char digit[4];
6063: char digitp[25];
6064:
6065: char fileresprobmorprev[FILENAMELENGTH];
6066:
6067: if(popbased==1){
6068: if(mobilav!=0)
6069: strcpy(digitp,"-POPULBASED-MOBILAV_");
6070: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
6071: }
6072: else
6073: strcpy(digitp,"-STABLBASED_");
1.126 brouard 6074:
1.218 brouard 6075: /* if (mobilav!=0) { */
6076: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6077: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
6078: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
6079: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
6080: /* } */
6081: /* } */
6082:
6083: strcpy(fileresprobmorprev,"PRMORPREV-");
6084: sprintf(digit,"%-d",ij);
6085: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
6086: strcat(fileresprobmorprev,digit); /* Tvar to be done */
6087: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
6088: strcat(fileresprobmorprev,fileresu);
6089: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
6090: printf("Problem with resultfile: %s\n", fileresprobmorprev);
6091: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
6092: }
6093: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
6094: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
6095: pstamp(ficresprobmorprev);
6096: 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 6097: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
6098: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
6099: fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
6100: }
6101: for(j=1;j<=cptcoveff;j++)
6102: fprintf(ficresprobmorprev,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,j)]);
6103: fprintf(ficresprobmorprev,"\n");
6104:
1.218 brouard 6105: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
6106: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6107: fprintf(ficresprobmorprev," p.%-d SE",j);
6108: for(i=1; i<=nlstate;i++)
6109: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
6110: }
6111: fprintf(ficresprobmorprev,"\n");
6112:
6113: fprintf(ficgp,"\n# Routine varevsij");
6114: fprintf(ficgp,"\nunset title \n");
6115: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
6116: 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");
6117: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
1.279 brouard 6118:
1.218 brouard 6119: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6120: pstamp(ficresvij);
6121: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
6122: if(popbased==1)
6123: 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);
6124: else
6125: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
6126: fprintf(ficresvij,"# Age");
6127: for(i=1; i<=nlstate;i++)
6128: for(j=1; j<=nlstate;j++)
6129: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
6130: fprintf(ficresvij,"\n");
6131:
6132: xp=vector(1,npar);
6133: dnewm=matrix(1,nlstate,1,npar);
6134: doldm=matrix(1,nlstate,1,nlstate);
6135: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
6136: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6137:
6138: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
6139: gpp=vector(nlstate+1,nlstate+ndeath);
6140: gmp=vector(nlstate+1,nlstate+ndeath);
6141: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 6142:
1.218 brouard 6143: if(estepm < stepm){
6144: printf ("Problem %d lower than %d\n",estepm, stepm);
6145: }
6146: else hstepm=estepm;
6147: /* For example we decided to compute the life expectancy with the smallest unit */
6148: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6149: nhstepm is the number of hstepm from age to agelim
6150: nstepm is the number of stepm from age to agelim.
6151: Look at function hpijx to understand why because of memory size limitations,
6152: we decided (b) to get a life expectancy respecting the most precise curvature of the
6153: survival function given by stepm (the optimization length). Unfortunately it
6154: means that if the survival funtion is printed every two years of age and if
6155: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6156: results. So we changed our mind and took the option of the best precision.
6157: */
6158: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6159: agelim = AGESUP;
6160: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6161: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6162: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6163: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6164: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
6165: gp=matrix(0,nhstepm,1,nlstate);
6166: gm=matrix(0,nhstepm,1,nlstate);
6167:
6168:
6169: for(theta=1; theta <=npar; theta++){
6170: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
6171: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6172: }
1.279 brouard 6173: /**< Computes the prevalence limit with parameter theta shifted of delta up to ftolpl precision and
6174: * returns into prlim .
1.288 brouard 6175: */
1.242 brouard 6176: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.279 brouard 6177:
6178: /* If popbased = 1 we use crossection prevalences. Previous step is useless but prlim is created */
1.218 brouard 6179: if (popbased==1) {
6180: if(mobilav ==0){
6181: for(i=1; i<=nlstate;i++)
6182: prlim[i][i]=probs[(int)age][i][ij];
6183: }else{ /* mobilav */
6184: for(i=1; i<=nlstate;i++)
6185: prlim[i][i]=mobaverage[(int)age][i][ij];
6186: }
6187: }
1.295 brouard 6188: /**< Computes the shifted transition matrix \f$ {}{h}_p^{ij}x\f$ at horizon h.
1.279 brouard 6189: */
6190: 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 6191: /**< 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 6192: * at horizon h in state j including mortality.
6193: */
1.218 brouard 6194: for(j=1; j<= nlstate; j++){
6195: for(h=0; h<=nhstepm; h++){
6196: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
6197: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
6198: }
6199: }
1.279 brouard 6200: /* Next for computing shifted+ probability of death (h=1 means
1.218 brouard 6201: computed over hstepm matrices product = hstepm*stepm months)
1.279 brouard 6202: as a weighted average of prlim(i) * p(i,j) p.3=w1*p13 + w2*p23 .
1.218 brouard 6203: */
6204: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6205: for(i=1,gpp[j]=0.; i<= nlstate; i++)
6206: gpp[j] += prlim[i][i]*p3mat[i][j][1];
1.279 brouard 6207: }
6208:
6209: /* Again with minus shift */
1.218 brouard 6210:
6211: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
6212: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 6213:
1.242 brouard 6214: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 6215:
6216: if (popbased==1) {
6217: if(mobilav ==0){
6218: for(i=1; i<=nlstate;i++)
6219: prlim[i][i]=probs[(int)age][i][ij];
6220: }else{ /* mobilav */
6221: for(i=1; i<=nlstate;i++)
6222: prlim[i][i]=mobaverage[(int)age][i][ij];
6223: }
6224: }
6225:
1.235 brouard 6226: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 6227:
6228: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
6229: for(h=0; h<=nhstepm; h++){
6230: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
6231: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
6232: }
6233: }
6234: /* This for computing probability of death (h=1 means
6235: computed over hstepm matrices product = hstepm*stepm months)
6236: as a weighted average of prlim.
6237: */
6238: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6239: for(i=1,gmp[j]=0.; i<= nlstate; i++)
6240: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6241: }
1.279 brouard 6242: /* end shifting computations */
6243:
6244: /**< Computing gradient matrix at horizon h
6245: */
1.218 brouard 6246: for(j=1; j<= nlstate; j++) /* vareij */
6247: for(h=0; h<=nhstepm; h++){
6248: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
6249: }
1.279 brouard 6250: /**< Gradient of overall mortality p.3 (or p.j)
6251: */
6252: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu mortality from j */
1.218 brouard 6253: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
6254: }
6255:
6256: } /* End theta */
1.279 brouard 6257:
6258: /* We got the gradient matrix for each theta and state j */
1.218 brouard 6259: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
6260:
6261: for(h=0; h<=nhstepm; h++) /* veij */
6262: for(j=1; j<=nlstate;j++)
6263: for(theta=1; theta <=npar; theta++)
6264: trgradg[h][j][theta]=gradg[h][theta][j];
6265:
6266: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
6267: for(theta=1; theta <=npar; theta++)
6268: trgradgp[j][theta]=gradgp[theta][j];
1.279 brouard 6269: /**< as well as its transposed matrix
6270: */
1.218 brouard 6271:
6272: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6273: for(i=1;i<=nlstate;i++)
6274: for(j=1;j<=nlstate;j++)
6275: vareij[i][j][(int)age] =0.;
1.279 brouard 6276:
6277: /* Computing trgradg by matcov by gradg at age and summing over h
6278: * and k (nhstepm) formula 15 of article
6279: * Lievre-Brouard-Heathcote
6280: */
6281:
1.218 brouard 6282: for(h=0;h<=nhstepm;h++){
6283: for(k=0;k<=nhstepm;k++){
6284: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
6285: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
6286: for(i=1;i<=nlstate;i++)
6287: for(j=1;j<=nlstate;j++)
6288: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
6289: }
6290: }
6291:
1.279 brouard 6292: /* pptj is p.3 or p.j = trgradgp by cov by gradgp, variance of
6293: * p.j overall mortality formula 49 but computed directly because
6294: * we compute the grad (wix pijx) instead of grad (pijx),even if
6295: * wix is independent of theta.
6296: */
1.218 brouard 6297: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
6298: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
6299: for(j=nlstate+1;j<=nlstate+ndeath;j++)
6300: for(i=nlstate+1;i<=nlstate+ndeath;i++)
6301: varppt[j][i]=doldmp[j][i];
6302: /* end ppptj */
6303: /* x centered again */
6304:
1.242 brouard 6305: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 6306:
6307: if (popbased==1) {
6308: if(mobilav ==0){
6309: for(i=1; i<=nlstate;i++)
6310: prlim[i][i]=probs[(int)age][i][ij];
6311: }else{ /* mobilav */
6312: for(i=1; i<=nlstate;i++)
6313: prlim[i][i]=mobaverage[(int)age][i][ij];
6314: }
6315: }
6316:
6317: /* This for computing probability of death (h=1 means
6318: computed over hstepm (estepm) matrices product = hstepm*stepm months)
6319: as a weighted average of prlim.
6320: */
1.235 brouard 6321: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 6322: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6323: for(i=1,gmp[j]=0.;i<= nlstate; i++)
6324: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6325: }
6326: /* end probability of death */
6327:
6328: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
6329: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6330: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
6331: for(i=1; i<=nlstate;i++){
6332: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
6333: }
6334: }
6335: fprintf(ficresprobmorprev,"\n");
6336:
6337: fprintf(ficresvij,"%.0f ",age );
6338: for(i=1; i<=nlstate;i++)
6339: for(j=1; j<=nlstate;j++){
6340: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
6341: }
6342: fprintf(ficresvij,"\n");
6343: free_matrix(gp,0,nhstepm,1,nlstate);
6344: free_matrix(gm,0,nhstepm,1,nlstate);
6345: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
6346: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
6347: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6348: } /* End age */
6349: free_vector(gpp,nlstate+1,nlstate+ndeath);
6350: free_vector(gmp,nlstate+1,nlstate+ndeath);
6351: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
6352: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
6353: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
6354: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
6355: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
6356: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
6357: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
6358: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
6359: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
6360: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
6361: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
6362: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
6363: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
6364: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
6365: 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);
6366: /* 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 6367: */
1.218 brouard 6368: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
6369: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 6370:
1.218 brouard 6371: free_vector(xp,1,npar);
6372: free_matrix(doldm,1,nlstate,1,nlstate);
6373: free_matrix(dnewm,1,nlstate,1,npar);
6374: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6375: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
6376: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6377: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6378: fclose(ficresprobmorprev);
6379: fflush(ficgp);
6380: fflush(fichtm);
6381: } /* end varevsij */
1.126 brouard 6382:
6383: /************ Variance of prevlim ******************/
1.269 brouard 6384: 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 6385: {
1.205 brouard 6386: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 6387: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 6388:
1.268 brouard 6389: double **dnewmpar,**doldm;
1.126 brouard 6390: int i, j, nhstepm, hstepm;
6391: double *xp;
6392: double *gp, *gm;
6393: double **gradg, **trgradg;
1.208 brouard 6394: double **mgm, **mgp;
1.126 brouard 6395: double age,agelim;
6396: int theta;
6397:
6398: pstamp(ficresvpl);
1.288 brouard 6399: fprintf(ficresvpl,"# Standard deviation of period (forward stable) prevalences \n");
1.241 brouard 6400: fprintf(ficresvpl,"# Age ");
6401: if(nresult >=1)
6402: fprintf(ficresvpl," Result# ");
1.126 brouard 6403: for(i=1; i<=nlstate;i++)
6404: fprintf(ficresvpl," %1d-%1d",i,i);
6405: fprintf(ficresvpl,"\n");
6406:
6407: xp=vector(1,npar);
1.268 brouard 6408: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 6409: doldm=matrix(1,nlstate,1,nlstate);
6410:
6411: hstepm=1*YEARM; /* Every year of age */
6412: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6413: agelim = AGESUP;
6414: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6415: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6416: if (stepm >= YEARM) hstepm=1;
6417: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6418: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 6419: mgp=matrix(1,npar,1,nlstate);
6420: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 6421: gp=vector(1,nlstate);
6422: gm=vector(1,nlstate);
6423:
6424: for(theta=1; theta <=npar; theta++){
6425: for(i=1; i<=npar; i++){ /* Computes gradient */
6426: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6427: }
1.288 brouard 6428: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
6429: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
6430: /* else */
6431: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6432: for(i=1;i<=nlstate;i++){
1.126 brouard 6433: gp[i] = prlim[i][i];
1.208 brouard 6434: mgp[theta][i] = prlim[i][i];
6435: }
1.126 brouard 6436: for(i=1; i<=npar; i++) /* Computes gradient */
6437: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 6438: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
6439: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
6440: /* else */
6441: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6442: for(i=1;i<=nlstate;i++){
1.126 brouard 6443: gm[i] = prlim[i][i];
1.208 brouard 6444: mgm[theta][i] = prlim[i][i];
6445: }
1.126 brouard 6446: for(i=1;i<=nlstate;i++)
6447: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 6448: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 6449: } /* End theta */
6450:
6451: trgradg =matrix(1,nlstate,1,npar);
6452:
6453: for(j=1; j<=nlstate;j++)
6454: for(theta=1; theta <=npar; theta++)
6455: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 6456: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6457: /* printf("\nmgm mgp %d ",(int)age); */
6458: /* for(j=1; j<=nlstate;j++){ */
6459: /* printf(" %d ",j); */
6460: /* for(theta=1; theta <=npar; theta++) */
6461: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6462: /* printf("\n "); */
6463: /* } */
6464: /* } */
6465: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6466: /* printf("\n gradg %d ",(int)age); */
6467: /* for(j=1; j<=nlstate;j++){ */
6468: /* printf("%d ",j); */
6469: /* for(theta=1; theta <=npar; theta++) */
6470: /* printf("%d %lf ",theta,gradg[theta][j]); */
6471: /* printf("\n "); */
6472: /* } */
6473: /* } */
1.126 brouard 6474:
6475: for(i=1;i<=nlstate;i++)
6476: varpl[i][(int)age] =0.;
1.209 brouard 6477: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 brouard 6478: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6479: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6480: }else{
1.268 brouard 6481: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6482: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6483: }
1.126 brouard 6484: for(i=1;i<=nlstate;i++)
6485: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6486:
6487: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 6488: if(nresult >=1)
6489: fprintf(ficresvpl,"%d ",nres );
1.288 brouard 6490: for(i=1; i<=nlstate;i++){
1.126 brouard 6491: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
1.288 brouard 6492: /* for(j=1;j<=nlstate;j++) */
6493: /* fprintf(ficresvpl," %d %.5f ",j,prlim[j][i]); */
6494: }
1.126 brouard 6495: fprintf(ficresvpl,"\n");
6496: free_vector(gp,1,nlstate);
6497: free_vector(gm,1,nlstate);
1.208 brouard 6498: free_matrix(mgm,1,npar,1,nlstate);
6499: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 6500: free_matrix(gradg,1,npar,1,nlstate);
6501: free_matrix(trgradg,1,nlstate,1,npar);
6502: } /* End age */
6503:
6504: free_vector(xp,1,npar);
6505: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 6506: free_matrix(dnewmpar,1,nlstate,1,nlstate);
6507:
6508: }
6509:
6510:
6511: /************ Variance of backprevalence limit ******************/
1.269 brouard 6512: 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 6513: {
6514: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
6515: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
6516:
6517: double **dnewmpar,**doldm;
6518: int i, j, nhstepm, hstepm;
6519: double *xp;
6520: double *gp, *gm;
6521: double **gradg, **trgradg;
6522: double **mgm, **mgp;
6523: double age,agelim;
6524: int theta;
6525:
6526: pstamp(ficresvbl);
6527: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
6528: fprintf(ficresvbl,"# Age ");
6529: if(nresult >=1)
6530: fprintf(ficresvbl," Result# ");
6531: for(i=1; i<=nlstate;i++)
6532: fprintf(ficresvbl," %1d-%1d",i,i);
6533: fprintf(ficresvbl,"\n");
6534:
6535: xp=vector(1,npar);
6536: dnewmpar=matrix(1,nlstate,1,npar);
6537: doldm=matrix(1,nlstate,1,nlstate);
6538:
6539: hstepm=1*YEARM; /* Every year of age */
6540: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6541: agelim = AGEINF;
6542: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
6543: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6544: if (stepm >= YEARM) hstepm=1;
6545: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6546: gradg=matrix(1,npar,1,nlstate);
6547: mgp=matrix(1,npar,1,nlstate);
6548: mgm=matrix(1,npar,1,nlstate);
6549: gp=vector(1,nlstate);
6550: gm=vector(1,nlstate);
6551:
6552: for(theta=1; theta <=npar; theta++){
6553: for(i=1; i<=npar; i++){ /* Computes gradient */
6554: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6555: }
6556: if(mobilavproj > 0 )
6557: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6558: else
6559: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6560: for(i=1;i<=nlstate;i++){
6561: gp[i] = bprlim[i][i];
6562: mgp[theta][i] = bprlim[i][i];
6563: }
6564: for(i=1; i<=npar; i++) /* Computes gradient */
6565: xp[i] = x[i] - (i==theta ?delti[theta]:0);
6566: if(mobilavproj > 0 )
6567: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6568: else
6569: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6570: for(i=1;i<=nlstate;i++){
6571: gm[i] = bprlim[i][i];
6572: mgm[theta][i] = bprlim[i][i];
6573: }
6574: for(i=1;i<=nlstate;i++)
6575: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
6576: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
6577: } /* End theta */
6578:
6579: trgradg =matrix(1,nlstate,1,npar);
6580:
6581: for(j=1; j<=nlstate;j++)
6582: for(theta=1; theta <=npar; theta++)
6583: trgradg[j][theta]=gradg[theta][j];
6584: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6585: /* printf("\nmgm mgp %d ",(int)age); */
6586: /* for(j=1; j<=nlstate;j++){ */
6587: /* printf(" %d ",j); */
6588: /* for(theta=1; theta <=npar; theta++) */
6589: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6590: /* printf("\n "); */
6591: /* } */
6592: /* } */
6593: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6594: /* printf("\n gradg %d ",(int)age); */
6595: /* for(j=1; j<=nlstate;j++){ */
6596: /* printf("%d ",j); */
6597: /* for(theta=1; theta <=npar; theta++) */
6598: /* printf("%d %lf ",theta,gradg[theta][j]); */
6599: /* printf("\n "); */
6600: /* } */
6601: /* } */
6602:
6603: for(i=1;i<=nlstate;i++)
6604: varbpl[i][(int)age] =0.;
6605: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
6606: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6607: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6608: }else{
6609: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6610: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6611: }
6612: for(i=1;i<=nlstate;i++)
6613: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6614:
6615: fprintf(ficresvbl,"%.0f ",age );
6616: if(nresult >=1)
6617: fprintf(ficresvbl,"%d ",nres );
6618: for(i=1; i<=nlstate;i++)
6619: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
6620: fprintf(ficresvbl,"\n");
6621: free_vector(gp,1,nlstate);
6622: free_vector(gm,1,nlstate);
6623: free_matrix(mgm,1,npar,1,nlstate);
6624: free_matrix(mgp,1,npar,1,nlstate);
6625: free_matrix(gradg,1,npar,1,nlstate);
6626: free_matrix(trgradg,1,nlstate,1,npar);
6627: } /* End age */
6628:
6629: free_vector(xp,1,npar);
6630: free_matrix(doldm,1,nlstate,1,npar);
6631: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 6632:
6633: }
6634:
6635: /************ Variance of one-step probabilities ******************/
6636: 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 6637: {
6638: int i, j=0, k1, l1, tj;
6639: int k2, l2, j1, z1;
6640: int k=0, l;
6641: int first=1, first1, first2;
6642: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
6643: double **dnewm,**doldm;
6644: double *xp;
6645: double *gp, *gm;
6646: double **gradg, **trgradg;
6647: double **mu;
6648: double age, cov[NCOVMAX+1];
6649: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
6650: int theta;
6651: char fileresprob[FILENAMELENGTH];
6652: char fileresprobcov[FILENAMELENGTH];
6653: char fileresprobcor[FILENAMELENGTH];
6654: double ***varpij;
6655:
6656: strcpy(fileresprob,"PROB_");
6657: strcat(fileresprob,fileres);
6658: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
6659: printf("Problem with resultfile: %s\n", fileresprob);
6660: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
6661: }
6662: strcpy(fileresprobcov,"PROBCOV_");
6663: strcat(fileresprobcov,fileresu);
6664: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
6665: printf("Problem with resultfile: %s\n", fileresprobcov);
6666: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
6667: }
6668: strcpy(fileresprobcor,"PROBCOR_");
6669: strcat(fileresprobcor,fileresu);
6670: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
6671: printf("Problem with resultfile: %s\n", fileresprobcor);
6672: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
6673: }
6674: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6675: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6676: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6677: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6678: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6679: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6680: pstamp(ficresprob);
6681: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
6682: fprintf(ficresprob,"# Age");
6683: pstamp(ficresprobcov);
6684: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
6685: fprintf(ficresprobcov,"# Age");
6686: pstamp(ficresprobcor);
6687: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
6688: fprintf(ficresprobcor,"# Age");
1.126 brouard 6689:
6690:
1.222 brouard 6691: for(i=1; i<=nlstate;i++)
6692: for(j=1; j<=(nlstate+ndeath);j++){
6693: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
6694: fprintf(ficresprobcov," p%1d-%1d ",i,j);
6695: fprintf(ficresprobcor," p%1d-%1d ",i,j);
6696: }
6697: /* fprintf(ficresprob,"\n");
6698: fprintf(ficresprobcov,"\n");
6699: fprintf(ficresprobcor,"\n");
6700: */
6701: xp=vector(1,npar);
6702: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6703: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6704: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
6705: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
6706: first=1;
6707: fprintf(ficgp,"\n# Routine varprob");
6708: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
6709: fprintf(fichtm,"\n");
6710:
1.288 brouard 6711: 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 6712: 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);
6713: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 6714: and drawn. It helps understanding how is the covariance between two incidences.\
6715: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 6716: 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 6717: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
6718: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
6719: standard deviations wide on each axis. <br>\
6720: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
6721: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
6722: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
6723:
1.222 brouard 6724: cov[1]=1;
6725: /* tj=cptcoveff; */
1.225 brouard 6726: tj = (int) pow(2,cptcoveff);
1.222 brouard 6727: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
6728: j1=0;
1.224 brouard 6729: for(j1=1; j1<=tj;j1++){ /* For each valid combination of covariates or only once*/
1.222 brouard 6730: if (cptcovn>0) {
6731: fprintf(ficresprob, "\n#********** Variable ");
1.225 brouard 6732: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6733: fprintf(ficresprob, "**********\n#\n");
6734: fprintf(ficresprobcov, "\n#********** Variable ");
1.225 brouard 6735: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcov, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6736: fprintf(ficresprobcov, "**********\n#\n");
1.220 brouard 6737:
1.222 brouard 6738: fprintf(ficgp, "\n#********** Variable ");
1.225 brouard 6739: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficgp, " V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6740: fprintf(ficgp, "**********\n#\n");
1.220 brouard 6741:
6742:
1.222 brouard 6743: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
1.225 brouard 6744: for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtm, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6745: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 6746:
1.222 brouard 6747: fprintf(ficresprobcor, "\n#********** Variable ");
1.225 brouard 6748: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcor, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6749: fprintf(ficresprobcor, "**********\n#");
6750: if(invalidvarcomb[j1]){
6751: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
6752: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
6753: continue;
6754: }
6755: }
6756: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
6757: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6758: gp=vector(1,(nlstate)*(nlstate+ndeath));
6759: gm=vector(1,(nlstate)*(nlstate+ndeath));
6760: for (age=bage; age<=fage; age ++){
6761: cov[2]=age;
6762: if(nagesqr==1)
6763: cov[3]= age*age;
6764: for (k=1; k<=cptcovn;k++) {
6765: cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)];
6766: /*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*//* j1 1 2 3 4
6767: * 1 1 1 1 1
6768: * 2 2 1 1 1
6769: * 3 1 2 1 1
6770: */
6771: /* nbcode[1][1]=0 nbcode[1][2]=1;*/
6772: }
6773: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; */
1.318 ! brouard 6774: for (k=1; k<=cptcovage;k++) cov[2+Tage[k]+nagesqr]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
1.222 brouard 6775: for (k=1; k<=cptcovprod;k++)
6776: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.220 brouard 6777:
6778:
1.222 brouard 6779: for(theta=1; theta <=npar; theta++){
6780: for(i=1; i<=npar; i++)
6781: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 6782:
1.222 brouard 6783: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 6784:
1.222 brouard 6785: k=0;
6786: for(i=1; i<= (nlstate); i++){
6787: for(j=1; j<=(nlstate+ndeath);j++){
6788: k=k+1;
6789: gp[k]=pmmij[i][j];
6790: }
6791: }
1.220 brouard 6792:
1.222 brouard 6793: for(i=1; i<=npar; i++)
6794: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 6795:
1.222 brouard 6796: pmij(pmmij,cov,ncovmodel,xp,nlstate);
6797: k=0;
6798: for(i=1; i<=(nlstate); i++){
6799: for(j=1; j<=(nlstate+ndeath);j++){
6800: k=k+1;
6801: gm[k]=pmmij[i][j];
6802: }
6803: }
1.220 brouard 6804:
1.222 brouard 6805: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
6806: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
6807: }
1.126 brouard 6808:
1.222 brouard 6809: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
6810: for(theta=1; theta <=npar; theta++)
6811: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 6812:
1.222 brouard 6813: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
6814: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 6815:
1.222 brouard 6816: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 6817:
1.222 brouard 6818: k=0;
6819: for(i=1; i<=(nlstate); i++){
6820: for(j=1; j<=(nlstate+ndeath);j++){
6821: k=k+1;
6822: mu[k][(int) age]=pmmij[i][j];
6823: }
6824: }
6825: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
6826: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
6827: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 6828:
1.222 brouard 6829: /*printf("\n%d ",(int)age);
6830: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6831: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6832: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6833: }*/
1.220 brouard 6834:
1.222 brouard 6835: fprintf(ficresprob,"\n%d ",(int)age);
6836: fprintf(ficresprobcov,"\n%d ",(int)age);
6837: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 6838:
1.222 brouard 6839: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
6840: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
6841: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6842: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
6843: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
6844: }
6845: i=0;
6846: for (k=1; k<=(nlstate);k++){
6847: for (l=1; l<=(nlstate+ndeath);l++){
6848: i++;
6849: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
6850: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
6851: for (j=1; j<=i;j++){
6852: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
6853: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
6854: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
6855: }
6856: }
6857: }/* end of loop for state */
6858: } /* end of loop for age */
6859: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
6860: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
6861: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
6862: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
6863:
6864: /* Confidence intervalle of pij */
6865: /*
6866: fprintf(ficgp,"\nunset parametric;unset label");
6867: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
6868: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
6869: 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);
6870: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
6871: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
6872: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
6873: */
6874:
6875: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
6876: first1=1;first2=2;
6877: for (k2=1; k2<=(nlstate);k2++){
6878: for (l2=1; l2<=(nlstate+ndeath);l2++){
6879: if(l2==k2) continue;
6880: j=(k2-1)*(nlstate+ndeath)+l2;
6881: for (k1=1; k1<=(nlstate);k1++){
6882: for (l1=1; l1<=(nlstate+ndeath);l1++){
6883: if(l1==k1) continue;
6884: i=(k1-1)*(nlstate+ndeath)+l1;
6885: if(i<=j) continue;
6886: for (age=bage; age<=fage; age ++){
6887: if ((int)age %5==0){
6888: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
6889: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
6890: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
6891: mu1=mu[i][(int) age]/stepm*YEARM ;
6892: mu2=mu[j][(int) age]/stepm*YEARM;
6893: c12=cv12/sqrt(v1*v2);
6894: /* Computing eigen value of matrix of covariance */
6895: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6896: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6897: if ((lc2 <0) || (lc1 <0) ){
6898: if(first2==1){
6899: first1=0;
6900: 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);
6901: }
6902: 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);
6903: /* lc1=fabs(lc1); */ /* If we want to have them positive */
6904: /* lc2=fabs(lc2); */
6905: }
1.220 brouard 6906:
1.222 brouard 6907: /* Eigen vectors */
1.280 brouard 6908: if(1+(v1-lc1)*(v1-lc1)/cv12/cv12 <1.e-5){
6909: printf(" Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
6910: fprintf(ficlog," Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
6911: v11=(1./sqrt(fabs(1+(v1-lc1)*(v1-lc1)/cv12/cv12)));
6912: }else
6913: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
1.222 brouard 6914: /*v21=sqrt(1.-v11*v11); *//* error */
6915: v21=(lc1-v1)/cv12*v11;
6916: v12=-v21;
6917: v22=v11;
6918: tnalp=v21/v11;
6919: if(first1==1){
6920: first1=0;
6921: 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);
6922: }
6923: 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);
6924: /*printf(fignu*/
6925: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
6926: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
6927: if(first==1){
6928: first=0;
6929: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
6930: fprintf(ficgp,"\nset parametric;unset label");
6931: 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);
6932: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 6933: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 6934: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 6935: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 6936: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
6937: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6938: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6939: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
6940: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6941: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
6942: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
6943: 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 6944: mu1,std,v11,sqrt(fabs(lc1)),v12,sqrt(fabs(lc2)), \
6945: mu2,std,v21,sqrt(fabs(lc1)),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 6946: }else{
6947: first=0;
6948: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
6949: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
6950: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
6951: 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 6952: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
6953: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 6954: }/* if first */
6955: } /* age mod 5 */
6956: } /* end loop age */
6957: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6958: first=1;
6959: } /*l12 */
6960: } /* k12 */
6961: } /*l1 */
6962: }/* k1 */
6963: } /* loop on combination of covariates j1 */
6964: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
6965: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
6966: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6967: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
6968: free_vector(xp,1,npar);
6969: fclose(ficresprob);
6970: fclose(ficresprobcov);
6971: fclose(ficresprobcor);
6972: fflush(ficgp);
6973: fflush(fichtmcov);
6974: }
1.126 brouard 6975:
6976:
6977: /******************* Printing html file ***********/
1.201 brouard 6978: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 6979: int lastpass, int stepm, int weightopt, char model[],\
6980: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.296 brouard 6981: int popforecast, int mobilav, int prevfcast, int mobilavproj, int prevbcast, int estepm , \
6982: double jprev1, double mprev1,double anprev1, double dateprev1, double dateprojd, double dateback1, \
6983: double jprev2, double mprev2,double anprev2, double dateprev2, double dateprojf, double dateback2){
1.237 brouard 6984: int jj1, k1, i1, cpt, k4, nres;
1.126 brouard 6985:
6986: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
6987: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
6988: </ul>");
1.237 brouard 6989: fprintf(fichtm,"<ul><li> model=1+age+%s\n \
6990: </ul>", model);
1.214 brouard 6991: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
6992: 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",
6993: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
6994: 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 6995: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
6996: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 6997: fprintf(fichtm,"\
6998: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 6999: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 7000: fprintf(fichtm,"\
1.217 brouard 7001: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
7002: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
7003: fprintf(fichtm,"\
