Annotation of imach/src/imach.c, revision 1.338
1.338 ! brouard 1: /* $Id: imach.c,v 1.337 2022/09/02 14:26:02 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.338 ! brouard 4: Revision 1.337 2022/09/02 14:26:02 brouard
! 5: Summary: version 0.99r35
! 6:
! 7: * src/imach.c: Version 0.99r35 because it outputs same results with
! 8: 1+age+V1+V1*age for females and 1+age for females only
! 9: (education=1 noweight)
! 10:
1.337 brouard 11: Revision 1.336 2022/08/31 09:52:36 brouard
12: *** empty log message ***
13:
1.336 brouard 14: Revision 1.335 2022/08/31 08:23:16 brouard
15: Summary: improvements...
16:
1.335 brouard 17: Revision 1.334 2022/08/25 09:08:41 brouard
18: Summary: In progress for quantitative
19:
1.334 brouard 20: Revision 1.333 2022/08/21 09:10:30 brouard
21: * src/imach.c (Module): Version 0.99r33 A lot of changes in
22: reassigning covariates: my first idea was that people will always
23: use the first covariate V1 into the model but in fact they are
24: producing data with many covariates and can use an equation model
25: with some of the covariate; it means that in a model V2+V3 instead
26: of codtabm(k,Tvaraff[j]) which calculates for combination k, for
27: three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
28: the equation model is restricted to two variables only (V2, V3)
29: and the combination for V2 should be codtabm(k,1) instead of
30: (codtabm(k,2), and the code should be
31: codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
32: made. All of these should be simplified once a day like we did in
33: hpxij() for example by using precov[nres] which is computed in
34: decoderesult for each nres of each resultline. Loop should be done
35: on the equation model globally by distinguishing only product with
36: age (which are changing with age) and no more on type of
37: covariates, single dummies, single covariates.
38:
1.333 brouard 39: Revision 1.332 2022/08/21 09:06:25 brouard
40: Summary: Version 0.99r33
41:
42: * src/imach.c (Module): Version 0.99r33 A lot of changes in
43: reassigning covariates: my first idea was that people will always
44: use the first covariate V1 into the model but in fact they are
45: producing data with many covariates and can use an equation model
46: with some of the covariate; it means that in a model V2+V3 instead
47: of codtabm(k,Tvaraff[j]) which calculates for combination k, for
48: three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
49: the equation model is restricted to two variables only (V2, V3)
50: and the combination for V2 should be codtabm(k,1) instead of
51: (codtabm(k,2), and the code should be
52: codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
53: made. All of these should be simplified once a day like we did in
54: hpxij() for example by using precov[nres] which is computed in
55: decoderesult for each nres of each resultline. Loop should be done
56: on the equation model globally by distinguishing only product with
57: age (which are changing with age) and no more on type of
58: covariates, single dummies, single covariates.
59:
1.332 brouard 60: Revision 1.331 2022/08/07 05:40:09 brouard
61: *** empty log message ***
62:
1.331 brouard 63: Revision 1.330 2022/08/06 07:18:25 brouard
64: Summary: last 0.99r31
65:
66: * imach.c (Module): Version of imach using partly decoderesult to rebuild xpxij function
67:
1.330 brouard 68: Revision 1.329 2022/08/03 17:29:54 brouard
69: * imach.c (Module): Many errors in graphs fixed with Vn*age covariates.
70:
1.329 brouard 71: Revision 1.328 2022/07/27 17:40:48 brouard
72: Summary: valgrind bug fixed by initializing to zero DummyV as well as Tage
73:
1.328 brouard 74: Revision 1.327 2022/07/27 14:47:35 brouard
75: Summary: Still a problem for one-step probabilities in case of quantitative variables
76:
1.327 brouard 77: Revision 1.326 2022/07/26 17:33:55 brouard
78: Summary: some test with nres=1
79:
1.326 brouard 80: Revision 1.325 2022/07/25 14:27:23 brouard
81: Summary: r30
82:
83: * imach.c (Module): Error cptcovn instead of nsd in bmij (was
84: coredumped, revealed by Feiuno, thank you.
85:
1.325 brouard 86: Revision 1.324 2022/07/23 17:44:26 brouard
87: *** empty log message ***
88:
1.324 brouard 89: Revision 1.323 2022/07/22 12:30:08 brouard
90: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
91:
1.323 brouard 92: Revision 1.322 2022/07/22 12:27:48 brouard
93: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
94:
1.322 brouard 95: Revision 1.321 2022/07/22 12:04:24 brouard
96: Summary: r28
97:
98: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
99:
1.321 brouard 100: Revision 1.320 2022/06/02 05:10:11 brouard
101: *** empty log message ***
102:
1.320 brouard 103: Revision 1.319 2022/06/02 04:45:11 brouard
104: * imach.c (Module): Adding the Wald tests from the log to the main
105: htm for better display of the maximum likelihood estimators.
106:
1.319 brouard 107: Revision 1.318 2022/05/24 08:10:59 brouard
108: * imach.c (Module): Some attempts to find a bug of wrong estimates
109: of confidencce intervals with product in the equation modelC
110:
1.318 brouard 111: Revision 1.317 2022/05/15 15:06:23 brouard
112: * imach.c (Module): Some minor improvements
113:
1.317 brouard 114: Revision 1.316 2022/05/11 15:11:31 brouard
115: Summary: r27
116:
1.316 brouard 117: Revision 1.315 2022/05/11 15:06:32 brouard
118: *** empty log message ***
119:
1.315 brouard 120: Revision 1.314 2022/04/13 17:43:09 brouard
121: * imach.c (Module): Adding link to text data files
122:
1.314 brouard 123: Revision 1.313 2022/04/11 15:57:42 brouard
124: * imach.c (Module): Error in rewriting the 'r' file with yearsfproj or yearsbproj fixed
125:
1.313 brouard 126: Revision 1.312 2022/04/05 21:24:39 brouard
127: *** empty log message ***
128:
1.312 brouard 129: Revision 1.311 2022/04/05 21:03:51 brouard
130: Summary: Fixed quantitative covariates
131:
132: Fixed covariates (dummy or quantitative)
133: with missing values have never been allowed but are ERRORS and
134: program quits. Standard deviations of fixed covariates were
135: wrongly computed. Mean and standard deviations of time varying
136: covariates are still not computed.
137:
1.311 brouard 138: Revision 1.310 2022/03/17 08:45:53 brouard
139: Summary: 99r25
140:
141: Improving detection of errors: result lines should be compatible with
142: the model.
143:
1.310 brouard 144: Revision 1.309 2021/05/20 12:39:14 brouard
145: Summary: Version 0.99r24
146:
1.309 brouard 147: Revision 1.308 2021/03/31 13:11:57 brouard
148: Summary: Version 0.99r23
149:
150:
151: * imach.c (Module): Still bugs in the result loop. Thank to Holly Benett
152:
1.308 brouard 153: Revision 1.307 2021/03/08 18:11:32 brouard
154: Summary: 0.99r22 fixed bug on result:
155:
1.307 brouard 156: Revision 1.306 2021/02/20 15:44:02 brouard
157: Summary: Version 0.99r21
158:
159: * imach.c (Module): Fix bug on quitting after result lines!
160: (Module): Version 0.99r21
161:
1.306 brouard 162: Revision 1.305 2021/02/20 15:28:30 brouard
163: * imach.c (Module): Fix bug on quitting after result lines!
164:
1.305 brouard 165: Revision 1.304 2021/02/12 11:34:20 brouard
166: * imach.c (Module): The use of a Windows BOM (huge) file is now an error
167:
1.304 brouard 168: Revision 1.303 2021/02/11 19:50:15 brouard
169: * (Module): imach.c Someone entered 'results:' instead of 'result:'. Now it is an error which is printed.
170:
1.303 brouard 171: Revision 1.302 2020/02/22 21:00:05 brouard
172: * (Module): imach.c Update mle=-3 (for computing Life expectancy
173: and life table from the data without any state)
174:
1.302 brouard 175: Revision 1.301 2019/06/04 13:51:20 brouard
176: Summary: Error in 'r'parameter file backcast yearsbproj instead of yearsfproj
177:
1.301 brouard 178: Revision 1.300 2019/05/22 19:09:45 brouard
179: Summary: version 0.99r19 of May 2019
180:
1.300 brouard 181: Revision 1.299 2019/05/22 18:37:08 brouard
182: Summary: Cleaned 0.99r19
183:
1.299 brouard 184: Revision 1.298 2019/05/22 18:19:56 brouard
185: *** empty log message ***
186:
1.298 brouard 187: Revision 1.297 2019/05/22 17:56:10 brouard
188: Summary: Fix bug by moving date2dmy and nhstepm which gaefin=-1
189:
1.297 brouard 190: Revision 1.296 2019/05/20 13:03:18 brouard
191: Summary: Projection syntax simplified
192:
193:
194: We can now start projections, forward or backward, from the mean date
195: of inteviews up to or down to a number of years of projection:
196: prevforecast=1 yearsfproj=15.3 mobil_average=0
197: or
198: prevforecast=1 starting-proj-date=1/1/2007 final-proj-date=12/31/2017 mobil_average=0
199: or
200: prevbackcast=1 yearsbproj=12.3 mobil_average=1
201: or
202: prevbackcast=1 starting-back-date=1/10/1999 final-back-date=1/1/1985 mobil_average=1
203:
1.296 brouard 204: Revision 1.295 2019/05/18 09:52:50 brouard
205: Summary: doxygen tex bug
206:
1.295 brouard 207: Revision 1.294 2019/05/16 14:54:33 brouard
208: Summary: There was some wrong lines added
209:
1.294 brouard 210: Revision 1.293 2019/05/09 15:17:34 brouard
211: *** empty log message ***
212:
1.293 brouard 213: Revision 1.292 2019/05/09 14:17:20 brouard
214: Summary: Some updates
215:
1.292 brouard 216: Revision 1.291 2019/05/09 13:44:18 brouard
217: Summary: Before ncovmax
218:
1.291 brouard 219: Revision 1.290 2019/05/09 13:39:37 brouard
220: Summary: 0.99r18 unlimited number of individuals
221:
222: 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.
223:
1.290 brouard 224: Revision 1.289 2018/12/13 09:16:26 brouard
225: Summary: Bug for young ages (<-30) will be in r17
226:
1.289 brouard 227: Revision 1.288 2018/05/02 20:58:27 brouard
228: Summary: Some bugs fixed
229:
1.288 brouard 230: Revision 1.287 2018/05/01 17:57:25 brouard
231: Summary: Bug fixed by providing frequencies only for non missing covariates
232:
1.287 brouard 233: Revision 1.286 2018/04/27 14:27:04 brouard
234: Summary: some minor bugs
235:
1.286 brouard 236: Revision 1.285 2018/04/21 21:02:16 brouard
237: Summary: Some bugs fixed, valgrind tested
238:
1.285 brouard 239: Revision 1.284 2018/04/20 05:22:13 brouard
240: Summary: Computing mean and stdeviation of fixed quantitative variables
241:
1.284 brouard 242: Revision 1.283 2018/04/19 14:49:16 brouard
243: Summary: Some minor bugs fixed
244:
1.283 brouard 245: Revision 1.282 2018/02/27 22:50:02 brouard
246: *** empty log message ***
247:
1.282 brouard 248: Revision 1.281 2018/02/27 19:25:23 brouard
249: Summary: Adding second argument for quitting
250:
1.281 brouard 251: Revision 1.280 2018/02/21 07:58:13 brouard
252: Summary: 0.99r15
253:
254: New Makefile with recent VirtualBox 5.26. Bug in sqrt negatve in imach.c
255:
1.280 brouard 256: Revision 1.279 2017/07/20 13:35:01 brouard
257: Summary: temporary working
258:
1.279 brouard 259: Revision 1.278 2017/07/19 14:09:02 brouard
260: Summary: Bug for mobil_average=0 and prevforecast fixed(?)
261:
1.278 brouard 262: Revision 1.277 2017/07/17 08:53:49 brouard
263: Summary: BOM files can be read now
264:
1.277 brouard 265: Revision 1.276 2017/06/30 15:48:31 brouard
266: Summary: Graphs improvements
267:
1.276 brouard 268: Revision 1.275 2017/06/30 13:39:33 brouard
269: Summary: Saito's color
270:
1.275 brouard 271: Revision 1.274 2017/06/29 09:47:08 brouard
272: Summary: Version 0.99r14
273:
1.274 brouard 274: Revision 1.273 2017/06/27 11:06:02 brouard
275: Summary: More documentation on projections
276:
1.273 brouard 277: Revision 1.272 2017/06/27 10:22:40 brouard
278: Summary: Color of backprojection changed from 6 to 5(yellow)
279:
1.272 brouard 280: Revision 1.271 2017/06/27 10:17:50 brouard
281: Summary: Some bug with rint
282:
1.271 brouard 283: Revision 1.270 2017/05/24 05:45:29 brouard
284: *** empty log message ***
285:
1.270 brouard 286: Revision 1.269 2017/05/23 08:39:25 brouard
287: Summary: Code into subroutine, cleanings
288:
1.269 brouard 289: Revision 1.268 2017/05/18 20:09:32 brouard
290: Summary: backprojection and confidence intervals of backprevalence
291:
1.268 brouard 292: Revision 1.267 2017/05/13 10:25:05 brouard
293: Summary: temporary save for backprojection
294:
1.267 brouard 295: Revision 1.266 2017/05/13 07:26:12 brouard
296: Summary: Version 0.99r13 (improvements and bugs fixed)
297:
1.266 brouard 298: Revision 1.265 2017/04/26 16:22:11 brouard
299: Summary: imach 0.99r13 Some bugs fixed
300:
1.265 brouard 301: Revision 1.264 2017/04/26 06:01:29 brouard
302: Summary: Labels in graphs
303:
1.264 brouard 304: Revision 1.263 2017/04/24 15:23:15 brouard
305: Summary: to save
306:
1.263 brouard 307: Revision 1.262 2017/04/18 16:48:12 brouard
308: *** empty log message ***
309:
1.262 brouard 310: Revision 1.261 2017/04/05 10:14:09 brouard
311: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
312:
1.261 brouard 313: Revision 1.260 2017/04/04 17:46:59 brouard
314: Summary: Gnuplot indexations fixed (humm)
315:
1.260 brouard 316: Revision 1.259 2017/04/04 13:01:16 brouard
317: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
318:
1.259 brouard 319: Revision 1.258 2017/04/03 10:17:47 brouard
320: Summary: Version 0.99r12
321:
322: Some cleanings, conformed with updated documentation.
323:
1.258 brouard 324: Revision 1.257 2017/03/29 16:53:30 brouard
325: Summary: Temp
326:
1.257 brouard 327: Revision 1.256 2017/03/27 05:50:23 brouard
328: Summary: Temporary
329:
1.256 brouard 330: Revision 1.255 2017/03/08 16:02:28 brouard
331: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
332:
1.255 brouard 333: Revision 1.254 2017/03/08 07:13:00 brouard
334: Summary: Fixing data parameter line
335:
1.254 brouard 336: Revision 1.253 2016/12/15 11:59:41 brouard
337: Summary: 0.99 in progress
338:
1.253 brouard 339: Revision 1.252 2016/09/15 21:15:37 brouard
340: *** empty log message ***
341:
1.252 brouard 342: Revision 1.251 2016/09/15 15:01:13 brouard
343: Summary: not working
344:
1.251 brouard 345: Revision 1.250 2016/09/08 16:07:27 brouard
346: Summary: continue
347:
1.250 brouard 348: Revision 1.249 2016/09/07 17:14:18 brouard
349: Summary: Starting values from frequencies
350:
1.249 brouard 351: Revision 1.248 2016/09/07 14:10:18 brouard
352: *** empty log message ***
353:
1.248 brouard 354: Revision 1.247 2016/09/02 11:11:21 brouard
355: *** empty log message ***
356:
1.247 brouard 357: Revision 1.246 2016/09/02 08:49:22 brouard
358: *** empty log message ***
359:
1.246 brouard 360: Revision 1.245 2016/09/02 07:25:01 brouard
361: *** empty log message ***
362:
1.245 brouard 363: Revision 1.244 2016/09/02 07:17:34 brouard
364: *** empty log message ***
365:
1.244 brouard 366: Revision 1.243 2016/09/02 06:45:35 brouard
367: *** empty log message ***
368:
1.243 brouard 369: Revision 1.242 2016/08/30 15:01:20 brouard
370: Summary: Fixing a lots
371:
1.242 brouard 372: Revision 1.241 2016/08/29 17:17:25 brouard
373: Summary: gnuplot problem in Back projection to fix
374:
1.241 brouard 375: Revision 1.240 2016/08/29 07:53:18 brouard
376: Summary: Better
377:
1.240 brouard 378: Revision 1.239 2016/08/26 15:51:03 brouard
379: Summary: Improvement in Powell output in order to copy and paste
380:
381: Author:
382:
1.239 brouard 383: Revision 1.238 2016/08/26 14:23:35 brouard
384: Summary: Starting tests of 0.99
385:
1.238 brouard 386: Revision 1.237 2016/08/26 09:20:19 brouard
387: Summary: to valgrind
388:
1.237 brouard 389: Revision 1.236 2016/08/25 10:50:18 brouard
390: *** empty log message ***
391:
1.236 brouard 392: Revision 1.235 2016/08/25 06:59:23 brouard
393: *** empty log message ***
394:
1.235 brouard 395: Revision 1.234 2016/08/23 16:51:20 brouard
396: *** empty log message ***
397:
1.234 brouard 398: Revision 1.233 2016/08/23 07:40:50 brouard
399: Summary: not working
400:
1.233 brouard 401: Revision 1.232 2016/08/22 14:20:21 brouard
402: Summary: not working
403:
1.232 brouard 404: Revision 1.231 2016/08/22 07:17:15 brouard
405: Summary: not working
406:
1.231 brouard 407: Revision 1.230 2016/08/22 06:55:53 brouard
408: Summary: Not working
409:
1.230 brouard 410: Revision 1.229 2016/07/23 09:45:53 brouard
411: Summary: Completing for func too
412:
1.229 brouard 413: Revision 1.228 2016/07/22 17:45:30 brouard
414: Summary: Fixing some arrays, still debugging
415:
1.227 brouard 416: Revision 1.226 2016/07/12 18:42:34 brouard
417: Summary: temp
418:
1.226 brouard 419: Revision 1.225 2016/07/12 08:40:03 brouard
420: Summary: saving but not running
421:
1.225 brouard 422: Revision 1.224 2016/07/01 13:16:01 brouard
423: Summary: Fixes
424:
1.224 brouard 425: Revision 1.223 2016/02/19 09:23:35 brouard
426: Summary: temporary
427:
1.223 brouard 428: Revision 1.222 2016/02/17 08:14:50 brouard
429: Summary: Probably last 0.98 stable version 0.98r6
430:
1.222 brouard 431: Revision 1.221 2016/02/15 23:35:36 brouard
432: Summary: minor bug
433:
1.220 brouard 434: Revision 1.219 2016/02/15 00:48:12 brouard
435: *** empty log message ***
436:
1.219 brouard 437: Revision 1.218 2016/02/12 11:29:23 brouard
438: Summary: 0.99 Back projections
439:
1.218 brouard 440: Revision 1.217 2015/12/23 17:18:31 brouard
441: Summary: Experimental backcast
442:
1.217 brouard 443: Revision 1.216 2015/12/18 17:32:11 brouard
444: Summary: 0.98r4 Warning and status=-2
445:
446: Version 0.98r4 is now:
447: - displaying an error when status is -1, date of interview unknown and date of death known;
448: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
449: Older changes concerning s=-2, dating from 2005 have been supersed.
450:
1.216 brouard 451: Revision 1.215 2015/12/16 08:52:24 brouard
452: Summary: 0.98r4 working
453:
1.215 brouard 454: Revision 1.214 2015/12/16 06:57:54 brouard
455: Summary: temporary not working
456:
1.214 brouard 457: Revision 1.213 2015/12/11 18:22:17 brouard
458: Summary: 0.98r4
459:
1.213 brouard 460: Revision 1.212 2015/11/21 12:47:24 brouard
461: Summary: minor typo
462:
1.212 brouard 463: Revision 1.211 2015/11/21 12:41:11 brouard
464: Summary: 0.98r3 with some graph of projected cross-sectional
465:
466: Author: Nicolas Brouard
467:
1.211 brouard 468: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 469: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 470: Summary: Adding ftolpl parameter
471: Author: N Brouard
472:
473: We had difficulties to get smoothed confidence intervals. It was due
474: to the period prevalence which wasn't computed accurately. The inner
475: parameter ftolpl is now an outer parameter of the .imach parameter
476: file after estepm. If ftolpl is small 1.e-4 and estepm too,
477: computation are long.
478:
1.209 brouard 479: Revision 1.208 2015/11/17 14:31:57 brouard
480: Summary: temporary
481:
1.208 brouard 482: Revision 1.207 2015/10/27 17:36:57 brouard
483: *** empty log message ***
484:
1.207 brouard 485: Revision 1.206 2015/10/24 07:14:11 brouard
486: *** empty log message ***
487:
1.206 brouard 488: Revision 1.205 2015/10/23 15:50:53 brouard
489: Summary: 0.98r3 some clarification for graphs on likelihood contributions
490:
1.205 brouard 491: Revision 1.204 2015/10/01 16:20:26 brouard
492: Summary: Some new graphs of contribution to likelihood
493:
1.204 brouard 494: Revision 1.203 2015/09/30 17:45:14 brouard
495: Summary: looking at better estimation of the hessian
496:
497: Also a better criteria for convergence to the period prevalence And
498: therefore adding the number of years needed to converge. (The
499: prevalence in any alive state shold sum to one
500:
1.203 brouard 501: Revision 1.202 2015/09/22 19:45:16 brouard
502: Summary: Adding some overall graph on contribution to likelihood. Might change
503:
1.202 brouard 504: Revision 1.201 2015/09/15 17:34:58 brouard
505: Summary: 0.98r0
506:
507: - Some new graphs like suvival functions
508: - Some bugs fixed like model=1+age+V2.
509:
1.201 brouard 510: Revision 1.200 2015/09/09 16:53:55 brouard
511: Summary: Big bug thanks to Flavia
512:
513: Even model=1+age+V2. did not work anymore
514:
1.200 brouard 515: Revision 1.199 2015/09/07 14:09:23 brouard
516: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
517:
1.199 brouard 518: Revision 1.198 2015/09/03 07:14:39 brouard
519: Summary: 0.98q5 Flavia
520:
1.198 brouard 521: Revision 1.197 2015/09/01 18:24:39 brouard
522: *** empty log message ***
523:
1.197 brouard 524: Revision 1.196 2015/08/18 23:17:52 brouard
525: Summary: 0.98q5
526:
1.196 brouard 527: Revision 1.195 2015/08/18 16:28:39 brouard
528: Summary: Adding a hack for testing purpose
529:
530: After reading the title, ftol and model lines, if the comment line has
531: a q, starting with #q, the answer at the end of the run is quit. It
532: permits to run test files in batch with ctest. The former workaround was
533: $ echo q | imach foo.imach
534:
1.195 brouard 535: Revision 1.194 2015/08/18 13:32:00 brouard
536: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
537:
1.194 brouard 538: Revision 1.193 2015/08/04 07:17:42 brouard
539: Summary: 0.98q4
540:
1.193 brouard 541: Revision 1.192 2015/07/16 16:49:02 brouard
542: Summary: Fixing some outputs
543:
1.192 brouard 544: Revision 1.191 2015/07/14 10:00:33 brouard
545: Summary: Some fixes
546:
1.191 brouard 547: Revision 1.190 2015/05/05 08:51:13 brouard
548: Summary: Adding digits in output parameters (7 digits instead of 6)
549:
550: Fix 1+age+.
551:
1.190 brouard 552: Revision 1.189 2015/04/30 14:45:16 brouard
553: Summary: 0.98q2
554:
1.189 brouard 555: Revision 1.188 2015/04/30 08:27:53 brouard
556: *** empty log message ***
557:
1.188 brouard 558: Revision 1.187 2015/04/29 09:11:15 brouard
559: *** empty log message ***
560:
1.187 brouard 561: Revision 1.186 2015/04/23 12:01:52 brouard
562: Summary: V1*age is working now, version 0.98q1
563:
564: Some codes had been disabled in order to simplify and Vn*age was
565: working in the optimization phase, ie, giving correct MLE parameters,
566: but, as usual, outputs were not correct and program core dumped.
567:
1.186 brouard 568: Revision 1.185 2015/03/11 13:26:42 brouard
569: Summary: Inclusion of compile and links command line for Intel Compiler
570:
1.185 brouard 571: Revision 1.184 2015/03/11 11:52:39 brouard
572: Summary: Back from Windows 8. Intel Compiler
573:
1.184 brouard 574: Revision 1.183 2015/03/10 20:34:32 brouard
575: Summary: 0.98q0, trying with directest, mnbrak fixed
576:
577: We use directest instead of original Powell test; probably no
578: incidence on the results, but better justifications;
579: We fixed Numerical Recipes mnbrak routine which was wrong and gave
580: wrong results.
581:
1.183 brouard 582: Revision 1.182 2015/02/12 08:19:57 brouard
583: Summary: Trying to keep directest which seems simpler and more general
584: Author: Nicolas Brouard
585:
1.182 brouard 586: Revision 1.181 2015/02/11 23:22:24 brouard
587: Summary: Comments on Powell added
588:
589: Author:
590:
1.181 brouard 591: Revision 1.180 2015/02/11 17:33:45 brouard
592: Summary: Finishing move from main to function (hpijx and prevalence_limit)
593:
1.180 brouard 594: Revision 1.179 2015/01/04 09:57:06 brouard
595: Summary: back to OS/X
596:
1.179 brouard 597: Revision 1.178 2015/01/04 09:35:48 brouard
598: *** empty log message ***
599:
1.178 brouard 600: Revision 1.177 2015/01/03 18:40:56 brouard
601: Summary: Still testing ilc32 on OSX
602:
1.177 brouard 603: Revision 1.176 2015/01/03 16:45:04 brouard
604: *** empty log message ***
605:
1.176 brouard 606: Revision 1.175 2015/01/03 16:33:42 brouard
607: *** empty log message ***
608:
1.175 brouard 609: Revision 1.174 2015/01/03 16:15:49 brouard
610: Summary: Still in cross-compilation
611:
1.174 brouard 612: Revision 1.173 2015/01/03 12:06:26 brouard
613: Summary: trying to detect cross-compilation
614:
1.173 brouard 615: Revision 1.172 2014/12/27 12:07:47 brouard
616: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
617:
1.172 brouard 618: Revision 1.171 2014/12/23 13:26:59 brouard
619: Summary: Back from Visual C
620:
621: Still problem with utsname.h on Windows
622:
1.171 brouard 623: Revision 1.170 2014/12/23 11:17:12 brouard
624: Summary: Cleaning some \%% back to %%
625:
626: The escape was mandatory for a specific compiler (which one?), but too many warnings.
627:
1.170 brouard 628: Revision 1.169 2014/12/22 23:08:31 brouard
629: Summary: 0.98p
630:
631: Outputs some informations on compiler used, OS etc. Testing on different platforms.
632:
1.169 brouard 633: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 634: Summary: update
1.169 brouard 635:
1.168 brouard 636: Revision 1.167 2014/12/22 13:50:56 brouard
637: Summary: Testing uname and compiler version and if compiled 32 or 64
638:
639: Testing on Linux 64
640:
1.167 brouard 641: Revision 1.166 2014/12/22 11:40:47 brouard
642: *** empty log message ***
643:
1.166 brouard 644: Revision 1.165 2014/12/16 11:20:36 brouard
645: Summary: After compiling on Visual C
646:
647: * imach.c (Module): Merging 1.61 to 1.162
648:
1.165 brouard 649: Revision 1.164 2014/12/16 10:52:11 brouard
650: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
651:
652: * imach.c (Module): Merging 1.61 to 1.162
653:
1.164 brouard 654: Revision 1.163 2014/12/16 10:30:11 brouard
655: * imach.c (Module): Merging 1.61 to 1.162
656:
1.163 brouard 657: Revision 1.162 2014/09/25 11:43:39 brouard
658: Summary: temporary backup 0.99!
659:
1.162 brouard 660: Revision 1.1 2014/09/16 11:06:58 brouard
661: Summary: With some code (wrong) for nlopt
662:
663: Author:
664:
665: Revision 1.161 2014/09/15 20:41:41 brouard
666: Summary: Problem with macro SQR on Intel compiler
667:
1.161 brouard 668: Revision 1.160 2014/09/02 09:24:05 brouard
669: *** empty log message ***
670:
1.160 brouard 671: Revision 1.159 2014/09/01 10:34:10 brouard
672: Summary: WIN32
673: Author: Brouard
674:
1.159 brouard 675: Revision 1.158 2014/08/27 17:11:51 brouard
676: *** empty log message ***
677:
1.158 brouard 678: Revision 1.157 2014/08/27 16:26:55 brouard
679: Summary: Preparing windows Visual studio version
680: Author: Brouard
681:
682: In order to compile on Visual studio, time.h is now correct and time_t
683: and tm struct should be used. difftime should be used but sometimes I
684: just make the differences in raw time format (time(&now).
685: Trying to suppress #ifdef LINUX
686: Add xdg-open for __linux in order to open default browser.
687:
1.157 brouard 688: Revision 1.156 2014/08/25 20:10:10 brouard
689: *** empty log message ***
690:
1.156 brouard 691: Revision 1.155 2014/08/25 18:32:34 brouard
692: Summary: New compile, minor changes
693: Author: Brouard
694:
1.155 brouard 695: Revision 1.154 2014/06/20 17:32:08 brouard
696: Summary: Outputs now all graphs of convergence to period prevalence
697:
1.154 brouard 698: Revision 1.153 2014/06/20 16:45:46 brouard
699: Summary: If 3 live state, convergence to period prevalence on same graph
700: Author: Brouard
701:
1.153 brouard 702: Revision 1.152 2014/06/18 17:54:09 brouard
703: Summary: open browser, use gnuplot on same dir than imach if not found in the path
704:
1.152 brouard 705: Revision 1.151 2014/06/18 16:43:30 brouard
706: *** empty log message ***
707:
1.151 brouard 708: Revision 1.150 2014/06/18 16:42:35 brouard
709: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
710: Author: brouard
711:
1.150 brouard 712: Revision 1.149 2014/06/18 15:51:14 brouard
713: Summary: Some fixes in parameter files errors
714: Author: Nicolas Brouard
715:
1.149 brouard 716: Revision 1.148 2014/06/17 17:38:48 brouard
717: Summary: Nothing new
718: Author: Brouard
719:
720: Just a new packaging for OS/X version 0.98nS
721:
1.148 brouard 722: Revision 1.147 2014/06/16 10:33:11 brouard
723: *** empty log message ***
724:
1.147 brouard 725: Revision 1.146 2014/06/16 10:20:28 brouard
726: Summary: Merge
727: Author: Brouard
728:
729: Merge, before building revised version.
730:
1.146 brouard 731: Revision 1.145 2014/06/10 21:23:15 brouard
732: Summary: Debugging with valgrind
733: Author: Nicolas Brouard
734:
735: Lot of changes in order to output the results with some covariates
736: After the Edimburgh REVES conference 2014, it seems mandatory to
737: improve the code.
738: No more memory valgrind error but a lot has to be done in order to
739: continue the work of splitting the code into subroutines.
740: Also, decodemodel has been improved. Tricode is still not
741: optimal. nbcode should be improved. Documentation has been added in
742: the source code.