1.288 brouard 7004: - Period (forward) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 7005: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 7006: fprintf(fichtm,"\
1.288 brouard 7007: - Backward prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.217 brouard 7008: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
7009: fprintf(fichtm,"\
1.211 brouard 7010: - (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 7011: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 7012: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 7013: if(prevfcast==1){
7014: fprintf(fichtm,"\
7015: - Prevalence projections by age and states: \
1.201 brouard 7016: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 7017: }
1.126 brouard 7018:
7019:
1.225 brouard 7020: m=pow(2,cptcoveff);
1.222 brouard 7021: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 7022:
1.317 brouard 7023: fprintf(fichtm," \n<ul><li><b>Graphs (first order)</b></li><p>");
1.264 brouard 7024:
7025: jj1=0;
7026:
7027: fprintf(fichtm," \n<ul>");
7028: for(nres=1; nres <= nresult; nres++) /* For each resultline */
7029: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
7030: if(m != 1 && TKresult[nres]!= k1)
7031: continue;
7032: jj1++;
7033: if (cptcovn > 0) {
7034: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
7035: for (cpt=1; cpt<=cptcoveff;cpt++){
7036: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7037: }
7038: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7039: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
7040: }
7041: fprintf(fichtm,"\">");
7042:
7043: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
7044: fprintf(fichtm,"************ Results for covariates");
7045: for (cpt=1; cpt<=cptcoveff;cpt++){
7046: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7047: }
7048: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7049: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7050: }
7051: if(invalidvarcomb[k1]){
7052: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
7053: continue;
7054: }
7055: fprintf(fichtm,"</a></li>");
7056: } /* cptcovn >0 */
7057: }
1.317 brouard 7058: fprintf(fichtm," \n</ul>");
1.264 brouard 7059:
1.222 brouard 7060: jj1=0;
1.237 brouard 7061:
7062: for(nres=1; nres <= nresult; nres++) /* For each resultline */
1.241 brouard 7063: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
1.253 brouard 7064: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7065: continue;
1.220 brouard 7066:
1.222 brouard 7067: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
7068: jj1++;
7069: if (cptcovn > 0) {
1.264 brouard 7070: fprintf(fichtm,"\n<p><a name=\"rescov");
7071: for (cpt=1; cpt<=cptcoveff;cpt++){
7072: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7073: }
7074: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7075: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
7076: }
7077: fprintf(fichtm,"\"</a>");
7078:
1.222 brouard 7079: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 7080: for (cpt=1; cpt<=cptcoveff;cpt++){
1.237 brouard 7081: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7082: printf(" V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);fflush(stdout);
7083: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
7084: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 7085: }
1.237 brouard 7086: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7087: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7088: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);fflush(stdout);
7089: }
7090:
1.230 brouard 7091: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.222 brouard 7092: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
7093: if(invalidvarcomb[k1]){
7094: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
7095: printf("\nCombination (%d) ignored because no cases \n",k1);
7096: continue;
7097: }
7098: }
7099: /* aij, bij */
1.259 brouard 7100: 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 7101: <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 7102: /* Pij */
1.241 brouard 7103: 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> \
7104: <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 7105: /* Quasi-incidences */
7106: 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 7107: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 7108: 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 7109: 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> \
7110: <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 7111: /* Survival functions (period) in state j */
7112: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 7113: fprintf(fichtm,"<br>\n- Survival functions in state %d. And probability to be observed in state %d being in state (1 to %d) at different ages. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br> \
1.241 brouard 7114: <img src=\"%s_%d-%d-%d.svg\">", cpt, cpt, nlstate, subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres,subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres,subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.222 brouard 7115: }
7116: /* State specific survival functions (period) */
7117: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 7118: fprintf(fichtm,"<br>\n- Survival functions in state %d and in any other live state (total).\
7119: And probability to be observed in various states (up to %d) being in state %d at different ages. \
1.283 brouard 7120: <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br> <img src=\"%s_%d-%d-%d.svg\">", cpt, nlstate, cpt, subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres,subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres,subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.222 brouard 7121: }
1.288 brouard 7122: /* Period (forward stable) prevalence in each health state */
1.222 brouard 7123: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 7124: 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> \
7125: <img src=\"%s_%d-%d-%d.svg\">", cpt, nlstate, cpt, subdirf2(optionfilefiname,"P_"),cpt,k1,nres,subdirf2(optionfilefiname,"P_"),cpt,k1,nres,subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.222 brouard 7126: }
1.296 brouard 7127: if(prevbcast==1){
1.288 brouard 7128: /* Backward prevalence in each health state */
1.222 brouard 7129: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 7130: 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 7131: <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 7132: }
1.217 brouard 7133: }
1.222 brouard 7134: if(prevfcast==1){
1.288 brouard 7135: /* Projection of prevalence up to period (forward stable) prevalence in each health state */
1.222 brouard 7136: for(cpt=1; cpt<=nlstate;cpt++){
1.314 brouard 7137: 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);
7138: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"F_"),subdirf2(optionfilefiname,"F_"));
7139: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",
7140: subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.222 brouard 7141: }
7142: }
1.296 brouard 7143: if(prevbcast==1){
1.268 brouard 7144: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
7145: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 7146: fprintf(fichtm,"<br>\n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), \
7147: 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 \
7148: 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 7149: 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);
7150: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"FB_"),subdirf2(optionfilefiname,"FB_"));
7151: fprintf(fichtm," <img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
1.268 brouard 7152: }
7153: }
1.220 brouard 7154:
1.222 brouard 7155: for(cpt=1; cpt<=nlstate;cpt++) {
1.314 brouard 7156: 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);
7157: fprintf(fichtm," (data from text file <a href=\"%s.txt\"> %s.txt</a>)\n<br>",subdirf2(optionfilefiname,"E_"),subdirf2(optionfilefiname,"E_"));
7158: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres );
1.222 brouard 7159: }
7160: /* } /\* end i1 *\/ */
7161: }/* End k1 */
7162: fprintf(fichtm,"</ul>");
1.126 brouard 7163:
1.222 brouard 7164: fprintf(fichtm,"\
1.126 brouard 7165: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 7166: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 7167: - 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 7168: But because parameters are usually highly correlated (a higher incidence of disability \
7169: and a higher incidence of recovery can give very close observed transition) it might \
7170: be very useful to look not only at linear confidence intervals estimated from the \
7171: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
7172: (parameters) of the logistic regression, it might be more meaningful to visualize the \
7173: covariance matrix of the one-step probabilities. \
7174: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 7175:
1.222 brouard 7176: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
7177: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
7178: fprintf(fichtm,"\
1.126 brouard 7179: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 7180: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 7181:
1.222 brouard 7182: fprintf(fichtm,"\
1.126 brouard 7183: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 7184: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
7185: fprintf(fichtm,"\
1.126 brouard 7186: - 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): \
7187: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 7188: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 7189: fprintf(fichtm,"\
1.126 brouard 7190: - (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): \
7191: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 7192: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 7193: fprintf(fichtm,"\
1.288 brouard 7194: - 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 7195: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
7196: fprintf(fichtm,"\
1.128 brouard 7197: - 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 7198: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
7199: fprintf(fichtm,"\
1.288 brouard 7200: - Standard deviation of forward (period) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 7201: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 7202:
7203: /* if(popforecast==1) fprintf(fichtm,"\n */
7204: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
7205: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
7206: /* <br>",fileres,fileres,fileres,fileres); */
7207: /* else */
7208: /* 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 7209: fflush(fichtm);
1.126 brouard 7210:
1.225 brouard 7211: m=pow(2,cptcoveff);
1.222 brouard 7212: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 7213:
1.317 brouard 7214: fprintf(fichtm," <ul><li><b>Graphs (second order)</b></li><p>");
7215:
7216: jj1=0;
7217:
7218: fprintf(fichtm," \n<ul>");
7219: for(nres=1; nres <= nresult; nres++) /* For each resultline */
7220: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
7221: if(m != 1 && TKresult[nres]!= k1)
7222: continue;
7223: jj1++;
7224: if (cptcovn > 0) {
7225: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescovsecond");
7226: for (cpt=1; cpt<=cptcoveff;cpt++){
7227: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7228: }
7229: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7230: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
7231: }
7232: fprintf(fichtm,"\">");
7233:
7234: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
7235: fprintf(fichtm,"************ Results for covariates");
7236: for (cpt=1; cpt<=cptcoveff;cpt++){
7237: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7238: }
7239: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7240: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7241: }
7242: if(invalidvarcomb[k1]){
7243: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
7244: continue;
7245: }
7246: fprintf(fichtm,"</a></li>");
7247: } /* cptcovn >0 */
7248: }
7249: fprintf(fichtm," \n</ul>");
7250:
1.222 brouard 7251: jj1=0;
1.237 brouard 7252:
1.241 brouard 7253: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.222 brouard 7254: for(k1=1; k1<=m;k1++){
1.253 brouard 7255: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7256: continue;
1.222 brouard 7257: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
7258: jj1++;
1.126 brouard 7259: if (cptcovn > 0) {
1.317 brouard 7260: fprintf(fichtm,"\n<p><a name=\"rescovsecond");
7261: for (cpt=1; cpt<=cptcoveff;cpt++){
7262: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7263: }
7264: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7265: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
7266: }
7267: fprintf(fichtm,"\"</a>");
7268:
1.126 brouard 7269: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.317 brouard 7270: for (cpt=1; cpt<=cptcoveff;cpt++){ /**< cptcoveff number of variables */
1.237 brouard 7271: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);
1.317 brouard 7272: printf(" V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);fflush(stdout);
1.237 brouard 7273: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
1.317 brouard 7274: }
1.237 brouard 7275: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7276: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7277: }
7278:
1.126 brouard 7279: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 7280:
1.222 brouard 7281: if(invalidvarcomb[k1]){
7282: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
7283: continue;
7284: }
1.126 brouard 7285: }
7286: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 7287: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.314 brouard 7288: 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);
7289: fprintf(fichtm," (data from text file <a href=\"%s\">%s</a>)\n <br>",subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
7290: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"V_"), cpt,k1,nres);
1.126 brouard 7291: }
7292: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.314 brouard 7293: health expectancies in each live states (1 to %d). If popbased=1 the smooth (due to the model) \
1.128 brouard 7294: true period expectancies (those weighted with period prevalences are also\
7295: drawn in addition to the population based expectancies computed using\
1.314 brouard 7296: 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);
7297: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>) \n<br>",subdirf2(optionfilefiname,"T_"),subdirf2(optionfilefiname,"T_"));
7298: fprintf(fichtm,"<img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 7299: /* } /\* end i1 *\/ */
7300: }/* End k1 */
1.241 brouard 7301: }/* End nres */
1.222 brouard 7302: fprintf(fichtm,"</ul>");
7303: fflush(fichtm);
1.126 brouard 7304: }
7305:
7306: /******************* Gnuplot file **************/
1.296 brouard 7307: 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 7308:
7309: char dirfileres[132],optfileres[132];
1.264 brouard 7310: char gplotcondition[132], gplotlabel[132];
1.237 brouard 7311: 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 7312: int lv=0, vlv=0, kl=0;
1.130 brouard 7313: int ng=0;
1.201 brouard 7314: int vpopbased;
1.223 brouard 7315: int ioffset; /* variable offset for columns */
1.270 brouard 7316: int iyearc=1; /* variable column for year of projection */
7317: int iagec=1; /* variable column for age of projection */
1.235 brouard 7318: int nres=0; /* Index of resultline */
1.266 brouard 7319: int istart=1; /* For starting graphs in projections */
1.219 brouard 7320:
1.126 brouard 7321: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
7322: /* printf("Problem with file %s",optionfilegnuplot); */
7323: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
7324: /* } */
7325:
7326: /*#ifdef windows */
7327: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 7328: /*#endif */
1.225 brouard 7329: m=pow(2,cptcoveff);
1.126 brouard 7330:
1.274 brouard 7331: /* diagram of the model */
7332: fprintf(ficgp,"\n#Diagram of the model \n");
7333: fprintf(ficgp,"\ndelta=0.03;delta2=0.07;unset arrow;\n");
7334: fprintf(ficgp,"yoff=(%d > 2? 0:1);\n",nlstate);
7335: 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);
7336:
7337: 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);
7338: fprintf(ficgp,"\n#show arrow\nunset label\n");
7339: 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);
7340: fprintf(ficgp,"\nset label %d+1 sprintf(\"State %%d\",%d+1) center at 0.,0. font \"helvetica, 16\" tc rgbcolor \"red\"\n",nlstate,nlstate);
7341: fprintf(ficgp,"\n#show label\nunset border;unset xtics; unset ytics;\n");
7342: fprintf(ficgp,"\n\nset ter svg size 640, 480;set out \"%s_.svg\" \n",subdirf2(optionfilefiname,"D_"));
7343: fprintf(ficgp,"unset log y; plot [-1.2:1.2][yoff-1.2:1.2] 1/0 not; set out;reset;\n");
7344:
1.202 brouard 7345: /* Contribution to likelihood */
7346: /* Plot the probability implied in the likelihood */
1.223 brouard 7347: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
7348: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
7349: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
7350: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 7351: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 7352: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
7353: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 7354: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
7355: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
7356: 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));
7357: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
7358: 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));
7359: for (i=1; i<= nlstate ; i ++) {
7360: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
7361: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
7362: 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);
7363: for (j=2; j<= nlstate+ndeath ; j ++) {
7364: 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);
7365: }
7366: fprintf(ficgp,";\nset out; unset ylabel;\n");
7367: }
7368: /* 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 */
7369: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
7370: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
7371: fprintf(ficgp,"\nset out;unset log\n");
7372: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 7373:
1.126 brouard 7374: strcpy(dirfileres,optionfilefiname);
7375: strcpy(optfileres,"vpl");
1.223 brouard 7376: /* 1eme*/
1.238 brouard 7377: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
7378: for (k1=1; k1<= m ; k1 ++){ /* For each valid combination of covariate */
1.236 brouard 7379: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.238 brouard 7380: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.253 brouard 7381: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7382: continue;
7383: /* We are interested in selected combination by the resultline */
1.246 brouard 7384: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.288 brouard 7385: fprintf(ficgp,"\n# 1st: Forward (stable period) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 7386: strcpy(gplotlabel,"(");
1.238 brouard 7387: for (k=1; k<=cptcoveff; k++){ /* For each covariate k get corresponding value lv for combination k1 */
7388: lv= decodtabm(k1,k,cptcoveff); /* Should be the value of the covariate corresponding to k1 combination */
7389: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7390: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7391: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7392: vlv= nbcode[Tvaraff[k]][lv]; /* vlv is the value of the covariate lv, 0 or 1 */
7393: /* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv */
1.246 brouard 7394: /* printf(" V%d=%d ",Tvaraff[k],vlv); */
1.238 brouard 7395: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7396: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7397: }
7398: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.246 brouard 7399: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 7400: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7401: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7402: }
7403: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 7404: /* printf("\n#\n"); */
1.238 brouard 7405: fprintf(ficgp,"\n#\n");
7406: if(invalidvarcomb[k1]){
1.260 brouard 7407: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 7408: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7409: continue;
7410: }
1.235 brouard 7411:
1.241 brouard 7412: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
7413: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.276 brouard 7414: /* fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel); */
7415: fprintf(ficgp,"set title \"Alive state %d %s\" font \"Helvetica,12\"\n",cpt,gplotlabel);
1.260 brouard 7416: 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);
7417: /* 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); */
7418: /* k1-1 error should be nres-1*/
1.238 brouard 7419: for (i=1; i<= nlstate ; i ++) {
7420: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7421: else fprintf(ficgp," %%*lf (%%*lf)");
7422: }
1.288 brouard 7423: 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 7424: for (i=1; i<= nlstate ; i ++) {
7425: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7426: else fprintf(ficgp," %%*lf (%%*lf)");
7427: }
1.260 brouard 7428: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 7429: for (i=1; i<= nlstate ; i ++) {
7430: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7431: else fprintf(ficgp," %%*lf (%%*lf)");
7432: }
1.265 brouard 7433: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
7434:
7435: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
7436: if(cptcoveff ==0){
1.271 brouard 7437: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+3*(cpt-1), cpt );
1.265 brouard 7438: }else{
7439: kl=0;
7440: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7441: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7442: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7443: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7444: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7445: vlv= nbcode[Tvaraff[k]][lv];
7446: kl++;
7447: /* 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 *\/ */
7448: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7449: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7450: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7451: if(k==cptcoveff){
7452: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
7453: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
7454: }else{
7455: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7456: kl++;
7457: }
7458: } /* end covariate */
7459: } /* end if no covariate */
7460:
1.296 brouard 7461: if(prevbcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
1.238 brouard 7462: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 7463: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 7464: if(cptcoveff ==0){
1.245 brouard 7465: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 7466: }else{
7467: kl=0;
7468: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7469: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7470: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7471: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7472: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7473: vlv= nbcode[Tvaraff[k]][lv];
1.223 brouard 7474: kl++;
1.238 brouard 7475: /* 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 *\/ */
7476: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7477: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7478: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7479: if(k==cptcoveff){
1.245 brouard 7480: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 7481: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 7482: }else{
7483: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7484: kl++;
7485: }
7486: } /* end covariate */
7487: } /* end if no covariate */
1.296 brouard 7488: if(prevbcast == 1){
1.268 brouard 7489: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
7490: /* k1-1 error should be nres-1*/
7491: for (i=1; i<= nlstate ; i ++) {
7492: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7493: else fprintf(ficgp," %%*lf (%%*lf)");
7494: }
1.271 brouard 7495: 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 7496: for (i=1; i<= nlstate ; i ++) {
7497: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7498: else fprintf(ficgp," %%*lf (%%*lf)");
7499: }
1.276 brouard 7500: 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 7501: for (i=1; i<= nlstate ; i ++) {
7502: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7503: else fprintf(ficgp," %%*lf (%%*lf)");
7504: }
1.274 brouard 7505: fprintf(ficgp,"\" t\"\" w l lt 4");
1.268 brouard 7506: } /* end if backprojcast */
1.296 brouard 7507: } /* end if prevbcast */
1.276 brouard 7508: /* fprintf(ficgp,"\nset out ;unset label;\n"); */
7509: fprintf(ficgp,"\nset out ;unset title;\n");
1.238 brouard 7510: } /* nres */
1.201 brouard 7511: } /* k1 */
7512: } /* cpt */
1.235 brouard 7513:
7514:
1.126 brouard 7515: /*2 eme*/
1.238 brouard 7516: for (k1=1; k1<= m ; k1 ++){
7517: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7518: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7519: continue;
7520: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 7521: strcpy(gplotlabel,"(");
1.238 brouard 7522: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.225 brouard 7523: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
1.223 brouard 7524: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7525: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7526: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7527: vlv= nbcode[Tvaraff[k]][lv];
7528: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7529: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7530: }
1.237 brouard 7531: /* for(k=1; k <= ncovds; k++){ */
1.236 brouard 7532: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 7533: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.236 brouard 7534: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7535: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7536: }
1.264 brouard 7537: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7538: fprintf(ficgp,"\n#\n");
1.223 brouard 7539: if(invalidvarcomb[k1]){
7540: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7541: continue;
7542: }
1.219 brouard 7543:
1.241 brouard 7544: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 7545: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 7546: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
7547: if(vpopbased==0){
1.238 brouard 7548: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 7549: }else
1.238 brouard 7550: fprintf(ficgp,"\nreplot ");
7551: for (i=1; i<= nlstate+1 ; i ++) {
7552: k=2*i;
1.261 brouard 7553: 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 7554: for (j=1; j<= nlstate+1 ; j ++) {
7555: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7556: else fprintf(ficgp," %%*lf (%%*lf)");
7557: }
7558: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
7559: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
1.261 brouard 7560: 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 7561: for (j=1; j<= nlstate+1 ; j ++) {
7562: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7563: else fprintf(ficgp," %%*lf (%%*lf)");
7564: }
7565: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 7566: 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 7567: for (j=1; j<= nlstate+1 ; j ++) {
7568: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7569: else fprintf(ficgp," %%*lf (%%*lf)");
7570: }
7571: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
7572: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
7573: } /* state */
7574: } /* vpopbased */
1.264 brouard 7575: 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 7576: } /* end nres */
7577: } /* k1 end 2 eme*/
7578:
7579:
7580: /*3eme*/
7581: for (k1=1; k1<= m ; k1 ++){
7582: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7583: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7584: continue;
7585:
7586: for (cpt=1; cpt<= nlstate ; cpt ++) {
1.261 brouard 7587: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 7588: strcpy(gplotlabel,"(");
1.238 brouard 7589: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7590: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7591: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7592: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7593: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7594: vlv= nbcode[Tvaraff[k]][lv];
7595: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7596: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7597: }
7598: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7599: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7600: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7601: }
1.264 brouard 7602: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7603: fprintf(ficgp,"\n#\n");
7604: if(invalidvarcomb[k1]){
7605: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7606: continue;
7607: }
7608:
7609: /* k=2+nlstate*(2*cpt-2); */
7610: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 7611: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 7612: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 7613: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 7614: 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 7615: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7616: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7617: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
7618: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7619: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7620: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 7621:
1.238 brouard 7622: */
7623: for (i=1; i< nlstate ; i ++) {
1.261 brouard 7624: 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 7625: /* 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 7626:
1.238 brouard 7627: }
1.261 brouard 7628: 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 7629: }
1.264 brouard 7630: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 7631: } /* end nres */
7632: } /* end kl 3eme */
1.126 brouard 7633:
1.223 brouard 7634: /* 4eme */
1.201 brouard 7635: /* Survival functions (period) from state i in state j by initial state i */
1.238 brouard 7636: for (k1=1; k1<=m; k1++){ /* For each covariate and each value */
7637: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7638: if(m != 1 && TKresult[nres]!= k1)
1.223 brouard 7639: continue;
1.238 brouard 7640: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 7641: strcpy(gplotlabel,"(");
1.238 brouard 7642: fprintf(ficgp,"\n#\n#\n# Survival functions in state j : 'LIJ_' files, cov=%d state=%d",k1, cpt);
7643: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7644: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7645: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7646: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7647: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7648: vlv= nbcode[Tvaraff[k]][lv];
7649: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7650: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7651: }
7652: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7653: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7654: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7655: }
1.264 brouard 7656: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7657: fprintf(ficgp,"\n#\n");
7658: if(invalidvarcomb[k1]){
7659: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7660: continue;
1.223 brouard 7661: }
1.238 brouard 7662:
1.241 brouard 7663: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 7664: 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 7665: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7666: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7667: k=3;
7668: for (i=1; i<= nlstate ; i ++){
7669: if(i==1){
7670: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7671: }else{
7672: fprintf(ficgp,", '' ");
7673: }
7674: l=(nlstate+ndeath)*(i-1)+1;
7675: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7676: for (j=2; j<= nlstate+ndeath ; j ++)
7677: fprintf(ficgp,"+$%d",k+l+j-1);
7678: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
7679: } /* nlstate */
1.264 brouard 7680: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7681: } /* end cpt state*/
7682: } /* end nres */
7683: } /* end covariate k1 */
7684:
1.220 brouard 7685: /* 5eme */
1.201 brouard 7686: /* Survival functions (period) from state i in state j by final state j */
1.238 brouard 7687: for (k1=1; k1<= m ; k1++){ /* For each covariate combination if any */
7688: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7689: if(m != 1 && TKresult[nres]!= k1)
1.227 brouard 7690: continue;
1.238 brouard 7691: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 7692: strcpy(gplotlabel,"(");
1.238 brouard 7693: 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);
7694: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7695: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7696: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7697: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7698: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7699: vlv= nbcode[Tvaraff[k]][lv];
7700: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7701: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7702: }
7703: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7704: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7705: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7706: }
1.264 brouard 7707: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7708: fprintf(ficgp,"\n#\n");
7709: if(invalidvarcomb[k1]){
7710: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7711: continue;
7712: }
1.227 brouard 7713:
1.241 brouard 7714: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 7715: 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 7716: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7717: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7718: k=3;
7719: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7720: if(j==1)
7721: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7722: else
7723: fprintf(ficgp,", '' ");
7724: l=(nlstate+ndeath)*(cpt-1) +j;
7725: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
7726: /* for (i=2; i<= nlstate+ndeath ; i ++) */
7727: /* fprintf(ficgp,"+$%d",k+l+i-1); */
7728: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
7729: } /* nlstate */
7730: fprintf(ficgp,", '' ");
7731: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
7732: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7733: l=(nlstate+ndeath)*(cpt-1) +j;
7734: if(j < nlstate)
7735: fprintf(ficgp,"$%d +",k+l);
7736: else
7737: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
7738: }
1.264 brouard 7739: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7740: } /* end cpt state*/
7741: } /* end covariate */
7742: } /* end nres */
1.227 brouard 7743:
1.220 brouard 7744: /* 6eme */
1.202 brouard 7745: /* CV preval stable (period) for each covariate */
1.237 brouard 7746: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7747: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7748: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7749: continue;
1.255 brouard 7750: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 7751: strcpy(gplotlabel,"(");
1.288 brouard 7752: fprintf(ficgp,"\n#\n#\n#CV preval stable (forward): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.225 brouard 7753: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.227 brouard 7754: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7755: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7756: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7757: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7758: vlv= nbcode[Tvaraff[k]][lv];
7759: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7760: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7761: }
1.237 brouard 7762: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7763: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7764: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7765: }
1.264 brouard 7766: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7767: fprintf(ficgp,"\n#\n");
1.223 brouard 7768: if(invalidvarcomb[k1]){
1.227 brouard 7769: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7770: continue;
1.223 brouard 7771: }
1.227 brouard 7772:
1.241 brouard 7773: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 7774: 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 7775: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7776: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 7777: k=3; /* Offset */
1.255 brouard 7778: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 7779: if(i==1)
7780: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7781: else
7782: fprintf(ficgp,", '' ");
1.255 brouard 7783: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7784: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7785: for (j=2; j<= nlstate ; j ++)
7786: fprintf(ficgp,"+$%d",k+l+j-1);
7787: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 7788: } /* nlstate */
1.264 brouard 7789: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 7790: } /* end cpt state*/
7791: } /* end covariate */
1.227 brouard 7792:
7793:
1.220 brouard 7794: /* 7eme */
1.296 brouard 7795: if(prevbcast == 1){
1.288 brouard 7796: /* CV backward prevalence for each covariate */
1.237 brouard 7797: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7798: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7799: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7800: continue;
1.268 brouard 7801: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 7802: strcpy(gplotlabel,"(");