743:
1.144 brouard 744: Revision 1.143 2014/01/26 09:45:38 brouard
745: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
746:
747: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
748: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
749:
1.143 brouard 750: Revision 1.142 2014/01/26 03:57:36 brouard
751: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
752:
753: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
754:
1.142 brouard 755: Revision 1.141 2014/01/26 02:42:01 brouard
756: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
757:
1.141 brouard 758: Revision 1.140 2011/09/02 10:37:54 brouard
759: Summary: times.h is ok with mingw32 now.
760:
1.140 brouard 761: Revision 1.139 2010/06/14 07:50:17 brouard
762: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
763: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
764:
1.139 brouard 765: Revision 1.138 2010/04/30 18:19:40 brouard
766: *** empty log message ***
767:
1.138 brouard 768: Revision 1.137 2010/04/29 18:11:38 brouard
769: (Module): Checking covariates for more complex models
770: than V1+V2. A lot of change to be done. Unstable.
771:
1.137 brouard 772: Revision 1.136 2010/04/26 20:30:53 brouard
773: (Module): merging some libgsl code. Fixing computation
774: of likelione (using inter/intrapolation if mle = 0) in order to
775: get same likelihood as if mle=1.
776: Some cleaning of code and comments added.
777:
1.136 brouard 778: Revision 1.135 2009/10/29 15:33:14 brouard
779: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
780:
1.135 brouard 781: Revision 1.134 2009/10/29 13:18:53 brouard
782: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
783:
1.134 brouard 784: Revision 1.133 2009/07/06 10:21:25 brouard
785: just nforces
786:
1.133 brouard 787: Revision 1.132 2009/07/06 08:22:05 brouard
788: Many tings
789:
1.132 brouard 790: Revision 1.131 2009/06/20 16:22:47 brouard
791: Some dimensions resccaled
792:
1.131 brouard 793: Revision 1.130 2009/05/26 06:44:34 brouard
794: (Module): Max Covariate is now set to 20 instead of 8. A
795: lot of cleaning with variables initialized to 0. Trying to make
796: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
797:
1.130 brouard 798: Revision 1.129 2007/08/31 13:49:27 lievre
799: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
800:
1.129 lievre 801: Revision 1.128 2006/06/30 13:02:05 brouard
802: (Module): Clarifications on computing e.j
803:
1.128 brouard 804: Revision 1.127 2006/04/28 18:11:50 brouard
805: (Module): Yes the sum of survivors was wrong since
806: imach-114 because nhstepm was no more computed in the age
807: loop. Now we define nhstepma in the age loop.
808: (Module): In order to speed up (in case of numerous covariates) we
809: compute health expectancies (without variances) in a first step
810: and then all the health expectancies with variances or standard
811: deviation (needs data from the Hessian matrices) which slows the
812: computation.
813: In the future we should be able to stop the program is only health
814: expectancies and graph are needed without standard deviations.
815:
1.127 brouard 816: Revision 1.126 2006/04/28 17:23:28 brouard
817: (Module): Yes the sum of survivors was wrong since
818: imach-114 because nhstepm was no more computed in the age
819: loop. Now we define nhstepma in the age loop.
820: Version 0.98h
821:
1.126 brouard 822: Revision 1.125 2006/04/04 15:20:31 lievre
823: Errors in calculation of health expectancies. Age was not initialized.
824: Forecasting file added.
825:
826: Revision 1.124 2006/03/22 17:13:53 lievre
827: Parameters are printed with %lf instead of %f (more numbers after the comma).
828: The log-likelihood is printed in the log file
829:
830: Revision 1.123 2006/03/20 10:52:43 brouard
831: * imach.c (Module): <title> changed, corresponds to .htm file
832: name. <head> headers where missing.
833:
834: * imach.c (Module): Weights can have a decimal point as for
835: English (a comma might work with a correct LC_NUMERIC environment,
836: otherwise the weight is truncated).
837: Modification of warning when the covariates values are not 0 or
838: 1.
839: Version 0.98g
840:
841: Revision 1.122 2006/03/20 09:45:41 brouard
842: (Module): Weights can have a decimal point as for
843: English (a comma might work with a correct LC_NUMERIC environment,
844: otherwise the weight is truncated).
845: Modification of warning when the covariates values are not 0 or
846: 1.
847: Version 0.98g
848:
849: Revision 1.121 2006/03/16 17:45:01 lievre
850: * imach.c (Module): Comments concerning covariates added
851:
852: * imach.c (Module): refinements in the computation of lli if
853: status=-2 in order to have more reliable computation if stepm is
854: not 1 month. Version 0.98f
855:
856: Revision 1.120 2006/03/16 15:10:38 lievre
857: (Module): refinements in the computation of lli if
858: status=-2 in order to have more reliable computation if stepm is
859: not 1 month. Version 0.98f
860:
861: Revision 1.119 2006/03/15 17:42:26 brouard
862: (Module): Bug if status = -2, the loglikelihood was
863: computed as likelihood omitting the logarithm. Version O.98e
864:
865: Revision 1.118 2006/03/14 18:20:07 brouard
866: (Module): varevsij Comments added explaining the second
867: table of variances if popbased=1 .
868: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
869: (Module): Function pstamp added
870: (Module): Version 0.98d
871:
872: Revision 1.117 2006/03/14 17:16:22 brouard
873: (Module): varevsij Comments added explaining the second
874: table of variances if popbased=1 .
875: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
876: (Module): Function pstamp added
877: (Module): Version 0.98d
878:
879: Revision 1.116 2006/03/06 10:29:27 brouard
880: (Module): Variance-covariance wrong links and
881: varian-covariance of ej. is needed (Saito).
882:
883: Revision 1.115 2006/02/27 12:17:45 brouard
884: (Module): One freematrix added in mlikeli! 0.98c
885:
886: Revision 1.114 2006/02/26 12:57:58 brouard
887: (Module): Some improvements in processing parameter
888: filename with strsep.
889:
890: Revision 1.113 2006/02/24 14:20:24 brouard
891: (Module): Memory leaks checks with valgrind and:
892: datafile was not closed, some imatrix were not freed and on matrix
893: allocation too.
894:
895: Revision 1.112 2006/01/30 09:55:26 brouard
896: (Module): Back to gnuplot.exe instead of wgnuplot.exe
897:
898: Revision 1.111 2006/01/25 20:38:18 brouard
899: (Module): Lots of cleaning and bugs added (Gompertz)
900: (Module): Comments can be added in data file. Missing date values
901: can be a simple dot '.'.
902:
903: Revision 1.110 2006/01/25 00:51:50 brouard
904: (Module): Lots of cleaning and bugs added (Gompertz)
905:
906: Revision 1.109 2006/01/24 19:37:15 brouard
907: (Module): Comments (lines starting with a #) are allowed in data.
908:
909: Revision 1.108 2006/01/19 18:05:42 lievre
910: Gnuplot problem appeared...
911: To be fixed
912:
913: Revision 1.107 2006/01/19 16:20:37 brouard
914: Test existence of gnuplot in imach path
915:
916: Revision 1.106 2006/01/19 13:24:36 brouard
917: Some cleaning and links added in html output
918:
919: Revision 1.105 2006/01/05 20:23:19 lievre
920: *** empty log message ***
921:
922: Revision 1.104 2005/09/30 16:11:43 lievre
923: (Module): sump fixed, loop imx fixed, and simplifications.
924: (Module): If the status is missing at the last wave but we know
925: that the person is alive, then we can code his/her status as -2
926: (instead of missing=-1 in earlier versions) and his/her
927: contributions to the likelihood is 1 - Prob of dying from last
928: health status (= 1-p13= p11+p12 in the easiest case of somebody in
929: the healthy state at last known wave). Version is 0.98
930:
931: Revision 1.103 2005/09/30 15:54:49 lievre
932: (Module): sump fixed, loop imx fixed, and simplifications.
933:
934: Revision 1.102 2004/09/15 17:31:30 brouard
935: Add the possibility to read data file including tab characters.
936:
937: Revision 1.101 2004/09/15 10:38:38 brouard
938: Fix on curr_time
939:
940: Revision 1.100 2004/07/12 18:29:06 brouard
941: Add version for Mac OS X. Just define UNIX in Makefile
942:
943: Revision 1.99 2004/06/05 08:57:40 brouard
944: *** empty log message ***
945:
946: Revision 1.98 2004/05/16 15:05:56 brouard
947: New version 0.97 . First attempt to estimate force of mortality
948: directly from the data i.e. without the need of knowing the health
949: state at each age, but using a Gompertz model: log u =a + b*age .
950: This is the basic analysis of mortality and should be done before any
951: other analysis, in order to test if the mortality estimated from the
952: cross-longitudinal survey is different from the mortality estimated
953: from other sources like vital statistic data.
954:
955: The same imach parameter file can be used but the option for mle should be -3.
956:
1.324 brouard 957: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 958: former routines in order to include the new code within the former code.
959:
960: The output is very simple: only an estimate of the intercept and of
961: the slope with 95% confident intervals.
962:
963: Current limitations:
964: A) Even if you enter covariates, i.e. with the
965: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
966: B) There is no computation of Life Expectancy nor Life Table.
967:
968: Revision 1.97 2004/02/20 13:25:42 lievre
969: Version 0.96d. Population forecasting command line is (temporarily)
970: suppressed.
971:
972: Revision 1.96 2003/07/15 15:38:55 brouard
973: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
974: rewritten within the same printf. Workaround: many printfs.
975:
976: Revision 1.95 2003/07/08 07:54:34 brouard
977: * imach.c (Repository):
978: (Repository): Using imachwizard code to output a more meaningful covariance
979: matrix (cov(a12,c31) instead of numbers.
980:
981: Revision 1.94 2003/06/27 13:00:02 brouard
982: Just cleaning
983:
984: Revision 1.93 2003/06/25 16:33:55 brouard
985: (Module): On windows (cygwin) function asctime_r doesn't
986: exist so I changed back to asctime which exists.
987: (Module): Version 0.96b
988:
989: Revision 1.92 2003/06/25 16:30:45 brouard
990: (Module): On windows (cygwin) function asctime_r doesn't
991: exist so I changed back to asctime which exists.
992:
993: Revision 1.91 2003/06/25 15:30:29 brouard
994: * imach.c (Repository): Duplicated warning errors corrected.
995: (Repository): Elapsed time after each iteration is now output. It
996: helps to forecast when convergence will be reached. Elapsed time
997: is stamped in powell. We created a new html file for the graphs
998: concerning matrix of covariance. It has extension -cov.htm.
999:
1000: Revision 1.90 2003/06/24 12:34:15 brouard
1001: (Module): Some bugs corrected for windows. Also, when
1002: mle=-1 a template is output in file "or"mypar.txt with the design
1003: of the covariance matrix to be input.
1004:
1005: Revision 1.89 2003/06/24 12:30:52 brouard
1006: (Module): Some bugs corrected for windows. Also, when
1007: mle=-1 a template is output in file "or"mypar.txt with the design
1008: of the covariance matrix to be input.
1009:
1010: Revision 1.88 2003/06/23 17:54:56 brouard
1011: * 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.
1012:
1013: Revision 1.87 2003/06/18 12:26:01 brouard
1014: Version 0.96
1015:
1016: Revision 1.86 2003/06/17 20:04:08 brouard
1017: (Module): Change position of html and gnuplot routines and added
1018: routine fileappend.
1019:
1020: Revision 1.85 2003/06/17 13:12:43 brouard
1021: * imach.c (Repository): Check when date of death was earlier that
1022: current date of interview. It may happen when the death was just
1023: prior to the death. In this case, dh was negative and likelihood
1024: was wrong (infinity). We still send an "Error" but patch by
1025: assuming that the date of death was just one stepm after the
1026: interview.
1027: (Repository): Because some people have very long ID (first column)
1028: we changed int to long in num[] and we added a new lvector for
1029: memory allocation. But we also truncated to 8 characters (left
1030: truncation)
1031: (Repository): No more line truncation errors.
1032:
1033: Revision 1.84 2003/06/13 21:44:43 brouard
1034: * imach.c (Repository): Replace "freqsummary" at a correct
1035: place. It differs from routine "prevalence" which may be called
1036: many times. Probs is memory consuming and must be used with
1037: parcimony.
1038: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
1039:
1040: Revision 1.83 2003/06/10 13:39:11 lievre
1041: *** empty log message ***
1042:
1043: Revision 1.82 2003/06/05 15:57:20 brouard
1044: Add log in imach.c and fullversion number is now printed.
1045:
1046: */
1047: /*
1048: Interpolated Markov Chain
1049:
1050: Short summary of the programme:
1051:
1.227 brouard 1052: This program computes Healthy Life Expectancies or State-specific
1053: (if states aren't health statuses) Expectancies from
1054: cross-longitudinal data. Cross-longitudinal data consist in:
1055:
1056: -1- a first survey ("cross") where individuals from different ages
1057: are interviewed on their health status or degree of disability (in
1058: the case of a health survey which is our main interest)
1059:
1060: -2- at least a second wave of interviews ("longitudinal") which
1061: measure each change (if any) in individual health status. Health
1062: expectancies are computed from the time spent in each health state
1063: according to a model. More health states you consider, more time is
1064: necessary to reach the Maximum Likelihood of the parameters involved
1065: in the model. The simplest model is the multinomial logistic model
1066: where pij is the probability to be observed in state j at the second
1067: wave conditional to be observed in state i at the first
1068: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
1069: etc , where 'age' is age and 'sex' is a covariate. If you want to
1070: have a more complex model than "constant and age", you should modify
1071: the program where the markup *Covariates have to be included here
1072: again* invites you to do it. More covariates you add, slower the
1.126 brouard 1073: convergence.
1074:
1075: The advantage of this computer programme, compared to a simple
1076: multinomial logistic model, is clear when the delay between waves is not
1077: identical for each individual. Also, if a individual missed an
1078: intermediate interview, the information is lost, but taken into
1079: account using an interpolation or extrapolation.
1080:
1081: hPijx is the probability to be observed in state i at age x+h
1082: conditional to the observed state i at age x. The delay 'h' can be
1083: split into an exact number (nh*stepm) of unobserved intermediate
1084: states. This elementary transition (by month, quarter,
1085: semester or year) is modelled as a multinomial logistic. The hPx
1086: matrix is simply the matrix product of nh*stepm elementary matrices
1087: and the contribution of each individual to the likelihood is simply
1088: hPijx.
1089:
1090: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 1091: of the life expectancies. It also computes the period (stable) prevalence.
1092:
1093: Back prevalence and projections:
1.227 brouard 1094:
1095: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
1096: double agemaxpar, double ftolpl, int *ncvyearp, double
1097: dateprev1,double dateprev2, int firstpass, int lastpass, int
1098: mobilavproj)
1099:
1100: Computes the back prevalence limit for any combination of
1101: covariate values k at any age between ageminpar and agemaxpar and
1102: returns it in **bprlim. In the loops,
1103:
1104: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
1105: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
1106:
1107: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 1108: Computes for any combination of covariates k and any age between bage and fage
1109: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
1110: oldm=oldms;savm=savms;
1.227 brouard 1111:
1.267 brouard 1112: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 1113: Computes the transition matrix starting at age 'age' over
1114: 'nhstepm*hstepm*stepm' months (i.e. until
1115: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 1116: nhstepm*hstepm matrices.
1117:
1118: Returns p3mat[i][j][h] after calling
1119: p3mat[i][j][h]=matprod2(newm,
1120: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
1121: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
1122: oldm);
1.226 brouard 1123:
1124: Important routines
1125:
1126: - func (or funcone), computes logit (pij) distinguishing
1127: o fixed variables (single or product dummies or quantitative);
1128: o varying variables by:
1129: (1) wave (single, product dummies, quantitative),
1130: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
1131: % fixed dummy (treated) or quantitative (not done because time-consuming);
1132: % varying dummy (not done) or quantitative (not done);
1133: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
1134: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
1135: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
1.325 brouard 1136: o There are 2**cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
1.226 brouard 1137: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 1138:
1.226 brouard 1139:
1140:
1.324 brouard 1141: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
1142: Institut national d'études démographiques, Paris.
1.126 brouard 1143: This software have been partly granted by Euro-REVES, a concerted action
1144: from the European Union.
1145: It is copyrighted identically to a GNU software product, ie programme and
1146: software can be distributed freely for non commercial use. Latest version
1147: can be accessed at http://euroreves.ined.fr/imach .
1148:
1149: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
1150: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
1151:
1152: **********************************************************************/
1153: /*
1154: main
1155: read parameterfile
1156: read datafile
1157: concatwav
1158: freqsummary
1159: if (mle >= 1)
1160: mlikeli
1161: print results files
1162: if mle==1
1163: computes hessian
1164: read end of parameter file: agemin, agemax, bage, fage, estepm
1165: begin-prev-date,...
1166: open gnuplot file
1167: open html file
1.145 brouard 1168: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
1169: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
1170: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
1171: freexexit2 possible for memory heap.
1172:
1173: h Pij x | pij_nom ficrestpij
1174: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
1175: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
1176: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
1177:
1178: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
1179: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
1180: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
1181: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
1182: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
1183:
1.126 brouard 1184: forecasting if prevfcast==1 prevforecast call prevalence()
1185: health expectancies
1186: Variance-covariance of DFLE
1187: prevalence()
1188: movingaverage()
1189: varevsij()
1190: if popbased==1 varevsij(,popbased)
1191: total life expectancies
1192: Variance of period (stable) prevalence
1193: end
1194: */
1195:
1.187 brouard 1196: /* #define DEBUG */
1197: /* #define DEBUGBRENT */
1.203 brouard 1198: /* #define DEBUGLINMIN */
1199: /* #define DEBUGHESS */
1200: #define DEBUGHESSIJ
1.224 brouard 1201: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 1202: #define POWELL /* Instead of NLOPT */
1.224 brouard 1203: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 1204: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
1205: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.319 brouard 1206: /* #define FLATSUP *//* Suppresses directions where likelihood is flat */
1.126 brouard 1207:
1208: #include <math.h>
1209: #include <stdio.h>
1210: #include <stdlib.h>
1211: #include <string.h>
1.226 brouard 1212: #include <ctype.h>
1.159 brouard 1213:
1214: #ifdef _WIN32
1215: #include <io.h>
1.172 brouard 1216: #include <windows.h>
1217: #include <tchar.h>
1.159 brouard 1218: #else
1.126 brouard 1219: #include <unistd.h>
1.159 brouard 1220: #endif
1.126 brouard 1221:
1222: #include <limits.h>
1223: #include <sys/types.h>
1.171 brouard 1224:
1225: #if defined(__GNUC__)
1226: #include <sys/utsname.h> /* Doesn't work on Windows */
1227: #endif
1228:
1.126 brouard 1229: #include <sys/stat.h>
1230: #include <errno.h>
1.159 brouard 1231: /* extern int errno; */
1.126 brouard 1232:
1.157 brouard 1233: /* #ifdef LINUX */
1234: /* #include <time.h> */
1235: /* #include "timeval.h" */
1236: /* #else */
1237: /* #include <sys/time.h> */
1238: /* #endif */
1239:
1.126 brouard 1240: #include <time.h>
1241:
1.136 brouard 1242: #ifdef GSL
1243: #include <gsl/gsl_errno.h>
1244: #include <gsl/gsl_multimin.h>
1245: #endif
1246:
1.167 brouard 1247:
1.162 brouard 1248: #ifdef NLOPT
1249: #include <nlopt.h>
1250: typedef struct {
1251: double (* function)(double [] );
1252: } myfunc_data ;
1253: #endif
1254:
1.126 brouard 1255: /* #include <libintl.h> */
1256: /* #define _(String) gettext (String) */
1257:
1.251 brouard 1258: #define MAXLINE 2048 /* Was 256 and 1024. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 1259:
1260: #define GNUPLOTPROGRAM "gnuplot"
1261: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
1.329 brouard 1262: #define FILENAMELENGTH 256
1.126 brouard 1263:
1264: #define GLOCK_ERROR_NOPATH -1 /* empty path */
1265: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
1266:
1.144 brouard 1267: #define MAXPARM 128 /**< Maximum number of parameters for the optimization */
1268: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 1269:
1270: #define NINTERVMAX 8
1.144 brouard 1271: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
1272: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
1.325 brouard 1273: #define NCOVMAX 30 /**< Maximum number of covariates used in the model, including generated covariates V1*V2 or V1*age */
1.197 brouard 1274: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 1275: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
1276: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.290 brouard 1277: /*#define MAXN 20000 */ /* Should by replaced by nobs, real number of observations and unlimited */
1.144 brouard 1278: #define YEARM 12. /**< Number of months per year */
1.218 brouard 1279: /* #define AGESUP 130 */
1.288 brouard 1280: /* #define AGESUP 150 */
1281: #define AGESUP 200
1.268 brouard 1282: #define AGEINF 0
1.218 brouard 1283: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1284: #define AGEBASE 40
1.194 brouard 1285: #define AGEOVERFLOW 1.e20
1.164 brouard 1286: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1287: #ifdef _WIN32
1288: #define DIRSEPARATOR '\\'
1289: #define CHARSEPARATOR "\\"
1290: #define ODIRSEPARATOR '/'
1291: #else
1.126 brouard 1292: #define DIRSEPARATOR '/'
1293: #define CHARSEPARATOR "/"
1294: #define ODIRSEPARATOR '\\'
1295: #endif
1296:
1.338 ! brouard 1297: /* $Id: imach.c,v 1.337 2022/09/02 14:26:02 brouard Exp $ */
1.126 brouard 1298: /* $State: Exp $ */
1.196 brouard 1299: #include "version.h"
1300: char version[]=__IMACH_VERSION__;
1.337 brouard 1301: char copyright[]="September 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";
1.338 ! brouard 1302: char fullversion[]="$Revision: 1.337 $ $Date: 2022/09/02 14:26:02 $";
1.126 brouard 1303: char strstart[80];
1304: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1305: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.187 brouard 1306: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.330 brouard 1307: /* Number of covariates model (1)=V2+V1+ V3*age+V2*V4 */
1308: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
1.335 brouard 1309: int cptcovn=0; /**< cptcovn decodemodel: number of covariates k of the models excluding age*products =6 and age*age but including products */
1.330 brouard 1310: int cptcovt=0; /**< cptcovt: total number of covariates of the model (2) nbocc(+)+1 = 8 excepting constant and age and age*age */
1.335 brouard 1311: int cptcovs=0; /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
1312: int cptcovsnq=0; /**< cptcovsnq number of SIMPLE covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1313: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1314: int cptcovprodnoage=0; /**< Number of covariate products without age */
1.335 brouard 1315: int cptcoveff=0; /* Total number of single dummy covariates (fixed or time varying) to vary for printing results (2**cptcoveff combinations of dummies)(computed in tricode as cptcov) */
1.233 brouard 1316: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1317: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.232 brouard 1318: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (dummy of quantitative) in the model */
1.234 brouard 1319: int nsd=0; /**< Total number of single dummy variables (output) */
1320: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1321: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1322: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1323: int ntveff=0; /**< ntveff number of effective time varying variables */
1324: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1325: int cptcov=0; /* Working variable */
1.334 brouard 1326: int firstobs=1, lastobs=10; /* nobs = lastobs-firstobs+1 declared globally ;*/
1.290 brouard 1327: int nobs=10; /* Number of observations in the data lastobs-firstobs */
1.218 brouard 1328: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.302 brouard 1329: int npar=NPARMAX; /* Number of parameters (nlstate+ndeath-1)*nlstate*ncovmodel; */
1.126 brouard 1330: int nlstate=2; /* Number of live states */
1331: int ndeath=1; /* Number of dead states */
1.130 brouard 1332: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.223 brouard 1333: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable */
1.126 brouard 1334: int popbased=0;
1335:
1336: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1337: int maxwav=0; /* Maxim number of waves */
1338: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1339: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1340: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 1341: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1342: int mle=1, weightopt=0;
1.126 brouard 1343: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1344: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1345: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1346: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1347: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1348: int selected(int kvar); /* Is covariate kvar selected for printing results */
1349:
1.130 brouard 1350: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1351: double **matprod2(); /* test */
1.126 brouard 1352: double **oldm, **newm, **savm; /* Working pointers to matrices */
1353: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1354: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1355:
1.136 brouard 1356: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1357: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1358: FILE *ficlog, *ficrespow;
1.130 brouard 1359: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1360: double fretone; /* Only one call to likelihood */
1.130 brouard 1361: long ipmx=0; /* Number of contributions */
1.126 brouard 1362: double sw; /* Sum of weights */
1363: char filerespow[FILENAMELENGTH];
1364: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1365: FILE *ficresilk;
1366: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1367: FILE *ficresprobmorprev;
1368: FILE *fichtm, *fichtmcov; /* Html File */
1369: FILE *ficreseij;
1370: char filerese[FILENAMELENGTH];
1371: FILE *ficresstdeij;
1372: char fileresstde[FILENAMELENGTH];
1373: FILE *ficrescveij;
1374: char filerescve[FILENAMELENGTH];
1375: FILE *ficresvij;
1376: char fileresv[FILENAMELENGTH];
1.269 brouard 1377:
1.126 brouard 1378: char title[MAXLINE];
1.234 brouard 1379: char model[MAXLINE]; /**< The model line */
1.217 brouard 1380: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1381: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1382: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1383: char command[FILENAMELENGTH];
1384: int outcmd=0;
1385:
1.217 brouard 1386: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1387: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1388: char filelog[FILENAMELENGTH]; /* Log file */
1389: char filerest[FILENAMELENGTH];
1390: char fileregp[FILENAMELENGTH];
1391: char popfile[FILENAMELENGTH];
1392:
1393: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1394:
1.157 brouard 1395: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1396: /* struct timezone tzp; */
1397: /* extern int gettimeofday(); */
1398: struct tm tml, *gmtime(), *localtime();
1399:
1400: extern time_t time();
1401:
1402: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1403: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1404: struct tm tm;
1405:
1.126 brouard 1406: char strcurr[80], strfor[80];
1407:
1408: char *endptr;
1409: long lval;
1410: double dval;
1411:
1412: #define NR_END 1
1413: #define FREE_ARG char*
1414: #define FTOL 1.0e-10
1415:
1416: #define NRANSI
1.240 brouard 1417: #define ITMAX 200
1418: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1419:
1420: #define TOL 2.0e-4
1421:
1422: #define CGOLD 0.3819660
1423: #define ZEPS 1.0e-10
1424: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1425:
1426: #define GOLD 1.618034
1427: #define GLIMIT 100.0
1428: #define TINY 1.0e-20
1429:
1430: static double maxarg1,maxarg2;
1431: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1432: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1433:
1434: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1435: #define rint(a) floor(a+0.5)
1.166 brouard 1436: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1437: #define mytinydouble 1.0e-16
1.166 brouard 1438: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1439: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1440: /* static double dsqrarg; */
1441: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1442: static double sqrarg;
1443: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1444: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1445: int agegomp= AGEGOMP;
1446:
1447: int imx;
1448: int stepm=1;
1449: /* Stepm, step in month: minimum step interpolation*/
1450:
1451: int estepm;
1452: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1453:
1454: int m,nb;
1455: long *num;
1.197 brouard 1456: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1457: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1458: covariate for which somebody answered excluding
1459: undefined. Usually 2: 0 and 1. */
1460: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1461: covariate for which somebody answered including
1462: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1463: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1464: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1465: double ***mobaverage, ***mobaverages; /* New global variable */
1.332 brouard 1466: double **precov; /* New global variable to store for each resultline, values of model covariates given by the resultlines (in order to speed up) */
1.126 brouard 1467: double *ageexmed,*agecens;
1468: double dateintmean=0;
1.296 brouard 1469: double anprojd, mprojd, jprojd; /* For eventual projections */
1470: double anprojf, mprojf, jprojf;
1.126 brouard 1471:
1.296 brouard 1472: double anbackd, mbackd, jbackd; /* For eventual backprojections */
1473: double anbackf, mbackf, jbackf;
1474: double jintmean,mintmean,aintmean;
1.126 brouard 1475: double *weight;
1476: int **s; /* Status */
1.141 brouard 1477: double *agedc;
1.145 brouard 1478: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1479: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1480: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1481: double **coqvar; /* Fixed quantitative covariate nqv */
1482: double ***cotvar; /* Time varying covariate ntv */
1.225 brouard 1483: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1484: double idx;
1485: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.319 brouard 1486: /* Some documentation */
1487: /* Design original data
1488: * V1 V2 V3 V4 V5 V6 V7 V8 Weight ddb ddth d1st s1 V9 V10 V11 V12 s2 V9 V10 V11 V12
1489: * < ncovcol=6 > nqv=2 (V7 V8) dv dv dv qtv dv dv dvv qtv
1490: * ntv=3 nqtv=1
1.330 brouard 1491: * cptcovn number of covariates (not including constant and age or age*age) = number of plus sign + 1 = 10+1=11
1.319 brouard 1492: * For time varying covariate, quanti or dummies
1493: * cotqvar[wav][iv(1 to nqtv)][i]= [1][12][i]=(V12) quanti
1494: * cotvar[wav][ntv+iv][i]= [3+(1 to nqtv)][i]=(V12) quanti
1495: * cotvar[wav][iv(1 to ntv)][i]= [1][1][i]=(V9) dummies at wav 1
1496: * cotvar[wav][iv(1 to ntv)][i]= [1][2][i]=(V10) dummies at wav 1
1.332 brouard 1497: * covar[Vk,i], value of the Vkth fixed covariate dummy or quanti for individual i:
1.319 brouard 1498: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
1499: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 + V9 + V9*age + V10
1500: * k= 1 2 3 4 5 6 7 8 9 10 11
1501: */
1502: /* According to the model, more columns can be added to covar by the product of covariates */
1.318 brouard 1503: /* 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
1504: # States 1=Coresidence, 2 Living alone, 3 Institution
1505: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1506: */
1.319 brouard 1507: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1508: /* k 1 2 3 4 5 6 7 8 9 */
1509: /*Typevar[k]= 0 0 0 2 1 0 2 1 0 *//*0 for simple covariate (dummy, quantitative,*/
1510: /* fixed or varying), 1 for age product, 2 for*/
1511: /* product */
1512: /*Dummy[k]= 1 0 0 1 3 1 1 2 0 *//*Dummy[k] 0=dummy (0 1), 1 quantitative */
1513: /*(single or product without age), 2 dummy*/
1514: /* with age product, 3 quant with age product*/
1515: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 */
1516: /* nsd 1 2 3 */ /* Counting single dummies covar fixed or tv */
1.330 brouard 1517: /*TnsdVar[Tvar] 1 2 3 */
1.337 brouard 1518: /*Tvaraff[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1.319 brouard 1519: /*TvarsD[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1.338 ! brouard 1520: /*TvarsDind[nsd] 2 3 9 */ /* position K of single dummy cova */
1.319 brouard 1521: /* nsq 1 2 */ /* Counting single quantit tv */
1522: /* TvarsQ[k] 5 2 */ /* Number of single quantitative cova */
1523: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1524: /* Tprod[i]=k 1 2 */ /* Position in model of the ith prod without age */
1525: /* cptcovage 1 2 */ /* Counting cov*age in the model equation */
1526: /* Tage[cptcovage]=k 5 8 */ /* Position in the model of ith cov*age */
1527: /* Tvard[1][1]@4={4,3,1,2} V4*V3 V1*V2 */ /* Position in model of the ith prod without age */
1.330 brouard 1528: /* Tvardk[4][1]=4;Tvardk[4][2]=3;Tvardk[7][1]=1;Tvardk[7][2]=2 */ /* Variables of a prod at position in the model equation*/
1.319 brouard 1529: /* TvarF TvarF[1]=Tvar[6]=2, TvarF[2]=Tvar[7]=7, TvarF[3]=Tvar[9]=1 ID of fixed covariates or product V2, V1*V2, V1 */
1.320 brouard 1530: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.234 brouard 1531: /* Type */
1532: /* V 1 2 3 4 5 */
1533: /* F F V V V */
1534: /* D Q D D Q */
1535: /* */
1536: int *TvarsD;
1.330 brouard 1537: int *TnsdVar;
1.234 brouard 1538: int *TvarsDind;
1539: int *TvarsQ;
1540: int *TvarsQind;
1541:
1.318 brouard 1542: #define MAXRESULTLINESPONE 10+1
1.235 brouard 1543: int nresult=0;
1.258 brouard 1544: int parameterline=0; /* # of the parameter (type) line */
1.334 brouard 1545: int TKresult[MAXRESULTLINESPONE]; /* TKresult[nres]=k for each resultline nres give the corresponding combination of dummies */
1546: int resultmodel[MAXRESULTLINESPONE][NCOVMAX];/* resultmodel[k1]=k3: k1th position in the model corresponds to the k3 position in the resultline */
1547: int modelresult[MAXRESULTLINESPONE][NCOVMAX];/* modelresult[k3]=k1: k1th position in the model corresponds to the k3 position in the resultline */
1548: int Tresult[MAXRESULTLINESPONE][NCOVMAX];/* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
1.332 brouard 1549: int Tinvresult[MAXRESULTLINESPONE][NCOVMAX];/* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
1550: double TinvDoQresult[MAXRESULTLINESPONE][NCOVMAX];/* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
1.334 brouard 1551: int Tvresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvresult[nres][result_position]= name of the dummy variable at the result_position in the nres resultline */
1.332 brouard 1552: double Tqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
1.318 brouard 1553: double Tqinvresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , value (output) */
1.332 brouard 1554: int Tvqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
1.318 brouard 1555:
1556: /* 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
1557: # States 1=Coresidence, 2 Living alone, 3 Institution
1558: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1559: */
1.234 brouard 1560: /* 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 1561: 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 */
1562: 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 */
1563: 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 */
1564: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1565: 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 */
1566: 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 1567: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1568: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1569: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1570: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1571: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1572: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1573: 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 */
1574: 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 */
1575:
1.230 brouard 1576: int *Tvarsel; /**< Selected covariates for output */
1577: double *Tvalsel; /**< Selected modality value of covariate for output */
1.226 brouard 1578: int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.227 brouard 1579: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1580: 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 1581: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1582: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1583: int *Tage;
1.227 brouard 1584: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1585: 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 1586: 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*/
1587: 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 1588: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1589: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1590: int **Tvard;
1.330 brouard 1591: int **Tvardk;
1.227 brouard 1592: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1593: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1594: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1595: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1596: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1597: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1598: double *lsurv, *lpop, *tpop;
1599:
1.231 brouard 1600: #define FD 1; /* Fixed dummy covariate */
1601: #define FQ 2; /* Fixed quantitative covariate */
1602: #define FP 3; /* Fixed product covariate */
1603: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1604: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1605: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1606: #define VD 10; /* Varying dummy covariate */
1607: #define VQ 11; /* Varying quantitative covariate */
1608: #define VP 12; /* Varying product covariate */
1609: #define VPDD 13; /* Varying product dummy*dummy covariate */
1610: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1611: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1612: #define APFD 16; /* Age product * fixed dummy covariate */
1613: #define APFQ 17; /* Age product * fixed quantitative covariate */
1614: #define APVD 18; /* Age product * varying dummy covariate */
1615: #define APVQ 19; /* Age product * varying quantitative covariate */
1616:
1617: #define FTYPE 1; /* Fixed covariate */
1618: #define VTYPE 2; /* Varying covariate (loop in wave) */
1619: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1620:
1621: struct kmodel{
1622: int maintype; /* main type */
1623: int subtype; /* subtype */
1624: };
1625: struct kmodel modell[NCOVMAX];
1626:
1.143 brouard 1627: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1628: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1629:
1630: /**************** split *************************/
1631: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1632: {
1633: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1634: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1635: */
1636: char *ss; /* pointer */
1.186 brouard 1637: int l1=0, l2=0; /* length counters */
1.126 brouard 1638:
1639: l1 = strlen(path ); /* length of path */
1640: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1641: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1642: if ( ss == NULL ) { /* no directory, so determine current directory */
1643: strcpy( name, path ); /* we got the fullname name because no directory */
1644: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1645: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1646: /* get current working directory */
1647: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1648: #ifdef WIN32
1649: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1650: #else
1651: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1652: #endif
1.126 brouard 1653: return( GLOCK_ERROR_GETCWD );
1654: }
1655: /* got dirc from getcwd*/
1656: printf(" DIRC = %s \n",dirc);
1.205 brouard 1657: } else { /* strip directory from path */
1.126 brouard 1658: ss++; /* after this, the filename */
1659: l2 = strlen( ss ); /* length of filename */
1660: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1661: strcpy( name, ss ); /* save file name */
1662: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1663: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1664: printf(" DIRC2 = %s \n",dirc);
1665: }
1666: /* We add a separator at the end of dirc if not exists */
1667: l1 = strlen( dirc ); /* length of directory */
1668: if( dirc[l1-1] != DIRSEPARATOR ){
1669: dirc[l1] = DIRSEPARATOR;
1670: dirc[l1+1] = 0;
1671: printf(" DIRC3 = %s \n",dirc);
1672: }
1673: ss = strrchr( name, '.' ); /* find last / */
1674: if (ss >0){
1675: ss++;
1676: strcpy(ext,ss); /* save extension */
1677: l1= strlen( name);
1678: l2= strlen(ss)+1;
1679: strncpy( finame, name, l1-l2);
1680: finame[l1-l2]= 0;
1681: }
1682:
1683: return( 0 ); /* we're done */
1684: }
1685:
1686:
1687: /******************************************/
1688:
1689: void replace_back_to_slash(char *s, char*t)
1690: {
1691: int i;
1692: int lg=0;
1693: i=0;
1694: lg=strlen(t);
1695: for(i=0; i<= lg; i++) {
1696: (s[i] = t[i]);
1697: if (t[i]== '\\') s[i]='/';
1698: }
1699: }
1700:
1.132 brouard 1701: char *trimbb(char *out, char *in)
1.137 brouard 1702: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1703: char *s;
1704: s=out;
1705: while (*in != '\0'){
1.137 brouard 1706: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1707: in++;
1708: }
1709: *out++ = *in++;
1710: }
1711: *out='\0';
1712: return s;
1713: }
1714:
1.187 brouard 1715: /* char *substrchaine(char *out, char *in, char *chain) */
1716: /* { */
1717: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1718: /* char *s, *t; */
1719: /* t=in;s=out; */
1720: /* while ((*in != *chain) && (*in != '\0')){ */
1721: /* *out++ = *in++; */
1722: /* } */
1723:
1724: /* /\* *in matches *chain *\/ */
1725: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1726: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1727: /* } */
1728: /* in--; chain--; */
1729: /* while ( (*in != '\0')){ */
1730: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1731: /* *out++ = *in++; */
1732: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1733: /* } */
1734: /* *out='\0'; */
1735: /* out=s; */
1736: /* return out; */
1737: /* } */
1738: char *substrchaine(char *out, char *in, char *chain)
1739: {
1740: /* Substract chain 'chain' from 'in', return and output 'out' */
1741: /* in="V1+V1*age+age*age+V2", chain="age*age" */
1742:
1743: char *strloc;
1744:
1745: strcpy (out, in);
1746: strloc = strstr(out, chain); /* strloc points to out at age*age+V2 */
1747: printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out);
1748: if(strloc != NULL){
1749: /* will affect out */ /* strloc+strlenc(chain)=+V2 */ /* Will also work in Unicode */
1750: memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1);
1751: /* strcpy (strloc, strloc +strlen(chain));*/
1752: }
1753: printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out);
1754: return out;
1755: }
1756:
1757:
1.145 brouard 1758: char *cutl(char *blocc, char *alocc, char *in, char occ)
1759: {
1.187 brouard 1760: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.145 brouard 1761: and alocc starts after first occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1.310 brouard 1762: gives alocc="abcdef" and blocc="ghi2j".
1.145 brouard 1763: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1764: */
1.160 brouard 1765: char *s, *t;
1.145 brouard 1766: t=in;s=in;
1767: while ((*in != occ) && (*in != '\0')){
1768: *alocc++ = *in++;
1769: }
1770: if( *in == occ){
1771: *(alocc)='\0';
1772: s=++in;
1773: }
1774:
1775: if (s == t) {/* occ not found */
1776: *(alocc-(in-s))='\0';
1777: in=s;
1778: }
1779: while ( *in != '\0'){
1780: *blocc++ = *in++;
1781: }
1782:
1783: *blocc='\0';
1784: return t;
1785: }
1.137 brouard 1786: char *cutv(char *blocc, char *alocc, char *in, char occ)
1787: {
1.187 brouard 1788: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1789: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1790: gives blocc="abcdef2ghi" and alocc="j".
1791: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1792: */
1793: char *s, *t;
1794: t=in;s=in;
1795: while (*in != '\0'){
1796: while( *in == occ){
1797: *blocc++ = *in++;
1798: s=in;
1799: }
1800: *blocc++ = *in++;
1801: }
1802: if (s == t) /* occ not found */
1803: *(blocc-(in-s))='\0';
1804: else
1805: *(blocc-(in-s)-1)='\0';
1806: in=s;
1807: while ( *in != '\0'){
1808: *alocc++ = *in++;
1809: }
1810:
1811: *alocc='\0';
1812: return s;
1813: }
1814:
1.126 brouard 1815: int nbocc(char *s, char occ)
1816: {
1817: int i,j=0;
1818: int lg=20;
1819: i=0;
1820: lg=strlen(s);
1821: for(i=0; i<= lg; i++) {
1.234 brouard 1822: if (s[i] == occ ) j++;
1.126 brouard 1823: }
1824: return j;
1825: }
1826:
1.137 brouard 1827: /* void cutv(char *u,char *v, char*t, char occ) */
1828: /* { */
1829: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1830: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1831: /* gives u="abcdef2ghi" and v="j" *\/ */
1832: /* int i,lg,j,p=0; */
1833: /* i=0; */
1834: /* lg=strlen(t); */
1835: /* for(j=0; j<=lg-1; j++) { */
1836: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1837: /* } */
1.126 brouard 1838:
1.137 brouard 1839: /* for(j=0; j<p; j++) { */
1840: /* (u[j] = t[j]); */
1841: /* } */
1842: /* u[p]='\0'; */
1.126 brouard 1843:
1.137 brouard 1844: /* for(j=0; j<= lg; j++) { */
1845: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1846: /* } */
1847: /* } */
1.126 brouard 1848:
1.160 brouard 1849: #ifdef _WIN32
1850: char * strsep(char **pp, const char *delim)
1851: {
1852: char *p, *q;
1853:
1854: if ((p = *pp) == NULL)
1855: return 0;
1856: if ((q = strpbrk (p, delim)) != NULL)
1857: {
1858: *pp = q + 1;
1859: *q = '\0';
1860: }
1861: else
1862: *pp = 0;
1863: return p;
1864: }
1865: #endif
1866:
1.126 brouard 1867: /********************** nrerror ********************/
1868:
1869: void nrerror(char error_text[])
1870: {
1871: fprintf(stderr,"ERREUR ...\n");
1872: fprintf(stderr,"%s\n",error_text);
1873: exit(EXIT_FAILURE);
1874: }
1875: /*********************** vector *******************/
1876: double *vector(int nl, int nh)
1877: {
1878: double *v;
1879: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
1880: if (!v) nrerror("allocation failure in vector");
1881: return v-nl+NR_END;
1882: }
1883:
1884: /************************ free vector ******************/
1885: void free_vector(double*v, int nl, int nh)
1886: {
1887: free((FREE_ARG)(v+nl-NR_END));
1888: }
1889:
1890: /************************ivector *******************************/
1891: int *ivector(long nl,long nh)
1892: {
1893: int *v;
1894: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
1895: if (!v) nrerror("allocation failure in ivector");
1896: return v-nl+NR_END;
1897: }
1898:
1899: /******************free ivector **************************/
1900: void free_ivector(int *v, long nl, long nh)
1901: {
1902: free((FREE_ARG)(v+nl-NR_END));
1903: }
1904:
1905: /************************lvector *******************************/
1906: long *lvector(long nl,long nh)
1907: {
1908: long *v;
1909: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
1910: if (!v) nrerror("allocation failure in ivector");
1911: return v-nl+NR_END;
1912: }
1913:
1914: /******************free lvector **************************/
1915: void free_lvector(long *v, long nl, long nh)
1916: {
1917: free((FREE_ARG)(v+nl-NR_END));
1918: }
1919:
1920: /******************* imatrix *******************************/
1921: int **imatrix(long nrl, long nrh, long ncl, long nch)
1922: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
1923: {
1924: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
1925: int **m;
1926:
1927: /* allocate pointers to rows */
1928: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
1929: if (!m) nrerror("allocation failure 1 in matrix()");
1930: m += NR_END;
1931: m -= nrl;
1932:
1933:
1934: /* allocate rows and set pointers to them */
1935: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
1936: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1937: m[nrl] += NR_END;
1938: m[nrl] -= ncl;
1939:
1940: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
1941:
1942: /* return pointer to array of pointers to rows */
1943: return m;
1944: }
1945:
1946: /****************** free_imatrix *************************/
1947: void free_imatrix(m,nrl,nrh,ncl,nch)
1948: int **m;
1949: long nch,ncl,nrh,nrl;
1950: /* free an int matrix allocated by imatrix() */
1951: {
1952: free((FREE_ARG) (m[nrl]+ncl-NR_END));
1953: free((FREE_ARG) (m+nrl-NR_END));
1954: }
1955:
1956: /******************* matrix *******************************/
1957: double **matrix(long nrl, long nrh, long ncl, long nch)
1958: {
1959: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
1960: double **m;
1961:
1962: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1963: if (!m) nrerror("allocation failure 1 in matrix()");
1964: m += NR_END;
1965: m -= nrl;
1966:
1967: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1968: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1969: m[nrl] += NR_END;
1970: m[nrl] -= ncl;
1971:
1972: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1973: return m;
1.145 brouard 1974: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
1975: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
1976: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 1977: */
1978: }
1979:
1980: /*************************free matrix ************************/
1981: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
1982: {
1983: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1984: free((FREE_ARG)(m+nrl-NR_END));
1985: }
1986:
1987: /******************* ma3x *******************************/
1988: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
1989: {
1990: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
1991: double ***m;
1992:
1993: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1994: if (!m) nrerror("allocation failure 1 in matrix()");
1995: m += NR_END;
1996: m -= nrl;
1997:
1998: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1999: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2000: m[nrl] += NR_END;
2001: m[nrl] -= ncl;
2002:
2003: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
2004:
2005: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
2006: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
2007: m[nrl][ncl] += NR_END;
2008: m[nrl][ncl] -= nll;
2009: for (j=ncl+1; j<=nch; j++)
2010: m[nrl][j]=m[nrl][j-1]+nlay;
2011:
2012: for (i=nrl+1; i<=nrh; i++) {
2013: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
2014: for (j=ncl+1; j<=nch; j++)
2015: m[i][j]=m[i][j-1]+nlay;
2016: }
2017: return m;
2018: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
2019: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
2020: */
2021: }
2022:
2023: /*************************free ma3x ************************/
2024: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
2025: {
2026: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
2027: free((FREE_ARG)(m[nrl]+ncl-NR_END));
2028: free((FREE_ARG)(m+nrl-NR_END));
2029: }
2030:
2031: /*************** function subdirf ***********/
2032: char *subdirf(char fileres[])
2033: {
2034: /* Caution optionfilefiname is hidden */
2035: strcpy(tmpout,optionfilefiname);
2036: strcat(tmpout,"/"); /* Add to the right */
2037: strcat(tmpout,fileres);
2038: return tmpout;
2039: }
2040:
2041: /*************** function subdirf2 ***********/
2042: char *subdirf2(char fileres[], char *preop)
2043: {
1.314 brouard 2044: /* Example subdirf2(optionfilefiname,"FB_") with optionfilefiname="texte", result="texte/FB_texte"
2045: Errors in subdirf, 2, 3 while printing tmpout is
1.315 brouard 2046: rewritten within the same printf. Workaround: many printfs */
1.126 brouard 2047: /* Caution optionfilefiname is hidden */
2048: strcpy(tmpout,optionfilefiname);
2049: strcat(tmpout,"/");
2050: strcat(tmpout,preop);
2051: strcat(tmpout,fileres);
2052: return tmpout;
2053: }
2054:
2055: /*************** function subdirf3 ***********/
2056: char *subdirf3(char fileres[], char *preop, char *preop2)
2057: {
2058:
2059: /* Caution optionfilefiname is hidden */
2060: strcpy(tmpout,optionfilefiname);
2061: strcat(tmpout,"/");
2062: strcat(tmpout,preop);
2063: strcat(tmpout,preop2);
2064: strcat(tmpout,fileres);
2065: return tmpout;
2066: }
1.213 brouard 2067:
2068: /*************** function subdirfext ***********/
2069: char *subdirfext(char fileres[], char *preop, char *postop)
2070: {
2071:
2072: strcpy(tmpout,preop);
2073: strcat(tmpout,fileres);
2074: strcat(tmpout,postop);
2075: return tmpout;
2076: }
1.126 brouard 2077:
1.213 brouard 2078: /*************** function subdirfext3 ***********/
2079: char *subdirfext3(char fileres[], char *preop, char *postop)
2080: {
2081:
2082: /* Caution optionfilefiname is hidden */
2083: strcpy(tmpout,optionfilefiname);
2084: strcat(tmpout,"/");
2085: strcat(tmpout,preop);
2086: strcat(tmpout,fileres);
2087: strcat(tmpout,postop);
2088: return tmpout;
2089: }
2090:
1.162 brouard 2091: char *asc_diff_time(long time_sec, char ascdiff[])
2092: {
2093: long sec_left, days, hours, minutes;
2094: days = (time_sec) / (60*60*24);
2095: sec_left = (time_sec) % (60*60*24);
2096: hours = (sec_left) / (60*60) ;
2097: sec_left = (sec_left) %(60*60);
2098: minutes = (sec_left) /60;
2099: sec_left = (sec_left) % (60);
2100: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
2101: return ascdiff;
2102: }
2103:
1.126 brouard 2104: /***************** f1dim *************************/
2105: extern int ncom;
2106: extern double *pcom,*xicom;
2107: extern double (*nrfunc)(double []);
2108:
2109: double f1dim(double x)
2110: {
2111: int j;
2112: double f;
2113: double *xt;
2114:
2115: xt=vector(1,ncom);
2116: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
2117: f=(*nrfunc)(xt);
2118: free_vector(xt,1,ncom);
2119: return f;
2120: }
2121:
2122: /*****************brent *************************/
2123: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 2124: {
2125: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
2126: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
2127: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
2128: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
2129: * returned function value.
2130: */
1.126 brouard 2131: int iter;
2132: double a,b,d,etemp;
1.159 brouard 2133: double fu=0,fv,fw,fx;
1.164 brouard 2134: double ftemp=0.;
1.126 brouard 2135: double p,q,r,tol1,tol2,u,v,w,x,xm;
2136: double e=0.0;
2137:
2138: a=(ax < cx ? ax : cx);
2139: b=(ax > cx ? ax : cx);
2140: x=w=v=bx;
2141: fw=fv=fx=(*f)(x);
2142: for (iter=1;iter<=ITMAX;iter++) {
2143: xm=0.5*(a+b);
2144: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
2145: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
2146: printf(".");fflush(stdout);
2147: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 2148: #ifdef DEBUGBRENT
1.126 brouard 2149: 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);
2150: 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);
2151: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
2152: #endif
2153: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
2154: *xmin=x;
2155: return fx;
2156: }
2157: ftemp=fu;
2158: if (fabs(e) > tol1) {
2159: r=(x-w)*(fx-fv);
2160: q=(x-v)*(fx-fw);
2161: p=(x-v)*q-(x-w)*r;
2162: q=2.0*(q-r);
2163: if (q > 0.0) p = -p;
2164: q=fabs(q);
2165: etemp=e;
2166: e=d;
2167: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 2168: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 2169: else {
1.224 brouard 2170: d=p/q;
2171: u=x+d;
2172: if (u-a < tol2 || b-u < tol2)
2173: d=SIGN(tol1,xm-x);
1.126 brouard 2174: }
2175: } else {
2176: d=CGOLD*(e=(x >= xm ? a-x : b-x));
2177: }
2178: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
2179: fu=(*f)(u);
2180: if (fu <= fx) {
2181: if (u >= x) a=x; else b=x;
2182: SHFT(v,w,x,u)
1.183 brouard 2183: SHFT(fv,fw,fx,fu)
2184: } else {
2185: if (u < x) a=u; else b=u;
2186: if (fu <= fw || w == x) {
1.224 brouard 2187: v=w;
2188: w=u;
2189: fv=fw;
2190: fw=fu;
1.183 brouard 2191: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 2192: v=u;
2193: fv=fu;
1.183 brouard 2194: }
2195: }
1.126 brouard 2196: }
2197: nrerror("Too many iterations in brent");
2198: *xmin=x;
2199: return fx;
2200: }
2201:
2202: /****************** mnbrak ***********************/
2203:
2204: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
2205: double (*func)(double))
1.183 brouard 2206: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
2207: the downhill direction (defined by the function as evaluated at the initial points) and returns
2208: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
2209: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
2210: */
1.126 brouard 2211: double ulim,u,r,q, dum;
2212: double fu;
1.187 brouard 2213:
2214: double scale=10.;
2215: int iterscale=0;
2216:
2217: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
2218: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
2219:
2220:
2221: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
2222: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
2223: /* *bx = *ax - (*ax - *bx)/scale; */
2224: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
2225: /* } */
2226:
1.126 brouard 2227: if (*fb > *fa) {
2228: SHFT(dum,*ax,*bx,dum)
1.183 brouard 2229: SHFT(dum,*fb,*fa,dum)
2230: }
1.126 brouard 2231: *cx=(*bx)+GOLD*(*bx-*ax);
2232: *fc=(*func)(*cx);
1.183 brouard 2233: #ifdef DEBUG
1.224 brouard 2234: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
2235: 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 2236: #endif
1.224 brouard 2237: 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 2238: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 2239: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 2240: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 2241: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
2242: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
2243: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 2244: fu=(*func)(u);
1.163 brouard 2245: #ifdef DEBUG
2246: /* f(x)=A(x-u)**2+f(u) */
2247: double A, fparabu;
2248: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2249: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 2250: 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);
2251: 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 2252: /* And thus,it can be that fu > *fc even if fparabu < *fc */
2253: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
2254: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
2255: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 2256: #endif
1.184 brouard 2257: #ifdef MNBRAKORIGINAL
1.183 brouard 2258: #else
1.191 brouard 2259: /* if (fu > *fc) { */
2260: /* #ifdef DEBUG */
2261: /* printf("mnbrak4 fu > fc \n"); */
2262: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
2263: /* #endif */
2264: /* /\* 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 *\\/ *\/ */
2265: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
2266: /* dum=u; /\* Shifting c and u *\/ */
2267: /* u = *cx; */
2268: /* *cx = dum; */
2269: /* dum = fu; */
2270: /* fu = *fc; */
2271: /* *fc =dum; */
2272: /* } else { /\* end *\/ */
2273: /* #ifdef DEBUG */
2274: /* printf("mnbrak3 fu < fc \n"); */
2275: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
2276: /* #endif */
2277: /* dum=u; /\* Shifting c and u *\/ */
2278: /* u = *cx; */
2279: /* *cx = dum; */
2280: /* dum = fu; */
2281: /* fu = *fc; */
2282: /* *fc =dum; */
2283: /* } */
1.224 brouard 2284: #ifdef DEBUGMNBRAK
2285: double A, fparabu;
2286: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2287: fparabu= *fa - A*(*ax-u)*(*ax-u);
2288: 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);
2289: 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 2290: #endif
1.191 brouard 2291: dum=u; /* Shifting c and u */
2292: u = *cx;
2293: *cx = dum;
2294: dum = fu;
2295: fu = *fc;
2296: *fc =dum;
1.183 brouard 2297: #endif
1.162 brouard 2298: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 2299: #ifdef DEBUG
1.224 brouard 2300: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
2301: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 2302: #endif
1.126 brouard 2303: fu=(*func)(u);
2304: if (fu < *fc) {
1.183 brouard 2305: #ifdef DEBUG
1.224 brouard 2306: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2307: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2308: #endif
2309: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
2310: SHFT(*fb,*fc,fu,(*func)(u))
2311: #ifdef DEBUG
2312: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 2313: #endif
2314: }
1.162 brouard 2315: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 2316: #ifdef DEBUG
1.224 brouard 2317: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
2318: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 2319: #endif
1.126 brouard 2320: u=ulim;
2321: fu=(*func)(u);
1.183 brouard 2322: } else { /* u could be left to b (if r > q parabola has a maximum) */
2323: #ifdef DEBUG
1.224 brouard 2324: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
2325: 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 2326: #endif
1.126 brouard 2327: u=(*cx)+GOLD*(*cx-*bx);
2328: fu=(*func)(u);
1.224 brouard 2329: #ifdef DEBUG
2330: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2331: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2332: #endif
1.183 brouard 2333: } /* end tests */
1.126 brouard 2334: SHFT(*ax,*bx,*cx,u)
1.183 brouard 2335: SHFT(*fa,*fb,*fc,fu)
2336: #ifdef DEBUG
1.224 brouard 2337: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2338: 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 2339: #endif
2340: } /* 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 2341: }
2342:
2343: /*************** linmin ************************/
1.162 brouard 2344: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2345: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2346: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2347: the value of func at the returned location p . This is actually all accomplished by calling the
2348: routines mnbrak and brent .*/
1.126 brouard 2349: int ncom;
2350: double *pcom,*xicom;
2351: double (*nrfunc)(double []);
2352:
1.224 brouard 2353: #ifdef LINMINORIGINAL
1.126 brouard 2354: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2355: #else
2356: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2357: #endif
1.126 brouard 2358: {
2359: double brent(double ax, double bx, double cx,
2360: double (*f)(double), double tol, double *xmin);
2361: double f1dim(double x);
2362: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2363: double *fc, double (*func)(double));
2364: int j;
2365: double xx,xmin,bx,ax;
2366: double fx,fb,fa;
1.187 brouard 2367:
1.203 brouard 2368: #ifdef LINMINORIGINAL
2369: #else
2370: double scale=10., axs, xxs; /* Scale added for infinity */
2371: #endif
2372:
1.126 brouard 2373: ncom=n;
2374: pcom=vector(1,n);
2375: xicom=vector(1,n);
2376: nrfunc=func;
2377: for (j=1;j<=n;j++) {
2378: pcom[j]=p[j];
1.202 brouard 2379: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2380: }
1.187 brouard 2381:
1.203 brouard 2382: #ifdef LINMINORIGINAL
2383: xx=1.;
2384: #else
2385: axs=0.0;
2386: xxs=1.;
2387: do{
2388: xx= xxs;
2389: #endif
1.187 brouard 2390: ax=0.;
2391: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2392: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2393: /* 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)) */
2394: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2395: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2396: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2397: /* 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 2398: #ifdef LINMINORIGINAL
2399: #else
2400: if (fx != fx){
1.224 brouard 2401: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2402: printf("|");
2403: fprintf(ficlog,"|");
1.203 brouard 2404: #ifdef DEBUGLINMIN
1.224 brouard 2405: 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 2406: #endif
2407: }
1.224 brouard 2408: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2409: #endif
2410:
1.191 brouard 2411: #ifdef DEBUGLINMIN
2412: 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 2413: 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 2414: #endif
1.224 brouard 2415: #ifdef LINMINORIGINAL
2416: #else
1.317 brouard 2417: if(fb == fx){ /* Flat function in the direction */
2418: xmin=xx;
1.224 brouard 2419: *flat=1;
1.317 brouard 2420: }else{
1.224 brouard 2421: *flat=0;
2422: #endif
2423: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2424: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2425: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2426: /* fmin = f(p[j] + xmin * xi[j]) */
2427: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2428: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2429: #ifdef DEBUG
1.224 brouard 2430: 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);
2431: 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);
2432: #endif
2433: #ifdef LINMINORIGINAL
2434: #else
2435: }
1.126 brouard 2436: #endif
1.191 brouard 2437: #ifdef DEBUGLINMIN
2438: printf("linmin end ");
1.202 brouard 2439: fprintf(ficlog,"linmin end ");
1.191 brouard 2440: #endif
1.126 brouard 2441: for (j=1;j<=n;j++) {
1.203 brouard 2442: #ifdef LINMINORIGINAL
2443: xi[j] *= xmin;
2444: #else
2445: #ifdef DEBUGLINMIN
2446: if(xxs <1.0)
2447: printf(" before xi[%d]=%12.8f", j,xi[j]);
2448: #endif
2449: 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) */
2450: #ifdef DEBUGLINMIN
2451: if(xxs <1.0)
2452: 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 );
2453: #endif
2454: #endif
1.187 brouard 2455: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2456: }
1.191 brouard 2457: #ifdef DEBUGLINMIN
1.203 brouard 2458: printf("\n");
1.191 brouard 2459: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2460: 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 2461: for (j=1;j<=n;j++) {
1.202 brouard 2462: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2463: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2464: if(j % ncovmodel == 0){
1.191 brouard 2465: printf("\n");
1.202 brouard 2466: fprintf(ficlog,"\n");
2467: }
1.191 brouard 2468: }
1.203 brouard 2469: #else
1.191 brouard 2470: #endif
1.126 brouard 2471: free_vector(xicom,1,n);
2472: free_vector(pcom,1,n);
2473: }
2474:
2475:
2476: /*************** powell ************************/
1.162 brouard 2477: /*
1.317 brouard 2478: Minimization of a function func of n variables. Input consists in an initial starting point
2479: p[1..n] ; an initial matrix xi[1..n][1..n] whose columns contain the initial set of di-
2480: rections (usually the n unit vectors); and ftol, the fractional tolerance in the function value
2481: such that failure to decrease by more than this amount in one iteration signals doneness. On
1.162 brouard 2482: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2483: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2484: */
1.224 brouard 2485: #ifdef LINMINORIGINAL
2486: #else
2487: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2488: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2489: #endif
1.126 brouard 2490: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2491: double (*func)(double []))
2492: {
1.224 brouard 2493: #ifdef LINMINORIGINAL
2494: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2495: double (*func)(double []));
1.224 brouard 2496: #else
1.241 brouard 2497: void linmin(double p[], double xi[], int n, double *fret,
2498: double (*func)(double []),int *flat);
1.224 brouard 2499: #endif
1.239 brouard 2500: int i,ibig,j,jk,k;
1.126 brouard 2501: double del,t,*pt,*ptt,*xit;
1.181 brouard 2502: double directest;
1.126 brouard 2503: double fp,fptt;
2504: double *xits;
2505: int niterf, itmp;
2506:
2507: pt=vector(1,n);
2508: ptt=vector(1,n);
2509: xit=vector(1,n);
2510: xits=vector(1,n);
2511: *fret=(*func)(p);
2512: for (j=1;j<=n;j++) pt[j]=p[j];
1.338 ! brouard 2513: rcurr_time = time(NULL);
! 2514: fp=(*fret); /* Initialisation */
1.126 brouard 2515: for (*iter=1;;++(*iter)) {
2516: ibig=0;
2517: del=0.0;
1.157 brouard 2518: rlast_time=rcurr_time;
2519: /* (void) gettimeofday(&curr_time,&tzp); */
2520: rcurr_time = time(NULL);
2521: curr_time = *localtime(&rcurr_time);
1.337 brouard 2522: /* printf("\nPowell iter=%d -2*LL=%.12f gain=%.12f=%.3g %ld sec. %ld sec.",*iter,*fret, fp-*fret,fp-*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout); */
2523: /* fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f gain=%.12f=%.3g %ld sec. %ld sec.",*iter,*fret, fp-*fret,fp-*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog); */
2524: printf("\nPowell iter=%d -2*LL=%.12f gain=%.3lg %ld sec. %ld sec.",*iter,*fret,fp-*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout);
2525: fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f gain=%.3lg %ld sec. %ld sec.",*iter,*fret,fp-*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog);
1.157 brouard 2526: /* fprintf(ficrespow,"%d %.12f %ld",*iter,*fret,curr_time.tm_sec-start_time.tm_sec); */
1.324 brouard 2527: fp=(*fret); /* From former iteration or initial value */
1.192 brouard 2528: for (i=1;i<=n;i++) {
1.126 brouard 2529: fprintf(ficrespow," %.12lf", p[i]);
2530: }
1.239 brouard 2531: fprintf(ficrespow,"\n");fflush(ficrespow);
2532: printf("\n#model= 1 + age ");
2533: fprintf(ficlog,"\n#model= 1 + age ");
2534: if(nagesqr==1){
1.241 brouard 2535: printf(" + age*age ");
2536: fprintf(ficlog," + age*age ");
1.239 brouard 2537: }
2538: for(j=1;j <=ncovmodel-2;j++){
2539: if(Typevar[j]==0) {
2540: printf(" + V%d ",Tvar[j]);
2541: fprintf(ficlog," + V%d ",Tvar[j]);
2542: }else if(Typevar[j]==1) {
2543: printf(" + V%d*age ",Tvar[j]);
2544: fprintf(ficlog," + V%d*age ",Tvar[j]);
2545: }else if(Typevar[j]==2) {
2546: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2547: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2548: }
2549: }
1.126 brouard 2550: printf("\n");
1.239 brouard 2551: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2552: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2553: fprintf(ficlog,"\n");
1.239 brouard 2554: for(i=1,jk=1; i <=nlstate; i++){
2555: for(k=1; k <=(nlstate+ndeath); k++){
2556: if (k != i) {
2557: printf("%d%d ",i,k);
2558: fprintf(ficlog,"%d%d ",i,k);
2559: for(j=1; j <=ncovmodel; j++){
2560: printf("%12.7f ",p[jk]);
2561: fprintf(ficlog,"%12.7f ",p[jk]);
2562: jk++;
2563: }
2564: printf("\n");
2565: fprintf(ficlog,"\n");
2566: }
2567: }
2568: }
1.241 brouard 2569: if(*iter <=3 && *iter >1){
1.157 brouard 2570: tml = *localtime(&rcurr_time);
2571: strcpy(strcurr,asctime(&tml));
2572: rforecast_time=rcurr_time;
1.126 brouard 2573: itmp = strlen(strcurr);
2574: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2575: strcurr[itmp-1]='\0';
1.162 brouard 2576: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2577: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.126 brouard 2578: for(niterf=10;niterf<=30;niterf+=10){
1.241 brouard 2579: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2580: forecast_time = *localtime(&rforecast_time);
2581: strcpy(strfor,asctime(&forecast_time));
2582: itmp = strlen(strfor);
2583: if(strfor[itmp-1]=='\n')
2584: strfor[itmp-1]='\0';
2585: 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);
2586: 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 2587: }
2588: }
1.187 brouard 2589: for (i=1;i<=n;i++) { /* For each direction i */
2590: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2591: fptt=(*fret);
2592: #ifdef DEBUG
1.203 brouard 2593: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2594: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2595: #endif
1.203 brouard 2596: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2597: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2598: #ifdef LINMINORIGINAL
1.188 brouard 2599: linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.224 brouard 2600: #else
2601: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2602: flatdir[i]=flat; /* Function is vanishing in that direction i */
2603: #endif
2604: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2605: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2606: /* because that direction will be replaced unless the gain del is small */
2607: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2608: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2609: /* with the new direction. */
2610: del=fabs(fptt-(*fret));
2611: ibig=i;
1.126 brouard 2612: }
2613: #ifdef DEBUG
2614: printf("%d %.12e",i,(*fret));
2615: fprintf(ficlog,"%d %.12e",i,(*fret));
2616: for (j=1;j<=n;j++) {
1.224 brouard 2617: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2618: printf(" x(%d)=%.12e",j,xit[j]);
2619: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2620: }
2621: for(j=1;j<=n;j++) {
1.225 brouard 2622: printf(" p(%d)=%.12e",j,p[j]);
2623: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2624: }
2625: printf("\n");
2626: fprintf(ficlog,"\n");
2627: #endif
1.187 brouard 2628: } /* end loop on each direction i */
2629: /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
1.188 brouard 2630: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.187 brouard 2631: /* New value of last point Pn is not computed, P(n-1) */
1.319 brouard 2632: for(j=1;j<=n;j++) {
2633: if(flatdir[j] >0){
2634: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2635: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
1.302 brouard 2636: }
1.319 brouard 2637: /* printf("\n"); */
2638: /* fprintf(ficlog,"\n"); */
2639: }
1.243 brouard 2640: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
2641: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2642: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2643: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2644: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2645: /* decreased of more than 3.84 */
2646: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2647: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2648: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2649:
1.188 brouard 2650: /* Starting the program with initial values given by a former maximization will simply change */
2651: /* the scales of the directions and the directions, because the are reset to canonical directions */
2652: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2653: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2654: #ifdef DEBUG
2655: int k[2],l;
2656: k[0]=1;
2657: k[1]=-1;
2658: printf("Max: %.12e",(*func)(p));
2659: fprintf(ficlog,"Max: %.12e",(*func)(p));
2660: for (j=1;j<=n;j++) {
2661: printf(" %.12e",p[j]);
2662: fprintf(ficlog," %.12e",p[j]);
2663: }
2664: printf("\n");
2665: fprintf(ficlog,"\n");
2666: for(l=0;l<=1;l++) {
2667: for (j=1;j<=n;j++) {
2668: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2669: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2670: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2671: }