1.288 brouard 7803: fprintf(ficgp,"\n#\n#\n#CV Backward stable prevalence: 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 7804: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7805: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7806: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7807: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
1.223 brouard 7808: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.227 brouard 7809: vlv= nbcode[Tvaraff[k]][lv];
7810: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7811: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 7812: }
1.237 brouard 7813: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7814: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7815: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7816: }
1.264 brouard 7817: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 7818: fprintf(ficgp,"\n#\n");
7819: if(invalidvarcomb[k1]){
7820: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7821: continue;
7822: }
7823:
1.241 brouard 7824: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 7825: 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 7826: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7827: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 7828: k=3; /* Offset */
1.268 brouard 7829: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 7830: if(i==1)
7831: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
7832: else
7833: fprintf(ficgp,", '' ");
7834: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 7835: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7836: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
7837: /* 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 7838: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 7839: /* for (j=2; j<= nlstate ; j ++) */
7840: /* fprintf(ficgp,"+$%d",k+l+j-1); */
7841: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 7842: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 7843: } /* nlstate */
1.264 brouard 7844: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 7845: } /* end cpt state*/
7846: } /* end covariate */
1.296 brouard 7847: } /* End if prevbcast */
1.218 brouard 7848:
1.223 brouard 7849: /* 8eme */
1.218 brouard 7850: if(prevfcast==1){
1.288 brouard 7851: /* Projection from cross-sectional to forward stable (period) prevalence for each covariate */
1.218 brouard 7852:
1.237 brouard 7853: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7854: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7855: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7856: continue;
1.211 brouard 7857: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 7858: strcpy(gplotlabel,"(");
1.288 brouard 7859: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to forward stable prevalence (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 7860: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7861: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7862: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7863: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7864: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7865: vlv= nbcode[Tvaraff[k]][lv];
7866: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7867: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 7868: }
1.237 brouard 7869: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7870: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7871: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7872: }
1.264 brouard 7873: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 7874: fprintf(ficgp,"\n#\n");
7875: if(invalidvarcomb[k1]){
7876: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7877: continue;
7878: }
7879:
7880: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 7881: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 7882: 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 7883: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 7884: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 7885:
7886: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
7887: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
7888: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
7889: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 7890: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7891: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7892: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7893: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 7894: if(i==istart){
1.227 brouard 7895: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
7896: }else{
7897: fprintf(ficgp,",\\\n '' ");
7898: }
7899: if(cptcoveff ==0){ /* No covariate */
7900: ioffset=2; /* Age is in 2 */
7901: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7902: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7903: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7904: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7905: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 7906: if(i==nlstate+1){
1.270 brouard 7907: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 7908: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
7909: fprintf(ficgp,",\\\n '' ");
7910: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 7911: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 7912: offyear, \
1.268 brouard 7913: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 7914: }else
1.227 brouard 7915: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
7916: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
7917: }else{ /* more than 2 covariates */
1.270 brouard 7918: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
7919: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7920: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7921: iyearc=ioffset-1;
7922: iagec=ioffset;
1.227 brouard 7923: fprintf(ficgp," u %d:(",ioffset);
7924: kl=0;
7925: strcpy(gplotcondition,"(");
7926: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
7927: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
7928: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7929: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7930: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7931: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
7932: kl++;
7933: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
7934: kl++;
7935: if(k <cptcoveff && cptcoveff>1)
7936: sprintf(gplotcondition+strlen(gplotcondition)," && ");
7937: }
7938: strcpy(gplotcondition+strlen(gplotcondition),")");
7939: /* 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 *\/ */
7940: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7941: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7942: /* '' 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*/
7943: if(i==nlstate+1){
1.270 brouard 7944: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
7945: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 7946: fprintf(ficgp,",\\\n '' ");
1.270 brouard 7947: fprintf(ficgp," u %d:(",iagec);
7948: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
7949: iyearc, iagec, offyear, \
7950: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 7951: /* '' 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 7952: }else{
7953: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
7954: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
7955: }
7956: } /* end if covariate */
7957: } /* nlstate */
1.264 brouard 7958: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 7959: } /* end cpt state*/
7960: } /* end covariate */
7961: } /* End if prevfcast */
1.227 brouard 7962:
1.296 brouard 7963: if(prevbcast==1){
1.268 brouard 7964: /* Back projection from cross-sectional to stable (mixed) for each covariate */
7965:
7966: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7967: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
7968: if(m != 1 && TKresult[nres]!= k1)
7969: continue;
7970: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
7971: strcpy(gplotlabel,"(");
7972: fprintf(ficgp,"\n#\n#\n#Back projection of prevalence to stable (mixed) back prevalence: 'BPROJ_' files, covariatecombination#=%d originstate=%d",k1, cpt);
7973: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7974: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7975: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7976: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7977: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7978: vlv= nbcode[Tvaraff[k]][lv];
7979: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
7980: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
7981: }
7982: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7983: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7984: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7985: }
7986: strcpy(gplotlabel+strlen(gplotlabel),")");
7987: fprintf(ficgp,"\n#\n");
7988: if(invalidvarcomb[k1]){
7989: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7990: continue;
7991: }
7992:
7993: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
7994: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
7995: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
7996: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
7997: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7998:
7999: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
8000: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
8001: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
8002: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
8003: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8004: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8005: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8006: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8007: if(i==istart){
8008: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
8009: }else{
8010: fprintf(ficgp,",\\\n '' ");
8011: }
8012: if(cptcoveff ==0){ /* No covariate */
8013: ioffset=2; /* Age is in 2 */
8014: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8015: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8016: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8017: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8018: fprintf(ficgp," u %d:(", ioffset);
8019: if(i==nlstate+1){
1.270 brouard 8020: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 8021: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
8022: fprintf(ficgp,",\\\n '' ");
8023: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 8024: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 8025: offbyear, \
8026: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
8027: }else
8028: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
8029: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
8030: }else{ /* more than 2 covariates */
1.270 brouard 8031: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
8032: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8033: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8034: iyearc=ioffset-1;
8035: iagec=ioffset;
1.268 brouard 8036: fprintf(ficgp," u %d:(",ioffset);
8037: kl=0;
8038: strcpy(gplotcondition,"(");
8039: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
8040: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
8041: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8042: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8043: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8044: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
8045: kl++;
8046: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
8047: kl++;
8048: if(k <cptcoveff && cptcoveff>1)
8049: sprintf(gplotcondition+strlen(gplotcondition)," && ");
8050: }
8051: strcpy(gplotcondition+strlen(gplotcondition),")");
8052: /* 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 *\/ */
8053: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8054: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8055: /* '' 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*/
8056: if(i==nlstate+1){
1.270 brouard 8057: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
8058: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 8059: fprintf(ficgp,",\\\n '' ");
1.270 brouard 8060: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 8061: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 brouard 8062: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
8063: iyearc,iagec,offbyear, \
8064: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 8065: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
8066: }else{
8067: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
8068: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
8069: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
8070: }
8071: } /* end if covariate */
8072: } /* nlstate */
8073: fprintf(ficgp,"\nset out; unset label;\n");
8074: } /* end cpt state*/
8075: } /* end covariate */
1.296 brouard 8076: } /* End if prevbcast */
1.268 brouard 8077:
1.227 brouard 8078:
1.238 brouard 8079: /* 9eme writing MLE parameters */
8080: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 8081: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 8082: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 8083: for(k=1; k <=(nlstate+ndeath); k++){
8084: if (k != i) {
1.227 brouard 8085: fprintf(ficgp,"# current state %d\n",k);
8086: for(j=1; j <=ncovmodel; j++){
8087: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
8088: jk++;
8089: }
8090: fprintf(ficgp,"\n");
1.126 brouard 8091: }
8092: }
1.223 brouard 8093: }
1.187 brouard 8094: fprintf(ficgp,"##############\n#\n");
1.227 brouard 8095:
1.145 brouard 8096: /*goto avoid;*/
1.238 brouard 8097: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
8098: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 8099: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
8100: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
8101: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
8102: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
8103: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
8104: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
8105: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
8106: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
8107: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
8108: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
8109: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
8110: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
8111: fprintf(ficgp,"#\n");
1.223 brouard 8112: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 8113: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.237 brouard 8114: fprintf(ficgp,"#model=%s \n",model);
1.238 brouard 8115: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.264 brouard 8116: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/* to be checked */
8117: for(k1=1; k1 <=m; k1++) /* For each combination of covariate */
1.237 brouard 8118: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.264 brouard 8119: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 8120: continue;
1.264 brouard 8121: fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1);
8122: strcpy(gplotlabel,"(");
1.276 brouard 8123: /*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*/
1.264 brouard 8124: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
8125: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
8126: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8127: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8128: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8129: vlv= nbcode[Tvaraff[k]][lv];
8130: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
8131: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
8132: }
1.237 brouard 8133: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8134: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 8135: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 8136: }
1.264 brouard 8137: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 8138: fprintf(ficgp,"\n#\n");
1.264 brouard 8139: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
1.276 brouard 8140: fprintf(ficgp,"\nset key outside ");
8141: /* fprintf(ficgp,"\nset label \"%s\" at graph 1.2,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel); */
8142: fprintf(ficgp,"\nset title \"%s\" font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 8143: fprintf(ficgp,"\nset ter svg size 640, 480 ");
8144: if (ng==1){
8145: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
8146: fprintf(ficgp,"\nunset log y");
8147: }else if (ng==2){
8148: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
8149: fprintf(ficgp,"\nset log y");
8150: }else if (ng==3){
8151: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
8152: fprintf(ficgp,"\nset log y");
8153: }else
8154: fprintf(ficgp,"\nunset title ");
8155: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
8156: i=1;
8157: for(k2=1; k2<=nlstate; k2++) {
8158: k3=i;
8159: for(k=1; k<=(nlstate+ndeath); k++) {
8160: if (k != k2){
8161: switch( ng) {
8162: case 1:
8163: if(nagesqr==0)
8164: fprintf(ficgp," p%d+p%d*x",i,i+1);
8165: else /* nagesqr =1 */
8166: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
8167: break;
8168: case 2: /* ng=2 */
8169: if(nagesqr==0)
8170: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
8171: else /* nagesqr =1 */
8172: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
8173: break;
8174: case 3:
8175: if(nagesqr==0)
8176: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
8177: else /* nagesqr =1 */
8178: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
8179: break;
8180: }
8181: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 8182: ijp=1; /* product no age */
8183: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
8184: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 8185: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.268 brouard 8186: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
8187: if(j==Tage[ij]) { /* Product by age To be looked at!!*/
8188: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
8189: if(DummyV[j]==0){
8190: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
8191: }else{ /* quantitative */
8192: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
8193: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
8194: }
8195: ij++;
1.237 brouard 8196: }
1.268 brouard 8197: }
8198: }else if(cptcovprod >0){
8199: if(j==Tprod[ijp]) { /* */
8200: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
8201: if(ijp <=cptcovprod) { /* Product */
8202: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
8203: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
8204: /* 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)]); */
8205: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
8206: }else{ /* Vn is dummy and Vm is quanti */
8207: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
8208: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
8209: }
8210: }else{ /* Vn*Vm Vn is quanti */
8211: if(DummyV[Tvard[ijp][2]]==0){
8212: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
8213: }else{ /* Both quanti */
8214: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
8215: }
1.237 brouard 8216: }
1.268 brouard 8217: ijp++;
1.237 brouard 8218: }
1.268 brouard 8219: } /* end Tprod */
1.237 brouard 8220: } else{ /* simple covariate */
1.264 brouard 8221: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 8222: if(Dummy[j]==0){
8223: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
8224: }else{ /* quantitative */
8225: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 8226: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 8227: }
1.237 brouard 8228: } /* end simple */
8229: } /* end j */
1.223 brouard 8230: }else{
8231: i=i-ncovmodel;
8232: if(ng !=1 ) /* For logit formula of log p11 is more difficult to get */
8233: fprintf(ficgp," (1.");
8234: }
1.227 brouard 8235:
1.223 brouard 8236: if(ng != 1){
8237: fprintf(ficgp,")/(1");
1.227 brouard 8238:
1.264 brouard 8239: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 8240: if(nagesqr==0)
1.264 brouard 8241: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 8242: else /* nagesqr =1 */
1.264 brouard 8243: 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 8244:
1.223 brouard 8245: ij=1;
8246: for(j=3; j <=ncovmodel-nagesqr; j++){
1.268 brouard 8247: if(cptcovage >0){
8248: if((j-2)==Tage[ij]) { /* Bug valgrind */
8249: if(ij <=cptcovage) { /* Bug valgrind */
8250: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);
8251: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
8252: ij++;
8253: }
8254: }
8255: }else
8256: fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);/* Valgrind bug nbcode */
1.223 brouard 8257: }
8258: fprintf(ficgp,")");
8259: }
8260: fprintf(ficgp,")");
8261: if(ng ==2)
1.276 brouard 8262: 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 8263: else /* ng= 3 */
1.276 brouard 8264: fprintf(ficgp," w l lw 2 lt (%d*%d+%d)%%%d+1 dt %d t \"i%d%d\" ", nlstate+ndeath, k2, k, nlstate+ndeath, k2, k2,k);
1.223 brouard 8265: }else{ /* end ng <> 1 */
8266: if( k !=k2) /* logit p11 is hard to draw */
1.276 brouard 8267: 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 8268: }
8269: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
8270: fprintf(ficgp,",");
8271: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
8272: fprintf(ficgp,",");
8273: i=i+ncovmodel;
8274: } /* end k */
8275: } /* end k2 */
1.276 brouard 8276: /* fprintf(ficgp,"\n set out; unset label;set key default;\n"); */
8277: fprintf(ficgp,"\n set out; unset title;set key default;\n");
1.264 brouard 8278: } /* end k1 */
1.223 brouard 8279: } /* end ng */
8280: /* avoid: */
8281: fflush(ficgp);
1.126 brouard 8282: } /* end gnuplot */
8283:
8284:
8285: /*************** Moving average **************/
1.219 brouard 8286: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 8287: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 8288:
1.222 brouard 8289: int i, cpt, cptcod;
8290: int modcovmax =1;
8291: int mobilavrange, mob;
8292: int iage=0;
1.288 brouard 8293: int firstA1=0, firstA2=0;
1.222 brouard 8294:
1.266 brouard 8295: double sum=0., sumr=0.;
1.222 brouard 8296: double age;
1.266 brouard 8297: double *sumnewp, *sumnewm, *sumnewmr;
8298: double *agemingood, *agemaxgood;
8299: double *agemingoodr, *agemaxgoodr;
1.222 brouard 8300:
8301:
1.278 brouard 8302: /* modcovmax=2*cptcoveff; Max number of modalities. We suppose */
8303: /* a covariate has 2 modalities, should be equal to ncovcombmax */
1.222 brouard 8304:
8305: sumnewp = vector(1,ncovcombmax);
8306: sumnewm = vector(1,ncovcombmax);
1.266 brouard 8307: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 8308: agemingood = vector(1,ncovcombmax);
1.266 brouard 8309: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 8310: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 8311: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 8312:
8313: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 8314: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 8315: sumnewp[cptcod]=0.;
1.266 brouard 8316: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
8317: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 8318: }
8319: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
8320:
1.266 brouard 8321: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
8322: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 8323: else mobilavrange=mobilav;
8324: for (age=bage; age<=fage; age++)
8325: for (i=1; i<=nlstate;i++)
8326: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
8327: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8328: /* We keep the original values on the extreme ages bage, fage and for
8329: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
8330: we use a 5 terms etc. until the borders are no more concerned.
8331: */
8332: for (mob=3;mob <=mobilavrange;mob=mob+2){
8333: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 8334: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
8335: sumnewm[cptcod]=0.;
8336: for (i=1; i<=nlstate;i++){
1.222 brouard 8337: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
8338: for (cpt=1;cpt<=(mob-1)/2;cpt++){
8339: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
8340: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
8341: }
8342: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 8343: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8344: } /* end i */
8345: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
8346: } /* end cptcod */
1.222 brouard 8347: }/* end age */
8348: }/* end mob */
1.266 brouard 8349: }else{
8350: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 8351: return -1;
1.266 brouard 8352: }
8353:
8354: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 8355: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
8356: if(invalidvarcomb[cptcod]){
8357: printf("\nCombination (%d) ignored because no cases \n",cptcod);
8358: continue;
8359: }
1.219 brouard 8360:
1.266 brouard 8361: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
8362: sumnewm[cptcod]=0.;
8363: sumnewmr[cptcod]=0.;
8364: for (i=1; i<=nlstate;i++){
8365: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8366: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8367: }
8368: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8369: agemingoodr[cptcod]=age;
8370: }
8371: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8372: agemingood[cptcod]=age;
8373: }
8374: } /* age */
8375: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 8376: sumnewm[cptcod]=0.;
1.266 brouard 8377: sumnewmr[cptcod]=0.;
1.222 brouard 8378: for (i=1; i<=nlstate;i++){
8379: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8380: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8381: }
8382: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8383: agemaxgoodr[cptcod]=age;
1.222 brouard 8384: }
8385: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 8386: agemaxgood[cptcod]=age;
8387: }
8388: } /* age */
8389: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
8390: /* but they will change */
1.288 brouard 8391: firstA1=0;firstA2=0;
1.266 brouard 8392: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
8393: sumnewm[cptcod]=0.;
8394: sumnewmr[cptcod]=0.;
8395: for (i=1; i<=nlstate;i++){
8396: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8397: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8398: }
8399: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8400: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8401: agemaxgoodr[cptcod]=age; /* age min */
8402: for (i=1; i<=nlstate;i++)
8403: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8404: }else{ /* bad we change the value with the values of good ages */
8405: for (i=1; i<=nlstate;i++){
8406: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
8407: } /* i */
8408: } /* end bad */
8409: }else{
8410: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8411: agemaxgood[cptcod]=age;
8412: }else{ /* bad we change the value with the values of good ages */
8413: for (i=1; i<=nlstate;i++){
8414: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
8415: } /* i */
8416: } /* end bad */
8417: }/* end else */
8418: sum=0.;sumr=0.;
8419: for (i=1; i<=nlstate;i++){
8420: sum+=mobaverage[(int)age][i][cptcod];
8421: sumr+=probs[(int)age][i][cptcod];
8422: }
8423: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.288 brouard 8424: if(!firstA1){
8425: firstA1=1;
8426: 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);
8427: }
8428: 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 8429: } /* end bad */
8430: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8431: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.288 brouard 8432: if(!firstA2){
8433: firstA2=1;
8434: 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);
8435: }
8436: 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 8437: } /* end bad */
8438: }/* age */
1.266 brouard 8439:
8440: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 8441: sumnewm[cptcod]=0.;
1.266 brouard 8442: sumnewmr[cptcod]=0.;
1.222 brouard 8443: for (i=1; i<=nlstate;i++){
8444: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8445: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8446: }
8447: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8448: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
8449: agemingoodr[cptcod]=age;
8450: for (i=1; i<=nlstate;i++)
8451: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8452: }else{ /* bad we change the value with the values of good ages */
8453: for (i=1; i<=nlstate;i++){
8454: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
8455: } /* i */
8456: } /* end bad */
8457: }else{
8458: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8459: agemingood[cptcod]=age;
8460: }else{ /* bad */
8461: for (i=1; i<=nlstate;i++){
8462: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
8463: } /* i */
8464: } /* end bad */
8465: }/* end else */
8466: sum=0.;sumr=0.;
8467: for (i=1; i<=nlstate;i++){
8468: sum+=mobaverage[(int)age][i][cptcod];
8469: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 8470: }
1.266 brouard 8471: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 8472: 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 8473: } /* end bad */
8474: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8475: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 8476: 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 8477: } /* end bad */
8478: }/* age */
1.266 brouard 8479:
1.222 brouard 8480:
8481: for (age=bage; age<=fage; age++){
1.235 brouard 8482: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 8483: sumnewp[cptcod]=0.;
8484: sumnewm[cptcod]=0.;
8485: for (i=1; i<=nlstate;i++){
8486: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
8487: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8488: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
8489: }
8490: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
8491: }
8492: /* printf("\n"); */
8493: /* } */
1.266 brouard 8494:
1.222 brouard 8495: /* brutal averaging */
1.266 brouard 8496: /* for (i=1; i<=nlstate;i++){ */
8497: /* for (age=1; age<=bage; age++){ */
8498: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
8499: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8500: /* } */
8501: /* for (age=fage; age<=AGESUP; age++){ */
8502: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
8503: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8504: /* } */
8505: /* } /\* end i status *\/ */
8506: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
8507: /* for (age=1; age<=AGESUP; age++){ */
8508: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
8509: /* mobaverage[(int)age][i][cptcod]=0.; */
8510: /* } */
8511: /* } */
1.222 brouard 8512: }/* end cptcod */
1.266 brouard 8513: free_vector(agemaxgoodr,1, ncovcombmax);
8514: free_vector(agemaxgood,1, ncovcombmax);
8515: free_vector(agemingood,1, ncovcombmax);
8516: free_vector(agemingoodr,1, ncovcombmax);
8517: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 8518: free_vector(sumnewm,1, ncovcombmax);
8519: free_vector(sumnewp,1, ncovcombmax);
8520: return 0;
8521: }/* End movingaverage */
1.218 brouard 8522:
1.126 brouard 8523:
1.296 brouard 8524:
1.126 brouard 8525: /************** Forecasting ******************/
1.296 brouard 8526: /* 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)*/
8527: 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){
8528: /* dateintemean, mean date of interviews
8529: dateprojd, year, month, day of starting projection
8530: dateprojf date of end of projection;year of end of projection (same day and month as proj1).
1.126 brouard 8531: agemin, agemax range of age
8532: dateprev1 dateprev2 range of dates during which prevalence is computed
8533: */
1.296 brouard 8534: /* double anprojd, mprojd, jprojd; */
8535: /* double anprojf, mprojf, jprojf; */
1.267 brouard 8536: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 8537: double agec; /* generic age */
1.296 brouard 8538: double agelim, ppij, yp,yp1,yp2;
1.126 brouard 8539: double *popeffectif,*popcount;
8540: double ***p3mat;
1.218 brouard 8541: /* double ***mobaverage; */
1.126 brouard 8542: char fileresf[FILENAMELENGTH];
8543:
8544: agelim=AGESUP;
1.211 brouard 8545: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8546: in each health status at the date of interview (if between dateprev1 and dateprev2).
8547: We still use firstpass and lastpass as another selection.
8548: */
1.214 brouard 8549: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8550: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 8551:
1.201 brouard 8552: strcpy(fileresf,"F_");
8553: strcat(fileresf,fileresu);
1.126 brouard 8554: if((ficresf=fopen(fileresf,"w"))==NULL) {
8555: printf("Problem with forecast resultfile: %s\n", fileresf);
8556: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
8557: }
1.235 brouard 8558: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
8559: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 8560:
1.225 brouard 8561: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 8562:
8563:
8564: stepsize=(int) (stepm+YEARM-1)/YEARM;
8565: if (stepm<=12) stepsize=1;
8566: if(estepm < stepm){
8567: printf ("Problem %d lower than %d\n",estepm, stepm);
8568: }
1.270 brouard 8569: else{
8570: hstepm=estepm;
8571: }
8572: if(estepm > stepm){ /* Yes every two year */
8573: stepsize=2;
8574: }
1.296 brouard 8575: hstepm=hstepm/stepm;
1.126 brouard 8576:
1.296 brouard 8577:
8578: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
8579: /* fractional in yp1 *\/ */
8580: /* aintmean=yp; */
8581: /* yp2=modf((yp1*12),&yp); */
8582: /* mintmean=yp; */
8583: /* yp1=modf((yp2*30.5),&yp); */
8584: /* jintmean=yp; */
8585: /* if(jintmean==0) jintmean=1; */
8586: /* if(mintmean==0) mintmean=1; */
1.126 brouard 8587:
1.296 brouard 8588:
8589: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */
8590: /* date2dmy(dateprojd,&jprojd, &mprojd, &anprojd); */
8591: /* date2dmy(dateprojf,&jprojf, &mprojf, &anprojf); */
1.227 brouard 8592: i1=pow(2,cptcoveff);
1.126 brouard 8593: if (cptcovn < 1){i1=1;}
8594:
1.296 brouard 8595: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.126 brouard 8596:
8597: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 8598:
1.126 brouard 8599: /* if (h==(int)(YEARM*yearp)){ */
1.235 brouard 8600: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8601: for(k=1; k<=i1;k++){
1.253 brouard 8602: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 8603: continue;
1.227 brouard 8604: if(invalidvarcomb[k]){
8605: printf("\nCombination (%d) projection ignored because no cases \n",k);
8606: continue;
8607: }
8608: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
8609: for(j=1;j<=cptcoveff;j++) {
8610: fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8611: }
1.235 brouard 8612: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 8613: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.235 brouard 8614: }
1.227 brouard 8615: fprintf(ficresf," yearproj age");
8616: for(j=1; j<=nlstate+ndeath;j++){
8617: for(i=1; i<=nlstate;i++)
8618: fprintf(ficresf," p%d%d",i,j);
8619: fprintf(ficresf," wp.%d",j);
8620: }
1.296 brouard 8621: for (yearp=0; yearp<=(anprojf-anprojd);yearp +=stepsize) {
1.227 brouard 8622: fprintf(ficresf,"\n");
1.296 brouard 8623: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jprojd,mprojd,anprojd+yearp);
1.270 brouard 8624: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
8625: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 8626: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
8627: nhstepm = nhstepm/hstepm;
8628: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8629: oldm=oldms;savm=savms;
1.268 brouard 8630: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 8631: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 8632: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 8633: for (h=0; h<=nhstepm; h++){
8634: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 8635: break;
8636: }
8637: }
8638: fprintf(ficresf,"\n");
8639: for(j=1;j<=cptcoveff;j++)
8640: fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.296 brouard 8641: fprintf(ficresf,"%.f %.f ",anprojd+yearp,agec+h*hstepm/YEARM*stepm);
1.268 brouard 8642:
8643: for(j=1; j<=nlstate+ndeath;j++) {
8644: ppij=0.;
8645: for(i=1; i<=nlstate;i++) {
1.278 brouard 8646: if (mobilav>=1)
8647: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
8648: else { /* even if mobilav==-1 we use mobaverage, probs may not sums to 1 */
8649: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
8650: }
1.268 brouard 8651: fprintf(ficresf," %.3f", p3mat[i][j][h]);
8652: } /* end i */
8653: fprintf(ficresf," %.3f", ppij);
8654: }/* end j */
1.227 brouard 8655: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8656: } /* end agec */
1.266 brouard 8657: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
8658: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 8659: } /* end yearp */
8660: } /* end k */
1.219 brouard 8661:
1.126 brouard 8662: fclose(ficresf);
1.215 brouard 8663: printf("End of Computing forecasting \n");
8664: fprintf(ficlog,"End of Computing forecasting\n");
8665:
1.126 brouard 8666: }
8667:
1.269 brouard 8668: /************** Back Forecasting ******************/
1.296 brouard 8669: /* 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){ */
8670: 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){
8671: /* back1, year, month, day of starting backprojection
1.267 brouard 8672: agemin, agemax range of age
8673: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 8674: anback2 year of end of backprojection (same day and month as back1).
8675: prevacurrent and prev are prevalences.
1.267 brouard 8676: */
8677: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
8678: double agec; /* generic age */
1.302 brouard 8679: double agelim, ppij, ppi, yp,yp1,yp2; /* ,jintmean,mintmean,aintmean;*/
1.267 brouard 8680: double *popeffectif,*popcount;
8681: double ***p3mat;
8682: /* double ***mobaverage; */
8683: char fileresfb[FILENAMELENGTH];
8684:
1.268 brouard 8685: agelim=AGEINF;
1.267 brouard 8686: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8687: in each health status at the date of interview (if between dateprev1 and dateprev2).
8688: We still use firstpass and lastpass as another selection.