2672: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2673: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2674: }
2675: #endif
2676:
2677: free_vector(xit,1,n);
2678: free_vector(xits,1,n);
2679: free_vector(ptt,1,n);
2680: free_vector(pt,1,n);
2681: return;
1.192 brouard 2682: } /* enough precision */
1.240 brouard 2683: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2684: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2685: ptt[j]=2.0*p[j]-pt[j];
2686: xit[j]=p[j]-pt[j];
2687: pt[j]=p[j];
2688: }
1.181 brouard 2689: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2690: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2691: if (*iter <=4) {
1.225 brouard 2692: #else
2693: #endif
1.224 brouard 2694: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2695: #else
1.161 brouard 2696: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2697: #endif
1.162 brouard 2698: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2699: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2700: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2701: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2702: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2703: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2704: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2705: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2706: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2707: /* Even if f3 <f1, directest can be negative and t >0 */
2708: /* mu² and del² are equal when f3=f1 */
2709: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2710: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2711: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2712: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2713: #ifdef NRCORIGINAL
2714: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2715: #else
2716: 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 2717: t= t- del*SQR(fp-fptt);
1.183 brouard 2718: #endif
1.202 brouard 2719: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2720: #ifdef DEBUG
1.181 brouard 2721: 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);
2722: 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 2723: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2724: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2725: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2726: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2727: 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);
2728: 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);
2729: #endif
1.183 brouard 2730: #ifdef POWELLORIGINAL
2731: if (t < 0.0) { /* Then we use it for new direction */
2732: #else
1.182 brouard 2733: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2734: 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 2735: 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 2736: 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 2737: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2738: }
1.181 brouard 2739: if (directest < 0.0) { /* Then we use it for new direction */
2740: #endif
1.191 brouard 2741: #ifdef DEBUGLINMIN
1.234 brouard 2742: printf("Before linmin in direction P%d-P0\n",n);
2743: for (j=1;j<=n;j++) {
2744: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2745: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2746: if(j % ncovmodel == 0){
2747: printf("\n");
2748: fprintf(ficlog,"\n");
2749: }
2750: }
1.224 brouard 2751: #endif
2752: #ifdef LINMINORIGINAL
1.234 brouard 2753: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2754: #else
1.234 brouard 2755: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2756: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2757: #endif
1.234 brouard 2758:
1.191 brouard 2759: #ifdef DEBUGLINMIN
1.234 brouard 2760: for (j=1;j<=n;j++) {
2761: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2762: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2763: if(j % ncovmodel == 0){
2764: printf("\n");
2765: fprintf(ficlog,"\n");
2766: }
2767: }
1.224 brouard 2768: #endif
1.234 brouard 2769: for (j=1;j<=n;j++) {
2770: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2771: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2772: }
1.224 brouard 2773: #ifdef LINMINORIGINAL
2774: #else
1.234 brouard 2775: for (j=1, flatd=0;j<=n;j++) {
2776: if(flatdir[j]>0)
2777: flatd++;
2778: }
2779: if(flatd >0){
1.255 brouard 2780: printf("%d flat directions: ",flatd);
2781: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 2782: for (j=1;j<=n;j++) {
2783: if(flatdir[j]>0){
2784: printf("%d ",j);
2785: fprintf(ficlog,"%d ",j);
2786: }
2787: }
2788: printf("\n");
2789: fprintf(ficlog,"\n");
1.319 brouard 2790: #ifdef FLATSUP
2791: free_vector(xit,1,n);
2792: free_vector(xits,1,n);
2793: free_vector(ptt,1,n);
2794: free_vector(pt,1,n);
2795: return;
2796: #endif
1.234 brouard 2797: }
1.191 brouard 2798: #endif
1.234 brouard 2799: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2800: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2801:
1.126 brouard 2802: #ifdef DEBUG
1.234 brouard 2803: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2804: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2805: for(j=1;j<=n;j++){
2806: printf(" %lf",xit[j]);
2807: fprintf(ficlog," %lf",xit[j]);
2808: }
2809: printf("\n");
2810: fprintf(ficlog,"\n");
1.126 brouard 2811: #endif
1.192 brouard 2812: } /* end of t or directest negative */
1.224 brouard 2813: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2814: #else
1.234 brouard 2815: } /* end if (fptt < fp) */
1.192 brouard 2816: #endif
1.225 brouard 2817: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2818: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2819: #else
1.224 brouard 2820: #endif
1.234 brouard 2821: } /* loop iteration */
1.126 brouard 2822: }
1.234 brouard 2823:
1.126 brouard 2824: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 2825:
1.235 brouard 2826: 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 2827: {
1.338 ! brouard 2828: /**< Computes the prevalence limit in each live state at age x and for covariate combination ij . Nicely done
1.279 brouard 2829: * (and selected quantitative values in nres)
2830: * by left multiplying the unit
2831: * matrix by transitions matrix until convergence is reached with precision ftolpl
2832: * Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I
2833: * Wx is row vector: population in state 1, population in state 2, population dead
2834: * or prevalence in state 1, prevalence in state 2, 0
2835: * newm is the matrix after multiplications, its rows are identical at a factor.
2836: * Inputs are the parameter, age, a tolerance for the prevalence limit ftolpl.
2837: * Output is prlim.
2838: * Initial matrix pimij
2839: */
1.206 brouard 2840: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2841: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2842: /* 0, 0 , 1} */
2843: /*
2844: * and after some iteration: */
2845: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2846: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2847: /* 0, 0 , 1} */
2848: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2849: /* {0.51571254859325999, 0.4842874514067399, */
2850: /* 0.51326036147820708, 0.48673963852179264} */
2851: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 2852:
1.332 brouard 2853: int i, ii,j,k, k1;
1.209 brouard 2854: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 2855: /* double **matprod2(); */ /* test */
1.218 brouard 2856: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 2857: double **newm;
1.209 brouard 2858: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 2859: int ncvloop=0;
1.288 brouard 2860: int first=0;
1.169 brouard 2861:
1.209 brouard 2862: min=vector(1,nlstate);
2863: max=vector(1,nlstate);
2864: meandiff=vector(1,nlstate);
2865:
1.218 brouard 2866: /* Starting with matrix unity */
1.126 brouard 2867: for (ii=1;ii<=nlstate+ndeath;ii++)
2868: for (j=1;j<=nlstate+ndeath;j++){
2869: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2870: }
1.169 brouard 2871:
2872: cov[1]=1.;
2873:
2874: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 2875: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 2876: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 2877: ncvloop++;
1.126 brouard 2878: newm=savm;
2879: /* Covariates have to be included here again */
1.138 brouard 2880: cov[2]=agefin;
1.319 brouard 2881: if(nagesqr==1){
2882: cov[3]= agefin*agefin;
2883: }
1.332 brouard 2884: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
2885: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
2886: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
2887: if(Typevar[k1]==1){ /* A product with age */
2888: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
2889: }else{
2890: cov[2+nagesqr+k1]=precov[nres][k1];
2891: }
2892: }/* End of loop on model equation */
2893:
2894: /* Start of old code (replaced by a loop on position in the model equation */
2895: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only of the model *\/ */
2896: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
2897: /* /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])]; *\/ */
2898: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TnsdVar[TvarsD[k]])]; */
2899: /* /\* model = 1 +age + V1*V3 + age*V1 + V2 + V1 + age*V2 + V3 + V3*age + V1*V2 */
2900: /* * k 1 2 3 4 5 6 7 8 */
2901: /* *cov[] 1 2 3 4 5 6 7 8 9 10 */
2902: /* *TypeVar[k] 2 1 0 0 1 0 1 2 */
2903: /* *Dummy[k] 0 2 0 0 2 0 2 0 */
2904: /* *Tvar[k] 4 1 2 1 2 3 3 5 */
2905: /* *nsd=3 (1) (2) (3) */
2906: /* *TvarsD[nsd] [1]=2 1 3 */
2907: /* *TnsdVar [2]=2 [1]=1 [3]=3 */
2908: /* *TvarsDind[nsd](=k) [1]=3 [2]=4 [3]=6 */
2909: /* *Tage[] [1]=1 [2]=2 [3]=3 */
2910: /* *Tvard[] [1][1]=1 [2][1]=1 */
2911: /* * [1][2]=3 [2][2]=2 */
2912: /* *Tprod[](=k) [1]=1 [2]=8 */
2913: /* *TvarsDp(=Tvar) [1]=1 [2]=2 [3]=3 [4]=5 */
2914: /* *TvarD (=k) [1]=1 [2]=3 [3]=4 [3]=6 [4]=6 */
2915: /* *TvarsDpType */
2916: /* *si model= 1 + age + V3 + V2*age + V2 + V3*age */
2917: /* * nsd=1 (1) (2) */
2918: /* *TvarsD[nsd] 3 2 */
2919: /* *TnsdVar (3)=1 (2)=2 */
2920: /* *TvarsDind[nsd](=k) [1]=1 [2]=3 */
2921: /* *Tage[] [1]=2 [2]= 3 */
2922: /* *\/ */
2923: /* /\* cov[++k1]=nbcode[TvarsD[k]][codtabm(ij,k)]; *\/ */
2924: /* /\* 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)); *\/ */
2925: /* } */
2926: /* for (k=1; k<=nsq;k++) { /\* For single quantitative varying covariates only of the model *\/ */
2927: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
2928: /* /\* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline *\/ */
2929: /* /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
2930: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][resultmodel[nres][k1]] */
2931: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
2932: /* /\* 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]); *\/ */
2933: /* } */
2934: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
2935: /* if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
2936: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
2937: /* /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
2938: /* } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
2939: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
2940: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
2941: /* } */
2942: /* /\* 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]); *\/ */
2943: /* } */
2944: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
2945: /* /\* 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]); *\/ */
2946: /* if(Dummy[Tvard[k][1]]==0){ */
2947: /* if(Dummy[Tvard[k][2]]==0){ */
2948: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
2949: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
2950: /* }else{ */
2951: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
2952: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
2953: /* } */
2954: /* }else{ */
2955: /* if(Dummy[Tvard[k][2]]==0){ */
2956: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
2957: /* /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
2958: /* }else{ */
2959: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
2960: /* /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\/ */
2961: /* } */
2962: /* } */
2963: /* } /\* End product without age *\/ */
2964: /* ENd of old code */
1.138 brouard 2965: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2966: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2967: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 2968: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2969: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.319 brouard 2970: /* age and covariate values of ij are in 'cov' */
1.142 brouard 2971: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 2972:
1.126 brouard 2973: savm=oldm;
2974: oldm=newm;
1.209 brouard 2975:
2976: for(j=1; j<=nlstate; j++){
2977: max[j]=0.;
2978: min[j]=1.;
2979: }
2980: for(i=1;i<=nlstate;i++){
2981: sumnew=0;
2982: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
2983: for(j=1; j<=nlstate; j++){
2984: prlim[i][j]= newm[i][j]/(1-sumnew);
2985: max[j]=FMAX(max[j],prlim[i][j]);
2986: min[j]=FMIN(min[j],prlim[i][j]);
2987: }
2988: }
2989:
1.126 brouard 2990: maxmax=0.;
1.209 brouard 2991: for(j=1; j<=nlstate; j++){
2992: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
2993: maxmax=FMAX(maxmax,meandiff[j]);
2994: /* 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 2995: } /* j loop */
1.203 brouard 2996: *ncvyear= (int)age- (int)agefin;
1.208 brouard 2997: /* 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 2998: if(maxmax < ftolpl){
1.209 brouard 2999: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
3000: free_vector(min,1,nlstate);
3001: free_vector(max,1,nlstate);
3002: free_vector(meandiff,1,nlstate);
1.126 brouard 3003: return prlim;
3004: }
1.288 brouard 3005: } /* agefin loop */
1.208 brouard 3006: /* After some age loop it doesn't converge */
1.288 brouard 3007: if(!first){
3008: first=1;
3009: 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 3010: 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);
3011: }else if (first >=1 && first <10){
3012: 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);
3013: first++;
3014: }else if (first ==10){
3015: 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);
3016: 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");
3017: fprintf(ficlog,"Warning: the stable prevalence no convergence; too many cases, giving up noticing, even in log file\n");
3018: first++;
1.288 brouard 3019: }
3020:
1.209 brouard 3021: /* 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); */
3022: free_vector(min,1,nlstate);
3023: free_vector(max,1,nlstate);
3024: free_vector(meandiff,1,nlstate);
1.208 brouard 3025:
1.169 brouard 3026: return prlim; /* should not reach here */
1.126 brouard 3027: }
3028:
1.217 brouard 3029:
3030: /**** Back Prevalence limit (stable or period prevalence) ****************/
3031:
1.218 brouard 3032: /* 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) */
3033: /* 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 3034: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 3035: {
1.264 brouard 3036: /* 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 3037: matrix by transitions matrix until convergence is reached with precision ftolpl */
3038: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
3039: /* Wx is row vector: population in state 1, population in state 2, population dead */
3040: /* or prevalence in state 1, prevalence in state 2, 0 */
3041: /* newm is the matrix after multiplications, its rows are identical at a factor */
3042: /* Initial matrix pimij */
3043: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
3044: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
3045: /* 0, 0 , 1} */
3046: /*
3047: * and after some iteration: */
3048: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
3049: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
3050: /* 0, 0 , 1} */
3051: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
3052: /* {0.51571254859325999, 0.4842874514067399, */
3053: /* 0.51326036147820708, 0.48673963852179264} */
3054: /* If we start from prlim again, prlim tends to a constant matrix */
3055:
1.332 brouard 3056: int i, ii,j,k, k1;
1.247 brouard 3057: int first=0;
1.217 brouard 3058: double *min, *max, *meandiff, maxmax,sumnew=0.;
3059: /* double **matprod2(); */ /* test */
3060: double **out, cov[NCOVMAX+1], **bmij();
3061: double **newm;
1.218 brouard 3062: double **dnewm, **doldm, **dsavm; /* for use */
3063: double **oldm, **savm; /* for use */
3064:
1.217 brouard 3065: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
3066: int ncvloop=0;
3067:
3068: min=vector(1,nlstate);
3069: max=vector(1,nlstate);
3070: meandiff=vector(1,nlstate);
3071:
1.266 brouard 3072: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
3073: oldm=oldms; savm=savms;
3074:
3075: /* Starting with matrix unity */
3076: for (ii=1;ii<=nlstate+ndeath;ii++)
3077: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 3078: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3079: }
3080:
3081: cov[1]=1.;
3082:
3083: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3084: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 3085: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
1.288 brouard 3086: /* for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
3087: for(agefin=age; agefin<FMIN(AGESUP,age+delaymax); agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 3088: ncvloop++;
1.218 brouard 3089: newm=savm; /* oldm should be kept from previous iteration or unity at start */
3090: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 3091: /* Covariates have to be included here again */
3092: cov[2]=agefin;
1.319 brouard 3093: if(nagesqr==1){
1.217 brouard 3094: cov[3]= agefin*agefin;;
1.319 brouard 3095: }
1.332 brouard 3096: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
3097: if(Typevar[k1]==1){ /* A product with age */
3098: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.242 brouard 3099: }else{
1.332 brouard 3100: cov[2+nagesqr+k1]=precov[nres][k1];
1.242 brouard 3101: }
1.332 brouard 3102: }/* End of loop on model equation */
3103:
3104: /* Old code */
3105:
3106: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
3107: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
3108: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])]; */
3109: /* /\* 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)); *\/ */
3110: /* } */
3111: /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
3112: /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
3113: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
3114: /* /\* /\\* 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])]); *\\/ *\/ */
3115: /* /\* } *\/ */
3116: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
3117: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3118: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
3119: /* /\* 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]); *\/ */
3120: /* } */
3121: /* /\* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; *\/ */
3122: /* /\* for (k=1; k<=cptcovprod;k++) /\\* Useless *\\/ *\/ */
3123: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\\/ *\/ */
3124: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3125: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
3126: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age *\\/ ERROR ???*\/ */
3127: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
3128: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3129: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
3130: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3131: /* } */
3132: /* /\* 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]); *\/ */
3133: /* } */
3134: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
3135: /* /\* 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]); *\/ */
3136: /* if(Dummy[Tvard[k][1]]==0){ */
3137: /* if(Dummy[Tvard[k][2]]==0){ */
3138: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3139: /* }else{ */
3140: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3141: /* } */
3142: /* }else{ */
3143: /* if(Dummy[Tvard[k][2]]==0){ */
3144: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3145: /* }else{ */
3146: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3147: /* } */
3148: /* } */
3149: /* } */
1.217 brouard 3150:
3151: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
3152: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
3153: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
3154: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3155: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 3156: /* ij should be linked to the correct index of cov */
3157: /* age and covariate values ij are in 'cov', but we need to pass
3158: * ij for the observed prevalence at age and status and covariate
3159: * number: prevacurrent[(int)agefin][ii][ij]
3160: */
3161: /* 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 *\/ */
3162: /* 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 *\/ */
3163: 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 3164: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 3165: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
3166: /* for(i=1; i<=nlstate+ndeath; i++) { */
3167: /* printf("%d newm= ",i); */
3168: /* for(j=1;j<=nlstate+ndeath;j++) { */
3169: /* printf("%f ",newm[i][j]); */
3170: /* } */
3171: /* printf("oldm * "); */
3172: /* for(j=1;j<=nlstate+ndeath;j++) { */
3173: /* printf("%f ",oldm[i][j]); */
3174: /* } */
1.268 brouard 3175: /* printf(" bmmij "); */
1.266 brouard 3176: /* for(j=1;j<=nlstate+ndeath;j++) { */
3177: /* printf("%f ",pmmij[i][j]); */
3178: /* } */
3179: /* printf("\n"); */
3180: /* } */
3181: /* } */
1.217 brouard 3182: savm=oldm;
3183: oldm=newm;
1.266 brouard 3184:
1.217 brouard 3185: for(j=1; j<=nlstate; j++){
3186: max[j]=0.;
3187: min[j]=1.;
3188: }
3189: for(j=1; j<=nlstate; j++){
3190: for(i=1;i<=nlstate;i++){
1.234 brouard 3191: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
3192: bprlim[i][j]= newm[i][j];
3193: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
3194: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 3195: }
3196: }
1.218 brouard 3197:
1.217 brouard 3198: maxmax=0.;
3199: for(i=1; i<=nlstate; i++){
1.318 brouard 3200: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column, could be nan! */
1.217 brouard 3201: maxmax=FMAX(maxmax,meandiff[i]);
3202: /* 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 3203: } /* i loop */
1.217 brouard 3204: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 3205: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3206: if(maxmax < ftolpl){
1.220 brouard 3207: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3208: free_vector(min,1,nlstate);
3209: free_vector(max,1,nlstate);
3210: free_vector(meandiff,1,nlstate);
3211: return bprlim;
3212: }
1.288 brouard 3213: } /* agefin loop */
1.217 brouard 3214: /* After some age loop it doesn't converge */
1.288 brouard 3215: if(!first){
1.247 brouard 3216: first=1;
3217: 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\
3218: 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);
3219: }
3220: 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 3221: 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);
3222: /* 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); */
3223: free_vector(min,1,nlstate);
3224: free_vector(max,1,nlstate);
3225: free_vector(meandiff,1,nlstate);
3226:
3227: return bprlim; /* should not reach here */
3228: }
3229:
1.126 brouard 3230: /*************** transition probabilities ***************/
3231:
3232: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
3233: {
1.138 brouard 3234: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 3235: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 3236: model to the ncovmodel covariates (including constant and age).
3237: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3238: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3239: ncth covariate in the global vector x is given by the formula:
3240: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3241: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3242: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3243: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 3244: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 3245: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 3246: Sum on j ps[i][j] should equal to 1.
1.138 brouard 3247: */
3248: double s1, lnpijopii;
1.126 brouard 3249: /*double t34;*/
1.164 brouard 3250: int i,j, nc, ii, jj;
1.126 brouard 3251:
1.223 brouard 3252: for(i=1; i<= nlstate; i++){
3253: for(j=1; j<i;j++){
3254: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3255: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3256: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3257: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3258: }
3259: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 3260: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 3261: }
3262: for(j=i+1; j<=nlstate+ndeath;j++){
3263: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3264: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3265: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3266: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3267: }
3268: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 3269: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 3270: }
3271: }
1.218 brouard 3272:
1.223 brouard 3273: for(i=1; i<= nlstate; i++){
3274: s1=0;
3275: for(j=1; j<i; j++){
3276: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
1.330 brouard 3277: /* printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
1.223 brouard 3278: }
3279: for(j=i+1; j<=nlstate+ndeath; j++){
3280: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
1.330 brouard 3281: /* printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
1.223 brouard 3282: }
3283: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3284: ps[i][i]=1./(s1+1.);
3285: /* Computing other pijs */
3286: for(j=1; j<i; j++)
1.325 brouard 3287: ps[i][j]= exp(ps[i][j])*ps[i][i];/* Bug valgrind */
1.223 brouard 3288: for(j=i+1; j<=nlstate+ndeath; j++)
3289: ps[i][j]= exp(ps[i][j])*ps[i][i];
3290: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3291: } /* end i */
1.218 brouard 3292:
1.223 brouard 3293: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3294: for(jj=1; jj<= nlstate+ndeath; jj++){
3295: ps[ii][jj]=0;
3296: ps[ii][ii]=1;
3297: }
3298: }
1.294 brouard 3299:
3300:
1.223 brouard 3301: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3302: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3303: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3304: /* } */
3305: /* printf("\n "); */
3306: /* } */
3307: /* printf("\n ");printf("%lf ",cov[2]);*/
3308: /*
3309: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 3310: goto end;*/
1.266 brouard 3311: return ps; /* Pointer is unchanged since its call */
1.126 brouard 3312: }
3313:
1.218 brouard 3314: /*************** backward transition probabilities ***************/
3315:
3316: /* 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 ) */
3317: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
3318: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
3319: {
1.302 brouard 3320: /* 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 3321: * 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 3322: */
1.218 brouard 3323: int i, ii, j,k;
1.222 brouard 3324:
3325: double **out, **pmij();
3326: double sumnew=0.;
1.218 brouard 3327: double agefin;
1.292 brouard 3328: 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 3329: double **dnewm, **dsavm, **doldm;
3330: double **bbmij;
3331:
1.218 brouard 3332: doldm=ddoldms; /* global pointers */
1.222 brouard 3333: dnewm=ddnewms;
3334: dsavm=ddsavms;
1.318 brouard 3335:
3336: /* Debug */
3337: /* printf("Bmij ij=%d, cov[2}=%f\n", ij, cov[2]); */
1.222 brouard 3338: agefin=cov[2];
1.268 brouard 3339: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 3340: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 3341: the observed prevalence (with this covariate ij) at beginning of transition */
3342: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 3343:
3344: /* P_x */
1.325 brouard 3345: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm *//* Bug valgrind */
1.268 brouard 3346: /* outputs pmmij which is a stochastic matrix in row */
3347:
3348: /* Diag(w_x) */
1.292 brouard 3349: /* Rescaling the cross-sectional prevalence: Problem with prevacurrent which can be zero */
1.268 brouard 3350: sumnew=0.;
1.269 brouard 3351: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 3352: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.297 brouard 3353: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 3354: sumnew+=prevacurrent[(int)agefin][ii][ij];
3355: }
3356: if(sumnew >0.01){ /* At least some value in the prevalence */
3357: for (ii=1;ii<=nlstate+ndeath;ii++){
3358: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 3359: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 3360: }
3361: }else{
3362: for (ii=1;ii<=nlstate+ndeath;ii++){
3363: for (j=1;j<=nlstate+ndeath;j++)
3364: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
3365: }
3366: /* if(sumnew <0.9){ */
3367: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
3368: /* } */
3369: }
3370: k3=0.0; /* We put the last diagonal to 0 */
3371: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
3372: doldm[ii][ii]= k3;
3373: }
3374: /* End doldm, At the end doldm is diag[(w_i)] */
3375:
1.292 brouard 3376: /* Left product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm): diag[(w_i)*Px */
3377: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* was a Bug Valgrind */
1.268 brouard 3378:
1.292 brouard 3379: /* Diag(Sum_i w^i_x p^ij_x, should be the prevalence at age x+stepm */
1.268 brouard 3380: /* 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 3381: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 3382: sumnew=0.;
1.222 brouard 3383: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 3384: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 3385: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 3386: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 3387: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 3388: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 3389: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3390: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 3391: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3392: /* }else */
1.268 brouard 3393: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
3394: } /*End ii */
3395: } /* 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 */
3396:
1.292 brouard 3397: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* was a Bug Valgrind */
1.268 brouard 3398: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 3399: /* end bmij */
1.266 brouard 3400: return ps; /*pointer is unchanged */
1.218 brouard 3401: }
1.217 brouard 3402: /*************** transition probabilities ***************/
3403:
1.218 brouard 3404: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 3405: {
3406: /* According to parameters values stored in x and the covariate's values stored in cov,
3407: computes the probability to be observed in state j being in state i by appying the
3408: model to the ncovmodel covariates (including constant and age).
3409: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3410: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3411: ncth covariate in the global vector x is given by the formula:
3412: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3413: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3414: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3415: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
3416: Outputs ps[i][j] the probability to be observed in j being in j according to
3417: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
3418: */
3419: double s1, lnpijopii;
3420: /*double t34;*/
3421: int i,j, nc, ii, jj;
3422:
1.234 brouard 3423: for(i=1; i<= nlstate; i++){
3424: for(j=1; j<i;j++){
3425: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3426: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3427: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3428: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3429: }
3430: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3431: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3432: }
3433: for(j=i+1; j<=nlstate+ndeath;j++){
3434: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3435: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3436: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3437: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3438: }
3439: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3440: }
3441: }
3442:
3443: for(i=1; i<= nlstate; i++){
3444: s1=0;
3445: for(j=1; j<i; j++){
3446: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3447: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3448: }
3449: for(j=i+1; j<=nlstate+ndeath; j++){
3450: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3451: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3452: }
3453: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3454: ps[i][i]=1./(s1+1.);
3455: /* Computing other pijs */
3456: for(j=1; j<i; j++)
3457: ps[i][j]= exp(ps[i][j])*ps[i][i];
3458: for(j=i+1; j<=nlstate+ndeath; j++)
3459: ps[i][j]= exp(ps[i][j])*ps[i][i];
3460: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3461: } /* end i */
3462:
3463: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3464: for(jj=1; jj<= nlstate+ndeath; jj++){
3465: ps[ii][jj]=0;
3466: ps[ii][ii]=1;
3467: }
3468: }
1.296 brouard 3469: /* Added for prevbcast */ /* Transposed matrix too */
1.234 brouard 3470: for(jj=1; jj<= nlstate+ndeath; jj++){
3471: s1=0.;
3472: for(ii=1; ii<= nlstate+ndeath; ii++){
3473: s1+=ps[ii][jj];
3474: }
3475: for(ii=1; ii<= nlstate; ii++){
3476: ps[ii][jj]=ps[ii][jj]/s1;
3477: }
3478: }
3479: /* Transposition */
3480: for(jj=1; jj<= nlstate+ndeath; jj++){
3481: for(ii=jj; ii<= nlstate+ndeath; ii++){
3482: s1=ps[ii][jj];
3483: ps[ii][jj]=ps[jj][ii];
3484: ps[jj][ii]=s1;
3485: }
3486: }
3487: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3488: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3489: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3490: /* } */
3491: /* printf("\n "); */
3492: /* } */
3493: /* printf("\n ");printf("%lf ",cov[2]);*/
3494: /*
3495: for(i=1; i<= npar; i++) printf("%f ",x[i]);
3496: goto end;*/
3497: return ps;
1.217 brouard 3498: }
3499:
3500:
1.126 brouard 3501: /**************** Product of 2 matrices ******************/
3502:
1.145 brouard 3503: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 3504: {
3505: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
3506: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
3507: /* in, b, out are matrice of pointers which should have been initialized
3508: before: only the contents of out is modified. The function returns
3509: a pointer to pointers identical to out */
1.145 brouard 3510: int i, j, k;
1.126 brouard 3511: for(i=nrl; i<= nrh; i++)
1.145 brouard 3512: for(k=ncolol; k<=ncoloh; k++){
3513: out[i][k]=0.;
3514: for(j=ncl; j<=nch; j++)
3515: out[i][k] +=in[i][j]*b[j][k];
3516: }
1.126 brouard 3517: return out;
3518: }
3519:
3520:
3521: /************* Higher Matrix Product ***************/
3522:
1.235 brouard 3523: 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 3524: {
1.336 brouard 3525: /* Already optimized with precov.
3526: Computes the transition matrix starting at age 'age' and dummies values in each resultline (loop on ij to find the corresponding combination) to over
1.126 brouard 3527: 'nhstepm*hstepm*stepm' months (i.e. until
3528: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3529: nhstepm*hstepm matrices.
3530: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3531: (typically every 2 years instead of every month which is too big
3532: for the memory).
3533: Model is determined by parameters x and covariates have to be
3534: included manually here.
3535:
3536: */
3537:
1.330 brouard 3538: int i, j, d, h, k, k1;
1.131 brouard 3539: double **out, cov[NCOVMAX+1];
1.126 brouard 3540: double **newm;
1.187 brouard 3541: double agexact;
1.214 brouard 3542: double agebegin, ageend;
1.126 brouard 3543:
3544: /* Hstepm could be zero and should return the unit matrix */
3545: for (i=1;i<=nlstate+ndeath;i++)
3546: for (j=1;j<=nlstate+ndeath;j++){
3547: oldm[i][j]=(i==j ? 1.0 : 0.0);
3548: po[i][j][0]=(i==j ? 1.0 : 0.0);
3549: }
3550: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3551: for(h=1; h <=nhstepm; h++){
3552: for(d=1; d <=hstepm; d++){
3553: newm=savm;
3554: /* Covariates have to be included here again */
3555: cov[1]=1.;
1.214 brouard 3556: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3557: cov[2]=agexact;
1.319 brouard 3558: if(nagesqr==1){
1.227 brouard 3559: cov[3]= agexact*agexact;
1.319 brouard 3560: }
1.330 brouard 3561: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
3562: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
3563: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.332 brouard 3564: if(Typevar[k1]==1){ /* A product with age */
3565: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
3566: }else{
3567: cov[2+nagesqr+k1]=precov[nres][k1];
3568: }
3569: }/* End of loop on model equation */
3570: /* Old code */
3571: /* if( Dummy[k1]==0 && Typevar[k1]==0 ){ /\* Single dummy *\/ */
3572: /* /\* V(Tvarsel)=Tvalsel=Tresult[nres][pos](value); V(Tvresult[nres][pos] (variable): V(variable)=value) *\/ */
3573: /* /\* for (k=1; k<=nsd;k++) { /\\* For single dummy covariates only *\\/ *\/ */
3574: /* /\* /\\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\\/ *\/ */
3575: /* /\* codtabm(ij,k) (1 & (ij-1) >> (k-1))+1 *\/ */
3576: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
3577: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
3578: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
3579: /* /\* nsd 1 2 3 *\/ /\* Counting single dummies covar fixed or tv *\/ */
3580: /* /\*TvarsD[nsd] 4 3 1 *\/ /\* ID of single dummy cova fixed or timevary*\/ */
3581: /* /\*TvarsDind[k] 2 3 9 *\/ /\* position K of single dummy cova *\/ */
3582: /* /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];or [codtabm(ij,TnsdVar[TvarsD[k]] *\/ */
3583: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
3584: /* /\* printf("hpxij Dummy combi=%d k=%d TvarsD[%d]=V%d TvarsDind[%d]=%d nbcode=%d cov=%lf codtabm(%d,TnsdVar[TvarsD[%d])=%d \n",ij,k, k, TvarsD[k],k,TvarsDind[k],nbcode[TvarsD[k]][codtabm(ij,TnsdVar[TvarsD[k]])],cov[2+nagesqr+TvarsDind[k]], ij, k, codtabm(ij,TnsdVar[TvarsD[k]])); *\/ */
3585: /* printf("hpxij Dummy combi=%d k1=%d Tvar[%d]=V%d cov[2+%d+%d]=%lf resultmodel[nres][%d]=%d nres/nresult=%d/%d \n",ij,k1,k1, Tvar[k1],nagesqr,k1,cov[2+nagesqr+k1],k1,resultmodel[nres][k1],nres,nresult); */
3586: /* printf("hpxij new Dummy precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3587: /* }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /\* Single quantitative variables *\/ */
3588: /* /\* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline *\/ */
3589: /* cov[2+nagesqr+k1]=Tqresult[nres][resultmodel[nres][k1]]; */
3590: /* /\* for (k=1; k<=nsq;k++) { /\\* For single varying covariates only *\\/ *\/ */
3591: /* /\* /\\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\\/ *\/ */
3592: /* /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
3593: /* printf("hPxij Quantitative k1=%d resultmodel[nres][%d]=%d,Tqresult[%d][%d]=%f\n",k1,k1,resultmodel[nres][k1],nres,resultmodel[nres][k1],Tqresult[nres][resultmodel[nres][k1]]); */
3594: /* printf("hpxij new Quanti precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3595: /* }else if( Dummy[k1]==2 ){ /\* For dummy with age product *\/ */
3596: /* /\* Tvar[k1] Variable in the age product age*V1 is 1 *\/ */
3597: /* /\* [Tinvresult[nres][V1] is its value in the resultline nres *\/ */
3598: /* cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvar[k1]]*cov[2]; */
3599: /* printf("DhPxij Dummy with age k1=%d Tvar[%d]=%d TinvDoQresult[nres=%d][%d]=%.f age=%.2f,cov[2+%d+%d]=%.3f\n",k1,k1,Tvar[k1],nres,TinvDoQresult[nres][Tvar[k1]],cov[2],nagesqr,k1,cov[2+nagesqr+k1]); */
3600: /* printf("hpxij new Dummy with age product precov[nres=%d][k1=%d]=%.4f * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
3601:
3602: /* /\* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; *\/ */
3603: /* /\* for (k=1; k<=cptcovage;k++){ /\\* For product with age V1+V1*age +V4 +age*V3 *\\/ *\/ */
3604: /* /\* 1+2 Tage[1]=2 TVar[2]=1 Dummy[2]=2, Tage[2]=4 TVar[4]=3 Dummy[4]=3 quant*\/ */
3605: /* /\* *\/ */
1.330 brouard 3606: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
3607: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
3608: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
1.332 brouard 3609: /* /\*cptcovage=2 1 2 *\/ */
3610: /* /\*Tage[k]= 5 8 *\/ */
3611: /* }else if( Dummy[k1]==3 ){ /\* For quant with age product *\/ */
3612: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
3613: /* printf("QhPxij Quant with age k1=%d resultmodel[nres][%d]=%d,Tqresult[%d][%d]=%f\n",k1,k1,resultmodel[nres][k1],nres,resultmodel[nres][k1],Tqresult[nres][resultmodel[nres][k1]]); */
3614: /* printf("hpxij new Quanti with age product precov[nres=%d][k1=%d] * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
3615: /* /\* if(Dummy[Tage[k]]== 2){ /\\* dummy with age *\\/ *\/ */
3616: /* /\* /\\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\\* dummy with age *\\\/ *\\/ *\/ */
3617: /* /\* /\\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\\/ *\/ */
3618: /* /\* /\\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\\/ *\/ */
3619: /* /\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\/ */
3620: /* /\* printf("hPxij Age combi=%d k=%d cptcovage=%d Tage[%d]=%d Tvar[Tage[%d]]=V%d nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[Tvar[Tage[k]]]])]=%d nres=%d\n",ij,k,cptcovage,k,Tage[k],k,Tvar[Tage[k]], nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[Tvar[Tage[k]]])],nres); *\/ */
3621: /* /\* } else if(Dummy[Tage[k]]== 3){ /\\* quantitative with age *\\/ *\/ */
3622: /* /\* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; *\/ */
3623: /* /\* } *\/ */
3624: /* /\* 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]); *\/ */
3625: /* }else if(Typevar[k1]==2 ){ /\* For product (not with age) *\/ */
3626: /* /\* for (k=1; k<=cptcovprod;k++){ /\\* For product without age *\\/ *\/ */
3627: /* /\* /\\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\\/ *\/ */
3628: /* /\* /\\* k 1 2 3 4 5 6 7 8 9 *\\/ *\/ */
3629: /* /\* /\\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\\/ *\/ */
3630: /* /\* /\\*cptcovprod=1 1 2 *\\/ *\/ */
3631: /* /\* /\\*Tprod[]= 4 7 *\\/ *\/ */
3632: /* /\* /\\*Tvard[][1] 4 1 *\\/ *\/ */
3633: /* /\* /\\*Tvard[][2] 3 2 *\\/ *\/ */
1.330 brouard 3634:
1.332 brouard 3635: /* /\* printf("hPxij Prod ij=%d k=%d Tprod[%d]=%d Tvard[%d][1]=V%d, Tvard[%d][2]=V%d nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])]=%d nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][1])]=%d\n",ij,k,k,Tprod[k], k,Tvard[k][1], k,Tvard[k][2],nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])],nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]); *\/ */
3636: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3637: /* cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]]; */
3638: /* printf("hPxij Prod ij=%d k1=%d cov[2+%d+%d]=%.5f Tvard[%d][1]=V%d * Tvard[%d][2]=V%d ; TinvDoQresult[nres][Tvardk[k1][1]]=%.4f * TinvDoQresult[nres][Tvardk[k1][1]]=%.4f\n",ij,k1,nagesqr,k1,cov[2+nagesqr+k1],k1,Tvardk[k1][1], k1,Tvardk[k1][2], TinvDoQresult[nres][Tvardk[k1][1]], TinvDoQresult[nres][Tvardk[k1][2]]); */
3639: /* printf("hpxij new Product no age product precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3640:
3641: /* /\* if(Dummy[Tvardk[k1][1]]==0){ *\/ */
3642: /* /\* if(Dummy[Tvardk[k1][2]]==0){ /\\* Product of dummies *\\/ *\/ */
3643: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3644: /* /\* cov[2+nagesqr+k1]=Tinvresult[nres][Tvardk[k1][1]] * Tinvresult[nres][Tvardk[k1][2]]; *\/ */
3645: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,TnsdVar[Tvard[k][1]])] * nbcode[Tvard[k][2]][codtabm(ij,TnsdVar[Tvard[k][2]])]; *\/ */
3646: /* /\* }else{ /\\* Product of dummy by quantitative *\\/ *\/ */
3647: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,TnsdVar[Tvard[k][1]])] * Tqresult[nres][k]; *\/ */
3648: /* /\* cov[2+nagesqr+k1]=Tresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]]; *\/ */
3649: /* /\* } *\/ */
3650: /* /\* }else{ /\\* Product of quantitative by...*\\/ *\/ */
3651: /* /\* if(Dummy[Tvard[k][2]]==0){ /\\* quant by dummy *\\/ *\/ */
3652: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][Tvard[k][1]]; *\\/ *\/ */
3653: /* /\* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; *\/ */
3654: /* /\* }else{ /\\* Product of two quant *\\/ *\/ */
3655: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\\/ *\/ */
3656: /* /\* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; *\/ */
3657: /* /\* } *\/ */
3658: /* /\* }/\\*end of products quantitative *\\/ *\/ */
3659: /* }/\*end of products *\/ */
3660: /* } /\* End of loop on model equation *\/ */
1.235 brouard 3661: /* for (k=1; k<=cptcovn;k++) */
3662: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3663: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3664: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3665: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3666: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3667:
3668:
1.126 brouard 3669: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3670: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.319 brouard 3671: /* right multiplication of oldm by the current matrix */
1.126 brouard 3672: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3673: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3674: /* if((int)age == 70){ */
3675: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3676: /* for(i=1; i<=nlstate+ndeath; i++) { */
3677: /* printf("%d pmmij ",i); */
3678: /* for(j=1;j<=nlstate+ndeath;j++) { */
3679: /* printf("%f ",pmmij[i][j]); */
3680: /* } */
3681: /* printf(" oldm "); */
3682: /* for(j=1;j<=nlstate+ndeath;j++) { */
3683: /* printf("%f ",oldm[i][j]); */
3684: /* } */
3685: /* printf("\n"); */
3686: /* } */
3687: /* } */
1.126 brouard 3688: savm=oldm;
3689: oldm=newm;
3690: }
3691: for(i=1; i<=nlstate+ndeath; i++)
3692: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 3693: po[i][j][h]=newm[i][j];
3694: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3695: }
1.128 brouard 3696: /*printf("h=%d ",h);*/
1.126 brouard 3697: } /* end h */
1.267 brouard 3698: /* printf("\n H=%d \n",h); */
1.126 brouard 3699: return po;
3700: }
3701:
1.217 brouard 3702: /************* Higher Back Matrix Product ***************/
1.218 brouard 3703: /* 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 3704: 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 3705: {
1.332 brouard 3706: /* For dummy covariates given in each resultline (for historical, computes the corresponding combination ij),
3707: computes the transition matrix starting at age 'age' over
1.217 brouard 3708: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3709: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3710: nhstepm*hstepm matrices.
3711: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3712: (typically every 2 years instead of every month which is too big
1.217 brouard 3713: for the memory).
1.218 brouard 3714: Model is determined by parameters x and covariates have to be
1.266 brouard 3715: included manually here. Then we use a call to bmij(x and cov)
3716: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 3717: */
1.217 brouard 3718:
1.332 brouard 3719: int i, j, d, h, k, k1;
1.266 brouard 3720: double **out, cov[NCOVMAX+1], **bmij();
3721: double **newm, ***newmm;
1.217 brouard 3722: double agexact;
3723: double agebegin, ageend;
1.222 brouard 3724: double **oldm, **savm;
1.217 brouard 3725:
1.266 brouard 3726: newmm=po; /* To be saved */
3727: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 3728: /* Hstepm could be zero and should return the unit matrix */
3729: for (i=1;i<=nlstate+ndeath;i++)
3730: for (j=1;j<=nlstate+ndeath;j++){
3731: oldm[i][j]=(i==j ? 1.0 : 0.0);
3732: po[i][j][0]=(i==j ? 1.0 : 0.0);
3733: }
3734: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3735: for(h=1; h <=nhstepm; h++){
3736: for(d=1; d <=hstepm; d++){
3737: newm=savm;
3738: /* Covariates have to be included here again */
3739: cov[1]=1.;
1.271 brouard 3740: agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 3741: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
1.318 brouard 3742: /* Debug */
3743: /* printf("hBxij age=%lf, agexact=%lf\n", age, agexact); */
1.217 brouard 3744: cov[2]=agexact;
1.332 brouard 3745: if(nagesqr==1){
1.222 brouard 3746: cov[3]= agexact*agexact;
1.332 brouard 3747: }
3748: /** New code */
3749: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
3750: if(Typevar[k1]==1){ /* A product with age */
3751: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.325 brouard 3752: }else{
1.332 brouard 3753: cov[2+nagesqr+k1]=precov[nres][k1];
1.325 brouard 3754: }
1.332 brouard 3755: }/* End of loop on model equation */
3756: /** End of new code */
3757: /** This was old code */
3758: /* for (k=1; k<=nsd;k++){ /\* For single dummy covariates only *\//\* cptcovn error *\/ */
3759: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
3760: /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
3761: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])];/\* Bug valgrind *\/ */
3762: /* /\* 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)); *\/ */
3763: /* } */
3764: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
3765: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3766: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
3767: /* /\* 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]); *\/ */
3768: /* } */
3769: /* for (k=1; k<=cptcovage;k++){ /\* Should start at cptcovn+1 *\//\* For product with age *\/ */
3770: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age error!!!*\\/ *\/ */
3771: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
3772: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3773: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
3774: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3775: /* } */
3776: /* /\* 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]); *\/ */
3777: /* } */
3778: /* for (k=1; k<=cptcovprod;k++){ /\* Useless because included in cptcovn *\/ */
3779: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])]*nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3780: /* if(Dummy[Tvard[k][1]]==0){ */
3781: /* if(Dummy[Tvard[k][2]]==0){ */
3782: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][1])]; */
3783: /* }else{ */
3784: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3785: /* } */
3786: /* }else{ */
3787: /* if(Dummy[Tvard[k][2]]==0){ */
3788: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3789: /* }else{ */
3790: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3791: /* } */
3792: /* } */
3793: /* } */
3794: /* /\*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*\/ */
3795: /* /\*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*\/ */
3796: /** End of old code */
3797:
1.218 brouard 3798: /* Careful transposed matrix */
1.266 brouard 3799: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 3800: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3801: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3802: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.325 brouard 3803: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);/* Bug valgrind */
1.217 brouard 3804: /* if((int)age == 70){ */
3805: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3806: /* for(i=1; i<=nlstate+ndeath; i++) { */
3807: /* printf("%d pmmij ",i); */
3808: /* for(j=1;j<=nlstate+ndeath;j++) { */
3809: /* printf("%f ",pmmij[i][j]); */
3810: /* } */
3811: /* printf(" oldm "); */
3812: /* for(j=1;j<=nlstate+ndeath;j++) { */
3813: /* printf("%f ",oldm[i][j]); */
3814: /* } */
3815: /* printf("\n"); */
3816: /* } */
3817: /* } */
3818: savm=oldm;
3819: oldm=newm;
3820: }
3821: for(i=1; i<=nlstate+ndeath; i++)
3822: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 3823: po[i][j][h]=newm[i][j];
1.268 brouard 3824: /* if(h==nhstepm) */
3825: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 3826: }
1.268 brouard 3827: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 3828: } /* end h */
1.268 brouard 3829: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 3830: return po;
3831: }
3832:
3833:
1.162 brouard 3834: #ifdef NLOPT
3835: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
3836: double fret;
3837: double *xt;
3838: int j;
3839: myfunc_data *d2 = (myfunc_data *) pd;
3840: /* xt = (p1-1); */
3841: xt=vector(1,n);
3842: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
3843:
3844: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
3845: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
3846: printf("Function = %.12lf ",fret);
3847: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
3848: printf("\n");
3849: free_vector(xt,1,n);
3850: return fret;
3851: }
3852: #endif
1.126 brouard 3853:
3854: /*************** log-likelihood *************/
3855: double func( double *x)
3856: {
1.336 brouard 3857: int i, ii, j, k, mi, d, kk, kf=0;
1.226 brouard 3858: int ioffset=0;
3859: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
3860: double **out;
3861: double lli; /* Individual log likelihood */
3862: int s1, s2;
1.228 brouard 3863: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
1.336 brouard 3864:
1.226 brouard 3865: double bbh, survp;
3866: double agexact;
1.336 brouard 3867: double agebegin, ageend;
1.226 brouard 3868: /*extern weight */
3869: /* We are differentiating ll according to initial status */
3870: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3871: /*for(i=1;i<imx;i++)
3872: printf(" %d\n",s[4][i]);
3873: */
1.162 brouard 3874:
1.226 brouard 3875: ++countcallfunc;
1.162 brouard 3876:
1.226 brouard 3877: cov[1]=1.;
1.126 brouard 3878:
1.226 brouard 3879: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3880: ioffset=0;
1.226 brouard 3881: if(mle==1){
3882: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3883: /* Computes the values of the ncovmodel covariates of the model
3884: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
3885: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
3886: to be observed in j being in i according to the model.
3887: */
1.243 brouard 3888: ioffset=2+nagesqr ;
1.233 brouard 3889: /* Fixed */
1.336 brouard 3890: for (kf=1; kf<=ncovf;kf++){ /* For each fixed covariate dummu or quant or prod */
1.319 brouard 3891: /* # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi */
3892: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
3893: /* TvarF[1]=Tvar[6]=2, TvarF[2]=Tvar[7]=7, TvarF[3]=Tvar[9]=1 ID of fixed covariates or product V2, V1*V2, V1 */
1.320 brouard 3894: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.336 brouard 3895: cov[ioffset+TvarFind[kf]]=covar[Tvar[TvarFind[kf]]][i];/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, only V1 is fixed (TvarFind[1]=6)*/
1.319 brouard 3896: /* V1*V2 (7) TvarFind[2]=7, TvarFind[3]=9 */
1.234 brouard 3897: }
1.226 brouard 3898: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
1.319 brouard 3899: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
1.226 brouard 3900: has been calculated etc */
3901: /* For an individual i, wav[i] gives the number of effective waves */
3902: /* We compute the contribution to Likelihood of each effective transition
3903: mw[mi][i] is real wave of the mi th effectve wave */
3904: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
3905: s2=s[mw[mi+1][i]][i];
3906: And the iv th varying covariate is the cotvar[mw[mi+1][i]][iv][i]
3907: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
3908: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
3909: */
1.336 brouard 3910: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
3911: /* Wave varying (but not age varying) */
1.319 brouard 3912: for(k=1; k <= ncovv ; k++){ /* Varying covariates in the model (single and product but no age )"V5+V4+V3+V4*V3+V5*age+V1*age+V1" +TvarVind 1,2,3,4(V4*V3) Tvar[1]@7{5, 4, 3, 6, 5, 1, 1 ; 6 because the created covar is after V5 and is 6, minus 1+1, 3,2,1,4 positions in cotvar*/
3913: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; but where is the crossproduct? */
1.242 brouard 3914: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
1.234 brouard 3915: }
3916: for (ii=1;ii<=nlstate+ndeath;ii++)
3917: for (j=1;j<=nlstate+ndeath;j++){
3918: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3919: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3920: }
1.336 brouard 3921:
3922: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
3923: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
1.234 brouard 3924: for(d=0; d<dh[mi][i]; d++){
3925: newm=savm;
3926: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3927: cov[2]=agexact;
3928: if(nagesqr==1)
3929: cov[3]= agexact*agexact; /* Should be changed here */
3930: for (kk=1; kk<=cptcovage;kk++) {
1.318 brouard 3931: if(!FixedV[Tvar[Tage[kk]]])
3932: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
3933: else
3934: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
1.234 brouard 3935: }
3936: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3937: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3938: savm=oldm;
3939: oldm=newm;
3940: } /* end mult */
3941:
3942: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
3943: /* But now since version 0.9 we anticipate for bias at large stepm.
3944: * If stepm is larger than one month (smallest stepm) and if the exact delay
3945: * (in months) between two waves is not a multiple of stepm, we rounded to
3946: * the nearest (and in case of equal distance, to the lowest) interval but now
3947: * we keep into memory the bias bh[mi][i] and also the previous matrix product
3948: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
3949: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 3950: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
3951: * -stepm/2 to stepm/2 .
3952: * For stepm=1 the results are the same as for previous versions of Imach.
3953: * For stepm > 1 the results are less biased than in previous versions.
3954: */
1.234 brouard 3955: s1=s[mw[mi][i]][i];
3956: s2=s[mw[mi+1][i]][i];
3957: bbh=(double)bh[mi][i]/(double)stepm;
3958: /* bias bh is positive if real duration
3959: * is higher than the multiple of stepm and negative otherwise.
3960: */
3961: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
3962: if( s2 > nlstate){
3963: /* i.e. if s2 is a death state and if the date of death is known
3964: then the contribution to the likelihood is the probability to
3965: die between last step unit time and current step unit time,
3966: which is also equal to probability to die before dh
3967: minus probability to die before dh-stepm .
3968: In version up to 0.92 likelihood was computed
3969: as if date of death was unknown. Death was treated as any other
3970: health state: the date of the interview describes the actual state
3971: and not the date of a change in health state. The former idea was
3972: to consider that at each interview the state was recorded
3973: (healthy, disable or death) and IMaCh was corrected; but when we
3974: introduced the exact date of death then we should have modified
3975: the contribution of an exact death to the likelihood. This new
3976: contribution is smaller and very dependent of the step unit
3977: stepm. It is no more the probability to die between last interview
3978: and month of death but the probability to survive from last
3979: interview up to one month before death multiplied by the
3980: probability to die within a month. Thanks to Chris
3981: Jackson for correcting this bug. Former versions increased
3982: mortality artificially. The bad side is that we add another loop
3983: which slows down the processing. The difference can be up to 10%
3984: lower mortality.
3985: */
3986: /* If, at the beginning of the maximization mostly, the
3987: cumulative probability or probability to be dead is
3988: constant (ie = 1) over time d, the difference is equal to
3989: 0. out[s1][3] = savm[s1][3]: probability, being at state
3990: s1 at precedent wave, to be dead a month before current
3991: wave is equal to probability, being at state s1 at
3992: precedent wave, to be dead at mont of the current
3993: wave. Then the observed probability (that this person died)
3994: is null according to current estimated parameter. In fact,
3995: it should be very low but not zero otherwise the log go to
3996: infinity.
3997: */
1.183 brouard 3998: /* #ifdef INFINITYORIGINAL */
3999: /* lli=log(out[s1][s2] - savm[s1][s2]); */
4000: /* #else */
4001: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
4002: /* lli=log(mytinydouble); */
4003: /* else */
4004: /* lli=log(out[s1][s2] - savm[s1][s2]); */
4005: /* #endif */
1.226 brouard 4006: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 4007:
1.226 brouard 4008: } else if ( s2==-1 ) { /* alive */
4009: for (j=1,survp=0. ; j<=nlstate; j++)
4010: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
4011: /*survp += out[s1][j]; */
4012: lli= log(survp);
4013: }
1.336 brouard 4014: /* else if (s2==-4) { */
4015: /* for (j=3,survp=0. ; j<=nlstate; j++) */
4016: /* survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; */
4017: /* lli= log(survp); */
4018: /* } */
4019: /* else if (s2==-5) { */
4020: /* for (j=1,survp=0. ; j<=2; j++) */
4021: /* survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; */
4022: /* lli= log(survp); */
4023: /* } */
1.226 brouard 4024: else{
4025: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
4026: /* 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 */
4027: }
4028: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
4029: /*if(lli ==000.0)*/
4030: /*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); */
4031: ipmx +=1;
4032: sw += weight[i];
4033: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4034: /* if (lli < log(mytinydouble)){ */
4035: /* 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); */
4036: /* 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]); */
4037: /* } */
4038: } /* end of wave */
4039: } /* end of individual */
4040: } else if(mle==2){
4041: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.319 brouard 4042: ioffset=2+nagesqr ;
4043: for (k=1; k<=ncovf;k++)
4044: cov[ioffset+TvarFind[k]]=covar[Tvar[TvarFind[k]]][i];
1.226 brouard 4045: for(mi=1; mi<= wav[i]-1; mi++){
1.319 brouard 4046: for(k=1; k <= ncovv ; k++){
4047: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
4048: }
1.226 brouard 4049: for (ii=1;ii<=nlstate+ndeath;ii++)
4050: for (j=1;j<=nlstate+ndeath;j++){
4051: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4052: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4053: }
4054: for(d=0; d<=dh[mi][i]; d++){
4055: newm=savm;
4056: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4057: cov[2]=agexact;
4058: if(nagesqr==1)
4059: cov[3]= agexact*agexact;
4060: for (kk=1; kk<=cptcovage;kk++) {
4061: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4062: }
4063: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4064: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4065: savm=oldm;
4066: oldm=newm;
4067: } /* end mult */
4068:
4069: s1=s[mw[mi][i]][i];
4070: s2=s[mw[mi+1][i]][i];
4071: bbh=(double)bh[mi][i]/(double)stepm;
4072: 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 */
4073: ipmx +=1;
4074: sw += weight[i];
4075: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4076: } /* end of wave */
4077: } /* end of individual */
4078: } else if(mle==3){ /* exponential inter-extrapolation */
4079: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4080: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4081: for(mi=1; mi<= wav[i]-1; mi++){
4082: for (ii=1;ii<=nlstate+ndeath;ii++)
4083: for (j=1;j<=nlstate+ndeath;j++){
4084: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4085: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4086: }
4087: for(d=0; d<dh[mi][i]; d++){
4088: newm=savm;
4089: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4090: cov[2]=agexact;
4091: if(nagesqr==1)
4092: cov[3]= agexact*agexact;
4093: for (kk=1; kk<=cptcovage;kk++) {
4094: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4095: }
4096: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4097: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4098: savm=oldm;
4099: oldm=newm;
4100: } /* end mult */
4101:
4102: s1=s[mw[mi][i]][i];
4103: s2=s[mw[mi+1][i]][i];
4104: bbh=(double)bh[mi][i]/(double)stepm;
4105: 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 */
4106: ipmx +=1;
4107: sw += weight[i];
4108: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4109: } /* end of wave */
4110: } /* end of individual */
4111: }else if (mle==4){ /* ml=4 no inter-extrapolation */
4112: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4113: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4114: for(mi=1; mi<= wav[i]-1; mi++){
4115: for (ii=1;ii<=nlstate+ndeath;ii++)
4116: for (j=1;j<=nlstate+ndeath;j++){
4117: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4118: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4119: }
4120: for(d=0; d<dh[mi][i]; d++){
4121: newm=savm;
4122: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4123: cov[2]=agexact;
4124: if(nagesqr==1)
4125: cov[3]= agexact*agexact;
4126: for (kk=1; kk<=cptcovage;kk++) {
4127: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4128: }
1.126 brouard 4129:
1.226 brouard 4130: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4131: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4132: savm=oldm;
4133: oldm=newm;
4134: } /* end mult */
4135:
4136: s1=s[mw[mi][i]][i];
4137: s2=s[mw[mi+1][i]][i];
4138: if( s2 > nlstate){
4139: lli=log(out[s1][s2] - savm[s1][s2]);
4140: } else if ( s2==-1 ) { /* alive */
4141: for (j=1,survp=0. ; j<=nlstate; j++)
4142: survp += out[s1][j];
4143: lli= log(survp);
4144: }else{
4145: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
4146: }
4147: ipmx +=1;
4148: sw += weight[i];
4149: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.126 brouard 4150: /* 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 4151: } /* end of wave */
4152: } /* end of individual */
4153: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
4154: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4155: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4156: for(mi=1; mi<= wav[i]-1; mi++){
4157: for (ii=1;ii<=nlstate+ndeath;ii++)
4158: for (j=1;j<=nlstate+ndeath;j++){
4159: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4160: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4161: }
4162: for(d=0; d<dh[mi][i]; d++){
4163: newm=savm;
4164: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4165: cov[2]=agexact;
4166: if(nagesqr==1)
4167: cov[3]= agexact*agexact;
4168: for (kk=1; kk<=cptcovage;kk++) {
4169: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4170: }
1.126 brouard 4171:
1.226 brouard 4172: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4173: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4174: savm=oldm;
4175: oldm=newm;
4176: } /* end mult */
4177:
4178: s1=s[mw[mi][i]][i];
4179: s2=s[mw[mi+1][i]][i];
4180: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
4181: ipmx +=1;
4182: sw += weight[i];
4183: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4184: /*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]);*/
4185: } /* end of wave */
4186: } /* end of individual */
4187: } /* End of if */
4188: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
4189: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
4190: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
4191: return -l;
1.126 brouard 4192: }
4193:
4194: /*************** log-likelihood *************/
4195: double funcone( double *x)
4196: {
1.228 brouard 4197: /* Same as func but slower because of a lot of printf and if */
1.335 brouard 4198: int i, ii, j, k, mi, d, kk, kf=0;
1.228 brouard 4199: int ioffset=0;
1.131 brouard 4200: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 4201: double **out;
4202: double lli; /* Individual log likelihood */
4203: double llt;
4204: int s1, s2;
1.228 brouard 4205: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
4206:
1.126 brouard 4207: double bbh, survp;
1.187 brouard 4208: double agexact;
1.214 brouard 4209: double agebegin, ageend;
1.126 brouard 4210: /*extern weight */
4211: /* We are differentiating ll according to initial status */
4212: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
4213: /*for(i=1;i<imx;i++)
4214: printf(" %d\n",s[4][i]);
4215: */
4216: cov[1]=1.;
4217:
4218: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 4219: ioffset=0;
4220: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.336 brouard 4221: /* Computes the values of the ncovmodel covariates of the model
4222: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
4223: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
4224: to be observed in j being in i according to the model.