8689: */
8690: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8691: /* firstpass, lastpass, stepm, weightopt, model); */
8692:
8693: /*Do we need to compute prevalence again?*/
8694:
8695: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
8696:
8697: strcpy(fileresfb,"FB_");
8698: strcat(fileresfb,fileresu);
8699: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
8700: printf("Problem with back forecast resultfile: %s\n", fileresfb);
8701: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
8702: }
8703: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8704: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8705:
8706: if (cptcoveff==0) ncodemax[cptcoveff]=1;
8707:
8708:
8709: stepsize=(int) (stepm+YEARM-1)/YEARM;
8710: if (stepm<=12) stepsize=1;
8711: if(estepm < stepm){
8712: printf ("Problem %d lower than %d\n",estepm, stepm);
8713: }
1.270 brouard 8714: else{
8715: hstepm=estepm;
8716: }
8717: if(estepm >= stepm){ /* Yes every two year */
8718: stepsize=2;
8719: }
1.267 brouard 8720:
8721: hstepm=hstepm/stepm;
1.296 brouard 8722: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
8723: /* fractional in yp1 *\/ */
8724: /* aintmean=yp; */
8725: /* yp2=modf((yp1*12),&yp); */
8726: /* mintmean=yp; */
8727: /* yp1=modf((yp2*30.5),&yp); */
8728: /* jintmean=yp; */
8729: /* if(jintmean==0) jintmean=1; */
8730: /* if(mintmean==0) jintmean=1; */
1.267 brouard 8731:
8732: i1=pow(2,cptcoveff);
8733: if (cptcovn < 1){i1=1;}
8734:
1.296 brouard 8735: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
8736: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 8737:
8738: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
8739:
8740: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8741: for(k=1; k<=i1;k++){
8742: if(i1 != 1 && TKresult[nres]!= k)
8743: continue;
8744: if(invalidvarcomb[k]){
8745: printf("\nCombination (%d) projection ignored because no cases \n",k);
8746: continue;
8747: }
1.268 brouard 8748: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.267 brouard 8749: for(j=1;j<=cptcoveff;j++) {
8750: fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8751: }
8752: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8753: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
8754: }
8755: fprintf(ficresfb," yearbproj age");
8756: for(j=1; j<=nlstate+ndeath;j++){
8757: for(i=1; i<=nlstate;i++)
1.268 brouard 8758: fprintf(ficresfb," b%d%d",i,j);
8759: fprintf(ficresfb," b.%d",j);
1.267 brouard 8760: }
1.296 brouard 8761: for (yearp=0; yearp>=(anbackf-anbackd);yearp -=stepsize) {
1.267 brouard 8762: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
8763: fprintf(ficresfb,"\n");
1.296 brouard 8764: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jbackd,mbackd,anbackd+yearp);
1.273 brouard 8765: /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
1.270 brouard 8766: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
8767: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 8768: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
1.271 brouard 8769: nhstepm=(int) (agec-agelim) *YEARM/stepm;/* nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
1.267 brouard 8770: nhstepm = nhstepm/hstepm;
8771: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8772: oldm=oldms;savm=savms;
1.268 brouard 8773: /* computes hbxij at age agec over 1 to nhstepm */
1.271 brouard 8774: /* printf("####prevbackforecast debug agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
1.267 brouard 8775: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 8776: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
8777: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
8778: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 8779: for (h=0; h<=nhstepm; h++){
1.268 brouard 8780: if (h*hstepm/YEARM*stepm ==-yearp) {
8781: break;
8782: }
8783: }
8784: fprintf(ficresfb,"\n");
8785: for(j=1;j<=cptcoveff;j++)
8786: fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.296 brouard 8787: fprintf(ficresfb,"%.f %.f ",anbackd+yearp,agec-h*hstepm/YEARM*stepm);
1.268 brouard 8788: for(i=1; i<=nlstate+ndeath;i++) {
8789: ppij=0.;ppi=0.;
8790: for(j=1; j<=nlstate;j++) {
8791: /* if (mobilav==1) */
1.269 brouard 8792: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
8793: ppi=ppi+prevacurrent[(int)agec][j][k];
8794: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
8795: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 8796: /* else { */
8797: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
8798: /* } */
1.268 brouard 8799: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
8800: } /* end j */
8801: if(ppi <0.99){
8802: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
8803: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
8804: }
8805: fprintf(ficresfb," %.3f", ppij);
8806: }/* end j */
1.267 brouard 8807: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8808: } /* end agec */
8809: } /* end yearp */
8810: } /* end k */
1.217 brouard 8811:
1.267 brouard 8812: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 8813:
1.267 brouard 8814: fclose(ficresfb);
8815: printf("End of Computing Back forecasting \n");
8816: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 8817:
1.267 brouard 8818: }
1.217 brouard 8819:
1.269 brouard 8820: /* Variance of prevalence limit: varprlim */
8821: 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 8822: /*------- Variance of forward period (stable) prevalence------*/
1.269 brouard 8823:
8824: char fileresvpl[FILENAMELENGTH];
8825: FILE *ficresvpl;
8826: double **oldm, **savm;
8827: double **varpl; /* Variances of prevalence limits by age */
8828: int i1, k, nres, j ;
8829:
8830: strcpy(fileresvpl,"VPL_");
8831: strcat(fileresvpl,fileresu);
8832: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
1.288 brouard 8833: printf("Problem with variance of forward period (stable) prevalence resultfile: %s\n", fileresvpl);
1.269 brouard 8834: exit(0);
8835: }
1.288 brouard 8836: printf("Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
8837: fprintf(ficlog, "Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
1.269 brouard 8838:
8839: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
8840: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
8841:
8842: i1=pow(2,cptcoveff);
8843: if (cptcovn < 1){i1=1;}
8844:
8845: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8846: for(k=1; k<=i1;k++){
8847: if(i1 != 1 && TKresult[nres]!= k)
8848: continue;
8849: fprintf(ficresvpl,"\n#****** ");
8850: printf("\n#****** ");
8851: fprintf(ficlog,"\n#****** ");
8852: for(j=1;j<=cptcoveff;j++) {
8853: fprintf(ficresvpl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8854: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8855: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8856: }
8857: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
8858: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8859: fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8860: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8861: }
8862: fprintf(ficresvpl,"******\n");
8863: printf("******\n");
8864: fprintf(ficlog,"******\n");
8865:
8866: varpl=matrix(1,nlstate,(int) bage, (int) fage);
8867: oldm=oldms;savm=savms;
8868: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
8869: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
8870: /*}*/
8871: }
8872:
8873: fclose(ficresvpl);
1.288 brouard 8874: printf("done variance-covariance of forward period prevalence\n");fflush(stdout);
8875: fprintf(ficlog,"done variance-covariance of forward period prevalence\n");fflush(ficlog);
1.269 brouard 8876:
8877: }
8878: /* Variance of back prevalence: varbprlim */
8879: 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){
8880: /*------- Variance of back (stable) prevalence------*/
8881:
8882: char fileresvbl[FILENAMELENGTH];
8883: FILE *ficresvbl;
8884:
8885: double **oldm, **savm;
8886: double **varbpl; /* Variances of back prevalence limits by age */
8887: int i1, k, nres, j ;
8888:
8889: strcpy(fileresvbl,"VBL_");
8890: strcat(fileresvbl,fileresu);
8891: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
8892: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
8893: exit(0);
8894: }
8895: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
8896: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
8897:
8898:
8899: i1=pow(2,cptcoveff);
8900: if (cptcovn < 1){i1=1;}
8901:
8902: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8903: for(k=1; k<=i1;k++){
8904: if(i1 != 1 && TKresult[nres]!= k)
8905: continue;
8906: fprintf(ficresvbl,"\n#****** ");
8907: printf("\n#****** ");
8908: fprintf(ficlog,"\n#****** ");
8909: for(j=1;j<=cptcoveff;j++) {
8910: fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8911: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8912: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8913: }
8914: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
8915: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8916: fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8917: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8918: }
8919: fprintf(ficresvbl,"******\n");
8920: printf("******\n");
8921: fprintf(ficlog,"******\n");
8922:
8923: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
8924: oldm=oldms;savm=savms;
8925:
8926: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
8927: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
8928: /*}*/
8929: }
8930:
8931: fclose(ficresvbl);
8932: printf("done variance-covariance of back prevalence\n");fflush(stdout);
8933: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
8934:
8935: } /* End of varbprlim */
8936:
1.126 brouard 8937: /************** Forecasting *****not tested NB*************/
1.227 brouard 8938: /* 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 8939:
1.227 brouard 8940: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
8941: /* int *popage; */
8942: /* double calagedatem, agelim, kk1, kk2; */
8943: /* double *popeffectif,*popcount; */
8944: /* double ***p3mat,***tabpop,***tabpopprev; */
8945: /* /\* double ***mobaverage; *\/ */
8946: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 8947:
1.227 brouard 8948: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8949: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8950: /* agelim=AGESUP; */
8951: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 8952:
1.227 brouard 8953: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 8954:
8955:
1.227 brouard 8956: /* strcpy(filerespop,"POP_"); */
8957: /* strcat(filerespop,fileresu); */
8958: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
8959: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
8960: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
8961: /* } */
8962: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
8963: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 8964:
1.227 brouard 8965: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 8966:
1.227 brouard 8967: /* /\* if (mobilav!=0) { *\/ */
8968: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
8969: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
8970: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
8971: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
8972: /* /\* } *\/ */
8973: /* /\* } *\/ */
1.126 brouard 8974:
1.227 brouard 8975: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
8976: /* if (stepm<=12) stepsize=1; */
1.126 brouard 8977:
1.227 brouard 8978: /* agelim=AGESUP; */
1.126 brouard 8979:
1.227 brouard 8980: /* hstepm=1; */
8981: /* hstepm=hstepm/stepm; */
1.218 brouard 8982:
1.227 brouard 8983: /* if (popforecast==1) { */
8984: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
8985: /* printf("Problem with population file : %s\n",popfile);exit(0); */
8986: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
8987: /* } */
8988: /* popage=ivector(0,AGESUP); */
8989: /* popeffectif=vector(0,AGESUP); */
8990: /* popcount=vector(0,AGESUP); */
1.126 brouard 8991:
1.227 brouard 8992: /* i=1; */
8993: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 8994:
1.227 brouard 8995: /* imx=i; */
8996: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
8997: /* } */
1.218 brouard 8998:
1.227 brouard 8999: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
9000: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
9001: /* k=k+1; */
9002: /* fprintf(ficrespop,"\n#******"); */
9003: /* for(j=1;j<=cptcoveff;j++) { */
9004: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
9005: /* } */
9006: /* fprintf(ficrespop,"******\n"); */
9007: /* fprintf(ficrespop,"# Age"); */
9008: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
9009: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 9010:
1.227 brouard 9011: /* for (cpt=0; cpt<=0;cpt++) { */
9012: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 9013:
1.227 brouard 9014: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
9015: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
9016: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 9017:
1.227 brouard 9018: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9019: /* oldm=oldms;savm=savms; */
9020: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 9021:
1.227 brouard 9022: /* for (h=0; h<=nhstepm; h++){ */
9023: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
9024: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
9025: /* } */
9026: /* for(j=1; j<=nlstate+ndeath;j++) { */
9027: /* kk1=0.;kk2=0; */
9028: /* for(i=1; i<=nlstate;i++) { */
9029: /* if (mobilav==1) */
9030: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
9031: /* else { */
9032: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
9033: /* } */
9034: /* } */
9035: /* if (h==(int)(calagedatem+12*cpt)){ */
9036: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
9037: /* /\*fprintf(ficrespop," %.3f", kk1); */
9038: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
9039: /* } */
9040: /* } */
9041: /* for(i=1; i<=nlstate;i++){ */
9042: /* kk1=0.; */
9043: /* for(j=1; j<=nlstate;j++){ */
9044: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
9045: /* } */
9046: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
9047: /* } */
1.218 brouard 9048:
1.227 brouard 9049: /* if (h==(int)(calagedatem+12*cpt)) */
9050: /* for(j=1; j<=nlstate;j++) */
9051: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
9052: /* } */
9053: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9054: /* } */
9055: /* } */
1.218 brouard 9056:
1.227 brouard 9057: /* /\******\/ */
1.218 brouard 9058:
1.227 brouard 9059: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
9060: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
9061: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
9062: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
9063: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 9064:
1.227 brouard 9065: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9066: /* oldm=oldms;savm=savms; */
9067: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
9068: /* for (h=0; h<=nhstepm; h++){ */
9069: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
9070: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
9071: /* } */
9072: /* for(j=1; j<=nlstate+ndeath;j++) { */
9073: /* kk1=0.;kk2=0; */
9074: /* for(i=1; i<=nlstate;i++) { */
9075: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
9076: /* } */
9077: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
9078: /* } */
9079: /* } */
9080: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9081: /* } */
9082: /* } */
9083: /* } */
9084: /* } */
1.218 brouard 9085:
1.227 brouard 9086: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 9087:
1.227 brouard 9088: /* if (popforecast==1) { */
9089: /* free_ivector(popage,0,AGESUP); */
9090: /* free_vector(popeffectif,0,AGESUP); */
9091: /* free_vector(popcount,0,AGESUP); */
9092: /* } */
9093: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9094: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9095: /* fclose(ficrespop); */
9096: /* } /\* End of popforecast *\/ */
1.218 brouard 9097:
1.126 brouard 9098: int fileappend(FILE *fichier, char *optionfich)
9099: {
9100: if((fichier=fopen(optionfich,"a"))==NULL) {
9101: printf("Problem with file: %s\n", optionfich);
9102: fprintf(ficlog,"Problem with file: %s\n", optionfich);
9103: return (0);
9104: }
9105: fflush(fichier);
9106: return (1);
9107: }
9108:
9109:
9110: /**************** function prwizard **********************/
9111: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
9112: {
9113:
9114: /* Wizard to print covariance matrix template */
9115:
1.164 brouard 9116: char ca[32], cb[32];
9117: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 9118: int numlinepar;
9119:
9120: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
9121: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
9122: for(i=1; i <=nlstate; i++){
9123: jj=0;
9124: for(j=1; j <=nlstate+ndeath; j++){
9125: if(j==i) continue;
9126: jj++;
9127: /*ca[0]= k+'a'-1;ca[1]='\0';*/
9128: printf("%1d%1d",i,j);
9129: fprintf(ficparo,"%1d%1d",i,j);
9130: for(k=1; k<=ncovmodel;k++){
9131: /* printf(" %lf",param[i][j][k]); */
9132: /* fprintf(ficparo," %lf",param[i][j][k]); */
9133: printf(" 0.");
9134: fprintf(ficparo," 0.");
9135: }
9136: printf("\n");
9137: fprintf(ficparo,"\n");
9138: }
9139: }
9140: printf("# Scales (for hessian or gradient estimation)\n");
9141: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
9142: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
9143: for(i=1; i <=nlstate; i++){
9144: jj=0;
9145: for(j=1; j <=nlstate+ndeath; j++){
9146: if(j==i) continue;
9147: jj++;
9148: fprintf(ficparo,"%1d%1d",i,j);
9149: printf("%1d%1d",i,j);
9150: fflush(stdout);
9151: for(k=1; k<=ncovmodel;k++){
9152: /* printf(" %le",delti3[i][j][k]); */
9153: /* fprintf(ficparo," %le",delti3[i][j][k]); */
9154: printf(" 0.");
9155: fprintf(ficparo," 0.");
9156: }
9157: numlinepar++;
9158: printf("\n");
9159: fprintf(ficparo,"\n");
9160: }
9161: }
9162: printf("# Covariance matrix\n");
9163: /* # 121 Var(a12)\n\ */
9164: /* # 122 Cov(b12,a12) Var(b12)\n\ */
9165: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
9166: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
9167: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
9168: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
9169: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
9170: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
9171: fflush(stdout);
9172: fprintf(ficparo,"# Covariance matrix\n");
9173: /* # 121 Var(a12)\n\ */
9174: /* # 122 Cov(b12,a12) Var(b12)\n\ */
9175: /* # ...\n\ */
9176: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
9177:
9178: for(itimes=1;itimes<=2;itimes++){
9179: jj=0;
9180: for(i=1; i <=nlstate; i++){
9181: for(j=1; j <=nlstate+ndeath; j++){
9182: if(j==i) continue;
9183: for(k=1; k<=ncovmodel;k++){
9184: jj++;
9185: ca[0]= k+'a'-1;ca[1]='\0';
9186: if(itimes==1){
9187: printf("#%1d%1d%d",i,j,k);
9188: fprintf(ficparo,"#%1d%1d%d",i,j,k);
9189: }else{
9190: printf("%1d%1d%d",i,j,k);
9191: fprintf(ficparo,"%1d%1d%d",i,j,k);
9192: /* printf(" %.5le",matcov[i][j]); */
9193: }
9194: ll=0;
9195: for(li=1;li <=nlstate; li++){
9196: for(lj=1;lj <=nlstate+ndeath; lj++){
9197: if(lj==li) continue;
9198: for(lk=1;lk<=ncovmodel;lk++){
9199: ll++;
9200: if(ll<=jj){
9201: cb[0]= lk +'a'-1;cb[1]='\0';
9202: if(ll<jj){
9203: if(itimes==1){
9204: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
9205: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
9206: }else{
9207: printf(" 0.");
9208: fprintf(ficparo," 0.");
9209: }
9210: }else{
9211: if(itimes==1){
9212: printf(" Var(%s%1d%1d)",ca,i,j);
9213: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
9214: }else{
9215: printf(" 0.");
9216: fprintf(ficparo," 0.");
9217: }
9218: }
9219: }
9220: } /* end lk */
9221: } /* end lj */
9222: } /* end li */
9223: printf("\n");
9224: fprintf(ficparo,"\n");
9225: numlinepar++;
9226: } /* end k*/
9227: } /*end j */
9228: } /* end i */
9229: } /* end itimes */
9230:
9231: } /* end of prwizard */
9232: /******************* Gompertz Likelihood ******************************/
9233: double gompertz(double x[])
9234: {
1.302 brouard 9235: double A=0.0,B=0.,L=0.0,sump=0.,num=0.;
1.126 brouard 9236: int i,n=0; /* n is the size of the sample */
9237:
1.220 brouard 9238: for (i=1;i<=imx ; i++) {
1.126 brouard 9239: sump=sump+weight[i];
9240: /* sump=sump+1;*/
9241: num=num+1;
9242: }
1.302 brouard 9243: L=0.0;
9244: /* agegomp=AGEGOMP; */
1.126 brouard 9245: /* for (i=0; i<=imx; i++)
9246: 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]);*/
9247:
1.302 brouard 9248: for (i=1;i<=imx ; i++) {
9249: /* mu(a)=mu(agecomp)*exp(teta*(age-agegomp))
9250: mu(a)=x[1]*exp(x[2]*(age-agegomp)); x[1] and x[2] are per year.
9251: * L= Product mu(agedeces)exp(-\int_ageexam^agedc mu(u) du ) for a death between agedc (in month)
9252: * and agedc +1 month, cens[i]=0: log(x[1]/YEARM)
9253: * +
9254: * exp(-\int_ageexam^agecens mu(u) du ) when censored, cens[i]=1
9255: */
9256: if (wav[i] > 1 || agedc[i] < AGESUP) {
9257: if (cens[i] == 1){
9258: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
9259: } else if (cens[i] == 0){
1.126 brouard 9260: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
1.302 brouard 9261: +log(x[1]/YEARM) +x[2]*(agedc[i]-agegomp)+log(YEARM);
9262: } else
9263: printf("Gompertz cens[%d] neither 1 nor 0\n",i);
1.126 brouard 9264: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
1.302 brouard 9265: L=L+A*weight[i];
1.126 brouard 9266: /* 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 9267: }
9268: }
1.126 brouard 9269:
1.302 brouard 9270: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
1.126 brouard 9271:
9272: return -2*L*num/sump;
9273: }
9274:
1.136 brouard 9275: #ifdef GSL
9276: /******************* Gompertz_f Likelihood ******************************/
9277: double gompertz_f(const gsl_vector *v, void *params)
9278: {
1.302 brouard 9279: double A=0.,B=0.,LL=0.0,sump=0.,num=0.;
1.136 brouard 9280: double *x= (double *) v->data;
9281: int i,n=0; /* n is the size of the sample */
9282:
9283: for (i=0;i<=imx-1 ; i++) {
9284: sump=sump+weight[i];
9285: /* sump=sump+1;*/
9286: num=num+1;
9287: }
9288:
9289:
9290: /* for (i=0; i<=imx; i++)
9291: 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]);*/
9292: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
9293: for (i=1;i<=imx ; i++)
9294: {
9295: if (cens[i] == 1 && wav[i]>1)
9296: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
9297:
9298: if (cens[i] == 0 && wav[i]>1)
9299: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
9300: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
9301:
9302: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
9303: if (wav[i] > 1 ) { /* ??? */
9304: LL=LL+A*weight[i];
9305: /* 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]);*/
9306: }
9307: }
9308:
9309: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
9310: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
9311:
9312: return -2*LL*num/sump;
9313: }
9314: #endif
9315:
1.126 brouard 9316: /******************* Printing html file ***********/
1.201 brouard 9317: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 9318: int lastpass, int stepm, int weightopt, char model[],\
9319: int imx, double p[],double **matcov,double agemortsup){
9320: int i,k;
9321:
9322: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
9323: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
9324: for (i=1;i<=2;i++)
9325: 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 9326: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 9327: fprintf(fichtm,"</ul>");
9328:
9329: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
9330:
9331: 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>");
9332:
9333: for (k=agegomp;k<(agemortsup-2);k++)
9334: 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]);
9335:
9336:
9337: fflush(fichtm);
9338: }
9339:
9340: /******************* Gnuplot file **************/
1.201 brouard 9341: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 9342:
9343: char dirfileres[132],optfileres[132];
1.164 brouard 9344:
1.126 brouard 9345: int ng;
9346:
9347:
9348: /*#ifdef windows */
9349: fprintf(ficgp,"cd \"%s\" \n",pathc);
9350: /*#endif */
9351:
9352:
9353: strcpy(dirfileres,optionfilefiname);
9354: strcpy(optfileres,"vpl");
1.199 brouard 9355: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 9356: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 9357: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 9358: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 9359: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
9360:
9361: }
9362:
1.136 brouard 9363: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
9364: {
1.126 brouard 9365:
1.136 brouard 9366: /*-------- data file ----------*/
9367: FILE *fic;
9368: char dummy[]=" ";
1.240 brouard 9369: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 9370: int lstra;
1.136 brouard 9371: int linei, month, year,iout;
1.302 brouard 9372: int noffset=0; /* This is the offset if BOM data file */
1.136 brouard 9373: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 9374: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 9375: char *stratrunc;
1.223 brouard 9376:
1.240 brouard 9377: DummyV=ivector(1,NCOVMAX); /* 1 to 3 */
9378: FixedV=ivector(1,NCOVMAX); /* 1 to 3 */
1.126 brouard 9379:
1.240 brouard 9380: for(v=1; v <=ncovcol;v++){
9381: DummyV[v]=0;
9382: FixedV[v]=0;
9383: }
9384: for(v=ncovcol+1; v <=ncovcol+nqv;v++){
9385: DummyV[v]=1;
9386: FixedV[v]=0;
9387: }
9388: for(v=ncovcol+nqv+1; v <=ncovcol+nqv+ntv;v++){
9389: DummyV[v]=0;
9390: FixedV[v]=1;
9391: }
9392: for(v=ncovcol+nqv+ntv+1; v <=ncovcol+nqv+ntv+nqtv;v++){
9393: DummyV[v]=1;
9394: FixedV[v]=1;
9395: }
9396: for(v=1; v <=ncovcol+nqv+ntv+nqtv;v++){
9397: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",v,v,DummyV[v],v,FixedV[v]);
9398: 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]);
9399: }
1.126 brouard 9400:
1.136 brouard 9401: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 9402: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
9403: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 9404: }
1.126 brouard 9405:
1.302 brouard 9406: /* Is it a BOM UTF-8 Windows file? */
9407: /* First data line */
9408: linei=0;
9409: while(fgets(line, MAXLINE, fic)) {
9410: noffset=0;
9411: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
9412: {
9413: noffset=noffset+3;
9414: printf("# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);fflush(stdout);
9415: fprintf(ficlog,"# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);
9416: fflush(ficlog); return 1;
9417: }
9418: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
9419: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
9420: {
9421: noffset=noffset+2;
1.304 brouard 9422: 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);
9423: 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 9424: fflush(ficlog); return 1;
9425: }
9426: else if( line[0] == 0 && line[1] == 0)
9427: {
9428: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
9429: noffset=noffset+4;
1.304 brouard 9430: 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);
9431: 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 9432: fflush(ficlog); return 1;
9433: }
9434: } else{
9435: ;/*printf(" Not a BOM file\n");*/
9436: }
9437: /* If line starts with a # it is a comment */
9438: if (line[noffset] == '#') {
9439: linei=linei+1;
9440: break;
9441: }else{
9442: break;
9443: }
9444: }
9445: fclose(fic);
9446: if((fic=fopen(datafile,"r"))==NULL) {
9447: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
9448: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
9449: }
9450: /* Not a Bom file */
9451:
1.136 brouard 9452: i=1;
9453: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
9454: linei=linei+1;
9455: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
9456: if(line[j] == '\t')
9457: line[j] = ' ';
9458: }
9459: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
9460: ;
9461: };
9462: line[j+1]=0; /* Trims blanks at end of line */
9463: if(line[0]=='#'){
9464: fprintf(ficlog,"Comment line\n%s\n",line);
9465: printf("Comment line\n%s\n",line);
9466: continue;
9467: }
9468: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 9469: strcpy(line, linetmp);
1.223 brouard 9470:
9471: /* Loops on waves */
9472: for (j=maxwav;j>=1;j--){
9473: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 9474: cutv(stra, strb, line, ' ');
9475: if(strb[0]=='.') { /* Missing value */
9476: lval=-1;
9477: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
9478: cotvar[j][ntv+iv][i]=-1; /* For performance reasons */
9479: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
9480: 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);
9481: 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);
9482: return 1;
9483: }
9484: }else{
9485: errno=0;
9486: /* what_kind_of_number(strb); */
9487: dval=strtod(strb,&endptr);
9488: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
9489: /* if(strb != endptr && *endptr == '\0') */
9490: /* dval=dlval; */
9491: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9492: if( strb[0]=='\0' || (*endptr != '\0')){
9493: 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);
9494: 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);
9495: return 1;
9496: }
9497: cotqvar[j][iv][i]=dval;
9498: cotvar[j][ntv+iv][i]=dval;
9499: }
9500: strcpy(line,stra);
1.223 brouard 9501: }/* end loop ntqv */
1.225 brouard 9502:
1.223 brouard 9503: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 9504: cutv(stra, strb, line, ' ');
9505: if(strb[0]=='.') { /* Missing value */
9506: lval=-1;
9507: }else{
9508: errno=0;
9509: lval=strtol(strb,&endptr,10);
9510: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9511: if( strb[0]=='\0' || (*endptr != '\0')){
9512: 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);
9513: 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);
9514: return 1;
9515: }
9516: }
9517: if(lval <-1 || lval >1){
9518: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.223 brouard 9519: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9520: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9521: For example, for multinomial values like 1, 2 and 3,\n \
9522: build V1=0 V2=0 for the reference value (1),\n \
9523: V1=1 V2=0 for (2) \n \
1.223 brouard 9524: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9525: output of IMaCh is often meaningless.\n \
1.223 brouard 9526: Exiting.\n",lval,linei, i,line,j);
1.238 brouard 9527: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.223 brouard 9528: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9529: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9530: For example, for multinomial values like 1, 2 and 3,\n \
9531: build V1=0 V2=0 for the reference value (1),\n \
9532: V1=1 V2=0 for (2) \n \
1.223 brouard 9533: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9534: output of IMaCh is often meaningless.\n \
1.223 brouard 9535: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.238 brouard 9536: return 1;
9537: }
9538: cotvar[j][iv][i]=(double)(lval);
9539: strcpy(line,stra);
1.223 brouard 9540: }/* end loop ntv */
1.225 brouard 9541:
1.223 brouard 9542: /* Statuses at wave */
1.137 brouard 9543: cutv(stra, strb, line, ' ');
1.223 brouard 9544: if(strb[0]=='.') { /* Missing value */
1.238 brouard 9545: lval=-1;
1.136 brouard 9546: }else{
1.238 brouard 9547: errno=0;
9548: lval=strtol(strb,&endptr,10);
9549: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9550: if( strb[0]=='\0' || (*endptr != '\0')){
9551: 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);
9552: 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);
9553: return 1;
9554: }
1.136 brouard 9555: }
1.225 brouard 9556:
1.136 brouard 9557: s[j][i]=lval;
1.225 brouard 9558:
1.223 brouard 9559: /* Date of Interview */
1.136 brouard 9560: strcpy(line,stra);
9561: cutv(stra, strb,line,' ');
1.169 brouard 9562: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9563: }
1.169 brouard 9564: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 9565: month=99;
9566: year=9999;
1.136 brouard 9567: }else{
1.225 brouard 9568: 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);
9569: 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);
9570: return 1;
1.136 brouard 9571: }
9572: anint[j][i]= (double) year;
1.302 brouard 9573: mint[j][i]= (double)month;
9574: /* if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){ */
9575: /* 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]); */
9576: /* 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]); */
9577: /* } */
1.136 brouard 9578: strcpy(line,stra);
1.223 brouard 9579: } /* End loop on waves */
1.225 brouard 9580:
1.223 brouard 9581: /* Date of death */
1.136 brouard 9582: cutv(stra, strb,line,' ');
1.169 brouard 9583: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9584: }
1.169 brouard 9585: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 9586: month=99;
9587: year=9999;
9588: }else{
1.141 brouard 9589: 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 9590: 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);
9591: return 1;
1.136 brouard 9592: }
9593: andc[i]=(double) year;
9594: moisdc[i]=(double) month;
9595: strcpy(line,stra);
9596:
1.223 brouard 9597: /* Date of birth */
1.136 brouard 9598: cutv(stra, strb,line,' ');
1.169 brouard 9599: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9600: }
1.169 brouard 9601: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 9602: month=99;
9603: year=9999;
9604: }else{
1.141 brouard 9605: 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);
9606: 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 9607: return 1;
1.136 brouard 9608: }
9609: if (year==9999) {
1.141 brouard 9610: 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);
9611: 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 9612: return 1;
9613:
1.136 brouard 9614: }
9615: annais[i]=(double)(year);
1.302 brouard 9616: moisnais[i]=(double)(month);
9617: for (j=1;j<=maxwav;j++){
9618: if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){
9619: 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]);
9620: 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]);
9621: }
9622: }
9623:
1.136 brouard 9624: strcpy(line,stra);
1.225 brouard 9625:
1.223 brouard 9626: /* Sample weight */
1.136 brouard 9627: cutv(stra, strb,line,' ');
9628: errno=0;
9629: dval=strtod(strb,&endptr);
9630: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 9631: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
9632: 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 9633: fflush(ficlog);
9634: return 1;
9635: }
9636: weight[i]=dval;
9637: strcpy(line,stra);
1.225 brouard 9638:
1.223 brouard 9639: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
9640: cutv(stra, strb, line, ' ');
9641: if(strb[0]=='.') { /* Missing value */
1.225 brouard 9642: lval=-1;
1.311 brouard 9643: coqvar[iv][i]=NAN;
9644: covar[ncovcol+iv][i]=NAN; /* including qvar in standard covar for performance reasons */
1.223 brouard 9645: }else{
1.225 brouard 9646: errno=0;
9647: /* what_kind_of_number(strb); */
9648: dval=strtod(strb,&endptr);
9649: /* if(strb != endptr && *endptr == '\0') */
9650: /* dval=dlval; */
9651: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9652: if( strb[0]=='\0' || (*endptr != '\0')){
9653: 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);
9654: 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);
9655: return 1;
9656: }
9657: coqvar[iv][i]=dval;
1.226 brouard 9658: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 9659: }
9660: strcpy(line,stra);
9661: }/* end loop nqv */
1.136 brouard 9662:
1.223 brouard 9663: /* Covariate values */
1.136 brouard 9664: for (j=ncovcol;j>=1;j--){
9665: cutv(stra, strb,line,' ');
1.223 brouard 9666: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 9667: lval=-1;
1.136 brouard 9668: }else{
1.225 brouard 9669: errno=0;
9670: lval=strtol(strb,&endptr,10);
9671: if( strb[0]=='\0' || (*endptr != '\0')){
9672: 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);
9673: 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);
9674: return 1;
9675: }
1.136 brouard 9676: }
9677: if(lval <-1 || lval >1){
1.225 brouard 9678: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9679: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9680: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9681: For example, for multinomial values like 1, 2 and 3,\n \
9682: build V1=0 V2=0 for the reference value (1),\n \
9683: V1=1 V2=0 for (2) \n \
1.136 brouard 9684: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9685: output of IMaCh is often meaningless.\n \
1.136 brouard 9686: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 9687: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9688: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9689: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9690: For example, for multinomial values like 1, 2 and 3,\n \
9691: build V1=0 V2=0 for the reference value (1),\n \
9692: V1=1 V2=0 for (2) \n \
1.136 brouard 9693: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9694: output of IMaCh is often meaningless.\n \
1.136 brouard 9695: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 9696: return 1;
1.136 brouard 9697: }
9698: covar[j][i]=(double)(lval);
9699: strcpy(line,stra);
9700: }
9701: lstra=strlen(stra);
1.225 brouard 9702:
1.136 brouard 9703: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
9704: stratrunc = &(stra[lstra-9]);
9705: num[i]=atol(stratrunc);
9706: }
9707: else
9708: num[i]=atol(stra);
9709: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
9710: 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;}*/
9711:
9712: i=i+1;
9713: } /* End loop reading data */
1.225 brouard 9714:
1.136 brouard 9715: *imax=i-1; /* Number of individuals */
9716: fclose(fic);
1.225 brouard 9717:
1.136 brouard 9718: return (0);
1.164 brouard 9719: /* endread: */
1.225 brouard 9720: printf("Exiting readdata: ");
9721: fclose(fic);
9722: return (1);
1.223 brouard 9723: }
1.126 brouard 9724:
1.234 brouard 9725: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 9726: char *p1 = *stri, *p2 = *stri;
1.235 brouard 9727: while (*p2 == ' ')
1.234 brouard 9728: p2++;
9729: /* while ((*p1++ = *p2++) !=0) */
9730: /* ; */
9731: /* do */
9732: /* while (*p2 == ' ') */
9733: /* p2++; */
9734: /* while (*p1++ == *p2++); */
9735: *stri=p2;
1.145 brouard 9736: }
9737:
1.235 brouard 9738: int decoderesult ( char resultline[], int nres)
1.230 brouard 9739: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
9740: {
1.235 brouard 9741: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 9742: char resultsav[MAXLINE];
1.234 brouard 9743: int resultmodel[MAXLINE];
9744: int modelresult[MAXLINE];
1.230 brouard 9745: char stra[80], strb[80], strc[80], strd[80],stre[80];
9746:
1.234 brouard 9747: removefirstspace(&resultline);
1.230 brouard 9748:
9749: if (strstr(resultline,"v") !=0){
9750: printf("Error. 'v' must be in upper case 'V' result: %s ",resultline);
9751: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultline);fflush(ficlog);
9752: return 1;
9753: }
9754: trimbb(resultsav, resultline);
9755: if (strlen(resultsav) >1){
9756: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' */
9757: }
1.253 brouard 9758: if(j == 0){ /* Resultline but no = */
9759: TKresult[nres]=0; /* Combination for the nresult and the model */
9760: return (0);
9761: }
1.234 brouard 9762: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
1.318 ! brouard 9763: 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 9764: 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 9765: }
9766: for(k=1; k<=j;k++){ /* Loop on any covariate of the result line */
9767: if(nbocc(resultsav,'=') >1){
1.318 ! brouard 9768: 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" */
! 9769: cutl(strc,strd,strb,'='); /* strb:"V4=1" strc="1" strd="V4" */
1.234 brouard 9770: }else
9771: cutl(strc,strd,resultsav,'=');
1.318 ! brouard 9772: Tvalsel[k]=atof(strc); /* 1 */ /* Tvalsel of k is the float value of the kth covariate appearing in this result line */
1.234 brouard 9773:
1.230 brouard 9774: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
1.318 ! brouard 9775: 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 9776: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
9777: /* cptcovsel++; */
9778: if (nbocc(stra,'=') >0)
9779: strcpy(resultsav,stra); /* and analyzes it */
9780: }
1.235 brouard 9781: /* Checking for missing or useless values in comparison of current model needs */
1.318 ! brouard 9782: for(k1=1; k1<= cptcovt ;k1++){ /* Loop on model. model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
! 9783: 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 9784: match=0;
1.318 ! brouard 9785: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
! 9786: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.236 brouard 9787: modelresult[k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.318 ! brouard 9788: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
1.234 brouard 9789: break;
9790: }
9791: }
9792: if(match == 0){
1.310 brouard 9793: printf("Error in result line: V%d is missing in result: %s according to model=%s\n",k1, resultline, model);
9794: fprintf(ficlog,"Error in result line: V%d is missing in result: %s according to model=%s\n",k1, resultline, model);
9795: return 1;
1.234 brouard 9796: }
9797: }
9798: }
1.235 brouard 9799: /* Checking for missing or useless values in comparison of current model needs */
1.318 ! brouard 9800: 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 9801: match=0;
1.318 ! brouard 9802: 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 9803: if(Typevar[k1]==0){ /* Single */
1.237 brouard 9804: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 */
1.318 ! brouard 9805: 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 9806: ++match;
9807: }
9808: }
9809: }
9810: if(match == 0){
9811: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
1.310 brouard 9812: fprintf(ficlog,"Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
9813: return 1;
1.234 brouard 9814: }else if(match > 1){
9815: printf("Error in result line: %d doubled; result: %s, model=%s\n",k2, resultline, model);
1.310 brouard 9816: fprintf(ficlog,"Error in result line: %d doubled; result: %s, model=%s\n",k2, resultline, model);
9817: return 1;
1.234 brouard 9818: }
9819: }
1.235 brouard 9820:
1.234 brouard 9821: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 9822: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9823: /* result line V4=1 V5=25.1 V3=0 V2=8 V1=1 */
9824: /* should give a combination of dummy V4=1, V3=0, V1=1 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 5 + (1offset) = 6*/
9825: /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
9826: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
9827: /* 1 0 0 0 */
9828: /* 2 1 0 0 */
9829: /* 3 0 1 0 */
9830: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 */
9831: /* 5 0 0 1 */
9832: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 */
9833: /* 7 0 1 1 */
9834: /* 8 1 1 1 */
1.237 brouard 9835: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
9836: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
9837: /* V5*age V5 known which value for nres? */
9838: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.318 ! brouard 9839: for(k1=1, k=0, k4=0, k4q=0; k1 <=cptcovt;k1++){ /* loop on model line */
1.235 brouard 9840: if( Dummy[k1]==0 && Typevar[k1]==0 ){ /* Single dummy */
1.237 brouard 9841: k3= resultmodel[k1]; /* resultmodel[2(V4)] = 1=k3 */
1.235 brouard 9842: k2=(int)Tvarsel[k3]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
9843: k+=Tvalsel[k3]*pow(2,k4); /* Tvalsel[1]=1 */
1.237 brouard 9844: Tresult[nres][k4+1]=Tvalsel[k3];/* Tresult[nres][1]=1(V4=1) Tresult[nres][2]=0(V3=0) */
9845: Tvresult[nres][k4+1]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
9846: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.235 brouard 9847: printf("Decoderesult Dummy k=%d, V(k2=V%d)= Tvalsel[%d]=%d, 2**(%d)\n",k, k2, k3, (int)Tvalsel[k3], k4);
9848: k4++;;
9849: } else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Single quantitative */
1.318 ! brouard 9850: k3q= resultmodel[k1]; /* resultmodel[1(V5)] = 25.1=k3q */
! 9851: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
1.237 brouard 9852: Tqresult[nres][k4q+1]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
9853: Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
9854: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.235 brouard 9855: printf("Decoderesult Quantitative nres=%d, V(k2q=V%d)= Tvalsel[%d]=%d, Tvarsel[%d]=%f\n",nres, k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]);
9856: k4q++;;
9857: }
9858: }
1.234 brouard 9859:
1.235 brouard 9860: TKresult[nres]=++k; /* Combination for the nresult and the model */
1.230 brouard 9861: return (0);
9862: }
1.235 brouard 9863:
1.230 brouard 9864: int decodemodel( char model[], int lastobs)
9865: /**< This routine decodes the model and returns:
1.224 brouard 9866: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
9867: * - nagesqr = 1 if age*age in the model, otherwise 0.