4225: */
1.243 brouard 4226: /* ioffset=2+nagesqr+cptcovage; */
4227: ioffset=2+nagesqr;
1.232 brouard 4228: /* Fixed */
1.224 brouard 4229: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 4230: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
1.335 brouard 4231: for (kf=1; kf<=ncovf;kf++){ /* Simple and product fixed covariates without age* products *//* Missing values are set to -1 but should be dropped */
4232: cov[ioffset+TvarFind[kf]]=covar[Tvar[TvarFind[kf]]][i];/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, only V1 is fixed (k=6)*/
1.232 brouard 4233: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
4234: /* cov[2+6]=covar[Tvar[6]][i]; */
4235: /* cov[2+6]=covar[2][i]; V2 */
4236: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
4237: /* cov[2+7]=covar[Tvar[7]][i]; */
4238: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
4239: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
4240: /* cov[2+9]=covar[Tvar[9]][i]; */
4241: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 4242: }
1.336 brouard 4243: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
4244: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
4245: has been calculated etc */
4246: /* For an individual i, wav[i] gives the number of effective waves */
4247: /* We compute the contribution to Likelihood of each effective transition
4248: mw[mi][i] is real wave of the mi th effectve wave */
4249: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
4250: s2=s[mw[mi+1][i]][i];
4251: And the iv th varying covariate is the cotvar[mw[mi+1][i]][iv][i]
4252: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
4253: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
4254: */
4255: /* This part may be useless now because everythin should be in covar */
1.232 brouard 4256: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
4257: /* 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?)*\/ */
4258: /* } */
1.231 brouard 4259: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
4260: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
4261: /* } */
1.225 brouard 4262:
1.233 brouard 4263:
4264: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.232 brouard 4265: /* Wave varying (but not age varying) */
4266: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 4267: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
4268: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
4269: }
1.232 brouard 4270: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates (single??)*\/ */
1.242 brouard 4271: /* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; /\* Counting the # varying covariate from 1 to ntveff *\/ */
4272: /* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; */
4273: /* k=ioffset-2-nagesqr-cptcovage+itv; /\* position in simple model *\/ */
4274: /* cov[ioffset+itv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; */
4275: /* 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 4276: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 4277: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
4278: /* /\* 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]); *\/ */
4279: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 4280: /* } */
1.126 brouard 4281: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 4282: for (j=1;j<=nlstate+ndeath;j++){
4283: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4284: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4285: }
1.214 brouard 4286:
4287: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
4288: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
4289: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 4290: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 4291: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
4292: and mw[mi+1][i]. dh depends on stepm.*/
4293: newm=savm;
1.247 brouard 4294: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 4295: cov[2]=agexact;
4296: if(nagesqr==1)
4297: cov[3]= agexact*agexact;
4298: for (kk=1; kk<=cptcovage;kk++) {
4299: if(!FixedV[Tvar[Tage[kk]]])
4300: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4301: else
4302: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
4303: }
4304: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
4305: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
4306: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4307: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4308: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
4309: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
4310: savm=oldm;
4311: oldm=newm;
1.126 brouard 4312: } /* end mult */
1.336 brouard 4313: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
4314: /* But now since version 0.9 we anticipate for bias at large stepm.
4315: * If stepm is larger than one month (smallest stepm) and if the exact delay
4316: * (in months) between two waves is not a multiple of stepm, we rounded to
4317: * the nearest (and in case of equal distance, to the lowest) interval but now
4318: * we keep into memory the bias bh[mi][i] and also the previous matrix product
4319: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
4320: * probability in order to take into account the bias as a fraction of the way
4321: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
4322: * -stepm/2 to stepm/2 .
4323: * For stepm=1 the results are the same as for previous versions of Imach.
4324: * For stepm > 1 the results are less biased than in previous versions.
4325: */
1.126 brouard 4326: s1=s[mw[mi][i]][i];
4327: s2=s[mw[mi+1][i]][i];
1.217 brouard 4328: /* if(s2==-1){ */
1.268 brouard 4329: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 4330: /* /\* exit(1); *\/ */
4331: /* } */
1.126 brouard 4332: bbh=(double)bh[mi][i]/(double)stepm;
4333: /* bias is positive if real duration
4334: * is higher than the multiple of stepm and negative otherwise.
4335: */
4336: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 4337: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 4338: } else if ( s2==-1 ) { /* alive */
1.242 brouard 4339: for (j=1,survp=0. ; j<=nlstate; j++)
4340: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
4341: lli= log(survp);
1.126 brouard 4342: }else if (mle==1){
1.242 brouard 4343: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 4344: } else if(mle==2){
1.242 brouard 4345: 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 4346: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 4347: 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 4348: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 4349: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 4350: } else{ /* mle=0 back to 1 */
1.242 brouard 4351: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
4352: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 4353: } /* End of if */
4354: ipmx +=1;
4355: sw += weight[i];
4356: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.335 brouard 4357: /* printf("Funcone 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],(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2])); */
1.126 brouard 4358: if(globpr){
1.246 brouard 4359: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 4360: %11.6f %11.6f %11.6f ", \
1.242 brouard 4361: 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 4362: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.335 brouard 4363: /* printf("%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\ */
4364: /* %11.6f %11.6f %11.6f ", \ */
4365: /* num[i], agebegin, ageend, i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],weight[i]*gipmx/gsw, */
4366: /* 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2])); */
1.242 brouard 4367: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
4368: llt +=ll[k]*gipmx/gsw;
4369: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
1.335 brouard 4370: /* printf(" %10.6f",-ll[k]*gipmx/gsw); */
1.242 brouard 4371: }
4372: fprintf(ficresilk," %10.6f\n", -llt);
1.335 brouard 4373: /* printf(" %10.6f\n", -llt); */
1.126 brouard 4374: }
1.335 brouard 4375: } /* end of wave */
4376: } /* end of individual */
4377: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
1.232 brouard 4378: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
1.335 brouard 4379: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
4380: if(globpr==0){ /* First time we count the contributions and weights */
4381: gipmx=ipmx;
4382: gsw=sw;
4383: }
1.232 brouard 4384: return -l;
1.126 brouard 4385: }
4386:
4387:
4388: /*************** function likelione ***********/
1.292 brouard 4389: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*func)(double []))
1.126 brouard 4390: {
4391: /* This routine should help understanding what is done with
4392: the selection of individuals/waves and
4393: to check the exact contribution to the likelihood.
4394: Plotting could be done.
4395: */
4396: int k;
4397:
4398: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 4399: strcpy(fileresilk,"ILK_");
1.202 brouard 4400: strcat(fileresilk,fileresu);
1.126 brouard 4401: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
4402: printf("Problem with resultfile: %s\n", fileresilk);
4403: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
4404: }
1.214 brouard 4405: 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");
4406: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 4407: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
4408: for(k=1; k<=nlstate; k++)
4409: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
4410: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total)\n");
4411: }
4412:
1.292 brouard 4413: *fretone=(*func)(p);
1.126 brouard 4414: if(*globpri !=0){
4415: fclose(ficresilk);
1.205 brouard 4416: if (mle ==0)
4417: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
4418: else if(mle >=1)
4419: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
4420: 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 4421: fprintf(fichtm,"\n<br>Equation of the model: <b>model=1+age+%s</b><br>\n",model);
1.208 brouard 4422:
4423: for (k=1; k<= nlstate ; k++) {
1.211 brouard 4424: 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 4425: <img src=\"%s-p%dj.png\">",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
4426: }
1.207 brouard 4427: 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 4428: <img src=\"%s-ori.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 4429: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.204 brouard 4430: <img src=\"%s-dest.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 4431: fflush(fichtm);
1.205 brouard 4432: }
1.126 brouard 4433: return;
4434: }
4435:
4436:
4437: /*********** Maximum Likelihood Estimation ***************/
4438:
4439: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
4440: {
1.319 brouard 4441: int i,j,k, jk, jkk=0, iter=0;
1.126 brouard 4442: double **xi;
4443: double fret;
4444: double fretone; /* Only one call to likelihood */
4445: /* char filerespow[FILENAMELENGTH];*/
1.162 brouard 4446:
4447: #ifdef NLOPT
4448: int creturn;
4449: nlopt_opt opt;
4450: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
4451: double *lb;
4452: double minf; /* the minimum objective value, upon return */
4453: double * p1; /* Shifted parameters from 0 instead of 1 */
4454: myfunc_data dinst, *d = &dinst;
4455: #endif
4456:
4457:
1.126 brouard 4458: xi=matrix(1,npar,1,npar);
4459: for (i=1;i<=npar;i++)
4460: for (j=1;j<=npar;j++)
4461: xi[i][j]=(i==j ? 1.0 : 0.0);
4462: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 4463: strcpy(filerespow,"POW_");
1.126 brouard 4464: strcat(filerespow,fileres);
4465: if((ficrespow=fopen(filerespow,"w"))==NULL) {
4466: printf("Problem with resultfile: %s\n", filerespow);
4467: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
4468: }
4469: fprintf(ficrespow,"# Powell\n# iter -2*LL");
4470: for (i=1;i<=nlstate;i++)
4471: for(j=1;j<=nlstate+ndeath;j++)
4472: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
4473: fprintf(ficrespow,"\n");
1.162 brouard 4474: #ifdef POWELL
1.319 brouard 4475: #ifdef LINMINORIGINAL
4476: #else /* LINMINORIGINAL */
4477:
4478: flatdir=ivector(1,npar);
4479: for (j=1;j<=npar;j++) flatdir[j]=0;
4480: #endif /*LINMINORIGINAL */
4481:
4482: #ifdef FLATSUP
4483: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
4484: /* reorganizing p by suppressing flat directions */
4485: for(i=1, jk=1; i <=nlstate; i++){
4486: for(k=1; k <=(nlstate+ndeath); k++){
4487: if (k != i) {
4488: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
4489: if(flatdir[jk]==1){
4490: printf(" To be skipped %d%d flatdir[%d]=%d ",i,k,jk, flatdir[jk]);
4491: }
4492: for(j=1; j <=ncovmodel; j++){
4493: printf("%12.7f ",p[jk]);
4494: jk++;
4495: }
4496: printf("\n");
4497: }
4498: }
4499: }
4500: /* skipping */
4501: /* for(i=1, jk=1, jkk=1;(flatdir[jk]==0)&& (i <=nlstate); i++){ */
4502: for(i=1, jk=1, jkk=1;i <=nlstate; i++){
4503: for(k=1; k <=(nlstate+ndeath); k++){
4504: if (k != i) {
4505: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
4506: if(flatdir[jk]==1){
4507: printf(" To be skipped %d%d flatdir[%d]=%d jk=%d p[%d] ",i,k,jk, flatdir[jk],jk, jk);
4508: for(j=1; j <=ncovmodel; jk++,j++){
4509: printf(" p[%d]=%12.7f",jk, p[jk]);
4510: /*q[jjk]=p[jk];*/
4511: }
4512: }else{
4513: printf(" To be kept %d%d flatdir[%d]=%d jk=%d q[%d]=p[%d] ",i,k,jk, flatdir[jk],jk, jkk, jk);
4514: for(j=1; j <=ncovmodel; jk++,jkk++,j++){
4515: printf(" p[%d]=%12.7f=q[%d]",jk, p[jk],jkk);
4516: /*q[jjk]=p[jk];*/
4517: }
4518: }
4519: printf("\n");
4520: }
4521: fflush(stdout);
4522: }
4523: }
4524: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
4525: #else /* FLATSUP */
1.126 brouard 4526: powell(p,xi,npar,ftol,&iter,&fret,func);
1.319 brouard 4527: #endif /* FLATSUP */
4528:
4529: #ifdef LINMINORIGINAL
4530: #else
4531: free_ivector(flatdir,1,npar);
4532: #endif /* LINMINORIGINAL*/
4533: #endif /* POWELL */
1.126 brouard 4534:
1.162 brouard 4535: #ifdef NLOPT
4536: #ifdef NEWUOA
4537: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
4538: #else
4539: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
4540: #endif
4541: lb=vector(0,npar-1);
4542: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
4543: nlopt_set_lower_bounds(opt, lb);
4544: nlopt_set_initial_step1(opt, 0.1);
4545:
4546: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
4547: d->function = func;
4548: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
4549: nlopt_set_min_objective(opt, myfunc, d);
4550: nlopt_set_xtol_rel(opt, ftol);
4551: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
4552: printf("nlopt failed! %d\n",creturn);
4553: }
4554: else {
4555: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
4556: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
4557: iter=1; /* not equal */
4558: }
4559: nlopt_destroy(opt);
4560: #endif
1.319 brouard 4561: #ifdef FLATSUP
4562: /* npared = npar -flatd/ncovmodel; */
4563: /* xired= matrix(1,npared,1,npared); */
4564: /* paramred= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel); */
4565: /* powell(pred,xired,npared,ftol,&iter,&fret,flatdir,func); */
4566: /* free_matrix(xire,1,npared,1,npared); */
4567: #else /* FLATSUP */
4568: #endif /* FLATSUP */
1.126 brouard 4569: free_matrix(xi,1,npar,1,npar);
4570: fclose(ficrespow);
1.203 brouard 4571: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
4572: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 4573: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 4574:
4575: }
4576:
4577: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 4578: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 4579: {
4580: double **a,**y,*x,pd;
1.203 brouard 4581: /* double **hess; */
1.164 brouard 4582: int i, j;
1.126 brouard 4583: int *indx;
4584:
4585: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 4586: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 4587: void lubksb(double **a, int npar, int *indx, double b[]) ;
4588: void ludcmp(double **a, int npar, int *indx, double *d) ;
4589: double gompertz(double p[]);
1.203 brouard 4590: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 4591:
4592: printf("\nCalculation of the hessian matrix. Wait...\n");
4593: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
4594: for (i=1;i<=npar;i++){
1.203 brouard 4595: printf("%d-",i);fflush(stdout);
4596: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 4597:
4598: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
4599:
4600: /* printf(" %f ",p[i]);
4601: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
4602: }
4603:
4604: for (i=1;i<=npar;i++) {
4605: for (j=1;j<=npar;j++) {
4606: if (j>i) {
1.203 brouard 4607: printf(".%d-%d",i,j);fflush(stdout);
4608: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
4609: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 4610:
4611: hess[j][i]=hess[i][j];
4612: /*printf(" %lf ",hess[i][j]);*/
4613: }
4614: }
4615: }
4616: printf("\n");
4617: fprintf(ficlog,"\n");
4618:
4619: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
4620: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
4621:
4622: a=matrix(1,npar,1,npar);
4623: y=matrix(1,npar,1,npar);
4624: x=vector(1,npar);
4625: indx=ivector(1,npar);
4626: for (i=1;i<=npar;i++)
4627: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
4628: ludcmp(a,npar,indx,&pd);
4629:
4630: for (j=1;j<=npar;j++) {
4631: for (i=1;i<=npar;i++) x[i]=0;
4632: x[j]=1;
4633: lubksb(a,npar,indx,x);
4634: for (i=1;i<=npar;i++){
4635: matcov[i][j]=x[i];
4636: }
4637: }
4638:
4639: printf("\n#Hessian matrix#\n");
4640: fprintf(ficlog,"\n#Hessian matrix#\n");
4641: for (i=1;i<=npar;i++) {
4642: for (j=1;j<=npar;j++) {
1.203 brouard 4643: printf("%.6e ",hess[i][j]);
4644: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 4645: }
4646: printf("\n");
4647: fprintf(ficlog,"\n");
4648: }
4649:
1.203 brouard 4650: /* printf("\n#Covariance matrix#\n"); */
4651: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
4652: /* for (i=1;i<=npar;i++) { */
4653: /* for (j=1;j<=npar;j++) { */
4654: /* printf("%.6e ",matcov[i][j]); */
4655: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
4656: /* } */
4657: /* printf("\n"); */
4658: /* fprintf(ficlog,"\n"); */
4659: /* } */
4660:
1.126 brouard 4661: /* Recompute Inverse */
1.203 brouard 4662: /* for (i=1;i<=npar;i++) */
4663: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
4664: /* ludcmp(a,npar,indx,&pd); */
4665:
4666: /* printf("\n#Hessian matrix recomputed#\n"); */
4667:
4668: /* for (j=1;j<=npar;j++) { */
4669: /* for (i=1;i<=npar;i++) x[i]=0; */
4670: /* x[j]=1; */
4671: /* lubksb(a,npar,indx,x); */
4672: /* for (i=1;i<=npar;i++){ */
4673: /* y[i][j]=x[i]; */
4674: /* printf("%.3e ",y[i][j]); */
4675: /* fprintf(ficlog,"%.3e ",y[i][j]); */
4676: /* } */
4677: /* printf("\n"); */
4678: /* fprintf(ficlog,"\n"); */
4679: /* } */
4680:
4681: /* Verifying the inverse matrix */
4682: #ifdef DEBUGHESS
4683: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 4684:
1.203 brouard 4685: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
4686: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 4687:
4688: for (j=1;j<=npar;j++) {
4689: for (i=1;i<=npar;i++){
1.203 brouard 4690: printf("%.2f ",y[i][j]);
4691: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 4692: }
4693: printf("\n");
4694: fprintf(ficlog,"\n");
4695: }
1.203 brouard 4696: #endif
1.126 brouard 4697:
4698: free_matrix(a,1,npar,1,npar);
4699: free_matrix(y,1,npar,1,npar);
4700: free_vector(x,1,npar);
4701: free_ivector(indx,1,npar);
1.203 brouard 4702: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 4703:
4704:
4705: }
4706:
4707: /*************** hessian matrix ****************/
4708: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 4709: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 4710: int i;
4711: int l=1, lmax=20;
1.203 brouard 4712: double k1,k2, res, fx;
1.132 brouard 4713: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 4714: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
4715: int k=0,kmax=10;
4716: double l1;
4717:
4718: fx=func(x);
4719: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 4720: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 4721: l1=pow(10,l);
4722: delts=delt;
4723: for(k=1 ; k <kmax; k=k+1){
4724: delt = delta*(l1*k);
4725: p2[theta]=x[theta] +delt;
1.145 brouard 4726: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 4727: p2[theta]=x[theta]-delt;
4728: k2=func(p2)-fx;
4729: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 4730: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 4731:
1.203 brouard 4732: #ifdef DEBUGHESSII
1.126 brouard 4733: 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);
4734: 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);
4735: #endif
4736: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
4737: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
4738: k=kmax;
4739: }
4740: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 4741: k=kmax; l=lmax*10;
1.126 brouard 4742: }
4743: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
4744: delts=delt;
4745: }
1.203 brouard 4746: } /* End loop k */
1.126 brouard 4747: }
4748: delti[theta]=delts;
4749: return res;
4750:
4751: }
4752:
1.203 brouard 4753: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 4754: {
4755: int i;
1.164 brouard 4756: int l=1, lmax=20;
1.126 brouard 4757: double k1,k2,k3,k4,res,fx;
1.132 brouard 4758: double p2[MAXPARM+1];
1.203 brouard 4759: int k, kmax=1;
4760: double v1, v2, cv12, lc1, lc2;
1.208 brouard 4761:
4762: int firstime=0;
1.203 brouard 4763:
1.126 brouard 4764: fx=func(x);
1.203 brouard 4765: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 4766: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 4767: p2[thetai]=x[thetai]+delti[thetai]*k;
4768: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4769: k1=func(p2)-fx;
4770:
1.203 brouard 4771: p2[thetai]=x[thetai]+delti[thetai]*k;
4772: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4773: k2=func(p2)-fx;
4774:
1.203 brouard 4775: p2[thetai]=x[thetai]-delti[thetai]*k;
4776: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4777: k3=func(p2)-fx;
4778:
1.203 brouard 4779: p2[thetai]=x[thetai]-delti[thetai]*k;
4780: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4781: k4=func(p2)-fx;
1.203 brouard 4782: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
4783: if(k1*k2*k3*k4 <0.){
1.208 brouard 4784: firstime=1;
1.203 brouard 4785: kmax=kmax+10;
1.208 brouard 4786: }
4787: if(kmax >=10 || firstime ==1){
1.246 brouard 4788: 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);
4789: 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 4790: 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);
4791: 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);
4792: }
4793: #ifdef DEBUGHESSIJ
4794: v1=hess[thetai][thetai];
4795: v2=hess[thetaj][thetaj];
4796: cv12=res;
4797: /* Computing eigen value of Hessian matrix */
4798: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4799: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4800: if ((lc2 <0) || (lc1 <0) ){
4801: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4802: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4803: 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);
4804: 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);
4805: }
1.126 brouard 4806: #endif
4807: }
4808: return res;
4809: }
4810:
1.203 brouard 4811: /* Not done yet: Was supposed to fix if not exactly at the maximum */
4812: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
4813: /* { */
4814: /* int i; */
4815: /* int l=1, lmax=20; */
4816: /* double k1,k2,k3,k4,res,fx; */
4817: /* double p2[MAXPARM+1]; */
4818: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
4819: /* int k=0,kmax=10; */
4820: /* double l1; */
4821:
4822: /* fx=func(x); */
4823: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
4824: /* l1=pow(10,l); */
4825: /* delts=delt; */
4826: /* for(k=1 ; k <kmax; k=k+1){ */
4827: /* delt = delti*(l1*k); */
4828: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
4829: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4830: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4831: /* k1=func(p2)-fx; */
4832:
4833: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4834: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4835: /* k2=func(p2)-fx; */
4836:
4837: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4838: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4839: /* k3=func(p2)-fx; */
4840:
4841: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4842: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4843: /* k4=func(p2)-fx; */
4844: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
4845: /* #ifdef DEBUGHESSIJ */
4846: /* 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); */
4847: /* 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); */
4848: /* #endif */
4849: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
4850: /* k=kmax; */
4851: /* } */
4852: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
4853: /* k=kmax; l=lmax*10; */
4854: /* } */
4855: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
4856: /* delts=delt; */
4857: /* } */
4858: /* } /\* End loop k *\/ */
4859: /* } */
4860: /* delti[theta]=delts; */
4861: /* return res; */
4862: /* } */
4863:
4864:
1.126 brouard 4865: /************** Inverse of matrix **************/
4866: void ludcmp(double **a, int n, int *indx, double *d)
4867: {
4868: int i,imax,j,k;
4869: double big,dum,sum,temp;
4870: double *vv;
4871:
4872: vv=vector(1,n);
4873: *d=1.0;
4874: for (i=1;i<=n;i++) {
4875: big=0.0;
4876: for (j=1;j<=n;j++)
4877: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 4878: if (big == 0.0){
4879: printf(" Singular Hessian matrix at row %d:\n",i);
4880: for (j=1;j<=n;j++) {
4881: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
4882: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
4883: }
4884: fflush(ficlog);
4885: fclose(ficlog);
4886: nrerror("Singular matrix in routine ludcmp");
4887: }
1.126 brouard 4888: vv[i]=1.0/big;
4889: }
4890: for (j=1;j<=n;j++) {
4891: for (i=1;i<j;i++) {
4892: sum=a[i][j];
4893: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
4894: a[i][j]=sum;
4895: }
4896: big=0.0;
4897: for (i=j;i<=n;i++) {
4898: sum=a[i][j];
4899: for (k=1;k<j;k++)
4900: sum -= a[i][k]*a[k][j];
4901: a[i][j]=sum;
4902: if ( (dum=vv[i]*fabs(sum)) >= big) {
4903: big=dum;
4904: imax=i;
4905: }
4906: }
4907: if (j != imax) {
4908: for (k=1;k<=n;k++) {
4909: dum=a[imax][k];
4910: a[imax][k]=a[j][k];
4911: a[j][k]=dum;
4912: }
4913: *d = -(*d);
4914: vv[imax]=vv[j];
4915: }
4916: indx[j]=imax;
4917: if (a[j][j] == 0.0) a[j][j]=TINY;
4918: if (j != n) {
4919: dum=1.0/(a[j][j]);
4920: for (i=j+1;i<=n;i++) a[i][j] *= dum;
4921: }
4922: }
4923: free_vector(vv,1,n); /* Doesn't work */
4924: ;
4925: }
4926:
4927: void lubksb(double **a, int n, int *indx, double b[])
4928: {
4929: int i,ii=0,ip,j;
4930: double sum;
4931:
4932: for (i=1;i<=n;i++) {
4933: ip=indx[i];
4934: sum=b[ip];
4935: b[ip]=b[i];
4936: if (ii)
4937: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
4938: else if (sum) ii=i;
4939: b[i]=sum;
4940: }
4941: for (i=n;i>=1;i--) {
4942: sum=b[i];
4943: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
4944: b[i]=sum/a[i][i];
4945: }
4946: }
4947:
4948: void pstamp(FILE *fichier)
4949: {
1.196 brouard 4950: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 4951: }
4952:
1.297 brouard 4953: void date2dmy(double date,double *day, double *month, double *year){
4954: double yp=0., yp1=0., yp2=0.;
4955:
4956: yp1=modf(date,&yp);/* extracts integral of date in yp and
4957: fractional in yp1 */
4958: *year=yp;
4959: yp2=modf((yp1*12),&yp);
4960: *month=yp;
4961: yp1=modf((yp2*30.5),&yp);
4962: *day=yp;
4963: if(*day==0) *day=1;
4964: if(*month==0) *month=1;
4965: }
4966:
1.253 brouard 4967:
4968:
1.126 brouard 4969: /************ Frequencies ********************/
1.251 brouard 4970: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 4971: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
4972: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 4973: { /* Some frequencies as well as proposing some starting values */
1.332 brouard 4974: /* Frequencies of any combination of dummy covariate used in the model equation */
1.265 brouard 4975: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 4976: int iind=0, iage=0;
4977: int mi; /* Effective wave */
4978: int first;
4979: double ***freq; /* Frequencies */
1.268 brouard 4980: 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 */
4981: 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 4982: double *meanq, *stdq, *idq;
1.226 brouard 4983: double **meanqt;
4984: double *pp, **prop, *posprop, *pospropt;
4985: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
4986: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
4987: double agebegin, ageend;
4988:
4989: pp=vector(1,nlstate);
1.251 brouard 4990: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4991: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
4992: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
4993: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
4994: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.284 brouard 4995: stdq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.283 brouard 4996: idq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.226 brouard 4997: meanqt=matrix(1,lastpass,1,nqtveff);
4998: strcpy(fileresp,"P_");
4999: strcat(fileresp,fileresu);
5000: /*strcat(fileresphtm,fileresu);*/
5001: if((ficresp=fopen(fileresp,"w"))==NULL) {
5002: printf("Problem with prevalence resultfile: %s\n", fileresp);
5003: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
5004: exit(0);
5005: }
1.240 brouard 5006:
1.226 brouard 5007: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
5008: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
5009: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
5010: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
5011: fflush(ficlog);
5012: exit(70);
5013: }
5014: else{
5015: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 5016: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 5017: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 5018: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
5019: }
1.319 brouard 5020: fprintf(ficresphtm,"Current page is file <a href=\"%s\">%s</a><br>\n\n<h4>Frequencies (weight=%d) and prevalence by age at begin of transition and dummy covariate value at beginning of transition</h4>\n",fileresphtm, fileresphtm, weightopt);
1.240 brouard 5021:
1.226 brouard 5022: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
5023: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
5024: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
5025: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
5026: fflush(ficlog);
5027: exit(70);
1.240 brouard 5028: } else{
1.226 brouard 5029: fprintf(ficresphtmfr,"<html><head>\n<title>IMaCh PHTM_Frequency table %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.319 brouard 5030: ,<hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 5031: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 5032: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
5033: }
1.319 brouard 5034: fprintf(ficresphtmfr,"Current page is file <a href=\"%s\">%s</a><br>\n\n<h4>(weight=%d) frequencies of all effective transitions of the model, by age at begin of transition, and covariate value at the begin of transition (if the covariate is a varying covariate) </h4>Unknown status is -1<br/>\n",fileresphtmfr, fileresphtmfr,weightopt);
1.240 brouard 5035:
1.253 brouard 5036: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
5037: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 5038: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 5039: j1=0;
1.126 brouard 5040:
1.227 brouard 5041: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
1.335 brouard 5042: j=cptcoveff; /* Only simple dummy covariates used in the model */
1.330 brouard 5043: /* j=cptcovn; /\* Only dummy covariates of the model *\/ */
1.226 brouard 5044: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 5045:
5046:
1.226 brouard 5047: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
5048: reference=low_education V1=0,V2=0
5049: med_educ V1=1 V2=0,
5050: high_educ V1=0 V2=1
1.330 brouard 5051: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcovn
1.226 brouard 5052: */
1.249 brouard 5053: dateintsum=0;
5054: k2cpt=0;
5055:
1.253 brouard 5056: if(cptcoveff == 0 )
1.265 brouard 5057: nl=1; /* Constant and age model only */
1.253 brouard 5058: else
5059: nl=2;
1.265 brouard 5060:
5061: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
5062: /* Loop on nj=1 or 2 if dummy covariates j!=0
1.335 brouard 5063: * Loop on j1(1 to 2**cptcoveff) covariate combination
1.265 brouard 5064: * freq[s1][s2][iage] =0.