9868: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
9869: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
9870: * - cptcovage number of covariates with age*products =2
9871: * - cptcovs number of simple covariates
9872: * - 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
9873: * which is a new column after the 9 (ncovcol) variables.
9874: * - if k is a product Vn*Vm covar[k][i] is filled with correct values for each individual
9875: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
9876: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
9877: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
9878: */
1.136 brouard 9879: {
1.238 brouard 9880: int i, j, k, ks, v;
1.227 brouard 9881: int j1, k1, k2, k3, k4;
1.136 brouard 9882: char modelsav[80];
1.145 brouard 9883: char stra[80], strb[80], strc[80], strd[80],stre[80];
1.187 brouard 9884: char *strpt;
1.136 brouard 9885:
1.145 brouard 9886: /*removespace(model);*/
1.136 brouard 9887: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.145 brouard 9888: j=0, j1=0, k1=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 9889: if (strstr(model,"AGE") !=0){
1.192 brouard 9890: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
9891: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 9892: return 1;
9893: }
1.141 brouard 9894: if (strstr(model,"v") !=0){
9895: printf("Error. 'v' must be in upper case 'V' model=%s ",model);
9896: fprintf(ficlog,"Error. 'v' must be in upper case model=%s ",model);fflush(ficlog);
9897: return 1;
9898: }
1.187 brouard 9899: strcpy(modelsav,model);
9900: if ((strpt=strstr(model,"age*age")) !=0){
9901: printf(" strpt=%s, model=%s\n",strpt, model);
9902: if(strpt != model){
1.234 brouard 9903: printf("Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 9904: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 9905: corresponding column of parameters.\n",model);
1.234 brouard 9906: fprintf(ficlog,"Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 9907: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 9908: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 9909: return 1;
1.225 brouard 9910: }
1.187 brouard 9911: nagesqr=1;
9912: if (strstr(model,"+age*age") !=0)
1.234 brouard 9913: substrchaine(modelsav, model, "+age*age");
1.187 brouard 9914: else if (strstr(model,"age*age+") !=0)
1.234 brouard 9915: substrchaine(modelsav, model, "age*age+");
1.187 brouard 9916: else
1.234 brouard 9917: substrchaine(modelsav, model, "age*age");
1.187 brouard 9918: }else
9919: nagesqr=0;
9920: if (strlen(modelsav) >1){
9921: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
9922: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.224 brouard 9923: cptcovs=j+1-j1; /**< Number of simple covariates V1+V1*age+V3 +V3*V4+age*age=> V1 + V3 =5-3=2 */
1.187 brouard 9924: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 9925: * cst, age and age*age
9926: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
9927: /* including age products which are counted in cptcovage.
9928: * but the covariates which are products must be treated
9929: * separately: ncovn=4- 2=2 (V1+V3). */
1.187 brouard 9930: cptcovprod=j1; /**< Number of products V1*V2 +v3*age = 2 */
9931: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.225 brouard 9932:
9933:
1.187 brouard 9934: /* Design
9935: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
9936: * < ncovcol=8 >
9937: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
9938: * k= 1 2 3 4 5 6 7 8
9939: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
9940: * covar[k,i], value of kth covariate if not including age for individual i:
1.224 brouard 9941: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
9942: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 9943: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
9944: * Tage[++cptcovage]=k
9945: * if products, new covar are created after ncovcol with k1
9946: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
9947: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
9948: * 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
9949: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
9950: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
9951: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
9952: * < ncovcol=8 >
9953: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
9954: * k= 1 2 3 4 5 6 7 8 9 10 11 12
9955: * Tvar[k]= 2 1 3 3 10 11 8 8 5 6 7 8
9956: * p Tvar[1]@12={2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
9957: * p Tprod[1]@2={ 6, 5}
9958: *p Tvard[1][1]@4= {7, 8, 5, 6}
9959: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
9960: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
9961: *How to reorganize?
9962: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
9963: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
9964: * {2, 1, 4, 8, 5, 6, 3, 7}
9965: * Struct []
9966: */
1.225 brouard 9967:
1.187 brouard 9968: /* This loop fills the array Tvar from the string 'model'.*/
9969: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
9970: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
9971: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
9972: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
9973: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
9974: /* k=1 Tvar[1]=2 (from V2) */
9975: /* k=5 Tvar[5] */
9976: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 9977: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 9978: /* } */
1.198 brouard 9979: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 9980: /*
9981: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 9982: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
9983: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
9984: }
1.187 brouard 9985: cptcovage=0;
9986: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model */
1.234 brouard 9987: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+'
1.225 brouard 9988: modelsav==V2+V1+V4+V3*age strb=V3*age stra=V2+V1+V4 */
1.234 brouard 9989: if (nbocc(modelsav,'+')==0) strcpy(strb,modelsav); /* and analyzes it */
9990: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
9991: /*scanf("%d",i);*/
9992: if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V4+V3*age strb=V3*age */
9993: cutl(strc,strd,strb,'*'); /**< strd*strc Vm*Vn: strb=V3*age(input) strc=age strd=V3 ; V3*V2 strc=V2, strd=V3 */
9994: if (strcmp(strc,"age")==0) { /**< Model includes age: Vn*age */
9995: /* covar is not filled and then is empty */
9996: cptcovprod--;
9997: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
9998: Tvar[k]=atoi(stre); /* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1 */
9999: Typevar[k]=1; /* 1 for age product */
10000: cptcovage++; /* Sums the number of covariates which include age as a product */
10001: Tage[cptcovage]=k; /* Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */
10002: /*printf("stre=%s ", stre);*/
10003: } else if (strcmp(strd,"age")==0) { /* or age*Vn */
10004: cptcovprod--;
10005: cutl(stre,strb,strc,'V');
10006: Tvar[k]=atoi(stre);
10007: Typevar[k]=1; /* 1 for age product */
10008: cptcovage++;
10009: Tage[cptcovage]=k;
10010: } else { /* Age is not in the model product V2+V1+V1*V4+V3*age+V3*V2 strb=V3*V2*/
10011: /* loops on k1=1 (V3*V2) and k1=2 V4*V3 */
10012: cptcovn++;
10013: cptcovprodnoage++;k1++;
10014: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
10015: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* For model-covariate k tells which data-covariate to use but
10016: because this model-covariate is a construction we invent a new column
10017: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
10018: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2
10019: Tvar[3=V1*V4]=4+1 Tvar[5=V3*V2]=4 + 2= 6, etc */
10020: Typevar[k]=2; /* 2 for double fixed dummy covariates */
10021: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
10022: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 */
10023: Tposprod[k]=k1; /* Tpsprod[3]=1, Tposprod[2]=5 */
10024: Tvard[k1][1] =atoi(strc); /* m 1 for V1*/
10025: Tvard[k1][2] =atoi(stre); /* n 4 for V4*/
10026: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
10027: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
10028: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
1.225 brouard 10029: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
1.234 brouard 10030: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
10031: for (i=1; i<=lastobs;i++){
10032: /* Computes the new covariate which is a product of
10033: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
10034: covar[ncovcol+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
10035: }
10036: } /* End age is not in the model */
10037: } /* End if model includes a product */
10038: else { /* no more sum */
10039: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
10040: /* scanf("%d",i);*/
10041: cutl(strd,strc,strb,'V');
10042: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
10043: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
10044: Tvar[k]=atoi(strd);
10045: Typevar[k]=0; /* 0 for simple covariates */
10046: }
10047: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 10048: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 10049: scanf("%d",i);*/
1.187 brouard 10050: } /* end of loop + on total covariates */
10051: } /* end if strlen(modelsave == 0) age*age might exist */
10052: } /* end if strlen(model == 0) */
1.136 brouard 10053:
10054: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
10055: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 10056:
1.136 brouard 10057: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 10058: printf("cptcovprod=%d ", cptcovprod);
10059: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
10060: scanf("%d ",i);*/
10061:
10062:
1.230 brouard 10063: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
10064: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 10065: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
10066: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
10067: k = 1 2 3 4 5 6 7 8 9
10068: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
10069: Typevar[k]= 0 0 0 2 1 0 2 1 1
1.227 brouard 10070: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
10071: Dummy[k] 1 0 0 0 3 1 1 2 3
10072: Tmodelind[combination of covar]=k;
1.225 brouard 10073: */
10074: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 10075: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 10076: /* 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 10077: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.318 ! brouard 10078: printf("Model=1+age+%s\n\
1.227 brouard 10079: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
10080: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
10081: 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 10082: fprintf(ficlog,"Model=1+age+%s\n\
1.227 brouard 10083: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
10084: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
10085: 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 10086: for(k=-1;k<=cptcovt; k++){ Fixed[k]=0; Dummy[k]=0;}
1.234 brouard 10087: 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 */
10088: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 10089: Fixed[k]= 0;
10090: Dummy[k]= 0;
1.225 brouard 10091: ncoveff++;
1.232 brouard 10092: ncovf++;
1.234 brouard 10093: nsd++;
10094: modell[k].maintype= FTYPE;
10095: TvarsD[nsd]=Tvar[k];
10096: TvarsDind[nsd]=k;
10097: TvarF[ncovf]=Tvar[k];
10098: TvarFind[ncovf]=k;
10099: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
10100: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
10101: }else if( Tvar[k] <=ncovcol && Typevar[k]==2){ /* Product of fixed dummy (<=ncovcol) covariates */
10102: Fixed[k]= 0;
10103: Dummy[k]= 0;
10104: ncoveff++;
10105: ncovf++;
10106: modell[k].maintype= FTYPE;
10107: TvarF[ncovf]=Tvar[k];
10108: TvarFind[ncovf]=k;
1.230 brouard 10109: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.231 brouard 10110: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.240 brouard 10111: }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 10112: Fixed[k]= 0;
10113: Dummy[k]= 1;
1.230 brouard 10114: nqfveff++;
1.234 brouard 10115: modell[k].maintype= FTYPE;
10116: modell[k].subtype= FQ;
10117: nsq++;
10118: TvarsQ[nsq]=Tvar[k];
10119: TvarsQind[nsq]=k;
1.232 brouard 10120: ncovf++;
1.234 brouard 10121: TvarF[ncovf]=Tvar[k];
10122: TvarFind[ncovf]=k;
1.231 brouard 10123: 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 10124: 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 10125: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.227 brouard 10126: Fixed[k]= 1;
10127: Dummy[k]= 0;
1.225 brouard 10128: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 10129: modell[k].maintype= VTYPE;
10130: modell[k].subtype= VD;
10131: nsd++;
10132: TvarsD[nsd]=Tvar[k];
10133: TvarsDind[nsd]=k;
10134: ncovv++; /* Only simple time varying variables */
10135: TvarV[ncovv]=Tvar[k];
1.242 brouard 10136: 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 10137: 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 */
10138: 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 10139: 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);
10140: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 10141: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.234 brouard 10142: Fixed[k]= 1;
10143: Dummy[k]= 1;
10144: nqtveff++;
10145: modell[k].maintype= VTYPE;
10146: modell[k].subtype= VQ;
10147: ncovv++; /* Only simple time varying variables */
10148: nsq++;
10149: TvarsQ[nsq]=Tvar[k];
10150: TvarsQind[nsq]=k;
10151: TvarV[ncovv]=Tvar[k];
1.242 brouard 10152: 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 10153: 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 */
10154: 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 10155: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
10156: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
10157: 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 10158: printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv);
1.227 brouard 10159: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 10160: ncova++;
10161: TvarA[ncova]=Tvar[k];
10162: TvarAind[ncova]=k;
1.231 brouard 10163: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 10164: Fixed[k]= 2;
10165: Dummy[k]= 2;
10166: modell[k].maintype= ATYPE;
10167: modell[k].subtype= APFD;
10168: /* ncoveff++; */
1.227 brouard 10169: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 10170: Fixed[k]= 2;
10171: Dummy[k]= 3;
10172: modell[k].maintype= ATYPE;
10173: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
10174: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 10175: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 10176: Fixed[k]= 3;
10177: Dummy[k]= 2;
10178: modell[k].maintype= ATYPE;
10179: modell[k].subtype= APVD; /* Product age * varying dummy */
10180: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 10181: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 10182: Fixed[k]= 3;
10183: Dummy[k]= 3;
10184: modell[k].maintype= ATYPE;
10185: modell[k].subtype= APVQ; /* Product age * varying quantitative */
10186: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 10187: }
10188: }else if (Typevar[k] == 2) { /* product without age */
10189: k1=Tposprod[k];
10190: if(Tvard[k1][1] <=ncovcol){
1.240 brouard 10191: if(Tvard[k1][2] <=ncovcol){
10192: Fixed[k]= 1;
10193: Dummy[k]= 0;
10194: modell[k].maintype= FTYPE;
10195: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
10196: ncovf++; /* Fixed variables without age */
10197: TvarF[ncovf]=Tvar[k];
10198: TvarFind[ncovf]=k;
10199: }else if(Tvard[k1][2] <=ncovcol+nqv){
10200: Fixed[k]= 0; /* or 2 ?*/
10201: Dummy[k]= 1;
10202: modell[k].maintype= FTYPE;
10203: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
10204: ncovf++; /* Varying variables without age */
10205: TvarF[ncovf]=Tvar[k];
10206: TvarFind[ncovf]=k;
10207: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10208: Fixed[k]= 1;
10209: Dummy[k]= 0;
10210: modell[k].maintype= VTYPE;
10211: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
10212: ncovv++; /* Varying variables without age */
10213: TvarV[ncovv]=Tvar[k];
10214: TvarVind[ncovv]=k;
10215: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10216: Fixed[k]= 1;
10217: Dummy[k]= 1;
10218: modell[k].maintype= VTYPE;
10219: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
10220: ncovv++; /* Varying variables without age */
10221: TvarV[ncovv]=Tvar[k];
10222: TvarVind[ncovv]=k;
10223: }
1.227 brouard 10224: }else if(Tvard[k1][1] <=ncovcol+nqv){
1.240 brouard 10225: if(Tvard[k1][2] <=ncovcol){
10226: Fixed[k]= 0; /* or 2 ?*/
10227: Dummy[k]= 1;
10228: modell[k].maintype= FTYPE;
10229: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
10230: ncovf++; /* Fixed variables without age */
10231: TvarF[ncovf]=Tvar[k];
10232: TvarFind[ncovf]=k;
10233: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10234: Fixed[k]= 1;
10235: Dummy[k]= 1;
10236: modell[k].maintype= VTYPE;
10237: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
10238: ncovv++; /* Varying variables without age */
10239: TvarV[ncovv]=Tvar[k];
10240: TvarVind[ncovv]=k;
10241: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10242: Fixed[k]= 1;
10243: Dummy[k]= 1;
10244: modell[k].maintype= VTYPE;
10245: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
10246: ncovv++; /* Varying variables without age */
10247: TvarV[ncovv]=Tvar[k];
10248: TvarVind[ncovv]=k;
10249: ncovv++; /* Varying variables without age */
10250: TvarV[ncovv]=Tvar[k];
10251: TvarVind[ncovv]=k;
10252: }
1.227 brouard 10253: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){
1.240 brouard 10254: if(Tvard[k1][2] <=ncovcol){
10255: Fixed[k]= 1;
10256: Dummy[k]= 1;
10257: modell[k].maintype= VTYPE;
10258: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
10259: ncovv++; /* Varying variables without age */
10260: TvarV[ncovv]=Tvar[k];
10261: TvarVind[ncovv]=k;
10262: }else if(Tvard[k1][2] <=ncovcol+nqv){
10263: Fixed[k]= 1;
10264: Dummy[k]= 1;
10265: modell[k].maintype= VTYPE;
10266: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
10267: ncovv++; /* Varying variables without age */
10268: TvarV[ncovv]=Tvar[k];
10269: TvarVind[ncovv]=k;
10270: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10271: Fixed[k]= 1;
10272: Dummy[k]= 0;
10273: modell[k].maintype= VTYPE;
10274: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
10275: ncovv++; /* Varying variables without age */
10276: TvarV[ncovv]=Tvar[k];
10277: TvarVind[ncovv]=k;
10278: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10279: Fixed[k]= 1;
10280: Dummy[k]= 1;
10281: modell[k].maintype= VTYPE;
10282: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
10283: ncovv++; /* Varying variables without age */
10284: TvarV[ncovv]=Tvar[k];
10285: TvarVind[ncovv]=k;
10286: }
1.227 brouard 10287: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 10288: if(Tvard[k1][2] <=ncovcol){
10289: Fixed[k]= 1;
10290: Dummy[k]= 1;
10291: modell[k].maintype= VTYPE;
10292: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
10293: ncovv++; /* Varying variables without age */
10294: TvarV[ncovv]=Tvar[k];
10295: TvarVind[ncovv]=k;
10296: }else if(Tvard[k1][2] <=ncovcol+nqv){
10297: Fixed[k]= 1;
10298: Dummy[k]= 1;
10299: modell[k].maintype= VTYPE;
10300: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
10301: ncovv++; /* Varying variables without age */
10302: TvarV[ncovv]=Tvar[k];
10303: TvarVind[ncovv]=k;
10304: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10305: Fixed[k]= 1;
10306: Dummy[k]= 1;
10307: modell[k].maintype= VTYPE;
10308: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
10309: ncovv++; /* Varying variables without age */
10310: TvarV[ncovv]=Tvar[k];
10311: TvarVind[ncovv]=k;
10312: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10313: Fixed[k]= 1;
10314: Dummy[k]= 1;
10315: modell[k].maintype= VTYPE;
10316: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
10317: ncovv++; /* Varying variables without age */
10318: TvarV[ncovv]=Tvar[k];
10319: TvarVind[ncovv]=k;
10320: }
1.227 brouard 10321: }else{
1.240 brouard 10322: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
10323: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
10324: } /*end k1*/
1.225 brouard 10325: }else{
1.226 brouard 10326: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
10327: 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 10328: }
1.227 brouard 10329: 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 10330: printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype);
1.227 brouard 10331: 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]);
10332: }
10333: /* Searching for doublons in the model */
10334: for(k1=1; k1<= cptcovt;k1++){
10335: for(k2=1; k2 <k1;k2++){
1.285 brouard 10336: /* if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){ */
10337: if((Typevar[k1]==Typevar[k2]) && (Fixed[k1]==Fixed[k2]) && (Dummy[k1]==Dummy[k2] )){
1.234 brouard 10338: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
10339: if(Tvar[k1]==Tvar[k2]){
1.285 brouard 10340: 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]);
10341: 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 10342: return(1);
10343: }
10344: }else if (Typevar[k1] ==2){
10345: k3=Tposprod[k1];
10346: k4=Tposprod[k2];
10347: 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])) ){
10348: 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]]);
10349: 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);
10350: return(1);
10351: }
10352: }
1.227 brouard 10353: }
10354: }
1.225 brouard 10355: }
10356: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
10357: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 10358: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
10359: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.137 brouard 10360: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 10361: /*endread:*/
1.225 brouard 10362: printf("Exiting decodemodel: ");
10363: return (1);
1.136 brouard 10364: }
10365:
1.169 brouard 10366: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 10367: {/* Check ages at death */
1.136 brouard 10368: int i, m;
1.218 brouard 10369: int firstone=0;
10370:
1.136 brouard 10371: for (i=1; i<=imx; i++) {
10372: for(m=2; (m<= maxwav); m++) {
10373: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
10374: anint[m][i]=9999;
1.216 brouard 10375: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
10376: s[m][i]=-1;
1.136 brouard 10377: }
10378: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 10379: *nberr = *nberr + 1;
1.218 brouard 10380: if(firstone == 0){
10381: firstone=1;
1.260 brouard 10382: 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 10383: }
1.262 brouard 10384: 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 10385: s[m][i]=-1; /* Droping the death status */
1.136 brouard 10386: }
10387: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 10388: (*nberr)++;
1.259 brouard 10389: 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 10390: 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 10391: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 10392: }
10393: }
10394: }
10395:
10396: for (i=1; i<=imx; i++) {
10397: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
10398: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 10399: 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 10400: if (s[m][i] >= nlstate+1) {
1.169 brouard 10401: if(agedc[i]>0){
10402: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 10403: agev[m][i]=agedc[i];
1.214 brouard 10404: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 10405: }else {
1.136 brouard 10406: if ((int)andc[i]!=9999){
10407: nbwarn++;
10408: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
10409: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
10410: agev[m][i]=-1;
10411: }
10412: }
1.169 brouard 10413: } /* agedc > 0 */
1.214 brouard 10414: } /* end if */
1.136 brouard 10415: else if(s[m][i] !=9){ /* Standard case, age in fractional
10416: years but with the precision of a month */
10417: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
10418: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
10419: agev[m][i]=1;
10420: else if(agev[m][i] < *agemin){
10421: *agemin=agev[m][i];
10422: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
10423: }
10424: else if(agev[m][i] >*agemax){
10425: *agemax=agev[m][i];
1.156 brouard 10426: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 10427: }
10428: /*agev[m][i]=anint[m][i]-annais[i];*/
10429: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 10430: } /* en if 9*/
1.136 brouard 10431: else { /* =9 */
1.214 brouard 10432: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 10433: agev[m][i]=1;
10434: s[m][i]=-1;
10435: }
10436: }
1.214 brouard 10437: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 10438: agev[m][i]=1;
1.214 brouard 10439: else{
10440: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
10441: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
10442: agev[m][i]=0;
10443: }
10444: } /* End for lastpass */
10445: }
1.136 brouard 10446:
10447: for (i=1; i<=imx; i++) {
10448: for(m=firstpass; (m<=lastpass); m++){
10449: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 10450: (*nberr)++;
1.136 brouard 10451: 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);
10452: 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);
10453: return 1;
10454: }
10455: }
10456: }
10457:
10458: /*for (i=1; i<=imx; i++){
10459: for (m=firstpass; (m<lastpass); m++){
10460: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
10461: }
10462:
10463: }*/
10464:
10465:
1.139 brouard 10466: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
10467: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 10468:
10469: return (0);
1.164 brouard 10470: /* endread:*/
1.136 brouard 10471: printf("Exiting calandcheckages: ");
10472: return (1);
10473: }
10474:
1.172 brouard 10475: #if defined(_MSC_VER)
10476: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
10477: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
10478: //#include "stdafx.h"
10479: //#include <stdio.h>
10480: //#include <tchar.h>
10481: //#include <windows.h>
10482: //#include <iostream>
10483: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
10484:
10485: LPFN_ISWOW64PROCESS fnIsWow64Process;
10486:
10487: BOOL IsWow64()
10488: {
10489: BOOL bIsWow64 = FALSE;
10490:
10491: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
10492: // (HANDLE, PBOOL);
10493:
10494: //LPFN_ISWOW64PROCESS fnIsWow64Process;
10495:
10496: HMODULE module = GetModuleHandle(_T("kernel32"));
10497: const char funcName[] = "IsWow64Process";
10498: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
10499: GetProcAddress(module, funcName);
10500:
10501: if (NULL != fnIsWow64Process)
10502: {
10503: if (!fnIsWow64Process(GetCurrentProcess(),
10504: &bIsWow64))
10505: //throw std::exception("Unknown error");
10506: printf("Unknown error\n");
10507: }
10508: return bIsWow64 != FALSE;
10509: }
10510: #endif
1.177 brouard 10511:
1.191 brouard 10512: void syscompilerinfo(int logged)
1.292 brouard 10513: {
10514: #include <stdint.h>
10515:
10516: /* #include "syscompilerinfo.h"*/
1.185 brouard 10517: /* command line Intel compiler 32bit windows, XP compatible:*/
10518: /* /GS /W3 /Gy
10519: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
10520: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
10521: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 10522: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
10523: */
10524: /* 64 bits */
1.185 brouard 10525: /*
10526: /GS /W3 /Gy
10527: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
10528: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
10529: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
10530: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
10531: /* Optimization are useless and O3 is slower than O2 */
10532: /*
10533: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
10534: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
10535: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
10536: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
10537: */
1.186 brouard 10538: /* Link is */ /* /OUT:"visual studio
1.185 brouard 10539: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
10540: /PDB:"visual studio
10541: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
10542: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
10543: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
10544: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
10545: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
10546: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
10547: uiAccess='false'"
10548: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
10549: /NOLOGO /TLBID:1
10550: */
1.292 brouard 10551:
10552:
1.177 brouard 10553: #if defined __INTEL_COMPILER
1.178 brouard 10554: #if defined(__GNUC__)
10555: struct utsname sysInfo; /* For Intel on Linux and OS/X */
10556: #endif
1.177 brouard 10557: #elif defined(__GNUC__)
1.179 brouard 10558: #ifndef __APPLE__
1.174 brouard 10559: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 10560: #endif
1.177 brouard 10561: struct utsname sysInfo;
1.178 brouard 10562: int cross = CROSS;
10563: if (cross){
10564: printf("Cross-");
1.191 brouard 10565: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 10566: }
1.174 brouard 10567: #endif
10568:
1.191 brouard 10569: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 10570: #if defined(__clang__)
1.191 brouard 10571: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 10572: #endif
10573: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 10574: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 10575: #endif
10576: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 10577: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 10578: #endif
10579: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 10580: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 10581: #endif
10582: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 10583: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 10584: #endif
10585: #if defined(_MSC_VER)
1.191 brouard 10586: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 10587: #endif
10588: #if defined(__PGI)
1.191 brouard 10589: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 10590: #endif
10591: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 10592: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 10593: #endif
1.191 brouard 10594: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 10595:
1.167 brouard 10596: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
10597: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
10598: // Windows (x64 and x86)
1.191 brouard 10599: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 10600: #elif __unix__ // all unices, not all compilers
10601: // Unix
1.191 brouard 10602: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 10603: #elif __linux__
10604: // linux
1.191 brouard 10605: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 10606: #elif __APPLE__
1.174 brouard 10607: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 10608: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 10609: #endif
10610:
10611: /* __MINGW32__ */
10612: /* __CYGWIN__ */
10613: /* __MINGW64__ */
10614: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
10615: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
10616: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
10617: /* _WIN64 // Defined for applications for Win64. */
10618: /* _M_X64 // Defined for compilations that target x64 processors. */
10619: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 10620:
1.167 brouard 10621: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 10622: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 10623: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 10624: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 10625: #else
1.191 brouard 10626: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 10627: #endif
10628:
1.169 brouard 10629: #if defined(__GNUC__)
10630: # if defined(__GNUC_PATCHLEVEL__)
10631: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10632: + __GNUC_MINOR__ * 100 \
10633: + __GNUC_PATCHLEVEL__)
10634: # else
10635: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10636: + __GNUC_MINOR__ * 100)
10637: # endif
1.174 brouard 10638: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 10639: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 10640:
10641: if (uname(&sysInfo) != -1) {
10642: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 10643: 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 10644: }
10645: else
10646: perror("uname() error");
1.179 brouard 10647: //#ifndef __INTEL_COMPILER
10648: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 10649: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 10650: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 10651: #endif
1.169 brouard 10652: #endif
1.172 brouard 10653:
1.286 brouard 10654: // void main ()
1.172 brouard 10655: // {
1.169 brouard 10656: #if defined(_MSC_VER)
1.174 brouard 10657: if (IsWow64()){
1.191 brouard 10658: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
10659: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 10660: }
10661: else{
1.191 brouard 10662: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
10663: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 10664: }
1.172 brouard 10665: // printf("\nPress Enter to continue...");
10666: // getchar();
10667: // }
10668:
1.169 brouard 10669: #endif
10670:
1.167 brouard 10671:
1.219 brouard 10672: }
1.136 brouard 10673:
1.219 brouard 10674: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.288 brouard 10675: /*--------------- Prevalence limit (forward period or forward stable prevalence) --------------*/
1.235 brouard 10676: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 10677: /* double ftolpl = 1.e-10; */
1.180 brouard 10678: double age, agebase, agelim;
1.203 brouard 10679: double tot;
1.180 brouard 10680:
1.202 brouard 10681: strcpy(filerespl,"PL_");
10682: strcat(filerespl,fileresu);
10683: if((ficrespl=fopen(filerespl,"w"))==NULL) {
1.288 brouard 10684: printf("Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
10685: fprintf(ficlog,"Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
1.202 brouard 10686: }
1.288 brouard 10687: printf("\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
10688: fprintf(ficlog,"\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 10689: pstamp(ficrespl);
1.288 brouard 10690: fprintf(ficrespl,"# Forward period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 10691: fprintf(ficrespl,"#Age ");
10692: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
10693: fprintf(ficrespl,"\n");
1.180 brouard 10694:
1.219 brouard 10695: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 10696:
1.219 brouard 10697: agebase=ageminpar;
10698: agelim=agemaxpar;
1.180 brouard 10699:
1.227 brouard 10700: /* i1=pow(2,ncoveff); */
1.234 brouard 10701: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 10702: if (cptcovn < 1){i1=1;}
1.180 brouard 10703:
1.238 brouard 10704: for(k=1; k<=i1;k++){ /* For each combination k of dummy covariates in the model */
10705: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 10706: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10707: continue;
1.235 brouard 10708:
1.238 brouard 10709: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10710: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
10711: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
10712: /* k=k+1; */
10713: /* to clean */
10714: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10715: fprintf(ficrespl,"#******");
10716: printf("#******");
10717: fprintf(ficlog,"#******");
10718: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10719: fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); /* Here problem for varying dummy*/
10720: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10721: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10722: }
10723: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
10724: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10725: fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10726: fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10727: }
10728: fprintf(ficrespl,"******\n");
10729: printf("******\n");
10730: fprintf(ficlog,"******\n");
10731: if(invalidvarcomb[k]){
10732: printf("\nCombination (%d) ignored because no case \n",k);
10733: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
10734: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
10735: continue;
10736: }
1.219 brouard 10737:
1.238 brouard 10738: fprintf(ficrespl,"#Age ");
10739: for(j=1;j<=cptcoveff;j++) {
10740: fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10741: }
10742: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
10743: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 10744:
1.238 brouard 10745: for (age=agebase; age<=agelim; age++){
10746: /* for (age=agebase; age<=agebase; age++){ */
10747: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres);
10748: fprintf(ficrespl,"%.0f ",age );
10749: for(j=1;j<=cptcoveff;j++)
10750: fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10751: tot=0.;
10752: for(i=1; i<=nlstate;i++){
10753: tot += prlim[i][i];
10754: fprintf(ficrespl," %.5f", prlim[i][i]);
10755: }
10756: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
10757: } /* Age */
10758: /* was end of cptcod */
10759: } /* cptcov */
10760: } /* nres */
1.219 brouard 10761: return 0;
1.180 brouard 10762: }
10763:
1.218 brouard 10764: 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 10765: /*--------------- Back Prevalence limit (backward stable prevalence) --------------*/
1.218 brouard 10766:
10767: /* Computes the back prevalence limit for any combination of covariate values
10768: * at any age between ageminpar and agemaxpar
10769: */
1.235 brouard 10770: int i, j, k, i1, nres=0 ;
1.217 brouard 10771: /* double ftolpl = 1.e-10; */
10772: double age, agebase, agelim;
10773: double tot;
1.218 brouard 10774: /* double ***mobaverage; */
10775: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 10776:
10777: strcpy(fileresplb,"PLB_");
10778: strcat(fileresplb,fileresu);
10779: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
1.288 brouard 10780: printf("Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
10781: fprintf(ficlog,"Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
1.217 brouard 10782: }
1.288 brouard 10783: printf("Computing backward prevalence: result on file '%s' \n", fileresplb);
10784: fprintf(ficlog,"Computing backward prevalence: result on file '%s' \n", fileresplb);
1.217 brouard 10785: pstamp(ficresplb);
1.288 brouard 10786: fprintf(ficresplb,"# Backward prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.217 brouard 10787: fprintf(ficresplb,"#Age ");
10788: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
10789: fprintf(ficresplb,"\n");
10790:
1.218 brouard 10791:
10792: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
10793:
10794: agebase=ageminpar;
10795: agelim=agemaxpar;
10796:
10797:
1.227 brouard 10798: i1=pow(2,cptcoveff);
1.218 brouard 10799: if (cptcovn < 1){i1=1;}
1.227 brouard 10800:
1.238 brouard 10801: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10802: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 10803: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10804: continue;
10805: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10806: fprintf(ficresplb,"#******");
10807: printf("#******");
10808: fprintf(ficlog,"#******");
10809: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10810: fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10811: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10812: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10813: }
10814: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
10815: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10816: fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10817: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10818: }
10819: fprintf(ficresplb,"******\n");
10820: printf("******\n");
10821: fprintf(ficlog,"******\n");
10822: if(invalidvarcomb[k]){
10823: printf("\nCombination (%d) ignored because no cases \n",k);
10824: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
10825: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
10826: continue;
10827: }
1.218 brouard 10828:
1.238 brouard 10829: fprintf(ficresplb,"#Age ");
10830: for(j=1;j<=cptcoveff;j++) {
10831: fprintf(ficresplb,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10832: }
10833: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
10834: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 10835:
10836:
1.238 brouard 10837: for (age=agebase; age<=agelim; age++){
10838: /* for (age=agebase; age<=agebase; age++){ */
10839: if(mobilavproj > 0){
10840: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
10841: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 10842: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 10843: }else if (mobilavproj == 0){
10844: 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);
10845: 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);
10846: exit(1);
10847: }else{
10848: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 10849: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 10850: /* printf("TOTOT\n"); */
10851: /* exit(1); */
1.238 brouard 10852: }
10853: fprintf(ficresplb,"%.0f ",age );
10854: for(j=1;j<=cptcoveff;j++)
10855: fprintf(ficresplb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10856: tot=0.;
10857: for(i=1; i<=nlstate;i++){
10858: tot += bprlim[i][i];
10859: fprintf(ficresplb," %.5f", bprlim[i][i]);
10860: }
10861: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
10862: } /* Age */
10863: /* was end of cptcod */
1.255 brouard 10864: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.238 brouard 10865: } /* end of any combination */
10866: } /* end of nres */
1.218 brouard 10867: /* hBijx(p, bage, fage); */
10868: /* fclose(ficrespijb); */
10869:
10870: return 0;
1.217 brouard 10871: }
1.218 brouard 10872:
1.180 brouard 10873: int hPijx(double *p, int bage, int fage){
10874: /*------------- h Pij x at various ages ------------*/
10875:
10876: int stepsize;
10877: int agelim;
10878: int hstepm;
10879: int nhstepm;
1.235 brouard 10880: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 10881:
10882: double agedeb;
10883: double ***p3mat;
10884:
1.201 brouard 10885: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
1.180 brouard 10886: if((ficrespij=fopen(filerespij,"w"))==NULL) {
10887: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
10888: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
10889: }
10890: printf("Computing pij: result on file '%s' \n", filerespij);
10891: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
10892:
10893: stepsize=(int) (stepm+YEARM-1)/YEARM;
10894: /*if (stepm<=24) stepsize=2;*/
10895:
10896: agelim=AGESUP;
10897: hstepm=stepsize*YEARM; /* Every year of age */
10898: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
1.218 brouard 10899:
1.180 brouard 10900: /* hstepm=1; aff par mois*/
10901: pstamp(ficrespij);
10902: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
1.227 brouard 10903: i1= pow(2,cptcoveff);
1.218 brouard 10904: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10905: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
10906: /* k=k+1; */
1.235 brouard 10907: for(nres=1; nres <= nresult; nres++) /* For each resultline */
10908: for(k=1; k<=i1;k++){
1.253 brouard 10909: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 10910: continue;
1.183 brouard 10911: fprintf(ficrespij,"\n#****** ");
1.227 brouard 10912: for(j=1;j<=cptcoveff;j++)
1.198 brouard 10913: fprintf(ficrespij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 10914: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
10915: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10916: fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10917: }
1.183 brouard 10918: fprintf(ficrespij,"******\n");
10919:
10920: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
10921: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
10922: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
10923:
10924: /* nhstepm=nhstepm*YEARM; aff par mois*/
1.180 brouard 10925:
1.183 brouard 10926: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10927: oldm=oldms;savm=savms;
1.235 brouard 10928: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.183 brouard 10929: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
10930: for(i=1; i<=nlstate;i++)
10931: for(j=1; j<=nlstate+ndeath;j++)
10932: fprintf(ficrespij," %1d-%1d",i,j);
10933: fprintf(ficrespij,"\n");
10934: for (h=0; h<=nhstepm; h++){
10935: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
10936: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.180 brouard 10937: for(i=1; i<=nlstate;i++)
10938: for(j=1; j<=nlstate+ndeath;j++)
1.183 brouard 10939: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.180 brouard 10940: fprintf(ficrespij,"\n");
10941: }
1.183 brouard 10942: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10943: fprintf(ficrespij,"\n");
10944: }
1.180 brouard 10945: /*}*/
10946: }
1.218 brouard 10947: return 0;
1.180 brouard 10948: }
1.218 brouard 10949:
10950: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 10951: /*------------- h Bij x at various ages ------------*/
10952:
10953: int stepsize;
1.218 brouard 10954: /* int agelim; */
10955: int ageminl;
1.217 brouard 10956: int hstepm;
10957: int nhstepm;
1.238 brouard 10958: int h, i, i1, j, k, nres;
1.218 brouard 10959:
1.217 brouard 10960: double agedeb;
10961: double ***p3mat;
1.218 brouard 10962:
10963: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
10964: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
10965: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
10966: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
10967: }
10968: printf("Computing pij back: result on file '%s' \n", filerespijb);
10969: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
10970:
10971: stepsize=(int) (stepm+YEARM-1)/YEARM;
10972: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 10973:
1.218 brouard 10974: /* agelim=AGESUP; */
1.289 brouard 10975: ageminl=AGEINF; /* was 30 */
1.218 brouard 10976: hstepm=stepsize*YEARM; /* Every year of age */
10977: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
10978:
10979: /* hstepm=1; aff par mois*/
10980: pstamp(ficrespijb);
1.255 brouard 10981: 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 10982: i1= pow(2,cptcoveff);
1.218 brouard 10983: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10984: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
10985: /* k=k+1; */
1.238 brouard 10986: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10987: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 10988: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10989: continue;
10990: fprintf(ficrespijb,"\n#****** ");
10991: for(j=1;j<=cptcoveff;j++)
10992: fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10993: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
10994: fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10995: }
10996: fprintf(ficrespijb,"******\n");
1.264 brouard 10997: if(invalidvarcomb[k]){ /* Is it necessary here? */
1.238 brouard 10998: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
10999: continue;
11000: }
11001:
11002: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
11003: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
11004: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
1.297 brouard 11005: 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 */
11006: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 or 28*/
1.238 brouard 11007:
11008: /* nhstepm=nhstepm*YEARM; aff par mois*/
11009:
1.266 brouard 11010: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
11011: /* and memory limitations if stepm is small */
11012:
1.238 brouard 11013: /* oldm=oldms;savm=savms; */
11014: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.267 brouard 11015: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.238 brouard 11016: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
1.255 brouard 11017: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
1.217 brouard 11018: for(i=1; i<=nlstate;i++)
11019: for(j=1; j<=nlstate+ndeath;j++)
1.238 brouard 11020: fprintf(ficrespijb," %1d-%1d",i,j);
1.217 brouard 11021: fprintf(ficrespijb,"\n");
1.238 brouard 11022: for (h=0; h<=nhstepm; h++){
11023: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
11024: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
11025: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
11026: for(i=1; i<=nlstate;i++)
11027: for(j=1; j<=nlstate+ndeath;j++)
11028: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);
11029: fprintf(ficrespijb,"\n");
11030: }
11031: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11032: fprintf(ficrespijb,"\n");
11033: } /* end age deb */
11034: } /* end combination */
11035: } /* end nres */
1.218 brouard 11036: return 0;
11037: } /* hBijx */
1.217 brouard 11038:
1.180 brouard 11039:
1.136 brouard 11040: /***********************************************/
11041: /**************** Main Program *****************/
11042: /***********************************************/
11043:
11044: int main(int argc, char *argv[])
11045: {
11046: #ifdef GSL
11047: const gsl_multimin_fminimizer_type *T;
11048: size_t iteri = 0, it;
11049: int rval = GSL_CONTINUE;
11050: int status = GSL_SUCCESS;
11051: double ssval;
11052: #endif
11053: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.290 brouard 11054: int i,j, k, iter=0,m,size=100, cptcod; /* Suppressing because nobs */
11055: /* int i,j, k, n=MAXN,iter=0,m,size=100, cptcod; */
1.209 brouard 11056: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 11057: int jj, ll, li, lj, lk;
1.136 brouard 11058: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 11059: int num_filled;
1.136 brouard 11060: int itimes;
11061: int NDIM=2;
11062: int vpopbased=0;
1.235 brouard 11063: int nres=0;
1.258 brouard 11064: int endishere=0;
1.277 brouard 11065: int noffset=0;
1.274 brouard 11066: int ncurrv=0; /* Temporary variable */
11067:
1.164 brouard 11068: char ca[32], cb[32];
1.136 brouard 11069: /* FILE *fichtm; *//* Html File */
11070: /* FILE *ficgp;*/ /*Gnuplot File */
11071: struct stat info;
1.191 brouard 11072: double agedeb=0.;
1.194 brouard 11073:
11074: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 11075: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 11076:
1.165 brouard 11077: double fret;
1.191 brouard 11078: double dum=0.; /* Dummy variable */
1.136 brouard 11079: double ***p3mat;
1.218 brouard 11080: /* double ***mobaverage; */
1.164 brouard 11081:
11082: char line[MAXLINE];
1.197 brouard 11083: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
11084:
1.234 brouard 11085: char modeltemp[MAXLINE];
1.230 brouard 11086: char resultline[MAXLINE];
11087:
1.136 brouard 11088: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 11089: char *tok, *val; /* pathtot */
1.290 brouard 11090: int firstobs=1, lastobs=10; /* nobs = lastobs-firstobs declared globally ;*/
1.195 brouard 11091: int c, h , cpt, c2;
1.191 brouard 11092: int jl=0;
11093: int i1, j1, jk, stepsize=0;
1.194 brouard 11094: int count=0;
11095:
1.164 brouard 11096: int *tab;
1.136 brouard 11097: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.296 brouard 11098: /* double anprojd, mprojd, jprojd; /\* For eventual projections *\/ */
11099: /* double anprojf, mprojf, jprojf; */
11100: /* double jintmean,mintmean,aintmean; */
11101: int prvforecast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
11102: int prvbackcast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
11103: double yrfproj= 10.0; /* Number of years of forward projections */
11104: double yrbproj= 10.0; /* Number of years of backward projections */
11105: int prevbcast=0; /* defined as global for mlikeli and mle, replacing backcast */
1.136 brouard 11106: int mobilav=0,popforecast=0;
1.191 brouard 11107: int hstepm=0, nhstepm=0;
1.136 brouard 11108: int agemortsup;
11109: float sumlpop=0.;
11110: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
11111: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
11112:
1.191 brouard 11113: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 11114: double ftolpl=FTOL;
11115: double **prlim;
1.217 brouard 11116: double **bprlim;
1.317 brouard 11117: double ***param; /* Matrix of parameters, param[i][j][k] param=ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel)
11118: state of origin, state of destination including death, for each covariate: constante, age, and V1 V2 etc. */
1.251 brouard 11119: double ***paramstart; /* Matrix of starting parameter values */
11120: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 11121: double **matcov; /* Matrix of covariance */
1.203 brouard 11122: double **hess; /* Hessian matrix */
1.136 brouard 11123: double ***delti3; /* Scale */
11124: double *delti; /* Scale */
11125: double ***eij, ***vareij;
11126: double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 11127:
1.136 brouard 11128: double *epj, vepp;
1.164 brouard 11129:
1.273 brouard 11130: double dateprev1, dateprev2;
1.296 brouard 11131: double jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000, dateproj1=0, dateproj2=0, dateprojd=0, dateprojf=0;
11132: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000, dateback1=0, dateback2=0, datebackd=0, datebackf=0;
11133:
1.217 brouard 11134:
1.136 brouard 11135: double **ximort;
1.145 brouard 11136: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 11137: int *dcwave;
11138:
1.164 brouard 11139: char z[1]="c";
1.136 brouard 11140:
11141: /*char *strt;*/
11142: char strtend[80];
1.126 brouard 11143:
1.164 brouard 11144:
1.126 brouard 11145: /* setlocale (LC_ALL, ""); */
11146: /* bindtextdomain (PACKAGE, LOCALEDIR); */
11147: /* textdomain (PACKAGE); */
11148: /* setlocale (LC_CTYPE, ""); */
11149: /* setlocale (LC_MESSAGES, ""); */
11150:
11151: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 11152: rstart_time = time(NULL);
11153: /* (void) gettimeofday(&start_time,&tzp);*/
11154: start_time = *localtime(&rstart_time);
1.126 brouard 11155: curr_time=start_time;
1.157 brouard 11156: /*tml = *localtime(&start_time.tm_sec);*/
11157: /* strcpy(strstart,asctime(&tml)); */
11158: strcpy(strstart,asctime(&start_time));
1.126 brouard 11159:
11160: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 11161: /* tp.tm_sec = tp.tm_sec +86400; */
11162: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 11163: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
11164: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
11165: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 11166: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 11167: /* strt=asctime(&tmg); */
11168: /* printf("Time(after) =%s",strstart); */
11169: /* (void) time (&time_value);
11170: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
11171: * tm = *localtime(&time_value);
11172: * strstart=asctime(&tm);
11173: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
11174: */
11175:
11176: nberr=0; /* Number of errors and warnings */
11177: nbwarn=0;
1.184 brouard 11178: #ifdef WIN32
11179: _getcwd(pathcd, size);
11180: #else
1.126 brouard 11181: getcwd(pathcd, size);
1.184 brouard 11182: #endif
1.191 brouard 11183: syscompilerinfo(0);
1.196 brouard 11184: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 11185: if(argc <=1){
11186: printf("\nEnter the parameter file name: ");
1.205 brouard 11187: if(!fgets(pathr,FILENAMELENGTH,stdin)){
11188: printf("ERROR Empty parameter file name\n");
11189: goto end;
11190: }
1.126 brouard 11191: i=strlen(pathr);
11192: if(pathr[i-1]=='\n')
11193: pathr[i-1]='\0';
1.156 brouard 11194: i=strlen(pathr);
1.205 brouard 11195: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 11196: pathr[i-1]='\0';
1.205 brouard 11197: }
11198: i=strlen(pathr);
11199: if( i==0 ){
11200: printf("ERROR Empty parameter file name\n");
11201: goto end;
11202: }
11203: for (tok = pathr; tok != NULL; ){
1.126 brouard 11204: printf("Pathr |%s|\n",pathr);
11205: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
11206: printf("val= |%s| pathr=%s\n",val,pathr);
11207: strcpy (pathtot, val);
11208: if(pathr[0] == '\0') break; /* Dirty */
11209: }
11210: }
1.281 brouard 11211: else if (argc<=2){
11212: strcpy(pathtot,argv[1]);
11213: }
1.126 brouard 11214: else{
11215: strcpy(pathtot,argv[1]);
1.281 brouard 11216: strcpy(z,argv[2]);
11217: printf("\nargv[2]=%s z=%c\n",argv[2],z[0]);
1.126 brouard 11218: }
11219: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
11220: /*cygwin_split_path(pathtot,path,optionfile);
11221: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
11222: /* cutv(path,optionfile,pathtot,'\\');*/
11223:
11224: /* Split argv[0], imach program to get pathimach */
11225: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
11226: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
11227: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
11228: /* strcpy(pathimach,argv[0]); */
11229: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
11230: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
11231: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 11232: #ifdef WIN32
11233: _chdir(path); /* Can be a relative path */
11234: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
11235: #else
1.126 brouard 11236: chdir(path); /* Can be a relative path */
1.184 brouard 11237: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
11238: #endif
11239: printf("Current directory %s!\n",pathcd);
1.126 brouard 11240: strcpy(command,"mkdir ");
11241: strcat(command,optionfilefiname);
11242: if((outcmd=system(command)) != 0){
1.169 brouard 11243: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 11244: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
11245: /* fclose(ficlog); */
11246: /* exit(1); */
11247: }
11248: /* if((imk=mkdir(optionfilefiname))<0){ */
11249: /* perror("mkdir"); */
11250: /* } */
11251:
11252: /*-------- arguments in the command line --------*/
11253:
1.186 brouard 11254: /* Main Log file */
1.126 brouard 11255: strcat(filelog, optionfilefiname);
11256: strcat(filelog,".log"); /* */
11257: if((ficlog=fopen(filelog,"w"))==NULL) {
11258: printf("Problem with logfile %s\n",filelog);
11259: goto end;
11260: }
11261: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 11262: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 11263: fprintf(ficlog,"\nEnter the parameter file name: \n");
11264: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
11265: path=%s \n\
11266: optionfile=%s\n\
11267: optionfilext=%s\n\
1.156 brouard 11268: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 11269:
1.197 brouard 11270: syscompilerinfo(1);
1.167 brouard 11271:
1.126 brouard 11272: printf("Local time (at start):%s",strstart);
11273: fprintf(ficlog,"Local time (at start): %s",strstart);
11274: fflush(ficlog);
11275: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 11276: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 11277:
11278: /* */
11279: strcpy(fileres,"r");
11280: strcat(fileres, optionfilefiname);
1.201 brouard 11281: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 11282: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 11283: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 11284:
1.186 brouard 11285: /* Main ---------arguments file --------*/
1.126 brouard 11286:
11287: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 11288: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
11289: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 11290: fflush(ficlog);
1.149 brouard 11291: /* goto end; */
11292: exit(70);
1.126 brouard 11293: }
11294:
11295: strcpy(filereso,"o");
1.201 brouard 11296: strcat(filereso,fileresu);
1.126 brouard 11297: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
11298: printf("Problem with Output resultfile: %s\n", filereso);
11299: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
11300: fflush(ficlog);
11301: goto end;
11302: }
1.278 brouard 11303: /*-------- Rewriting parameter file ----------*/
11304: strcpy(rfileres,"r"); /* "Rparameterfile */
11305: strcat(rfileres,optionfilefiname); /* Parameter file first name */
11306: strcat(rfileres,"."); /* */
11307: strcat(rfileres,optionfilext); /* Other files have txt extension */
11308: if((ficres =fopen(rfileres,"w"))==NULL) {
11309: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
11310: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
11311: fflush(ficlog);
11312: goto end;
11313: }
11314: fprintf(ficres,"#IMaCh %s\n",version);
1.126 brouard 11315:
1.278 brouard 11316:
1.126 brouard 11317: /* Reads comments: lines beginning with '#' */
11318: numlinepar=0;
1.277 brouard 11319: /* Is it a BOM UTF-8 Windows file? */
11320: /* First parameter line */
1.197 brouard 11321: while(fgets(line, MAXLINE, ficpar)) {
1.277 brouard 11322: noffset=0;
11323: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
11324: {
11325: noffset=noffset+3;
11326: printf("# File is an UTF8 Bom.\n"); // 0xBF
11327: }
1.302 brouard 11328: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
11329: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
1.277 brouard 11330: {
11331: noffset=noffset+2;
11332: printf("# File is an UTF16BE BOM file\n");
11333: }
11334: else if( line[0] == 0 && line[1] == 0)
11335: {
11336: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
11337: noffset=noffset+4;
11338: printf("# File is an UTF16BE BOM file\n");
11339: }
11340: } else{
11341: ;/*printf(" Not a BOM file\n");*/
11342: }
11343:
1.197 brouard 11344: /* If line starts with a # it is a comment */
1.277 brouard 11345: if (line[noffset] == '#') {
1.197 brouard 11346: numlinepar++;
11347: fputs(line,stdout);
11348: fputs(line,ficparo);
1.278 brouard 11349: fputs(line,ficres);
1.197 brouard 11350: fputs(line,ficlog);
11351: continue;
11352: }else
11353: break;
11354: }
11355: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
11356: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
11357: if (num_filled != 5) {
11358: printf("Should be 5 parameters\n");
1.283 brouard 11359: fprintf(ficlog,"Should be 5 parameters\n");
1.197 brouard 11360: }
1.126 brouard 11361: numlinepar++;
1.197 brouard 11362: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.283 brouard 11363: fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
11364: fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
11365: fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.197 brouard 11366: }
11367: /* Second parameter line */
11368: while(fgets(line, MAXLINE, ficpar)) {
1.283 brouard 11369: /* while(fscanf(ficpar,"%[^\n]", line)) { */
11370: /* If line starts with a # it is a comment. Strangely fgets reads the EOL and fputs doesn't */
1.197 brouard 11371: if (line[0] == '#') {
11372: numlinepar++;
1.283 brouard 11373: printf("%s",line);
11374: fprintf(ficres,"%s",line);
11375: fprintf(ficparo,"%s",line);
11376: fprintf(ficlog,"%s",line);
1.197 brouard 11377: continue;
11378: }else
11379: break;
11380: }
1.223 brouard 11381: 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", \
11382: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
11383: if (num_filled != 11) {
11384: 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 11385: printf("but line=%s\n",line);
1.283 brouard 11386: 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");
11387: fprintf(ficlog,"but line=%s\n",line);
1.197 brouard 11388: }
1.286 brouard 11389: if( lastpass > maxwav){
11390: printf("Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
11391: fprintf(ficlog,"Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
11392: fflush(ficlog);
11393: goto end;
11394: }
11395: 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 11396: 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 11397: 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 11398: 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 11399: }
1.203 brouard 11400: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 11401: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 11402: /* Third parameter line */
11403: while(fgets(line, MAXLINE, ficpar)) {
11404: /* If line starts with a # it is a comment */
11405: if (line[0] == '#') {
11406: numlinepar++;
1.283 brouard 11407: printf("%s",line);
11408: fprintf(ficres,"%s",line);
11409: fprintf(ficparo,"%s",line);
11410: fprintf(ficlog,"%s",line);
1.197 brouard 11411: continue;
11412: }else
11413: break;
11414: }
1.201 brouard 11415: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){
1.279 brouard 11416: if (num_filled != 1){
1.302 brouard 11417: printf("ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
11418: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
1.197 brouard 11419: model[0]='\0';
11420: goto end;
11421: }
11422: else{
11423: if (model[0]=='+'){
11424: for(i=1; i<=strlen(model);i++)
11425: modeltemp[i-1]=model[i];
1.201 brouard 11426: strcpy(model,modeltemp);
1.197 brouard 11427: }
11428: }
1.199 brouard 11429: /* printf(" model=1+age%s modeltemp= %s, model=%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 11430: printf("model=1+age+%s\n",model);fflush(stdout);
1.283 brouard 11431: fprintf(ficparo,"model=1+age+%s\n",model);fflush(stdout);
11432: fprintf(ficres,"model=1+age+%s\n",model);fflush(stdout);
11433: fprintf(ficlog,"model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 11434: }
11435: /* 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); */
11436: /* numlinepar=numlinepar+3; /\* In general *\/ */
11437: /* 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 11438: /* 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); */
11439: /* 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 11440: fflush(ficlog);
1.190 brouard 11441: /* if(model[0]=='#'|| model[0]== '\0'){ */
11442: if(model[0]=='#'){
1.279 brouard 11443: printf("Error in 'model' line: model should start with 'model=1+age+' and end without space \n \
11444: 'model=1+age+' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age' or \n \
11445: 'model=1+age+V1+V2' or 'model=1+age+V1+V2+V1*V2' etc. \n"); \
1.187 brouard 11446: if(mle != -1){
1.279 brouard 11447: 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 11448: exit(1);
11449: }
11450: }
1.126 brouard 11451: while((c=getc(ficpar))=='#' && c!= EOF){
11452: ungetc(c,ficpar);
11453: fgets(line, MAXLINE, ficpar);
11454: numlinepar++;
1.195 brouard 11455: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
11456: z[0]=line[1];
11457: }
11458: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 11459: fputs(line, stdout);
11460: //puts(line);
1.126 brouard 11461: fputs(line,ficparo);
11462: fputs(line,ficlog);
11463: }
11464: ungetc(c,ficpar);
11465:
11466:
1.290 brouard 11467: covar=matrix(0,NCOVMAX,firstobs,lastobs); /**< used in readdata */
11468: if(nqv>=1)coqvar=matrix(1,nqv,firstobs,lastobs); /**< Fixed quantitative covariate */
11469: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,firstobs,lastobs); /**< Time varying quantitative covariate */
11470: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,firstobs,lastobs); /**< Time varying covariate (dummy and quantitative)*/
1.136 brouard 11471: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
11472: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
11473: v1+v2*age+v2*v3 makes cptcovn = 3
11474: */
11475: if (strlen(model)>1)
1.187 brouard 11476: 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 11477: else
1.187 brouard 11478: ncovmodel=2; /* Constant and age */
1.133 brouard 11479: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
11480: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 11481: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
11482: 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);
11483: 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);
11484: fflush(stdout);
11485: fclose (ficlog);
11486: goto end;
11487: }
1.126 brouard 11488: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
11489: delti=delti3[1][1];
11490: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
11491: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 11492: /* We could also provide initial parameters values giving by simple logistic regression
11493: * only one way, that is without matrix product. We will have nlstate maximizations */
11494: /* for(i=1;i<nlstate;i++){ */
11495: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
11496: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
11497: /* } */
1.126 brouard 11498: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 11499: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
11500: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 11501: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
11502: fclose (ficparo);
11503: fclose (ficlog);
11504: goto end;
11505: exit(0);
1.220 brouard 11506: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 11507: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 11508: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
11509: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 11510: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
11511: matcov=matrix(1,npar,1,npar);
1.203 brouard 11512: hess=matrix(1,npar,1,npar);
1.220 brouard 11513: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 11514: /* Read guessed parameters */
1.126 brouard 11515: /* Reads comments: lines beginning with '#' */
11516: while((c=getc(ficpar))=='#' && c!= EOF){
11517: ungetc(c,ficpar);
11518: fgets(line, MAXLINE, ficpar);
11519: numlinepar++;
1.141 brouard 11520: fputs(line,stdout);
1.126 brouard 11521: fputs(line,ficparo);
11522: fputs(line,ficlog);
11523: }
11524: ungetc(c,ficpar);
11525:
11526: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 11527: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 11528: for(i=1; i <=nlstate; i++){
1.234 brouard 11529: j=0;
1.126 brouard 11530: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 11531: if(jj==i) continue;
11532: j++;
1.292 brouard 11533: while((c=getc(ficpar))=='#' && c!= EOF){
11534: ungetc(c,ficpar);