5065: * Loop on iind
5066: * ++freq[s1][s2][iage] weighted
5067: * end iind
5068: * if covariate and j!0
5069: * headers Variable on one line
5070: * endif cov j!=0
5071: * header of frequency table by age
5072: * Loop on age
5073: * pp[s1]+=freq[s1][s2][iage] weighted
5074: * pos+=freq[s1][s2][iage] weighted
5075: * Loop on s1 initial state
5076: * fprintf(ficresp
5077: * end s1
5078: * end age
5079: * if j!=0 computes starting values
5080: * end compute starting values
5081: * end j1
5082: * end nl
5083: */
1.253 brouard 5084: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
5085: if(nj==1)
5086: j=0; /* First pass for the constant */
1.265 brouard 5087: else{
1.335 brouard 5088: j=cptcoveff; /* Other passes for the covariate values number of simple covariates in the model V2+V1 =2 (simple dummy fixed or time varying) */
1.265 brouard 5089: }
1.251 brouard 5090: first=1;
1.332 brouard 5091: for (j1 = 1; j1 <= (int) pow(2,j); j1++){ /* Loop on all dummy covariates combination of the model, ie excluding quantitatives, V4=0, V3=0 for example, fixed or varying covariates */
1.251 brouard 5092: posproptt=0.;
1.330 brouard 5093: /*printf("cptcovn=%d Tvaraff=%d", cptcovn,Tvaraff[1]);
1.251 brouard 5094: scanf("%d", i);*/
5095: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 5096: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 5097: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 5098: freq[i][s2][m]=0;
1.251 brouard 5099:
5100: for (i=1; i<=nlstate; i++) {
1.240 brouard 5101: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 5102: prop[i][m]=0;
5103: posprop[i]=0;
5104: pospropt[i]=0;
5105: }
1.283 brouard 5106: for (z1=1; z1<= nqfveff; z1++) { /* zeroing for each combination j1 as well as for the total */
1.284 brouard 5107: idq[z1]=0.;
5108: meanq[z1]=0.;
5109: stdq[z1]=0.;
1.283 brouard 5110: }
5111: /* for (z1=1; z1<= nqtveff; z1++) { */
1.251 brouard 5112: /* for(m=1;m<=lastpass;m++){ */
1.283 brouard 5113: /* meanqt[m][z1]=0.; */
5114: /* } */
5115: /* } */
1.251 brouard 5116: /* dateintsum=0; */
5117: /* k2cpt=0; */
5118:
1.265 brouard 5119: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 5120: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
5121: bool=1;
5122: if(j !=0){
5123: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
1.335 brouard 5124: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
5125: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
1.251 brouard 5126: /* if(Tvaraff[z1] ==-20){ */
5127: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
5128: /* }else if(Tvaraff[z1] ==-10){ */
5129: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
1.330 brouard 5130: /* }else */ /* TODO TODO codtabm(j1,z1) or codtabm(j1,Tvaraff[z1]]z1)*/
1.335 brouard 5131: /* if( iind >=imx-3) printf("Searching error iind=%d Tvaraff[z1]=%d covar[Tvaraff[z1]][iind]=%.f TnsdVar[Tvaraff[z1]]=%d, cptcoveff=%d, cptcovs=%d \n",iind, Tvaraff[z1], covar[Tvaraff[z1]][iind],TnsdVar[Tvaraff[z1]],cptcoveff, cptcovs); */
5132: if(Tvaraff[z1]<1 || Tvaraff[z1]>=NCOVMAX)
1.338 ! brouard 5133: printf("Error Tvaraff[z1]=%d<1 or >=%d, cptcoveff=%d model=1+age+%s\n",Tvaraff[z1],NCOVMAX, cptcoveff, model);
1.332 brouard 5134: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]){ /* for combination j1 of covariates */
1.265 brouard 5135: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 5136: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
1.332 brouard 5137: /* 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", */
5138: /* bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),*/
5139: /* j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
1.251 brouard 5140: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
5141: } /* Onlyf fixed */
5142: } /* end z1 */
1.335 brouard 5143: } /* cptcoveff > 0 */
1.251 brouard 5144: } /* end any */
5145: }/* end j==0 */
1.265 brouard 5146: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 5147: /* for(m=firstpass; m<=lastpass; m++){ */
1.284 brouard 5148: for(mi=1; mi<wav[iind];mi++){ /* For each wave */
1.251 brouard 5149: m=mw[mi][iind];
5150: if(j!=0){
5151: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
1.335 brouard 5152: for (z1=1; z1<=cptcoveff; z1++) {
1.251 brouard 5153: if( Fixed[Tmodelind[z1]]==1){
5154: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
1.332 brouard 5155: if (cotvar[m][iv][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) /* iv=1 to ntv, right modality. If covariate's
1.251 brouard 5156: value is -1, we don't select. It differs from the
5157: constant and age model which counts them. */
5158: bool=0; /* not selected */
5159: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
1.334 brouard 5160: /* i1=Tvaraff[z1]; */
5161: /* i2=TnsdVar[i1]; */
5162: /* i3=nbcode[i1][i2]; */
5163: /* i4=covar[i1][iind]; */
5164: /* if(i4 != i3){ */
5165: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) { /* Bug valgrind */
1.251 brouard 5166: bool=0;
5167: }
5168: }
5169: }
5170: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
5171: } /* end j==0 */
5172: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
1.284 brouard 5173: if(bool==1){ /*Selected */
1.251 brouard 5174: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
5175: and mw[mi+1][iind]. dh depends on stepm. */
5176: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
5177: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
5178: if(m >=firstpass && m <=lastpass){
5179: k2=anint[m][iind]+(mint[m][iind]/12.);
5180: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
5181: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
5182: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
5183: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
5184: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
5185: if (m<lastpass) {
5186: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
5187: /* 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]); */
5188: if(s[m][iind]==-1)
5189: 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.));
5190: 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 5191: for (z1=1; z1<= nqfveff; z1++) { /* Quantitative variables, calculating mean on known values only */
5192: if(!isnan(covar[ncovcol+z1][iind])){
1.332 brouard 5193: idq[z1]=idq[z1]+weight[iind];
5194: meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /* Computes mean of quantitative with selected filter */
5195: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; *//*error*/
5196: stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]; /* *weight[iind];*/ /* Computes mean of quantitative with selected filter */
1.311 brouard 5197: }
1.284 brouard 5198: }
1.251 brouard 5199: /* if((int)agev[m][iind] == 55) */
5200: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
5201: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
5202: 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 5203: }
1.251 brouard 5204: } /* end if between passes */
5205: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
5206: dateintsum=dateintsum+k2; /* on all covariates ?*/
5207: k2cpt++;
5208: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 5209: }
1.251 brouard 5210: }else{
5211: bool=1;
5212: }/* end bool 2 */
5213: } /* end m */
1.284 brouard 5214: /* for (z1=1; z1<= nqfveff; z1++) { /\* Quantitative variables, calculating mean *\/ */
5215: /* idq[z1]=idq[z1]+weight[iind]; */
5216: /* meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /\* Computes mean of quantitative with selected filter *\/ */
5217: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /\* *weight[iind];*\/ /\* Computes mean of quantitative with selected filter *\/ */
5218: /* } */
1.251 brouard 5219: } /* end bool */
5220: } /* end iind = 1 to imx */
1.319 brouard 5221: /* prop[s][age] is fed for any initial and valid live state as well as
1.251 brouard 5222: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
5223:
5224:
5225: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.335 brouard 5226: if(cptcoveff==0 && nj==1) /* no covariate and first pass */
1.265 brouard 5227: pstamp(ficresp);
1.335 brouard 5228: if (cptcoveff>0 && j!=0){
1.265 brouard 5229: pstamp(ficresp);
1.251 brouard 5230: printf( "\n#********** Variable ");
5231: fprintf(ficresp, "\n#********** Variable ");
5232: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
5233: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
5234: fprintf(ficlog, "\n#********** Variable ");
1.330 brouard 5235: for (z1=1; z1<=cptcovs; z1++){
1.251 brouard 5236: if(!FixedV[Tvaraff[z1]]){
1.330 brouard 5237: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5238: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5239: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5240: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5241: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.250 brouard 5242: }else{
1.330 brouard 5243: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5244: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5245: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5246: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5247: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.251 brouard 5248: }
5249: }
5250: printf( "**********\n#");
5251: fprintf(ficresp, "**********\n#");
5252: fprintf(ficresphtm, "**********</h3>\n");
5253: fprintf(ficresphtmfr, "**********</h3>\n");
5254: fprintf(ficlog, "**********\n");
5255: }
1.284 brouard 5256: /*
5257: Printing means of quantitative variables if any
5258: */
5259: for (z1=1; z1<= nqfveff; z1++) {
1.311 brouard 5260: fprintf(ficlog,"Mean of fixed quantitative variable V%d on %.3g (weighted) individuals sum=%f", ncovcol+z1, idq[z1], meanq[z1]);
1.312 brouard 5261: fprintf(ficlog,", mean=%.3g\n",meanq[z1]/idq[z1]);
1.284 brouard 5262: if(weightopt==1){
5263: printf(" Weighted mean and standard deviation of");
5264: fprintf(ficlog," Weighted mean and standard deviation of");
5265: fprintf(ficresphtmfr," Weighted mean and standard deviation of");
5266: }
1.311 brouard 5267: /* mu = \frac{w x}{\sum w}
5268: var = \frac{\sum w (x-mu)^2}{\sum w} = \frac{w x^2}{\sum w} - mu^2
5269: */
5270: 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]));
5271: 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]));
5272: 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 5273: }
5274: /* for (z1=1; z1<= nqtveff; z1++) { */
5275: /* for(m=1;m<=lastpass;m++){ */
5276: /* fprintf(ficresphtmfr,"V quantitative id %d, pass id=%d, mean=%f<p>\n", z1, m, meanqt[m][z1]); */
5277: /* } */
5278: /* } */
1.283 brouard 5279:
1.251 brouard 5280: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.335 brouard 5281: if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
1.265 brouard 5282: fprintf(ficresp, " Age");
1.335 brouard 5283: if(nj==2) for (z1=1; z1<=cptcoveff; z1++) {
5284: printf(" V%d=%d, z1=%d, Tvaraff[z1]=%d, j1=%d, TnsdVar[Tvaraff[%d]]=%d |",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])], z1, Tvaraff[z1], j1,z1,TnsdVar[Tvaraff[z1]]);
5285: fprintf(ficresp, " V%d=%d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5286: }
1.251 brouard 5287: for(i=1; i<=nlstate;i++) {
1.335 brouard 5288: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 5289: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
5290: }
1.335 brouard 5291: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 5292: fprintf(ficresphtm, "\n");
5293:
5294: /* Header of frequency table by age */
5295: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
5296: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 5297: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 5298: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5299: if(s2!=0 && m!=0)
5300: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 5301: }
1.226 brouard 5302: }
1.251 brouard 5303: fprintf(ficresphtmfr, "\n");
5304:
5305: /* For each age */
5306: for(iage=iagemin; iage <= iagemax+3; iage++){
5307: fprintf(ficresphtm,"<tr>");
5308: if(iage==iagemax+1){
5309: fprintf(ficlog,"1");
5310: fprintf(ficresphtmfr,"<tr><th>0</th> ");
5311: }else if(iage==iagemax+2){
5312: fprintf(ficlog,"0");
5313: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
5314: }else if(iage==iagemax+3){
5315: fprintf(ficlog,"Total");
5316: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
5317: }else{
1.240 brouard 5318: if(first==1){
1.251 brouard 5319: first=0;
5320: printf("See log file for details...\n");
5321: }
5322: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
5323: fprintf(ficlog,"Age %d", iage);
5324: }
1.265 brouard 5325: for(s1=1; s1 <=nlstate ; s1++){
5326: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
5327: pp[s1] += freq[s1][m][iage];
1.251 brouard 5328: }
1.265 brouard 5329: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5330: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 5331: pos += freq[s1][m][iage];
5332: if(pp[s1]>=1.e-10){
1.251 brouard 5333: if(first==1){
1.265 brouard 5334: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5335: }
1.265 brouard 5336: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5337: }else{
5338: if(first==1)
1.265 brouard 5339: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
5340: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 5341: }
5342: }
5343:
1.265 brouard 5344: for(s1=1; s1 <=nlstate ; s1++){
5345: /* posprop[s1]=0; */
5346: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
5347: pp[s1] += freq[s1][m][iage];
5348: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
5349:
5350: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
5351: pos += pp[s1]; /* pos is the total number of transitions until this age */
5352: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
5353: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5354: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
5355: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5356: }
5357:
5358: /* Writing ficresp */
1.335 brouard 5359: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 5360: if( iage <= iagemax){
5361: fprintf(ficresp," %d",iage);
5362: }
5363: }else if( nj==2){
5364: if( iage <= iagemax){
5365: fprintf(ficresp," %d",iage);
1.335 brouard 5366: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.265 brouard 5367: }
1.240 brouard 5368: }
1.265 brouard 5369: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 5370: if(pos>=1.e-5){
1.251 brouard 5371: if(first==1)
1.265 brouard 5372: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
5373: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 5374: }else{
5375: if(first==1)
1.265 brouard 5376: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
5377: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 5378: }
5379: if( iage <= iagemax){
5380: if(pos>=1.e-5){
1.335 brouard 5381: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 5382: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5383: }else if( nj==2){
5384: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5385: }
5386: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5387: /*probs[iage][s1][j1]= pp[s1]/pos;*/
5388: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
5389: } else{
1.335 brouard 5390: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
1.265 brouard 5391: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 5392: }
1.240 brouard 5393: }
1.265 brouard 5394: pospropt[s1] +=posprop[s1];
5395: } /* end loop s1 */
1.251 brouard 5396: /* pospropt=0.; */
1.265 brouard 5397: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 5398: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5399: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 5400: if(first==1){
1.265 brouard 5401: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5402: }
1.265 brouard 5403: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
5404: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5405: }
1.265 brouard 5406: if(s1!=0 && m!=0)
5407: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 5408: }
1.265 brouard 5409: } /* end loop s1 */
1.251 brouard 5410: posproptt=0.;
1.265 brouard 5411: for(s1=1; s1 <=nlstate; s1++){
5412: posproptt += pospropt[s1];
1.251 brouard 5413: }
5414: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 5415: fprintf(ficresphtm,"</tr>\n");
1.335 brouard 5416: if((cptcoveff==0 && nj==1)|| nj==2 ) {
1.265 brouard 5417: if(iage <= iagemax)
5418: fprintf(ficresp,"\n");
1.240 brouard 5419: }
1.251 brouard 5420: if(first==1)
5421: printf("Others in log...\n");
5422: fprintf(ficlog,"\n");
5423: } /* end loop age iage */
1.265 brouard 5424:
1.251 brouard 5425: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 5426: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5427: if(posproptt < 1.e-5){
1.265 brouard 5428: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 5429: }else{
1.265 brouard 5430: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 5431: }
1.226 brouard 5432: }
1.251 brouard 5433: fprintf(ficresphtm,"</tr>\n");
5434: fprintf(ficresphtm,"</table>\n");
5435: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 5436: if(posproptt < 1.e-5){
1.251 brouard 5437: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
5438: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 5439: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
5440: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 5441: invalidvarcomb[j1]=1;
1.226 brouard 5442: }else{
1.338 ! brouard 5443: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced (or no resultline).</p>",j1);
1.251 brouard 5444: invalidvarcomb[j1]=0;
1.226 brouard 5445: }
1.251 brouard 5446: fprintf(ficresphtmfr,"</table>\n");
5447: fprintf(ficlog,"\n");
5448: if(j!=0){
5449: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 5450: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5451: for(k=1; k <=(nlstate+ndeath); k++){
5452: if (k != i) {
1.265 brouard 5453: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 5454: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 5455: if(j1==1){ /* All dummy covariates to zero */
5456: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
5457: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 5458: printf("%d%d ",i,k);
5459: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5460: 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]));
5461: 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]));
5462: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 5463: }
1.253 brouard 5464: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
5465: for(iage=iagemin; iage <= iagemax+3; iage++){
5466: x[iage]= (double)iage;
5467: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 5468: /* 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 5469: }
1.268 brouard 5470: /* Some are not finite, but linreg will ignore these ages */
5471: no=0;
1.253 brouard 5472: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 5473: pstart[s1]=b;
5474: pstart[s1-1]=a;
1.252 brouard 5475: }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 */
5476: 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]);
5477: 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 5478: 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 5479: printf("%d%d ",i,k);
5480: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5481: 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 5482: }else{ /* Other cases, like quantitative fixed or varying covariates */
5483: ;
5484: }
5485: /* printf("%12.7f )", param[i][jj][k]); */
5486: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5487: s1++;
1.251 brouard 5488: } /* end jj */
5489: } /* end k!= i */
5490: } /* end k */
1.265 brouard 5491: } /* end i, s1 */
1.251 brouard 5492: } /* end j !=0 */
5493: } /* end selected combination of covariate j1 */
5494: if(j==0){ /* We can estimate starting values from the occurences in each case */
5495: printf("#Freqsummary: Starting values for the constants:\n");
5496: fprintf(ficlog,"\n");
1.265 brouard 5497: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5498: for(k=1; k <=(nlstate+ndeath); k++){
5499: if (k != i) {
5500: printf("%d%d ",i,k);
5501: fprintf(ficlog,"%d%d ",i,k);
5502: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 5503: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 5504: if(jj==1){ /* Age has to be done */
1.265 brouard 5505: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
5506: 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]));
5507: 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 5508: }
5509: /* printf("%12.7f )", param[i][jj][k]); */
5510: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5511: s1++;
1.250 brouard 5512: }
1.251 brouard 5513: printf("\n");
5514: fprintf(ficlog,"\n");
1.250 brouard 5515: }
5516: }
1.284 brouard 5517: } /* end of state i */
1.251 brouard 5518: printf("#Freqsummary\n");
5519: fprintf(ficlog,"\n");
1.265 brouard 5520: for(s1=-1; s1 <=nlstate+ndeath; s1++){
5521: for(s2=-1; s2 <=nlstate+ndeath; s2++){
5522: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
5523: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
5524: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
5525: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
5526: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
5527: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 5528: /* } */
5529: }
1.265 brouard 5530: } /* end loop s1 */
1.251 brouard 5531:
5532: printf("\n");
5533: fprintf(ficlog,"\n");
5534: } /* end j=0 */
1.249 brouard 5535: } /* end j */
1.252 brouard 5536:
1.253 brouard 5537: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 5538: for(i=1, jk=1; i <=nlstate; i++){
5539: for(j=1; j <=nlstate+ndeath; j++){
5540: if(j!=i){
5541: /*ca[0]= k+'a'-1;ca[1]='\0';*/
5542: printf("%1d%1d",i,j);
5543: fprintf(ficparo,"%1d%1d",i,j);
5544: for(k=1; k<=ncovmodel;k++){
5545: /* printf(" %lf",param[i][j][k]); */
5546: /* fprintf(ficparo," %lf",param[i][j][k]); */
5547: p[jk]=pstart[jk];
5548: printf(" %f ",pstart[jk]);
5549: fprintf(ficparo," %f ",pstart[jk]);
5550: jk++;
5551: }
5552: printf("\n");
5553: fprintf(ficparo,"\n");
5554: }
5555: }
5556: }
5557: } /* end mle=-2 */
1.226 brouard 5558: dateintmean=dateintsum/k2cpt;
1.296 brouard 5559: date2dmy(dateintmean,&jintmean,&mintmean,&aintmean);
1.240 brouard 5560:
1.226 brouard 5561: fclose(ficresp);
5562: fclose(ficresphtm);
5563: fclose(ficresphtmfr);
1.283 brouard 5564: free_vector(idq,1,nqfveff);
1.226 brouard 5565: free_vector(meanq,1,nqfveff);
1.284 brouard 5566: free_vector(stdq,1,nqfveff);
1.226 brouard 5567: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 5568: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
5569: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 5570: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 5571: free_vector(pospropt,1,nlstate);
5572: free_vector(posprop,1,nlstate);
1.251 brouard 5573: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 5574: free_vector(pp,1,nlstate);
5575: /* End of freqsummary */
5576: }
1.126 brouard 5577:
1.268 brouard 5578: /* Simple linear regression */
5579: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
5580:
5581: /* y=a+bx regression */
5582: double sumx = 0.0; /* sum of x */
5583: double sumx2 = 0.0; /* sum of x**2 */
5584: double sumxy = 0.0; /* sum of x * y */
5585: double sumy = 0.0; /* sum of y */
5586: double sumy2 = 0.0; /* sum of y**2 */
5587: double sume2 = 0.0; /* sum of square or residuals */
5588: double yhat;
5589:
5590: double denom=0;
5591: int i;
5592: int ne=*no;
5593:
5594: for ( i=ifi, ne=0;i<=ila;i++) {
5595: if(!isfinite(x[i]) || !isfinite(y[i])){
5596: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5597: continue;
5598: }
5599: ne=ne+1;
5600: sumx += x[i];
5601: sumx2 += x[i]*x[i];
5602: sumxy += x[i] * y[i];
5603: sumy += y[i];
5604: sumy2 += y[i]*y[i];
5605: denom = (ne * sumx2 - sumx*sumx);
5606: /* 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); */
5607: }
5608:
5609: denom = (ne * sumx2 - sumx*sumx);
5610: if (denom == 0) {
5611: // vertical, slope m is infinity
5612: *b = INFINITY;
5613: *a = 0;
5614: if (r) *r = 0;
5615: return 1;
5616: }
5617:
5618: *b = (ne * sumxy - sumx * sumy) / denom;
5619: *a = (sumy * sumx2 - sumx * sumxy) / denom;
5620: if (r!=NULL) {
5621: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
5622: sqrt((sumx2 - sumx*sumx/ne) *
5623: (sumy2 - sumy*sumy/ne));
5624: }
5625: *no=ne;
5626: for ( i=ifi, ne=0;i<=ila;i++) {
5627: if(!isfinite(x[i]) || !isfinite(y[i])){
5628: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5629: continue;
5630: }
5631: ne=ne+1;
5632: yhat = y[i] - *a -*b* x[i];
5633: sume2 += yhat * yhat ;
5634:
5635: denom = (ne * sumx2 - sumx*sumx);
5636: /* 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); */
5637: }
5638: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
5639: *sa= *sb * sqrt(sumx2/ne);
5640:
5641: return 0;
5642: }
5643:
1.126 brouard 5644: /************ Prevalence ********************/
1.227 brouard 5645: 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)
5646: {
5647: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
5648: in each health status at the date of interview (if between dateprev1 and dateprev2).
5649: We still use firstpass and lastpass as another selection.
5650: */
1.126 brouard 5651:
1.227 brouard 5652: int i, m, jk, j1, bool, z1,j, iv;
5653: int mi; /* Effective wave */
5654: int iage;
5655: double agebegin, ageend;
5656:
5657: double **prop;
5658: double posprop;
5659: double y2; /* in fractional years */
5660: int iagemin, iagemax;
5661: int first; /** to stop verbosity which is redirected to log file */
5662:
5663: iagemin= (int) agemin;
5664: iagemax= (int) agemax;
5665: /*pp=vector(1,nlstate);*/
1.251 brouard 5666: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5667: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
5668: j1=0;
1.222 brouard 5669:
1.227 brouard 5670: /*j=cptcoveff;*/
5671: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 5672:
1.288 brouard 5673: first=0;
1.335 brouard 5674: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of simple dummy covariates */
1.227 brouard 5675: for (i=1; i<=nlstate; i++)
1.251 brouard 5676: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 5677: prop[i][iage]=0.0;
5678: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
5679: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
5680: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
5681:
5682: for (i=1; i<=imx; i++) { /* Each individual */
5683: bool=1;
5684: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
5685: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
5686: m=mw[mi][i];
5687: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
5688: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
5689: for (z1=1; z1<=cptcoveff; z1++){
5690: if( Fixed[Tmodelind[z1]]==1){
5691: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
1.332 brouard 5692: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) /* iv=1 to ntv, right modality */
1.227 brouard 5693: bool=0;
5694: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
1.332 brouard 5695: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) {
1.227 brouard 5696: bool=0;
5697: }
5698: }
5699: if(bool==1){ /* Otherwise we skip that wave/person */
5700: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
5701: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
5702: if(m >=firstpass && m <=lastpass){
5703: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
5704: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
5705: if(agev[m][i]==0) agev[m][i]=iagemax+1;
5706: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 5707: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 5708: 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);
5709: exit(1);
5710: }
5711: if (s[m][i]>0 && s[m][i]<=nlstate) {
5712: /*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]]);*/
5713: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
5714: prop[s[m][i]][iagemax+3] += weight[i];
5715: } /* end valid statuses */
5716: } /* end selection of dates */
5717: } /* end selection of waves */
5718: } /* end bool */
5719: } /* end wave */
5720: } /* end individual */
5721: for(i=iagemin; i <= iagemax+3; i++){
5722: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
5723: posprop += prop[jk][i];
5724: }
5725:
5726: for(jk=1; jk <=nlstate ; jk++){
5727: if( i <= iagemax){
5728: if(posprop>=1.e-5){
5729: probs[i][jk][j1]= prop[jk][i]/posprop;
5730: } else{
1.288 brouard 5731: if(!first){
5732: first=1;
1.266 brouard 5733: 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]);
5734: }else{
1.288 brouard 5735: 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 5736: }
5737: }
5738: }
5739: }/* end jk */
5740: }/* end i */
1.222 brouard 5741: /*} *//* end i1 */
1.227 brouard 5742: } /* end j1 */
1.222 brouard 5743:
1.227 brouard 5744: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
5745: /*free_vector(pp,1,nlstate);*/
1.251 brouard 5746: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5747: } /* End of prevalence */
1.126 brouard 5748:
5749: /************* Waves Concatenation ***************/
5750:
5751: 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)
5752: {
1.298 brouard 5753: /* 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 5754: Death is a valid wave (if date is known).
5755: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
5756: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
1.298 brouard 5757: and mw[mi+1][i]. dh depends on stepm. s[m][i] exists for any wave from firstpass to lastpass
1.227 brouard 5758: */
1.126 brouard 5759:
1.224 brouard 5760: int i=0, mi=0, m=0, mli=0;
1.126 brouard 5761: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
5762: double sum=0., jmean=0.;*/
1.224 brouard 5763: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 5764: int j, k=0,jk, ju, jl;
5765: double sum=0.;
5766: first=0;
1.214 brouard 5767: firstwo=0;
1.217 brouard 5768: firsthree=0;
1.218 brouard 5769: firstfour=0;
1.164 brouard 5770: jmin=100000;
1.126 brouard 5771: jmax=-1;
5772: jmean=0.;
1.224 brouard 5773:
5774: /* Treating live states */
1.214 brouard 5775: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 5776: mi=0; /* First valid wave */
1.227 brouard 5777: mli=0; /* Last valid wave */
1.309 brouard 5778: m=firstpass; /* Loop on waves */
5779: while(s[m][i] <= nlstate){ /* a live state or unknown state */
1.227 brouard 5780: 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 */
5781: mli=m-1;/* mw[++mi][i]=m-1; */
5782: }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 5783: 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 5784: mli=m;
1.224 brouard 5785: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
5786: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 5787: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 5788: }
1.309 brouard 5789: else{ /* m = lastpass, eventual special issue with warning */
1.224 brouard 5790: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 5791: break;
1.224 brouard 5792: #else
1.317 brouard 5793: 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 5794: if(firsthree == 0){
1.302 brouard 5795: 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 5796: firsthree=1;
1.317 brouard 5797: }else if(firsthree >=1 && firsthree < 10){
5798: 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);
5799: firsthree++;
5800: }else if(firsthree == 10){
5801: printf("Information, too many Information flags: no more reported to log either\n");
5802: fprintf(ficlog,"Information, too many Information flags: no more reported to log either\n");
5803: firsthree++;
5804: }else{
5805: firsthree++;
1.227 brouard 5806: }
1.309 brouard 5807: mw[++mi][i]=m; /* Valid transition with unknown status */
1.227 brouard 5808: mli=m;
5809: }
5810: if(s[m][i]==-2){ /* Vital status is really unknown */
5811: nbwarn++;
1.309 brouard 5812: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified?not a transition */
1.227 brouard 5813: 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);
5814: 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);
5815: }
5816: break;
5817: }
5818: break;
1.224 brouard 5819: #endif
1.227 brouard 5820: }/* End m >= lastpass */
1.126 brouard 5821: }/* end while */
1.224 brouard 5822:
1.227 brouard 5823: /* 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 5824: /* After last pass */
1.224 brouard 5825: /* Treating death states */
1.214 brouard 5826: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 5827: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
5828: /* } */
1.126 brouard 5829: mi++; /* Death is another wave */
5830: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 5831: /* Only death is a correct wave */
1.126 brouard 5832: mw[mi][i]=m;
1.257 brouard 5833: } /* else not in a death state */
1.224 brouard 5834: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 5835: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 5836: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.309 brouard 5837: 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 5838: nbwarn++;
5839: if(firstfiv==0){
1.309 brouard 5840: 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 5841: firstfiv=1;
5842: }else{
1.309 brouard 5843: 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 5844: }
1.309 brouard 5845: s[m][i]=nlstate+1; /* Fixing the status as death. Be careful if multiple death states */
5846: }else{ /* Month of Death occured afer last wave month, potential bias */
1.227 brouard 5847: nberr++;
5848: if(firstwo==0){
1.309 brouard 5849: 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 5850: firstwo=1;
5851: }
1.309 brouard 5852: 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 5853: }
1.257 brouard 5854: }else{ /* if date of interview is unknown */
1.227 brouard 5855: /* death is known but not confirmed by death status at any wave */
5856: if(firstfour==0){
1.309 brouard 5857: 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 5858: firstfour=1;
5859: }
1.309 brouard 5860: 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 5861: }
1.224 brouard 5862: } /* end if date of death is known */
5863: #endif
1.309 brouard 5864: wav[i]=mi; /* mi should be the last effective wave (or mli), */
5865: /* wav[i]=mw[mi][i]; */
1.126 brouard 5866: if(mi==0){
5867: nbwarn++;
5868: if(first==0){
1.227 brouard 5869: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
5870: first=1;
1.126 brouard 5871: }
5872: if(first==1){
1.227 brouard 5873: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 5874: }
5875: } /* end mi==0 */
5876: } /* End individuals */
1.214 brouard 5877: /* wav and mw are no more changed */
1.223 brouard 5878:
1.317 brouard 5879: printf("Information, you have to check %d informations which haven't been logged!\n",firsthree);
5880: fprintf(ficlog,"Information, you have to check %d informations which haven't been logged!\n",firsthree);
5881:
5882:
1.126 brouard 5883: for(i=1; i<=imx; i++){
5884: for(mi=1; mi<wav[i];mi++){
5885: if (stepm <=0)
1.227 brouard 5886: dh[mi][i]=1;
1.126 brouard 5887: else{
1.260 brouard 5888: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 5889: if (agedc[i] < 2*AGESUP) {
5890: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
5891: if(j==0) j=1; /* Survives at least one month after exam */
5892: else if(j<0){
5893: nberr++;
5894: 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]);
5895: j=1; /* Temporary Dangerous patch */
5896: 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);
5897: 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]);
5898: 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);
5899: }
5900: k=k+1;
5901: if (j >= jmax){
5902: jmax=j;
5903: ijmax=i;
5904: }
5905: if (j <= jmin){
5906: jmin=j;
5907: ijmin=i;
5908: }
5909: sum=sum+j;
5910: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
5911: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
5912: }
5913: }
5914: else{
5915: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 5916: /* 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 5917:
1.227 brouard 5918: k=k+1;
5919: if (j >= jmax) {
5920: jmax=j;
5921: ijmax=i;
5922: }
5923: else if (j <= jmin){
5924: jmin=j;
5925: ijmin=i;
5926: }
5927: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
5928: /*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]);*/
5929: if(j<0){
5930: nberr++;
5931: 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]);
5932: 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]);
5933: }
5934: sum=sum+j;
5935: }
5936: jk= j/stepm;
5937: jl= j -jk*stepm;
5938: ju= j -(jk+1)*stepm;
5939: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
5940: if(jl==0){
5941: dh[mi][i]=jk;
5942: bh[mi][i]=0;
5943: }else{ /* We want a negative bias in order to only have interpolation ie
5944: * to avoid the price of an extra matrix product in likelihood */
5945: dh[mi][i]=jk+1;
5946: bh[mi][i]=ju;
5947: }
5948: }else{
5949: if(jl <= -ju){
5950: dh[mi][i]=jk;
5951: bh[mi][i]=jl; /* bias is positive if real duration
5952: * is higher than the multiple of stepm and negative otherwise.