11535: fgets(line, MAXLINE, ficpar);
11536: numlinepar++;
11537: fputs(line,stdout);
11538: fputs(line,ficparo);
11539: fputs(line,ficlog);
11540: }
11541: ungetc(c,ficpar);
1.234 brouard 11542: fscanf(ficpar,"%1d%1d",&i1,&j1);
11543: if ((i1 != i) || (j1 != jj)){
11544: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 11545: It might be a problem of design; if ncovcol and the model are correct\n \
11546: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 11547: exit(1);
11548: }
11549: fprintf(ficparo,"%1d%1d",i1,j1);
11550: if(mle==1)
11551: printf("%1d%1d",i,jj);
11552: fprintf(ficlog,"%1d%1d",i,jj);
11553: for(k=1; k<=ncovmodel;k++){
11554: fscanf(ficpar," %lf",¶m[i][j][k]);
11555: if(mle==1){
11556: printf(" %lf",param[i][j][k]);
11557: fprintf(ficlog," %lf",param[i][j][k]);
11558: }
11559: else
11560: fprintf(ficlog," %lf",param[i][j][k]);
11561: fprintf(ficparo," %lf",param[i][j][k]);
11562: }
11563: fscanf(ficpar,"\n");
11564: numlinepar++;
11565: if(mle==1)
11566: printf("\n");
11567: fprintf(ficlog,"\n");
11568: fprintf(ficparo,"\n");
1.126 brouard 11569: }
11570: }
11571: fflush(ficlog);
1.234 brouard 11572:
1.251 brouard 11573: /* Reads parameters values */
1.126 brouard 11574: p=param[1][1];
1.251 brouard 11575: pstart=paramstart[1][1];
1.126 brouard 11576:
11577: /* Reads comments: lines beginning with '#' */
11578: while((c=getc(ficpar))=='#' && c!= EOF){
11579: ungetc(c,ficpar);
11580: fgets(line, MAXLINE, ficpar);
11581: numlinepar++;
1.141 brouard 11582: fputs(line,stdout);
1.126 brouard 11583: fputs(line,ficparo);
11584: fputs(line,ficlog);
11585: }
11586: ungetc(c,ficpar);
11587:
11588: for(i=1; i <=nlstate; i++){
11589: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 11590: fscanf(ficpar,"%1d%1d",&i1,&j1);
11591: if ( (i1-i) * (j1-j) != 0){
11592: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
11593: exit(1);
11594: }
11595: printf("%1d%1d",i,j);
11596: fprintf(ficparo,"%1d%1d",i1,j1);
11597: fprintf(ficlog,"%1d%1d",i1,j1);
11598: for(k=1; k<=ncovmodel;k++){
11599: fscanf(ficpar,"%le",&delti3[i][j][k]);
11600: printf(" %le",delti3[i][j][k]);
11601: fprintf(ficparo," %le",delti3[i][j][k]);
11602: fprintf(ficlog," %le",delti3[i][j][k]);
11603: }
11604: fscanf(ficpar,"\n");
11605: numlinepar++;
11606: printf("\n");
11607: fprintf(ficparo,"\n");
11608: fprintf(ficlog,"\n");
1.126 brouard 11609: }
11610: }
11611: fflush(ficlog);
1.234 brouard 11612:
1.145 brouard 11613: /* Reads covariance matrix */
1.126 brouard 11614: delti=delti3[1][1];
1.220 brouard 11615:
11616:
1.126 brouard 11617: /* 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 11618:
1.126 brouard 11619: /* Reads comments: lines beginning with '#' */
11620: while((c=getc(ficpar))=='#' && c!= EOF){
11621: ungetc(c,ficpar);
11622: fgets(line, MAXLINE, ficpar);
11623: numlinepar++;
1.141 brouard 11624: fputs(line,stdout);
1.126 brouard 11625: fputs(line,ficparo);
11626: fputs(line,ficlog);
11627: }
11628: ungetc(c,ficpar);
1.220 brouard 11629:
1.126 brouard 11630: matcov=matrix(1,npar,1,npar);
1.203 brouard 11631: hess=matrix(1,npar,1,npar);
1.131 brouard 11632: for(i=1; i <=npar; i++)
11633: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 11634:
1.194 brouard 11635: /* Scans npar lines */
1.126 brouard 11636: for(i=1; i <=npar; i++){
1.226 brouard 11637: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 11638: if(count != 3){
1.226 brouard 11639: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11640: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11641: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11642: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11643: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11644: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11645: exit(1);
1.220 brouard 11646: }else{
1.226 brouard 11647: if(mle==1)
11648: printf("%1d%1d%d",i1,j1,jk);
11649: }
11650: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
11651: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 11652: for(j=1; j <=i; j++){
1.226 brouard 11653: fscanf(ficpar," %le",&matcov[i][j]);
11654: if(mle==1){
11655: printf(" %.5le",matcov[i][j]);
11656: }
11657: fprintf(ficlog," %.5le",matcov[i][j]);
11658: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 11659: }
11660: fscanf(ficpar,"\n");
11661: numlinepar++;
11662: if(mle==1)
1.220 brouard 11663: printf("\n");
1.126 brouard 11664: fprintf(ficlog,"\n");
11665: fprintf(ficparo,"\n");
11666: }
1.194 brouard 11667: /* End of read covariance matrix npar lines */
1.126 brouard 11668: for(i=1; i <=npar; i++)
11669: for(j=i+1;j<=npar;j++)
1.226 brouard 11670: matcov[i][j]=matcov[j][i];
1.126 brouard 11671:
11672: if(mle==1)
11673: printf("\n");
11674: fprintf(ficlog,"\n");
11675:
11676: fflush(ficlog);
11677:
11678: } /* End of mle != -3 */
1.218 brouard 11679:
1.186 brouard 11680: /* Main data
11681: */
1.290 brouard 11682: nobs=lastobs-firstobs+1; /* was = lastobs;*/
11683: /* num=lvector(1,n); */
11684: /* moisnais=vector(1,n); */
11685: /* annais=vector(1,n); */
11686: /* moisdc=vector(1,n); */
11687: /* andc=vector(1,n); */
11688: /* weight=vector(1,n); */
11689: /* agedc=vector(1,n); */
11690: /* cod=ivector(1,n); */
11691: /* for(i=1;i<=n;i++){ */
11692: num=lvector(firstobs,lastobs);
11693: moisnais=vector(firstobs,lastobs);
11694: annais=vector(firstobs,lastobs);
11695: moisdc=vector(firstobs,lastobs);
11696: andc=vector(firstobs,lastobs);
11697: weight=vector(firstobs,lastobs);
11698: agedc=vector(firstobs,lastobs);
11699: cod=ivector(firstobs,lastobs);
11700: for(i=firstobs;i<=lastobs;i++){
1.234 brouard 11701: num[i]=0;
11702: moisnais[i]=0;
11703: annais[i]=0;
11704: moisdc[i]=0;
11705: andc[i]=0;
11706: agedc[i]=0;
11707: cod[i]=0;
11708: weight[i]=1.0; /* Equal weights, 1 by default */
11709: }
1.290 brouard 11710: mint=matrix(1,maxwav,firstobs,lastobs);
11711: anint=matrix(1,maxwav,firstobs,lastobs);
11712: s=imatrix(1,maxwav+1,firstobs,lastobs); /* s[i][j] health state for wave i and individual j */
1.126 brouard 11713: tab=ivector(1,NCOVMAX);
1.144 brouard 11714: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 11715: 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 11716:
1.136 brouard 11717: /* Reads data from file datafile */
11718: if (readdata(datafile, firstobs, lastobs, &imx)==1)
11719: goto end;
11720:
11721: /* Calculation of the number of parameters from char model */
1.234 brouard 11722: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 11723: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
11724: k=3 V4 Tvar[k=3]= 4 (from V4)
11725: k=2 V1 Tvar[k=2]= 1 (from V1)
11726: k=1 Tvar[1]=2 (from V2)
1.234 brouard 11727: */
11728:
11729: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
11730: TvarsDind=ivector(1,NCOVMAX); /* */
11731: TvarsD=ivector(1,NCOVMAX); /* */
11732: TvarsQind=ivector(1,NCOVMAX); /* */
11733: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 11734: TvarF=ivector(1,NCOVMAX); /* */
11735: TvarFind=ivector(1,NCOVMAX); /* */
11736: TvarV=ivector(1,NCOVMAX); /* */
11737: TvarVind=ivector(1,NCOVMAX); /* */
11738: TvarA=ivector(1,NCOVMAX); /* */
11739: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 11740: TvarFD=ivector(1,NCOVMAX); /* */
11741: TvarFDind=ivector(1,NCOVMAX); /* */
11742: TvarFQ=ivector(1,NCOVMAX); /* */
11743: TvarFQind=ivector(1,NCOVMAX); /* */
11744: TvarVD=ivector(1,NCOVMAX); /* */
11745: TvarVDind=ivector(1,NCOVMAX); /* */
11746: TvarVQ=ivector(1,NCOVMAX); /* */
11747: TvarVQind=ivector(1,NCOVMAX); /* */
11748:
1.230 brouard 11749: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 11750: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 11751: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
11752: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
11753: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.137 brouard 11754: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
11755: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
11756: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
11757: */
11758: /* For model-covariate k tells which data-covariate to use but
11759: because this model-covariate is a construction we invent a new column
11760: ncovcol + k1
11761: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
11762: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 11763: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
11764: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 11765: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
11766: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 11767: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 11768: */
1.145 brouard 11769: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
11770: 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 11771: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
11772: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.145 brouard 11773: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 11774: 4 covariates (3 plus signs)
11775: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
11776: */
1.230 brouard 11777: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 11778: * individual dummy, fixed or varying:
11779: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
11780: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 11781: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
11782: * V1 df, V2 qf, V3 & V4 dv, V5 qv
11783: * Tmodelind[1]@9={9,0,3,2,}*/
11784: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
11785: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 11786: * individual quantitative, fixed or varying:
11787: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
11788: * 3, 1, 0, 0, 0, 0, 0, 0},
11789: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.186 brouard 11790: /* Main decodemodel */
11791:
1.187 brouard 11792:
1.223 brouard 11793: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 11794: goto end;
11795:
1.137 brouard 11796: if((double)(lastobs-imx)/(double)imx > 1.10){
11797: nbwarn++;
11798: 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);
11799: 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);
11800: }
1.136 brouard 11801: /* if(mle==1){*/
1.137 brouard 11802: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
11803: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 11804: }
11805:
11806: /*-calculation of age at interview from date of interview and age at death -*/
11807: agev=matrix(1,maxwav,1,imx);
11808:
11809: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
11810: goto end;
11811:
1.126 brouard 11812:
1.136 brouard 11813: agegomp=(int)agemin;
1.290 brouard 11814: free_vector(moisnais,firstobs,lastobs);
11815: free_vector(annais,firstobs,lastobs);
1.126 brouard 11816: /* free_matrix(mint,1,maxwav,1,n);
11817: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 11818: /* free_vector(moisdc,1,n); */
11819: /* free_vector(andc,1,n); */
1.145 brouard 11820: /* */
11821:
1.126 brouard 11822: wav=ivector(1,imx);
1.214 brouard 11823: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
11824: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
11825: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
11826: 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.*/
11827: bh=imatrix(1,lastpass-firstpass+2,1,imx);
11828: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 11829:
11830: /* Concatenates waves */
1.214 brouard 11831: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
11832: Death is a valid wave (if date is known).
11833: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
11834: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
11835: and mw[mi+1][i]. dh depends on stepm.
11836: */
11837:
1.126 brouard 11838: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 11839: /* Concatenates waves */
1.145 brouard 11840:
1.290 brouard 11841: free_vector(moisdc,firstobs,lastobs);
11842: free_vector(andc,firstobs,lastobs);
1.215 brouard 11843:
1.126 brouard 11844: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
11845: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
11846: ncodemax[1]=1;
1.145 brouard 11847: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 11848: cptcoveff=0;
1.220 brouard 11849: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
11850: tricode(&cptcoveff,Tvar,nbcode,imx, Ndum); /**< Fills nbcode[Tvar[j]][l]; */
1.227 brouard 11851: }
11852:
11853: ncovcombmax=pow(2,cptcoveff);
11854: invalidvarcomb=ivector(1, ncovcombmax);
11855: for(i=1;i<ncovcombmax;i++)
11856: invalidvarcomb[i]=0;
11857:
1.211 brouard 11858: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 11859: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 11860: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 11861:
1.200 brouard 11862: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 11863: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 11864: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 11865: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
11866: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
11867: * (currently 0 or 1) in the data.
11868: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
11869: * corresponding modality (h,j).
11870: */
11871:
1.145 brouard 11872: h=0;
11873: /*if (cptcovn > 0) */
1.126 brouard 11874: m=pow(2,cptcoveff);
11875:
1.144 brouard 11876: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 11877: * For k=4 covariates, h goes from 1 to m=2**k
11878: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
11879: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.186 brouard 11880: * h\k 1 2 3 4
1.143 brouard 11881: *______________________________
11882: * 1 i=1 1 i=1 1 i=1 1 i=1 1
11883: * 2 2 1 1 1
11884: * 3 i=2 1 2 1 1
11885: * 4 2 2 1 1
11886: * 5 i=3 1 i=2 1 2 1
11887: * 6 2 1 2 1
11888: * 7 i=4 1 2 2 1
11889: * 8 2 2 2 1
1.197 brouard 11890: * 9 i=5 1 i=3 1 i=2 1 2
11891: * 10 2 1 1 2
11892: * 11 i=6 1 2 1 2
11893: * 12 2 2 1 2
11894: * 13 i=7 1 i=4 1 2 2
11895: * 14 2 1 2 2
11896: * 15 i=8 1 2 2 2
11897: * 16 2 2 2 2
1.143 brouard 11898: */
1.212 brouard 11899: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 11900: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
11901: * and the value of each covariate?
11902: * V1=1, V2=1, V3=2, V4=1 ?
11903: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
11904: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
11905: * In order to get the real value in the data, we use nbcode
11906: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
11907: * We are keeping this crazy system in order to be able (in the future?)
11908: * to have more than 2 values (0 or 1) for a covariate.
11909: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
11910: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
11911: * bbbbbbbb
11912: * 76543210
11913: * h-1 00000101 (6-1=5)
1.219 brouard 11914: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 11915: * &
11916: * 1 00000001 (1)
1.219 brouard 11917: * 00000000 = 1 & ((h-1) >> (k-1))
11918: * +1= 00000001 =1
1.211 brouard 11919: *
11920: * h=14, k=3 => h'=h-1=13, k'=k-1=2
11921: * h' 1101 =2^3+2^2+0x2^1+2^0
11922: * >>k' 11
11923: * & 00000001
11924: * = 00000001
11925: * +1 = 00000010=2 = codtabm(14,3)
11926: * Reverse h=6 and m=16?
11927: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
11928: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
11929: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
11930: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
11931: * V3=decodtabm(14,3,2**4)=2
11932: * h'=13 1101 =2^3+2^2+0x2^1+2^0
11933: *(h-1) >> (j-1) 0011 =13 >> 2
11934: * &1 000000001
11935: * = 000000001
11936: * +1= 000000010 =2
11937: * 2211
11938: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
11939: * V3=2
1.220 brouard 11940: * codtabm and decodtabm are identical
1.211 brouard 11941: */
11942:
1.145 brouard 11943:
11944: free_ivector(Ndum,-1,NCOVMAX);
11945:
11946:
1.126 brouard 11947:
1.186 brouard 11948: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 11949: strcpy(optionfilegnuplot,optionfilefiname);
11950: if(mle==-3)
1.201 brouard 11951: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 11952: strcat(optionfilegnuplot,".gp");
11953:
11954: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
11955: printf("Problem with file %s",optionfilegnuplot);
11956: }
11957: else{
1.204 brouard 11958: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 11959: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 11960: //fprintf(ficgp,"set missing 'NaNq'\n");
11961: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 11962: }
11963: /* fclose(ficgp);*/
1.186 brouard 11964:
11965:
11966: /* Initialisation of --------- index.htm --------*/
1.126 brouard 11967:
11968: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
11969: if(mle==-3)
1.201 brouard 11970: strcat(optionfilehtm,"-MORT_");
1.126 brouard 11971: strcat(optionfilehtm,".htm");
11972: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 11973: printf("Problem with %s \n",optionfilehtm);
11974: exit(0);
1.126 brouard 11975: }
11976:
11977: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
11978: strcat(optionfilehtmcov,"-cov.htm");
11979: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
11980: printf("Problem with %s \n",optionfilehtmcov), exit(0);
11981: }
11982: else{
11983: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
11984: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 11985: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 11986: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
11987: }
11988:
1.213 brouard 11989: 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å¦è¡“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 11990: <hr size=\"2\" color=\"#EC5E5E\"> \n\
11991: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 11992: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 11993: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n\
1.126 brouard 11994: \n\
11995: <hr size=\"2\" color=\"#EC5E5E\">\
11996: <ul><li><h4>Parameter files</h4>\n\
11997: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
11998: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
11999: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
12000: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
12001: - Date and time at start: %s</ul>\n",\
12002: optionfilehtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model,\
12003: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
12004: fileres,fileres,\
12005: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
12006: fflush(fichtm);
12007:
12008: strcpy(pathr,path);
12009: strcat(pathr,optionfilefiname);
1.184 brouard 12010: #ifdef WIN32
12011: _chdir(optionfilefiname); /* Move to directory named optionfile */
12012: #else
1.126 brouard 12013: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 12014: #endif
12015:
1.126 brouard 12016:
1.220 brouard 12017: /* Calculates basic frequencies. Computes observed prevalence at single age
12018: and for any valid combination of covariates
1.126 brouard 12019: and prints on file fileres'p'. */
1.251 brouard 12020: freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 12021: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 12022:
12023: fprintf(fichtm,"\n");
1.286 brouard 12024: 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 12025: ftol, stepm);
12026: fprintf(fichtm,"\n<li>Number of fixed dummy covariates: ncovcol=%d ", ncovcol);
12027: ncurrv=1;
12028: for(i=ncurrv; i <=ncovcol; i++) fprintf(fichtm,"V%d ", i);
12029: fprintf(fichtm,"\n<li> Number of fixed quantitative variables: nqv=%d ", nqv);
12030: ncurrv=i;
12031: for(i=ncurrv; i <=ncurrv-1+nqv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 12032: fprintf(fichtm,"\n<li> Number of time varying (wave varying) dummy covariates: ntv=%d ", ntv);
1.274 brouard 12033: ncurrv=i;
12034: for(i=ncurrv; i <=ncurrv-1+ntv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 12035: fprintf(fichtm,"\n<li>Number of time varying quantitative covariates: nqtv=%d ", nqtv);
1.274 brouard 12036: ncurrv=i;
12037: for(i=ncurrv; i <=ncurrv-1+nqtv; i++) fprintf(fichtm,"V%d ", i);
12038: 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", \
12039: nlstate, ndeath, maxwav, mle, weightopt);
12040:
12041: fprintf(fichtm,"<h4> Diagram of states <a href=\"%s_.svg\">%s_.svg</a></h4> \n\
12042: <img src=\"%s_.svg\">", subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"));
12043:
12044:
1.317 brouard 12045: fprintf(fichtm,"\n<h4>Some descriptive statistics </h4>\n<br>Number of (used) observations=%d <br>\n\
1.126 brouard 12046: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
12047: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
1.274 brouard 12048: imx,agemin,agemax,jmin,jmax,jmean);
1.126 brouard 12049: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 12050: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
12051: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
12052: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
12053: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 12054:
1.126 brouard 12055: /* For Powell, parameters are in a vector p[] starting at p[1]
12056: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
12057: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
12058:
12059: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 12060: /* For mortality only */
1.126 brouard 12061: if (mle==-3){
1.136 brouard 12062: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 12063: for(i=1;i<=NDIM;i++)
12064: for(j=1;j<=NDIM;j++)
12065: ximort[i][j]=0.;
1.186 brouard 12066: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.290 brouard 12067: cens=ivector(firstobs,lastobs);
12068: ageexmed=vector(firstobs,lastobs);
12069: agecens=vector(firstobs,lastobs);
12070: dcwave=ivector(firstobs,lastobs);
1.223 brouard 12071:
1.126 brouard 12072: for (i=1; i<=imx; i++){
12073: dcwave[i]=-1;
12074: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 12075: if (s[m][i]>nlstate) {
12076: dcwave[i]=m;
12077: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
12078: break;
12079: }
1.126 brouard 12080: }
1.226 brouard 12081:
1.126 brouard 12082: for (i=1; i<=imx; i++) {
12083: if (wav[i]>0){
1.226 brouard 12084: ageexmed[i]=agev[mw[1][i]][i];
12085: j=wav[i];
12086: agecens[i]=1.;
12087:
12088: if (ageexmed[i]> 1 && wav[i] > 0){
12089: agecens[i]=agev[mw[j][i]][i];
12090: cens[i]= 1;
12091: }else if (ageexmed[i]< 1)
12092: cens[i]= -1;
12093: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
12094: cens[i]=0 ;
1.126 brouard 12095: }
12096: else cens[i]=-1;
12097: }
12098:
12099: for (i=1;i<=NDIM;i++) {
12100: for (j=1;j<=NDIM;j++)
1.226 brouard 12101: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 12102: }
12103:
1.302 brouard 12104: p[1]=0.0268; p[NDIM]=0.083;
12105: /* printf("%lf %lf", p[1], p[2]); */
1.126 brouard 12106:
12107:
1.136 brouard 12108: #ifdef GSL
12109: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 12110: #else
1.126 brouard 12111: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 12112: #endif
1.201 brouard 12113: strcpy(filerespow,"POW-MORT_");
12114: strcat(filerespow,fileresu);
1.126 brouard 12115: if((ficrespow=fopen(filerespow,"w"))==NULL) {
12116: printf("Problem with resultfile: %s\n", filerespow);
12117: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
12118: }
1.136 brouard 12119: #ifdef GSL
12120: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 12121: #else
1.126 brouard 12122: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 12123: #endif
1.126 brouard 12124: /* for (i=1;i<=nlstate;i++)
12125: for(j=1;j<=nlstate+ndeath;j++)
12126: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
12127: */
12128: fprintf(ficrespow,"\n");
1.136 brouard 12129: #ifdef GSL
12130: /* gsl starts here */
12131: T = gsl_multimin_fminimizer_nmsimplex;
12132: gsl_multimin_fminimizer *sfm = NULL;
12133: gsl_vector *ss, *x;
12134: gsl_multimin_function minex_func;
12135:
12136: /* Initial vertex size vector */
12137: ss = gsl_vector_alloc (NDIM);
12138:
12139: if (ss == NULL){
12140: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
12141: }
12142: /* Set all step sizes to 1 */
12143: gsl_vector_set_all (ss, 0.001);
12144:
12145: /* Starting point */
1.126 brouard 12146:
1.136 brouard 12147: x = gsl_vector_alloc (NDIM);
12148:
12149: if (x == NULL){
12150: gsl_vector_free(ss);
12151: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
12152: }
12153:
12154: /* Initialize method and iterate */
12155: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 12156: /* gsl_vector_set(x, 0, 0.0268); */
12157: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 12158: gsl_vector_set(x, 0, p[1]);
12159: gsl_vector_set(x, 1, p[2]);
12160:
12161: minex_func.f = &gompertz_f;
12162: minex_func.n = NDIM;
12163: minex_func.params = (void *)&p; /* ??? */
12164:
12165: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
12166: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
12167:
12168: printf("Iterations beginning .....\n\n");
12169: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
12170:
12171: iteri=0;
12172: while (rval == GSL_CONTINUE){
12173: iteri++;
12174: status = gsl_multimin_fminimizer_iterate(sfm);
12175:
12176: if (status) printf("error: %s\n", gsl_strerror (status));
12177: fflush(0);
12178:
12179: if (status)
12180: break;
12181:
12182: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
12183: ssval = gsl_multimin_fminimizer_size (sfm);
12184:
12185: if (rval == GSL_SUCCESS)
12186: printf ("converged to a local maximum at\n");
12187:
12188: printf("%5d ", iteri);
12189: for (it = 0; it < NDIM; it++){
12190: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
12191: }
12192: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
12193: }
12194:
12195: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
12196:
12197: gsl_vector_free(x); /* initial values */
12198: gsl_vector_free(ss); /* inital step size */
12199: for (it=0; it<NDIM; it++){
12200: p[it+1]=gsl_vector_get(sfm->x,it);
12201: fprintf(ficrespow," %.12lf", p[it]);
12202: }
12203: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
12204: #endif
12205: #ifdef POWELL
12206: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
12207: #endif
1.126 brouard 12208: fclose(ficrespow);
12209:
1.203 brouard 12210: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 12211:
12212: for(i=1; i <=NDIM; i++)
12213: for(j=i+1;j<=NDIM;j++)
1.220 brouard 12214: matcov[i][j]=matcov[j][i];
1.126 brouard 12215:
12216: printf("\nCovariance matrix\n ");
1.203 brouard 12217: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 12218: for(i=1; i <=NDIM; i++) {
12219: for(j=1;j<=NDIM;j++){
1.220 brouard 12220: printf("%f ",matcov[i][j]);
12221: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 12222: }
1.203 brouard 12223: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 12224: }
12225:
12226: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 12227: for (i=1;i<=NDIM;i++) {
1.126 brouard 12228: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 12229: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
12230: }
1.302 brouard 12231: lsurv=vector(agegomp,AGESUP);
12232: lpop=vector(agegomp,AGESUP);
12233: tpop=vector(agegomp,AGESUP);
1.126 brouard 12234: lsurv[agegomp]=100000;
12235:
12236: for (k=agegomp;k<=AGESUP;k++) {
12237: agemortsup=k;
12238: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
12239: }
12240:
12241: for (k=agegomp;k<agemortsup;k++)
12242: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
12243:
12244: for (k=agegomp;k<agemortsup;k++){
12245: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
12246: sumlpop=sumlpop+lpop[k];
12247: }
12248:
12249: tpop[agegomp]=sumlpop;
12250: for (k=agegomp;k<(agemortsup-3);k++){
12251: /* tpop[k+1]=2;*/
12252: tpop[k+1]=tpop[k]-lpop[k];
12253: }
12254:
12255:
12256: printf("\nAge lx qx dx Lx Tx e(x)\n");
12257: for (k=agegomp;k<(agemortsup-2);k++)
12258: 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]);
12259:
12260:
12261: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 12262: ageminpar=50;
12263: agemaxpar=100;
1.194 brouard 12264: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
12265: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
12266: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12267: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
12268: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
12269: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12270: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 12271: }else{
12272: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
12273: 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 12274: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 12275: }
1.201 brouard 12276: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 12277: stepm, weightopt,\
12278: model,imx,p,matcov,agemortsup);
12279:
1.302 brouard 12280: free_vector(lsurv,agegomp,AGESUP);
12281: free_vector(lpop,agegomp,AGESUP);
12282: free_vector(tpop,agegomp,AGESUP);
1.220 brouard 12283: free_matrix(ximort,1,NDIM,1,NDIM);
1.290 brouard 12284: free_ivector(dcwave,firstobs,lastobs);
12285: free_vector(agecens,firstobs,lastobs);
12286: free_vector(ageexmed,firstobs,lastobs);
12287: free_ivector(cens,firstobs,lastobs);
1.220 brouard 12288: #ifdef GSL
1.136 brouard 12289: #endif
1.186 brouard 12290: } /* Endof if mle==-3 mortality only */
1.205 brouard 12291: /* Standard */
12292: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
12293: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
12294: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 12295: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 12296: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
12297: for (k=1; k<=npar;k++)
12298: printf(" %d %8.5f",k,p[k]);
12299: printf("\n");
1.205 brouard 12300: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
12301: /* mlikeli uses func not funcone */
1.247 brouard 12302: /* for(i=1;i<nlstate;i++){ */
12303: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
12304: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
12305: /* } */
1.205 brouard 12306: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
12307: }
12308: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
12309: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
12310: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
12311: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
12312: }
12313: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 12314: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
12315: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
12316: for (k=1; k<=npar;k++)
12317: printf(" %d %8.5f",k,p[k]);
12318: printf("\n");
12319:
12320: /*--------- results files --------------*/
1.283 brouard 12321: /* 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 12322:
12323:
12324: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
12325: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
12326: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
12327: for(i=1,jk=1; i <=nlstate; i++){
12328: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 12329: if (k != i) {
12330: printf("%d%d ",i,k);
12331: fprintf(ficlog,"%d%d ",i,k);
12332: fprintf(ficres,"%1d%1d ",i,k);
12333: for(j=1; j <=ncovmodel; j++){
12334: printf("%12.7f ",p[jk]);
12335: fprintf(ficlog,"%12.7f ",p[jk]);
12336: fprintf(ficres,"%12.7f ",p[jk]);
12337: jk++;
12338: }
12339: printf("\n");
12340: fprintf(ficlog,"\n");
12341: fprintf(ficres,"\n");
12342: }
1.126 brouard 12343: }
12344: }
1.203 brouard 12345: if(mle != 0){
12346: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 12347: ftolhess=ftol; /* Usually correct */
1.203 brouard 12348: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
12349: 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");
12350: 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");
12351: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 12352: for(k=1; k <=(nlstate+ndeath); k++){
12353: if (k != i) {
12354: printf("%d%d ",i,k);
12355: fprintf(ficlog,"%d%d ",i,k);
12356: for(j=1; j <=ncovmodel; j++){
12357: printf("%12.7f W=%8.3f CI=[%12.7f ; %12.7f] ",p[jk], p[jk]/sqrt(matcov[jk][jk]), p[jk]-1.96*sqrt(matcov[jk][jk]),p[jk]+1.96*sqrt(matcov[jk][jk]));
12358: fprintf(ficlog,"%12.7f W=%8.3f CI=[%12.7f ; %12.7f] ",p[jk], p[jk]/sqrt(matcov[jk][jk]), p[jk]-1.96*sqrt(matcov[jk][jk]),p[jk]+1.96*sqrt(matcov[jk][jk]));
12359: jk++;
12360: }
12361: printf("\n");
12362: fprintf(ficlog,"\n");
12363: }
12364: }
1.193 brouard 12365: }
1.203 brouard 12366: } /* end of hesscov and Wald tests */
1.225 brouard 12367:
1.203 brouard 12368: /* */
1.126 brouard 12369: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
12370: printf("# Scales (for hessian or gradient estimation)\n");
12371: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
12372: for(i=1,jk=1; i <=nlstate; i++){
12373: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 12374: if (j!=i) {
12375: fprintf(ficres,"%1d%1d",i,j);
12376: printf("%1d%1d",i,j);
12377: fprintf(ficlog,"%1d%1d",i,j);
12378: for(k=1; k<=ncovmodel;k++){
12379: printf(" %.5e",delti[jk]);
12380: fprintf(ficlog," %.5e",delti[jk]);
12381: fprintf(ficres," %.5e",delti[jk]);
12382: jk++;
12383: }
12384: printf("\n");
12385: fprintf(ficlog,"\n");
12386: fprintf(ficres,"\n");
12387: }
1.126 brouard 12388: }
12389: }
12390:
12391: 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 12392: if(mle >= 1) /* To big for the screen */
1.126 brouard 12393: 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");
12394: 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");
12395: /* # 121 Var(a12)\n\ */
12396: /* # 122 Cov(b12,a12) Var(b12)\n\ */
12397: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
12398: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
12399: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
12400: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
12401: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
12402: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
12403:
12404:
12405: /* Just to have a covariance matrix which will be more understandable
12406: even is we still don't want to manage dictionary of variables
12407: */
12408: for(itimes=1;itimes<=2;itimes++){
12409: jj=0;
12410: for(i=1; i <=nlstate; i++){
1.225 brouard 12411: for(j=1; j <=nlstate+ndeath; j++){
12412: if(j==i) continue;
12413: for(k=1; k<=ncovmodel;k++){
12414: jj++;
12415: ca[0]= k+'a'-1;ca[1]='\0';
12416: if(itimes==1){
12417: if(mle>=1)
12418: printf("#%1d%1d%d",i,j,k);
12419: fprintf(ficlog,"#%1d%1d%d",i,j,k);
12420: fprintf(ficres,"#%1d%1d%d",i,j,k);
12421: }else{
12422: if(mle>=1)
12423: printf("%1d%1d%d",i,j,k);
12424: fprintf(ficlog,"%1d%1d%d",i,j,k);
12425: fprintf(ficres,"%1d%1d%d",i,j,k);
12426: }
12427: ll=0;
12428: for(li=1;li <=nlstate; li++){
12429: for(lj=1;lj <=nlstate+ndeath; lj++){
12430: if(lj==li) continue;
12431: for(lk=1;lk<=ncovmodel;lk++){
12432: ll++;
12433: if(ll<=jj){
12434: cb[0]= lk +'a'-1;cb[1]='\0';
12435: if(ll<jj){
12436: if(itimes==1){
12437: if(mle>=1)
12438: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12439: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12440: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12441: }else{
12442: if(mle>=1)
12443: printf(" %.5e",matcov[jj][ll]);
12444: fprintf(ficlog," %.5e",matcov[jj][ll]);
12445: fprintf(ficres," %.5e",matcov[jj][ll]);
12446: }
12447: }else{
12448: if(itimes==1){
12449: if(mle>=1)
12450: printf(" Var(%s%1d%1d)",ca,i,j);
12451: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
12452: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
12453: }else{
12454: if(mle>=1)
12455: printf(" %.7e",matcov[jj][ll]);
12456: fprintf(ficlog," %.7e",matcov[jj][ll]);
12457: fprintf(ficres," %.7e",matcov[jj][ll]);
12458: }
12459: }
12460: }
12461: } /* end lk */
12462: } /* end lj */
12463: } /* end li */
12464: if(mle>=1)
12465: printf("\n");
12466: fprintf(ficlog,"\n");
12467: fprintf(ficres,"\n");
12468: numlinepar++;
12469: } /* end k*/
12470: } /*end j */
1.126 brouard 12471: } /* end i */
12472: } /* end itimes */
12473:
12474: fflush(ficlog);
12475: fflush(ficres);
1.225 brouard 12476: while(fgets(line, MAXLINE, ficpar)) {
12477: /* If line starts with a # it is a comment */
12478: if (line[0] == '#') {
12479: numlinepar++;
12480: fputs(line,stdout);
12481: fputs(line,ficparo);
12482: fputs(line,ficlog);
1.299 brouard 12483: fputs(line,ficres);
1.225 brouard 12484: continue;
12485: }else
12486: break;
12487: }
12488:
1.209 brouard 12489: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
12490: /* ungetc(c,ficpar); */
12491: /* fgets(line, MAXLINE, ficpar); */
12492: /* fputs(line,stdout); */
12493: /* fputs(line,ficparo); */
12494: /* } */
12495: /* ungetc(c,ficpar); */
1.126 brouard 12496:
12497: estepm=0;
1.209 brouard 12498: 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 12499:
12500: if (num_filled != 6) {
12501: 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);
12502: 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);
12503: goto end;
12504: }
12505: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
12506: }
12507: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
12508: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
12509:
1.209 brouard 12510: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 12511: if (estepm==0 || estepm < stepm) estepm=stepm;
12512: if (fage <= 2) {
12513: bage = ageminpar;
12514: fage = agemaxpar;
12515: }
12516:
12517: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 12518: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
12519: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 12520:
1.186 brouard 12521: /* Other stuffs, more or less useful */
1.254 brouard 12522: while(fgets(line, MAXLINE, ficpar)) {
12523: /* If line starts with a # it is a comment */
12524: if (line[0] == '#') {
12525: numlinepar++;
12526: fputs(line,stdout);
12527: fputs(line,ficparo);
12528: fputs(line,ficlog);
1.299 brouard 12529: fputs(line,ficres);
1.254 brouard 12530: continue;
12531: }else
12532: break;
12533: }
12534:
12535: 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){
12536:
12537: if (num_filled != 7) {
12538: 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);
12539: 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);
12540: goto end;
12541: }
12542: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
12543: 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);
12544: 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);
12545: 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 12546: }
1.254 brouard 12547:
12548: while(fgets(line, MAXLINE, ficpar)) {
12549: /* If line starts with a # it is a comment */
12550: if (line[0] == '#') {
12551: numlinepar++;
12552: fputs(line,stdout);
12553: fputs(line,ficparo);
12554: fputs(line,ficlog);
1.299 brouard 12555: fputs(line,ficres);
1.254 brouard 12556: continue;
12557: }else
12558: break;
1.126 brouard 12559: }
12560:
12561:
12562: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
12563: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
12564:
1.254 brouard 12565: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
12566: if (num_filled != 1) {
12567: 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);
12568: 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);
12569: goto end;
12570: }
12571: printf("pop_based=%d\n",popbased);
12572: fprintf(ficlog,"pop_based=%d\n",popbased);
12573: fprintf(ficparo,"pop_based=%d\n",popbased);
12574: fprintf(ficres,"pop_based=%d\n",popbased);
12575: }
12576:
1.258 brouard 12577: /* Results */
1.307 brouard 12578: endishere=0;
1.258 brouard 12579: nresult=0;
1.308 brouard 12580: parameterline=0;
1.258 brouard 12581: do{
12582: if(!fgets(line, MAXLINE, ficpar)){
12583: endishere=1;
1.308 brouard 12584: parameterline=15;
1.258 brouard 12585: }else if (line[0] == '#') {
12586: /* If line starts with a # it is a comment */
1.254 brouard 12587: numlinepar++;
12588: fputs(line,stdout);
12589: fputs(line,ficparo);
12590: fputs(line,ficlog);
1.299 brouard 12591: fputs(line,ficres);
1.254 brouard 12592: continue;
1.258 brouard 12593: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
12594: parameterline=11;
1.296 brouard 12595: else if(sscanf(line,"prevbackcast=%[^\n]\n",modeltemp))
1.258 brouard 12596: parameterline=12;
1.307 brouard 12597: else if(sscanf(line,"result:%[^\n]\n",modeltemp)){
1.258 brouard 12598: parameterline=13;
1.307 brouard 12599: }
1.258 brouard 12600: else{
12601: parameterline=14;
1.254 brouard 12602: }
1.308 brouard 12603: switch (parameterline){ /* =0 only if only comments */
1.258 brouard 12604: case 11:
1.296 brouard 12605: 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)){
12606: 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 12607: 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);
12608: 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);
12609: 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);
12610: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 12611: dateproj1=anproj1+(mproj1-1)/12.+(jproj1-1)/365.;
12612: dateproj2=anproj2+(mproj2-1)/12.+(jproj2-1)/365.;
1.296 brouard 12613: prvforecast = 1;
12614: }
12615: else if((num_filled=sscanf(line,"prevforecast=%d yearsfproj=%lf mobil_average=%d\n",&prevfcast,&yrfproj,&mobilavproj)) !=EOF){/* && (num_filled == 3))*/
1.313 brouard 12616: printf("prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
12617: fprintf(ficlog,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
12618: fprintf(ficres,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
1.296 brouard 12619: prvforecast = 2;
12620: }
12621: else {
12622: 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);
12623: 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);
12624: goto end;
1.258 brouard 12625: }
1.254 brouard 12626: break;
1.258 brouard 12627: case 12:
1.296 brouard 12628: 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)){
12629: 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);
12630: 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);
12631: 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);
12632: 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);
12633: /* day and month of back2 are not used but only year anback2.*/
1.273 brouard 12634: dateback1=anback1+(mback1-1)/12.+(jback1-1)/365.;
12635: dateback2=anback2+(mback2-1)/12.+(jback2-1)/365.;
1.296 brouard 12636: prvbackcast = 1;
12637: }
12638: else if((num_filled=sscanf(line,"prevbackcast=%d yearsbproj=%lf mobil_average=%d\n",&prevbcast,&yrbproj,&mobilavproj)) ==3){/* && (num_filled == 3))*/
1.313 brouard 12639: printf("prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
12640: fprintf(ficlog,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
12641: fprintf(ficres,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
1.296 brouard 12642: prvbackcast = 2;
12643: }
12644: else {
12645: 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);
12646: 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);
12647: goto end;
1.258 brouard 12648: }
1.230 brouard 12649: break;
1.258 brouard 12650: case 13:
1.307 brouard 12651: num_filled=sscanf(line,"result:%[^\n]\n",resultline);
12652: nresult++; /* Sum of resultlines */
12653: printf("Result %d: result:%s\n",nresult, resultline);
1.318 ! brouard 12654: if(nresult > MAXRESULTLINESPONE-1){
! 12655: 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);
! 12656: 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 12657: goto end;
12658: }
1.310 brouard 12659: if(!decoderesult(resultline, nresult)){ /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
1.314 brouard 12660: fprintf(ficparo,"result: %s\n",resultline);
12661: fprintf(ficres,"result: %s\n",resultline);
12662: fprintf(ficlog,"result: %s\n",resultline);
1.310 brouard 12663: } else
12664: goto end;
1.307 brouard 12665: break;
12666: case 14:
12667: printf("Error: Unknown command '%s'\n",line);
12668: fprintf(ficlog,"Error: Unknown command '%s'\n",line);
1.314 brouard 12669: if(line[0] == ' ' || line[0] == '\n'){
12670: printf("It should not be an empty line '%s'\n",line);
12671: fprintf(ficlog,"It should not be an empty line '%s'\n",line);
12672: }
1.307 brouard 12673: if(ncovmodel >=2 && nresult==0 ){
12674: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
12675: fprintf(ficlog,"ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 12676: }
1.307 brouard 12677: /* goto end; */
12678: break;
1.308 brouard 12679: case 15:
12680: printf("End of resultlines.\n");
12681: fprintf(ficlog,"End of resultlines.\n");
12682: break;
12683: default: /* parameterline =0 */
1.307 brouard 12684: nresult=1;
12685: decoderesult(".",nresult ); /* No covariate */
1.258 brouard 12686: } /* End switch parameterline */
12687: }while(endishere==0); /* End do */
1.126 brouard 12688:
1.230 brouard 12689: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 12690: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 12691:
12692: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 12693: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 12694: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 12695: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12696: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 12697: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 12698: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12699: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 12700: }else{
1.270 brouard 12701: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
1.296 brouard 12702: /* It seems that anprojd which is computed from the mean year at interview which is known yet because of freqsummary */
12703: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */ /* Done in freqsummary */
12704: if(prvforecast==1){
12705: dateprojd=(jproj1+12*mproj1+365*anproj1)/365;
12706: jprojd=jproj1;
12707: mprojd=mproj1;
12708: anprojd=anproj1;
12709: dateprojf=(jproj2+12*mproj2+365*anproj2)/365;
12710: jprojf=jproj2;
12711: mprojf=mproj2;
12712: anprojf=anproj2;
12713: } else if(prvforecast == 2){
12714: dateprojd=dateintmean;
12715: date2dmy(dateprojd,&jprojd, &mprojd, &anprojd);
12716: dateprojf=dateintmean+yrfproj;
12717: date2dmy(dateprojf,&jprojf, &mprojf, &anprojf);
12718: }
12719: if(prvbackcast==1){
12720: datebackd=(jback1+12*mback1+365*anback1)/365;
12721: jbackd=jback1;
12722: mbackd=mback1;
12723: anbackd=anback1;
12724: datebackf=(jback2+12*mback2+365*anback2)/365;
12725: jbackf=jback2;
12726: mbackf=mback2;
12727: anbackf=anback2;
12728: } else if(prvbackcast == 2){
12729: datebackd=dateintmean;
12730: date2dmy(datebackd,&jbackd, &mbackd, &anbackd);
12731: datebackf=dateintmean-yrbproj;
12732: date2dmy(datebackf,&jbackf, &mbackf, &anbackf);
12733: }
12734:
12735: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, prevbcast, pathc,p, (int)anprojd-bage, (int)anbackd-fage);
1.220 brouard 12736: }
12737: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.296 brouard 12738: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,prevbcast, estepm, \
12739: jprev1,mprev1,anprev1,dateprev1, dateprojd, datebackd,jprev2,mprev2,anprev2,dateprev2,dateprojf, datebackf);
1.220 brouard 12740:
1.225 brouard 12741: /*------------ free_vector -------------*/
12742: /* chdir(path); */
1.220 brouard 12743:
1.215 brouard 12744: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
12745: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
12746: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
12747: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.290 brouard 12748: free_lvector(num,firstobs,lastobs);
12749: free_vector(agedc,firstobs,lastobs);
1.126 brouard 12750: /*free_matrix(covar,0,NCOVMAX,1,n);*/
12751: /*free_matrix(covar,1,NCOVMAX,1,n);*/
12752: fclose(ficparo);
12753: fclose(ficres);
1.220 brouard 12754:
12755:
1.186 brouard 12756: /* Other results (useful)*/
1.220 brouard 12757:
12758:
1.126 brouard 12759: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 12760: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
12761: prlim=matrix(1,nlstate,1,nlstate);
1.209 brouard 12762: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 12763: fclose(ficrespl);
12764:
12765: /*------------- h Pij x at various ages ------------*/
1.180 brouard 12766: /*#include "hpijx.h"*/
12767: hPijx(p, bage, fage);
1.145 brouard 12768: fclose(ficrespij);
1.227 brouard 12769:
1.220 brouard 12770: /* ncovcombmax= pow(2,cptcoveff); */
1.219 brouard 12771: /*-------------- Variance of one-step probabilities---*/
1.145 brouard 12772: k=1;
1.126 brouard 12773: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 12774:
1.269 brouard 12775: /* Prevalence for each covariate combination in probs[age][status][cov] */
12776: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
12777: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 12778: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 12779: for(k=1;k<=ncovcombmax;k++)
12780: probs[i][j][k]=0.;
1.269 brouard 12781: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
12782: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 12783: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 12784: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
12785: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 12786: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 12787: for(k=1;k<=ncovcombmax;k++)
12788: mobaverages[i][j][k]=0.;
1.219 brouard 12789: mobaverage=mobaverages;
12790: if (mobilav!=0) {
1.235 brouard 12791: printf("Movingaveraging observed prevalence\n");
1.258 brouard 12792: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 12793: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
12794: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
12795: printf(" Error in movingaverage mobilav=%d\n",mobilav);
12796: }
1.269 brouard 12797: } else if (mobilavproj !=0) {
1.235 brouard 12798: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 12799: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 12800: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
12801: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
12802: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
12803: }
1.269 brouard 12804: }else{
12805: printf("Internal error moving average\n");
12806: fflush(stdout);
12807: exit(1);
1.219 brouard 12808: }
12809: }/* end if moving average */
1.227 brouard 12810:
1.126 brouard 12811: /*---------- Forecasting ------------------*/
1.296 brouard 12812: if(prevfcast==1){
12813: /* /\* if(stepm ==1){*\/ */
12814: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
12815: /*This done previously after freqsummary.*/
12816: /* dateprojd=(jproj1+12*mproj1+365*anproj1)/365; */
12817: /* dateprojf=(jproj2+12*mproj2+365*anproj2)/365; */
12818:
12819: /* } else if (prvforecast==2){ */
12820: /* /\* if(stepm ==1){*\/ */
12821: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
12822: /* } */
12823: /*prevforecast(fileresu, dateintmean, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);*/
12824: prevforecast(fileresu,dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, p, cptcoveff);
1.126 brouard 12825: }
1.269 brouard 12826:
1.296 brouard 12827: /* Prevbcasting */
12828: if(prevbcast==1){
1.219 brouard 12829: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12830: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12831: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12832:
12833: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
12834:
12835: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 12836:
1.219 brouard 12837: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
12838: fclose(ficresplb);
12839:
1.222 brouard 12840: hBijx(p, bage, fage, mobaverage);
12841: fclose(ficrespijb);
1.219 brouard 12842:
1.296 brouard 12843: /* /\* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, *\/ */
12844: /* /\* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); *\/ */
12845: /* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, */
12846: /* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); */
12847: prevbackforecast(fileresu, mobaverage, dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2,
12848: mobilavproj, bage, fage, firstpass, lastpass, p, cptcoveff);
12849:
12850:
1.269 brouard 12851: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 12852:
12853:
1.269 brouard 12854: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 12855: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
12856: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
12857: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.296 brouard 12858: } /* end Prevbcasting */
1.268 brouard 12859:
1.186 brouard 12860:
12861: /* ------ Other prevalence ratios------------ */
1.126 brouard 12862:
1.215 brouard 12863: free_ivector(wav,1,imx);
12864: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
12865: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
12866: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 12867:
12868:
1.127 brouard 12869: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 12870:
1.201 brouard 12871: strcpy(filerese,"E_");
12872: strcat(filerese,fileresu);
1.126 brouard 12873: if((ficreseij=fopen(filerese,"w"))==NULL) {
12874: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
12875: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
12876: }
1.208 brouard 12877: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
12878: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 12879:
12880: pstamp(ficreseij);
1.219 brouard 12881:
1.235 brouard 12882: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
12883: if (cptcovn < 1){i1=1;}
12884:
12885: for(nres=1; nres <= nresult; nres++) /* For each resultline */
12886: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 12887: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 12888: continue;
1.219 brouard 12889: fprintf(ficreseij,"\n#****** ");
1.235 brouard 12890: printf("\n#****** ");
1.225 brouard 12891: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 12892: fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 12893: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12894: }
12895: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12896: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12897: fprintf(ficreseij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
1.219 brouard 12898: }
12899: fprintf(ficreseij,"******\n");
1.235 brouard 12900: printf("******\n");
1.219 brouard 12901:
12902: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12903: oldm=oldms;savm=savms;
1.235 brouard 12904: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 12905:
1.219 brouard 12906: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 12907: }
12908: fclose(ficreseij);
1.208 brouard 12909: printf("done evsij\n");fflush(stdout);
12910: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 12911:
1.218 brouard 12912:
1.227 brouard 12913: /*---------- State-specific expectancies and variances ------------*/
1.218 brouard 12914:
1.201 brouard 12915: strcpy(filerest,"T_");
12916: strcat(filerest,fileresu);
1.127 brouard 12917: if((ficrest=fopen(filerest,"w"))==NULL) {
12918: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
12919: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
12920: }
1.208 brouard 12921: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
12922: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 12923: strcpy(fileresstde,"STDE_");
12924: strcat(fileresstde,fileresu);
1.126 brouard 12925: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 12926: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
12927: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 12928: }
1.227 brouard 12929: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
12930: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 12931:
1.201 brouard 12932: strcpy(filerescve,"CVE_");
12933: strcat(filerescve,fileresu);
1.126 brouard 12934: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 12935: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
12936: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 12937: }
1.227 brouard 12938: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
12939: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 12940:
1.201 brouard 12941: strcpy(fileresv,"V_");
12942: strcat(fileresv,fileresu);
1.126 brouard 12943: if((ficresvij=fopen(fileresv,"w"))==NULL) {
12944: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
12945: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
12946: }
1.227 brouard 12947: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
12948: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 12949:
1.235 brouard 12950: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
12951: if (cptcovn < 1){i1=1;}
12952:
12953: for(nres=1; nres <= nresult; nres++) /* For each resultline */
12954: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 12955: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 12956: continue;
1.242 brouard 12957: printf("\n#****** Result for:");
12958: fprintf(ficrest,"\n#****** Result for:");
12959: fprintf(ficlog,"\n#****** Result for:");
1.227 brouard 12960: for(j=1;j<=cptcoveff;j++){
12961: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12962: fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12963: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12964: }
1.235 brouard 12965: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12966: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12967: fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12968: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12969: }
1.208 brouard 12970: fprintf(ficrest,"******\n");
1.227 brouard 12971: fprintf(ficlog,"******\n");
12972: printf("******\n");
1.208 brouard 12973:
12974: fprintf(ficresstdeij,"\n#****** ");
12975: fprintf(ficrescveij,"\n#****** ");
1.225 brouard 12976: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 12977: fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12978: fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.208 brouard 12979: }
1.235 brouard 12980: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12981: fprintf(ficresstdeij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12982: fprintf(ficrescveij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12983: }
1.208 brouard 12984: fprintf(ficresstdeij,"******\n");
12985: fprintf(ficrescveij,"******\n");
12986:
12987: fprintf(ficresvij,"\n#****** ");
1.238 brouard 12988: /* pstamp(ficresvij); */
1.225 brouard 12989: for(j=1;j<=cptcoveff;j++)
1.227 brouard 12990: fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 12991: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12992: fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12993: }
1.208 brouard 12994: fprintf(ficresvij,"******\n");
12995:
12996: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12997: oldm=oldms;savm=savms;
1.235 brouard 12998: printf(" cvevsij ");
12999: fprintf(ficlog, " cvevsij ");
13000: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 13001: printf(" end cvevsij \n ");
13002: fprintf(ficlog, " end cvevsij \n ");
13003:
13004: /*
13005: */
13006: /* goto endfree; */
13007:
13008: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
13009: pstamp(ficrest);
13010:
1.269 brouard 13011: epj=vector(1,nlstate+1);
1.208 brouard 13012: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 13013: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
13014: cptcod= 0; /* To be deleted */
13015: printf("varevsij vpopbased=%d \n",vpopbased);
13016: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 13017: 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 13018: 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 ");
13019: if(vpopbased==1)
13020: 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);
13021: else
1.288 brouard 13022: fprintf(ficrest,"the age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 13023: fprintf(ficrest,"# Age popbased mobilav e.. (std) ");
13024: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
13025: fprintf(ficrest,"\n");
13026: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
1.288 brouard 13027: printf("Computing age specific forward period (stable) prevalences in each health state \n");
13028: fprintf(ficlog,"Computing age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 13029: for(age=bage; age <=fage ;age++){
1.235 brouard 13030: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 13031: if (vpopbased==1) {
13032: if(mobilav ==0){
13033: for(i=1; i<=nlstate;i++)
13034: prlim[i][i]=probs[(int)age][i][k];
13035: }else{ /* mobilav */
13036: for(i=1; i<=nlstate;i++)
13037: prlim[i][i]=mobaverage[(int)age][i][k];
13038: }
13039: }
1.219 brouard 13040:
1.227 brouard 13041: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
13042: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
13043: /* printf(" age %4.0f ",age); */
13044: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
13045: for(i=1, epj[j]=0.;i <=nlstate;i++) {
13046: epj[j] += prlim[i][i]*eij[i][j][(int)age];
13047: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
13048: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
13049: }
13050: epj[nlstate+1] +=epj[j];
13051: }
13052: /* printf(" age %4.0f \n",age); */
1.219 brouard 13053:
1.227 brouard 13054: for(i=1, vepp=0.;i <=nlstate;i++)
13055: for(j=1;j <=nlstate;j++)
13056: vepp += vareij[i][j][(int)age];
13057: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
13058: for(j=1;j <=nlstate;j++){
13059: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
13060: }
13061: fprintf(ficrest,"\n");
13062: }
1.208 brouard 13063: } /* End vpopbased */
1.269 brouard 13064: free_vector(epj,1,nlstate+1);
1.208 brouard 13065: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
13066: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 13067: printf("done selection\n");fflush(stdout);
13068: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 13069:
1.235 brouard 13070: } /* End k selection */
1.227 brouard 13071:
13072: printf("done State-specific expectancies\n");fflush(stdout);
13073: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
13074:
1.288 brouard 13075: /* variance-covariance of forward period prevalence*/
1.269 brouard 13076: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 13077:
1.227 brouard 13078:
1.290 brouard 13079: free_vector(weight,firstobs,lastobs);
1.227 brouard 13080: free_imatrix(Tvard,1,NCOVMAX,1,2);
1.290 brouard 13081: free_imatrix(s,1,maxwav+1,firstobs,lastobs);
13082: free_matrix(anint,1,maxwav,firstobs,lastobs);
13083: free_matrix(mint,1,maxwav,firstobs,lastobs);
13084: free_ivector(cod,firstobs,lastobs);
1.227 brouard 13085: free_ivector(tab,1,NCOVMAX);
13086: fclose(ficresstdeij);
13087: fclose(ficrescveij);
13088: fclose(ficresvij);
13089: fclose(ficrest);
13090: fclose(ficpar);
13091:
13092:
1.126 brouard 13093: /*---------- End : free ----------------*/
1.219 brouard 13094: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 13095: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
13096: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 13097: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
13098: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 13099: } /* mle==-3 arrives here for freeing */
1.227 brouard 13100: /* endfree:*/
13101: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
13102: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
13103: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.290 brouard 13104: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,firstobs,lastobs);
13105: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,firstobs,lastobs);
13106: if(nqv>=1)free_matrix(coqvar,1,nqv,firstobs,lastobs);
13107: free_matrix(covar,0,NCOVMAX,firstobs,lastobs);
1.227 brouard 13108: free_matrix(matcov,1,npar,1,npar);
13109: free_matrix(hess,1,npar,1,npar);
13110: /*free_vector(delti,1,npar);*/
13111: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
13112: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 13113: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 13114: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
13115:
13116: free_ivector(ncodemax,1,NCOVMAX);
13117: free_ivector(ncodemaxwundef,1,NCOVMAX);
13118: free_ivector(Dummy,-1,NCOVMAX);
13119: free_ivector(Fixed,-1,NCOVMAX);
1.238 brouard 13120: free_ivector(DummyV,1,NCOVMAX);
13121: free_ivector(FixedV,1,NCOVMAX);
1.227 brouard 13122: free_ivector(Typevar,-1,NCOVMAX);
13123: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 13124: free_ivector(TvarsQ,1,NCOVMAX);
13125: free_ivector(TvarsQind,1,NCOVMAX);
13126: free_ivector(TvarsD,1,NCOVMAX);
13127: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 13128: free_ivector(TvarFD,1,NCOVMAX);
13129: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 13130: free_ivector(TvarF,1,NCOVMAX);
13131: free_ivector(TvarFind,1,NCOVMAX);
13132: free_ivector(TvarV,1,NCOVMAX);
13133: free_ivector(TvarVind,1,NCOVMAX);
13134: free_ivector(TvarA,1,NCOVMAX);
13135: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 13136: free_ivector(TvarFQ,1,NCOVMAX);
13137: free_ivector(TvarFQind,1,NCOVMAX);
13138: free_ivector(TvarVD,1,NCOVMAX);
13139: free_ivector(TvarVDind,1,NCOVMAX);
13140: free_ivector(TvarVQ,1,NCOVMAX);
13141: free_ivector(TvarVQind,1,NCOVMAX);
1.230 brouard 13142: free_ivector(Tvarsel,1,NCOVMAX);
13143: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 13144: free_ivector(Tposprod,1,NCOVMAX);
13145: free_ivector(Tprod,1,NCOVMAX);
13146: free_ivector(Tvaraff,1,NCOVMAX);
13147: free_ivector(invalidvarcomb,1,ncovcombmax);
13148: free_ivector(Tage,1,NCOVMAX);
13149: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 13150: free_ivector(TmodelInvind,1,NCOVMAX);
13151: free_ivector(TmodelInvQind,1,NCOVMAX);
1.227 brouard 13152:
13153: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
13154: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 13155: fflush(fichtm);
13156: fflush(ficgp);
13157:
1.227 brouard 13158:
1.126 brouard 13159: if((nberr >0) || (nbwarn>0)){
1.216 brouard 13160: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
13161: 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 13162: }else{
13163: printf("End of Imach\n");
13164: fprintf(ficlog,"End of Imach\n");
13165: }
13166: printf("See log file on %s\n",filelog);
13167: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 13168: /*(void) gettimeofday(&end_time,&tzp);*/
13169: rend_time = time(NULL);
13170: end_time = *localtime(&rend_time);
13171: /* tml = *localtime(&end_time.tm_sec); */
13172: strcpy(strtend,asctime(&end_time));
1.126 brouard 13173: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
13174: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 13175: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 13176:
1.157 brouard 13177: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
13178: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
13179: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 13180: /* printf("Total time was %d uSec.\n", total_usecs);*/
13181: /* if(fileappend(fichtm,optionfilehtm)){ */
13182: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
13183: fclose(fichtm);
13184: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
13185: fclose(fichtmcov);
13186: fclose(ficgp);
13187: fclose(ficlog);
13188: /*------ End -----------*/
1.227 brouard 13189:
1.281 brouard 13190:
13191: /* Executes gnuplot */
1.227 brouard 13192:
13193: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 13194: #ifdef WIN32
1.227 brouard 13195: if (_chdir(pathcd) != 0)
13196: printf("Can't move to directory %s!\n",path);
13197: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 13198: #else
1.227 brouard 13199: if(chdir(pathcd) != 0)
13200: printf("Can't move to directory %s!\n", path);
13201: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 13202: #endif
1.126 brouard 13203: printf("Current directory %s!\n",pathcd);
13204: /*strcat(plotcmd,CHARSEPARATOR);*/
13205: sprintf(plotcmd,"gnuplot");
1.157 brouard 13206: #ifdef _WIN32
1.126 brouard 13207: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
13208: #endif
13209: if(!stat(plotcmd,&info)){
1.158 brouard 13210: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 13211: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 13212: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 13213: }else
13214: strcpy(pplotcmd,plotcmd);
1.157 brouard 13215: #ifdef __unix
1.126 brouard 13216: strcpy(plotcmd,GNUPLOTPROGRAM);
13217: if(!stat(plotcmd,&info)){
1.158 brouard 13218: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 13219: }else
13220: strcpy(pplotcmd,plotcmd);
13221: #endif
13222: }else
13223: strcpy(pplotcmd,plotcmd);
13224:
13225: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 13226: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.292 brouard 13227: strcpy(pplotcmd,plotcmd);
1.227 brouard 13228:
1.126 brouard 13229: if((outcmd=system(plotcmd)) != 0){
1.292 brouard 13230: printf("Error in gnuplot, command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 13231: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 13232: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.292 brouard 13233: if((outcmd=system(plotcmd)) != 0){
1.153 brouard 13234: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.292 brouard 13235: strcpy(plotcmd,pplotcmd);
13236: }
1.126 brouard 13237: }
1.158 brouard 13238: printf(" Successful, please wait...");
1.126 brouard 13239: while (z[0] != 'q') {
13240: /* chdir(path); */
1.154 brouard 13241: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 13242: scanf("%s",z);
13243: /* if (z[0] == 'c') system("./imach"); */
13244: if (z[0] == 'e') {
1.158 brouard 13245: #ifdef __APPLE__
1.152 brouard 13246: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 13247: #elif __linux
13248: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 13249: #else
1.152 brouard 13250: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 13251: #endif
13252: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
13253: system(pplotcmd);
1.126 brouard 13254: }
13255: else if (z[0] == 'g') system(plotcmd);
13256: else if (z[0] == 'q') exit(0);
13257: }
1.227 brouard 13258: end:
1.126 brouard 13259: while (z[0] != 'q') {
1.195 brouard 13260: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 13261: scanf("%s",z);
13262: }
1.283 brouard 13263: printf("End\n");
1.282 brouard 13264: exit(0);
1.126 brouard 13265: }
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