5953: */
5954: }
5955: else{
5956: dh[mi][i]=jk+1;
5957: bh[mi][i]=ju;
5958: }
5959: if(dh[mi][i]==0){
5960: dh[mi][i]=1; /* At least one step */
5961: bh[mi][i]=ju; /* At least one step */
5962: /* 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);*/
5963: }
5964: } /* end if mle */
1.126 brouard 5965: }
5966: } /* end wave */
5967: }
5968: jmean=sum/k;
5969: 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 5970: 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 5971: }
1.126 brouard 5972:
5973: /*********** Tricode ****************************/
1.220 brouard 5974: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 5975: {
5976: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
5977: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
5978: * Boring subroutine which should only output nbcode[Tvar[j]][k]
5979: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
5980: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
5981: */
1.130 brouard 5982:
1.242 brouard 5983: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
5984: int modmaxcovj=0; /* Modality max of covariates j */
5985: int cptcode=0; /* Modality max of covariates j */
5986: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 5987:
5988:
1.242 brouard 5989: /* cptcoveff=0; */
5990: /* *cptcov=0; */
1.126 brouard 5991:
1.242 brouard 5992: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.285 brouard 5993: for (k=1; k <= maxncov; k++)
5994: for(j=1; j<=2; j++)
5995: nbcode[k][j]=0; /* Valgrind */
1.126 brouard 5996:
1.242 brouard 5997: /* Loop on covariates without age and products and no quantitative variable */
1.335 brouard 5998: for (k=1; k<=cptcovt; k++) { /* cptcovt: total number of covariates of the model (2) nbocc(+)+1 = 8 excepting constant and age and age*age */
1.242 brouard 5999: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
6000: if(Dummy[k]==0 && Typevar[k] !=1){ /* Dummy covariate and not age product */
6001: switch(Fixed[k]) {
6002: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
1.311 brouard 6003: modmaxcovj=0;
6004: modmincovj=0;
1.242 brouard 6005: 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*/
6006: ij=(int)(covar[Tvar[k]][i]);
6007: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
6008: * If product of Vn*Vm, still boolean *:
6009: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
6010: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
6011: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
6012: modality of the nth covariate of individual i. */
6013: if (ij > modmaxcovj)
6014: modmaxcovj=ij;
6015: else if (ij < modmincovj)
6016: modmincovj=ij;
1.287 brouard 6017: if (ij <0 || ij >1 ){
1.311 brouard 6018: printf("ERROR, IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
6019: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
6020: fflush(ficlog);
6021: exit(1);
1.287 brouard 6022: }
6023: if ((ij < -1) || (ij > NCOVMAX)){
1.242 brouard 6024: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
6025: exit(1);
6026: }else
6027: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
6028: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
6029: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
6030: /* getting the maximum value of the modality of the covariate
6031: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
6032: female ies 1, then modmaxcovj=1.
6033: */
6034: } /* end for loop on individuals i */
6035: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
6036: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
6037: cptcode=modmaxcovj;
6038: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
6039: /*for (i=0; i<=cptcode; i++) {*/
6040: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
6041: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
6042: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
6043: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
6044: if( j != -1){
6045: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
6046: covariate for which somebody answered excluding
6047: undefined. Usually 2: 0 and 1. */
6048: }
6049: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
6050: covariate for which somebody answered including
6051: undefined. Usually 3: -1, 0 and 1. */
6052: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
6053: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
6054: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 6055:
1.242 brouard 6056: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
6057: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
6058: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
6059: /* modmincovj=3; modmaxcovj = 7; */
6060: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
6061: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
6062: /* defining two dummy variables: variables V1_1 and V1_2.*/
6063: /* nbcode[Tvar[j]][ij]=k; */
6064: /* nbcode[Tvar[j]][1]=0; */
6065: /* nbcode[Tvar[j]][2]=1; */
6066: /* nbcode[Tvar[j]][3]=2; */
6067: /* To be continued (not working yet). */
6068: ij=0; /* ij is similar to i but can jump over null modalities */
1.287 brouard 6069:
6070: /* 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*/
6071: /* Skipping the case of missing values by reducing nbcode to 0 and 1 and not -1, 0, 1 */
6072: /* model=V1+V2+V3, if V2=-1, 0 or 1, then nbcode[2][1]=0 and nbcode[2][2]=1 instead of
6073: * nbcode[2][1]=-1, nbcode[2][2]=0 and nbcode[2][3]=1 */
6074: /*, could be restored in the future */
6075: 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 6076: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
6077: break;
6078: }
6079: ij++;
1.287 brouard 6080: 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 6081: cptcode = ij; /* New max modality for covar j */
6082: } /* end of loop on modality i=-1 to 1 or more */
6083: break;
6084: case 1: /* Testing on varying covariate, could be simple and
6085: * should look at waves or product of fixed *
6086: * varying. No time to test -1, assuming 0 and 1 only */
6087: ij=0;
6088: for(i=0; i<=1;i++){
6089: nbcode[Tvar[k]][++ij]=i;
6090: }
6091: break;
6092: default:
6093: break;
6094: } /* end switch */
6095: } /* end dummy test */
1.334 brouard 6096: if(Dummy[k]==1 && Typevar[k] !=1){ /* Quantitative covariate and not age product */
1.311 brouard 6097: 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*/
1.335 brouard 6098: if(Tvar[k]<=0 || Tvar[k]>=NCOVMAX){
6099: printf("Error k=%d \n",k);
6100: exit(1);
6101: }
1.311 brouard 6102: if(isnan(covar[Tvar[k]][i])){
6103: printf("ERROR, IMaCh doesn't treat fixed quantitative covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
6104: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
6105: fflush(ficlog);
6106: exit(1);
6107: }
6108: }
1.335 brouard 6109: } /* end Quanti */
1.287 brouard 6110: } /* 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 6111:
6112: for (k=-1; k< maxncov; k++) Ndum[k]=0;
6113: /* Look at fixed dummy (single or product) covariates to check empty modalities */
6114: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
6115: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
6116: 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 */
6117: 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 */
6118: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
6119: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
6120:
6121: ij=0;
6122: /* for (i=0; i<= maxncov-1; i++) { /\* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) *\/ */
1.335 brouard 6123: for (k=1; k<= cptcovt; k++) { /* cptcovt: total number of covariates of the model (2) nbocc(+)+1 = 8 excepting constant and age and age*age */
6124: /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
1.242 brouard 6125: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
6126: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
1.335 brouard 6127: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy simple and non empty in the model */
6128: /* Typevar[k] =0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
6129: /* Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product*/
1.242 brouard 6130: /* If product not in single variable we don't print results */
6131: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
1.335 brouard 6132: ++ij;/* V5 + V4 + V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V1, *//* V5 quanti, V2 quanti, V4, V3, V1 dummies */
6133: /* k= 1 2 3 4 5 6 7 8 9 */
6134: /* Tvar[k]= 5 4 3 6 5 2 7 1 1 */
6135: /* ij 1 2 3 */
6136: /* Tvaraff[ij]= 4 3 1 */
6137: /* Tmodelind[ij]=2 3 9 */
6138: /* TmodelInvind[ij]=2 1 1 */
1.242 brouard 6139: 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*/
6140: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
6141: 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 */
6142: if(Fixed[k]!=0)
6143: anyvaryingduminmodel=1;
6144: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
6145: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
6146: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
6147: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
6148: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
6149: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
6150: }
6151: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
6152: /* ij--; */
6153: /* cptcoveff=ij; /\*Number of total covariates*\/ */
1.335 brouard 6154: *cptcov=ij; /* cptcov= Number of total real effective simple dummies (fixed or time arying) effective (used as cptcoveff in other functions)
1.242 brouard 6155: * because they can be excluded from the model and real
6156: * if in the model but excluded because missing values, but how to get k from ij?*/
6157: for(j=ij+1; j<= cptcovt; j++){
6158: Tvaraff[j]=0;
6159: Tmodelind[j]=0;
6160: }
6161: for(j=ntveff+1; j<= cptcovt; j++){
6162: TmodelInvind[j]=0;
6163: }
6164: /* To be sorted */
6165: ;
6166: }
1.126 brouard 6167:
1.145 brouard 6168:
1.126 brouard 6169: /*********** Health Expectancies ****************/
6170:
1.235 brouard 6171: 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 6172:
6173: {
6174: /* Health expectancies, no variances */
1.329 brouard 6175: /* cij is the combination in the list of combination of dummy covariates */
6176: /* strstart is a string of time at start of computing */
1.164 brouard 6177: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 6178: int nhstepma, nstepma; /* Decreasing with age */
6179: double age, agelim, hf;
6180: double ***p3mat;
6181: double eip;
6182:
1.238 brouard 6183: /* pstamp(ficreseij); */
1.126 brouard 6184: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
6185: fprintf(ficreseij,"# Age");
6186: for(i=1; i<=nlstate;i++){
6187: for(j=1; j<=nlstate;j++){
6188: fprintf(ficreseij," e%1d%1d ",i,j);
6189: }
6190: fprintf(ficreseij," e%1d. ",i);
6191: }
6192: fprintf(ficreseij,"\n");
6193:
6194:
6195: if(estepm < stepm){
6196: printf ("Problem %d lower than %d\n",estepm, stepm);
6197: }
6198: else hstepm=estepm;
6199: /* We compute the life expectancy from trapezoids spaced every estepm months
6200: * This is mainly to measure the difference between two models: for example
6201: * if stepm=24 months pijx are given only every 2 years and by summing them
6202: * we are calculating an estimate of the Life Expectancy assuming a linear
6203: * progression in between and thus overestimating or underestimating according
6204: * to the curvature of the survival function. If, for the same date, we
6205: * estimate the model with stepm=1 month, we can keep estepm to 24 months
6206: * to compare the new estimate of Life expectancy with the same linear
6207: * hypothesis. A more precise result, taking into account a more precise
6208: * curvature will be obtained if estepm is as small as stepm. */
6209:
6210: /* For example we decided to compute the life expectancy with the smallest unit */
6211: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6212: nhstepm is the number of hstepm from age to agelim
6213: nstepm is the number of stepm from age to agelin.
1.270 brouard 6214: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 6215: and note for a fixed period like estepm months */
6216: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
6217: survival function given by stepm (the optimization length). Unfortunately it
6218: means that if the survival funtion is printed only each two years of age and if
6219: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6220: results. So we changed our mind and took the option of the best precision.
6221: */
6222: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6223:
6224: agelim=AGESUP;
6225: /* If stepm=6 months */
6226: /* Computed by stepm unit matrices, product of hstepm matrices, stored
6227: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
6228:
6229: /* nhstepm age range expressed in number of stepm */
6230: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6231: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6232: /* if (stepm >= YEARM) hstepm=1;*/
6233: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6234: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6235:
6236: for (age=bage; age<=fage; age ++){
6237: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6238: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6239: /* if (stepm >= YEARM) hstepm=1;*/
6240: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
6241:
6242: /* If stepm=6 months */
6243: /* Computed by stepm unit matrices, product of hstepma matrices, stored
6244: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
1.330 brouard 6245: /* printf("HELLO evsij Entering hpxij age=%d cij=%d hstepm=%d x[1]=%f nres=%d\n",(int) age, cij, hstepm, x[1], nres); */
1.235 brouard 6246: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 6247:
6248: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6249:
6250: printf("%d|",(int)age);fflush(stdout);
6251: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
6252:
6253: /* Computing expectancies */
6254: for(i=1; i<=nlstate;i++)
6255: for(j=1; j<=nlstate;j++)
6256: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
6257: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
6258:
6259: /* 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]);*/
6260:
6261: }
6262:
6263: fprintf(ficreseij,"%3.0f",age );
6264: for(i=1; i<=nlstate;i++){
6265: eip=0;
6266: for(j=1; j<=nlstate;j++){
6267: eip +=eij[i][j][(int)age];
6268: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
6269: }
6270: fprintf(ficreseij,"%9.4f", eip );
6271: }
6272: fprintf(ficreseij,"\n");
6273:
6274: }
6275: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6276: printf("\n");
6277: fprintf(ficlog,"\n");
6278:
6279: }
6280:
1.235 brouard 6281: 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 6282:
6283: {
6284: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 6285: to initial status i, ei. .
1.126 brouard 6286: */
1.336 brouard 6287: /* Very time consuming function, but already optimized with precov */
1.126 brouard 6288: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
6289: int nhstepma, nstepma; /* Decreasing with age */
6290: double age, agelim, hf;
6291: double ***p3matp, ***p3matm, ***varhe;
6292: double **dnewm,**doldm;
6293: double *xp, *xm;
6294: double **gp, **gm;
6295: double ***gradg, ***trgradg;
6296: int theta;
6297:
6298: double eip, vip;
6299:
6300: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
6301: xp=vector(1,npar);
6302: xm=vector(1,npar);
6303: dnewm=matrix(1,nlstate*nlstate,1,npar);
6304: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
6305:
6306: pstamp(ficresstdeij);
6307: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
6308: fprintf(ficresstdeij,"# Age");
6309: for(i=1; i<=nlstate;i++){
6310: for(j=1; j<=nlstate;j++)
6311: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
6312: fprintf(ficresstdeij," e%1d. ",i);
6313: }
6314: fprintf(ficresstdeij,"\n");
6315:
6316: pstamp(ficrescveij);
6317: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
6318: fprintf(ficrescveij,"# Age");
6319: for(i=1; i<=nlstate;i++)
6320: for(j=1; j<=nlstate;j++){
6321: cptj= (j-1)*nlstate+i;
6322: for(i2=1; i2<=nlstate;i2++)
6323: for(j2=1; j2<=nlstate;j2++){
6324: cptj2= (j2-1)*nlstate+i2;
6325: if(cptj2 <= cptj)
6326: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
6327: }
6328: }
6329: fprintf(ficrescveij,"\n");
6330:
6331: if(estepm < stepm){
6332: printf ("Problem %d lower than %d\n",estepm, stepm);
6333: }
6334: else hstepm=estepm;
6335: /* We compute the life expectancy from trapezoids spaced every estepm months
6336: * This is mainly to measure the difference between two models: for example
6337: * if stepm=24 months pijx are given only every 2 years and by summing them
6338: * we are calculating an estimate of the Life Expectancy assuming a linear
6339: * progression in between and thus overestimating or underestimating according
6340: * to the curvature of the survival function. If, for the same date, we
6341: * estimate the model with stepm=1 month, we can keep estepm to 24 months
6342: * to compare the new estimate of Life expectancy with the same linear
6343: * hypothesis. A more precise result, taking into account a more precise
6344: * curvature will be obtained if estepm is as small as stepm. */
6345:
6346: /* For example we decided to compute the life expectancy with the smallest unit */
6347: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6348: nhstepm is the number of hstepm from age to agelim
6349: nstepm is the number of stepm from age to agelin.
6350: Look at hpijx to understand the reason of that which relies in memory size
6351: and note for a fixed period like estepm months */
6352: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
6353: survival function given by stepm (the optimization length). Unfortunately it
6354: means that if the survival funtion is printed only each two years of age and if
6355: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6356: results. So we changed our mind and took the option of the best precision.
6357: */
6358: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6359:
6360: /* If stepm=6 months */
6361: /* nhstepm age range expressed in number of stepm */
6362: agelim=AGESUP;
6363: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
6364: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6365: /* if (stepm >= YEARM) hstepm=1;*/
6366: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6367:
6368: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6369: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6370: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
6371: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
6372: gp=matrix(0,nhstepm,1,nlstate*nlstate);
6373: gm=matrix(0,nhstepm,1,nlstate*nlstate);
6374:
6375: for (age=bage; age<=fage; age ++){
6376: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6377: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6378: /* if (stepm >= YEARM) hstepm=1;*/
6379: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 6380:
1.126 brouard 6381: /* If stepm=6 months */
6382: /* Computed by stepm unit matrices, product of hstepma matrices, stored
6383: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
6384:
6385: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 6386:
1.126 brouard 6387: /* Computing Variances of health expectancies */
6388: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
6389: decrease memory allocation */
6390: for(theta=1; theta <=npar; theta++){
6391: for(i=1; i<=npar; i++){
1.222 brouard 6392: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6393: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 6394: }
1.235 brouard 6395: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
6396: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 6397:
1.126 brouard 6398: for(j=1; j<= nlstate; j++){
1.222 brouard 6399: for(i=1; i<=nlstate; i++){
6400: for(h=0; h<=nhstepm-1; h++){
6401: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
6402: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
6403: }
6404: }
1.126 brouard 6405: }
1.218 brouard 6406:
1.126 brouard 6407: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 6408: for(h=0; h<=nhstepm-1; h++){
6409: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
6410: }
1.126 brouard 6411: }/* End theta */
6412:
6413:
6414: for(h=0; h<=nhstepm-1; h++)
6415: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 6416: for(theta=1; theta <=npar; theta++)
6417: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 6418:
1.218 brouard 6419:
1.222 brouard 6420: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 6421: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 6422: varhe[ij][ji][(int)age] =0.;
1.218 brouard 6423:
1.222 brouard 6424: printf("%d|",(int)age);fflush(stdout);
6425: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
6426: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 6427: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 6428: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
6429: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
6430: for(ij=1;ij<=nlstate*nlstate;ij++)
6431: for(ji=1;ji<=nlstate*nlstate;ji++)
6432: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 6433: }
6434: }
1.320 brouard 6435: /* if((int)age ==50){ */
6436: /* printf(" age=%d cij=%d nres=%d varhe[%d][%d]=%f ",(int)age, cij, nres, 1,2,varhe[1][2]); */
6437: /* } */
1.126 brouard 6438: /* Computing expectancies */
1.235 brouard 6439: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 6440: for(i=1; i<=nlstate;i++)
6441: for(j=1; j<=nlstate;j++)
1.222 brouard 6442: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
6443: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 6444:
1.222 brouard 6445: /* 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 6446:
1.222 brouard 6447: }
1.269 brouard 6448:
6449: /* Standard deviation of expectancies ij */
1.126 brouard 6450: fprintf(ficresstdeij,"%3.0f",age );
6451: for(i=1; i<=nlstate;i++){
6452: eip=0.;
6453: vip=0.;
6454: for(j=1; j<=nlstate;j++){
1.222 brouard 6455: eip += eij[i][j][(int)age];
6456: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
6457: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
6458: 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 6459: }
6460: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
6461: }
6462: fprintf(ficresstdeij,"\n");
1.218 brouard 6463:
1.269 brouard 6464: /* Variance of expectancies ij */
1.126 brouard 6465: fprintf(ficrescveij,"%3.0f",age );
6466: for(i=1; i<=nlstate;i++)
6467: for(j=1; j<=nlstate;j++){
1.222 brouard 6468: cptj= (j-1)*nlstate+i;
6469: for(i2=1; i2<=nlstate;i2++)
6470: for(j2=1; j2<=nlstate;j2++){
6471: cptj2= (j2-1)*nlstate+i2;
6472: if(cptj2 <= cptj)
6473: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
6474: }
1.126 brouard 6475: }
6476: fprintf(ficrescveij,"\n");
1.218 brouard 6477:
1.126 brouard 6478: }
6479: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
6480: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
6481: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
6482: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
6483: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6484: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6485: printf("\n");
6486: fprintf(ficlog,"\n");
1.218 brouard 6487:
1.126 brouard 6488: free_vector(xm,1,npar);
6489: free_vector(xp,1,npar);
6490: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
6491: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
6492: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
6493: }
1.218 brouard 6494:
1.126 brouard 6495: /************ Variance ******************/
1.235 brouard 6496: 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 6497: {
1.279 brouard 6498: /** Variance of health expectancies
6499: * double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);
6500: * double **newm;
6501: * int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)
6502: */
1.218 brouard 6503:
6504: /* int movingaverage(); */
6505: double **dnewm,**doldm;
6506: double **dnewmp,**doldmp;
6507: int i, j, nhstepm, hstepm, h, nstepm ;
1.288 brouard 6508: int first=0;
1.218 brouard 6509: int k;
6510: double *xp;
1.279 brouard 6511: double **gp, **gm; /**< for var eij */
6512: double ***gradg, ***trgradg; /**< for var eij */
6513: double **gradgp, **trgradgp; /**< for var p point j */
6514: double *gpp, *gmp; /**< for var p point j */
6515: double **varppt; /**< for var p point j nlstate to nlstate+ndeath */
1.218 brouard 6516: double ***p3mat;
6517: double age,agelim, hf;
6518: /* double ***mobaverage; */
6519: int theta;
6520: char digit[4];
6521: char digitp[25];
6522:
6523: char fileresprobmorprev[FILENAMELENGTH];
6524:
6525: if(popbased==1){
6526: if(mobilav!=0)
6527: strcpy(digitp,"-POPULBASED-MOBILAV_");
6528: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
6529: }
6530: else
6531: strcpy(digitp,"-STABLBASED_");
1.126 brouard 6532:
1.218 brouard 6533: /* if (mobilav!=0) { */
6534: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6535: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
6536: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
6537: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
6538: /* } */
6539: /* } */
6540:
6541: strcpy(fileresprobmorprev,"PRMORPREV-");
6542: sprintf(digit,"%-d",ij);
6543: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
6544: strcat(fileresprobmorprev,digit); /* Tvar to be done */
6545: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
6546: strcat(fileresprobmorprev,fileresu);
6547: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
6548: printf("Problem with resultfile: %s\n", fileresprobmorprev);
6549: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
6550: }
6551: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
6552: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
6553: pstamp(ficresprobmorprev);
6554: 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 6555: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
1.337 brouard 6556:
6557: /* We use TinvDoQresult[nres][resultmodel[nres][j] we sort according to the equation model and the resultline: it is a choice */
6558: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ /\* To be done*\/ */
6559: /* fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
6560: /* } */
6561: for (j=1; j<= cptcovs; j++){ /* For each selected (single) quantitative value */ /* To be done*/
6562: fprintf(ficresprobmorprev," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 6563: }
1.337 brouard 6564: /* for(j=1;j<=cptcoveff;j++) */
6565: /* fprintf(ficresprobmorprev," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,TnsdVar[Tvaraff[j]])]); */
1.238 brouard 6566: fprintf(ficresprobmorprev,"\n");
6567:
1.218 brouard 6568: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
6569: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6570: fprintf(ficresprobmorprev," p.%-d SE",j);
6571: for(i=1; i<=nlstate;i++)
6572: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
6573: }
6574: fprintf(ficresprobmorprev,"\n");
6575:
6576: fprintf(ficgp,"\n# Routine varevsij");
6577: fprintf(ficgp,"\nunset title \n");
6578: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
6579: 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");
6580: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
1.279 brouard 6581:
1.218 brouard 6582: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6583: pstamp(ficresvij);
6584: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
6585: if(popbased==1)
6586: 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);
6587: else
6588: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
6589: fprintf(ficresvij,"# Age");
6590: for(i=1; i<=nlstate;i++)
6591: for(j=1; j<=nlstate;j++)
6592: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
6593: fprintf(ficresvij,"\n");
6594:
6595: xp=vector(1,npar);
6596: dnewm=matrix(1,nlstate,1,npar);
6597: doldm=matrix(1,nlstate,1,nlstate);
6598: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
6599: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6600:
6601: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
6602: gpp=vector(nlstate+1,nlstate+ndeath);
6603: gmp=vector(nlstate+1,nlstate+ndeath);
6604: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 6605:
1.218 brouard 6606: if(estepm < stepm){
6607: printf ("Problem %d lower than %d\n",estepm, stepm);
6608: }
6609: else hstepm=estepm;
6610: /* For example we decided to compute the life expectancy with the smallest unit */
6611: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6612: nhstepm is the number of hstepm from age to agelim
6613: nstepm is the number of stepm from age to agelim.
6614: Look at function hpijx to understand why because of memory size limitations,
6615: we decided (b) to get a life expectancy respecting the most precise curvature of the
6616: survival function given by stepm (the optimization length). Unfortunately it
6617: means that if the survival funtion is printed every two years of age and if
6618: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6619: results. So we changed our mind and took the option of the best precision.
6620: */
6621: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6622: agelim = AGESUP;
6623: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6624: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6625: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6626: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6627: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
6628: gp=matrix(0,nhstepm,1,nlstate);
6629: gm=matrix(0,nhstepm,1,nlstate);
6630:
6631:
6632: for(theta=1; theta <=npar; theta++){
6633: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
6634: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6635: }
1.279 brouard 6636: /**< Computes the prevalence limit with parameter theta shifted of delta up to ftolpl precision and
6637: * returns into prlim .
1.288 brouard 6638: */
1.242 brouard 6639: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.279 brouard 6640:
6641: /* If popbased = 1 we use crossection prevalences. Previous step is useless but prlim is created */
1.218 brouard 6642: if (popbased==1) {
6643: if(mobilav ==0){
6644: for(i=1; i<=nlstate;i++)
6645: prlim[i][i]=probs[(int)age][i][ij];
6646: }else{ /* mobilav */
6647: for(i=1; i<=nlstate;i++)
6648: prlim[i][i]=mobaverage[(int)age][i][ij];
6649: }
6650: }
1.295 brouard 6651: /**< Computes the shifted transition matrix \f$ {}{h}_p^{ij}x\f$ at horizon h.
1.279 brouard 6652: */
6653: 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 6654: /**< 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 6655: * at horizon h in state j including mortality.
6656: */
1.218 brouard 6657: for(j=1; j<= nlstate; j++){
6658: for(h=0; h<=nhstepm; h++){
6659: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
6660: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
6661: }
6662: }
1.279 brouard 6663: /* Next for computing shifted+ probability of death (h=1 means
1.218 brouard 6664: computed over hstepm matrices product = hstepm*stepm months)
1.279 brouard 6665: as a weighted average of prlim(i) * p(i,j) p.3=w1*p13 + w2*p23 .
1.218 brouard 6666: */
6667: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6668: for(i=1,gpp[j]=0.; i<= nlstate; i++)
6669: gpp[j] += prlim[i][i]*p3mat[i][j][1];
1.279 brouard 6670: }
6671:
6672: /* Again with minus shift */
1.218 brouard 6673:
6674: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
6675: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 6676:
1.242 brouard 6677: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 6678:
6679: if (popbased==1) {
6680: if(mobilav ==0){
6681: for(i=1; i<=nlstate;i++)
6682: prlim[i][i]=probs[(int)age][i][ij];
6683: }else{ /* mobilav */
6684: for(i=1; i<=nlstate;i++)
6685: prlim[i][i]=mobaverage[(int)age][i][ij];
6686: }
6687: }
6688:
1.235 brouard 6689: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 6690:
6691: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
6692: for(h=0; h<=nhstepm; h++){
6693: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
6694: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
6695: }
6696: }
6697: /* This for computing probability of death (h=1 means
6698: computed over hstepm matrices product = hstepm*stepm months)
6699: as a weighted average of prlim.
6700: */
6701: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6702: for(i=1,gmp[j]=0.; i<= nlstate; i++)
6703: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6704: }
1.279 brouard 6705: /* end shifting computations */
6706:
6707: /**< Computing gradient matrix at horizon h
6708: */
1.218 brouard 6709: for(j=1; j<= nlstate; j++) /* vareij */
6710: for(h=0; h<=nhstepm; h++){
6711: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
6712: }
1.279 brouard 6713: /**< Gradient of overall mortality p.3 (or p.j)
6714: */
6715: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu mortality from j */
1.218 brouard 6716: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
6717: }
6718:
6719: } /* End theta */
1.279 brouard 6720:
6721: /* We got the gradient matrix for each theta and state j */
1.218 brouard 6722: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
6723:
6724: for(h=0; h<=nhstepm; h++) /* veij */
6725: for(j=1; j<=nlstate;j++)
6726: for(theta=1; theta <=npar; theta++)
6727: trgradg[h][j][theta]=gradg[h][theta][j];
6728:
6729: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
6730: for(theta=1; theta <=npar; theta++)
6731: trgradgp[j][theta]=gradgp[theta][j];
1.279 brouard 6732: /**< as well as its transposed matrix
6733: */
1.218 brouard 6734:
6735: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6736: for(i=1;i<=nlstate;i++)
6737: for(j=1;j<=nlstate;j++)
6738: vareij[i][j][(int)age] =0.;
1.279 brouard 6739:
6740: /* Computing trgradg by matcov by gradg at age and summing over h
6741: * and k (nhstepm) formula 15 of article
6742: * Lievre-Brouard-Heathcote
6743: */
6744:
1.218 brouard 6745: for(h=0;h<=nhstepm;h++){
6746: for(k=0;k<=nhstepm;k++){
6747: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
6748: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
6749: for(i=1;i<=nlstate;i++)
6750: for(j=1;j<=nlstate;j++)
6751: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
6752: }
6753: }
6754:
1.279 brouard 6755: /* pptj is p.3 or p.j = trgradgp by cov by gradgp, variance of
6756: * p.j overall mortality formula 49 but computed directly because
6757: * we compute the grad (wix pijx) instead of grad (pijx),even if
6758: * wix is independent of theta.
6759: */
1.218 brouard 6760: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
6761: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
6762: for(j=nlstate+1;j<=nlstate+ndeath;j++)
6763: for(i=nlstate+1;i<=nlstate+ndeath;i++)
6764: varppt[j][i]=doldmp[j][i];
6765: /* end ppptj */
6766: /* x centered again */
6767:
1.242 brouard 6768: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 6769:
6770: if (popbased==1) {
6771: if(mobilav ==0){
6772: for(i=1; i<=nlstate;i++)
6773: prlim[i][i]=probs[(int)age][i][ij];
6774: }else{ /* mobilav */
6775: for(i=1; i<=nlstate;i++)
6776: prlim[i][i]=mobaverage[(int)age][i][ij];
6777: }
6778: }
6779:
6780: /* This for computing probability of death (h=1 means
6781: computed over hstepm (estepm) matrices product = hstepm*stepm months)
6782: as a weighted average of prlim.
6783: */
1.235 brouard 6784: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 6785: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6786: for(i=1,gmp[j]=0.;i<= nlstate; i++)
6787: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6788: }
6789: /* end probability of death */
6790:
6791: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
6792: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6793: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
6794: for(i=1; i<=nlstate;i++){
6795: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
6796: }
6797: }
6798: fprintf(ficresprobmorprev,"\n");
6799:
6800: fprintf(ficresvij,"%.0f ",age );
6801: for(i=1; i<=nlstate;i++)
6802: for(j=1; j<=nlstate;j++){
6803: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
6804: }
6805: fprintf(ficresvij,"\n");
6806: free_matrix(gp,0,nhstepm,1,nlstate);
6807: free_matrix(gm,0,nhstepm,1,nlstate);
6808: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
6809: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
6810: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6811: } /* End age */
6812: free_vector(gpp,nlstate+1,nlstate+ndeath);
6813: free_vector(gmp,nlstate+1,nlstate+ndeath);
6814: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
6815: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
6816: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
6817: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
6818: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
6819: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
6820: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
6821: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
6822: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
6823: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
6824: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
6825: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
6826: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
6827: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
6828: 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);
6829: /* 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 6830: */
1.218 brouard 6831: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
6832: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 6833:
1.218 brouard 6834: free_vector(xp,1,npar);
6835: free_matrix(doldm,1,nlstate,1,nlstate);
6836: free_matrix(dnewm,1,nlstate,1,npar);
6837: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6838: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
6839: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6840: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6841: fclose(ficresprobmorprev);
6842: fflush(ficgp);
6843: fflush(fichtm);
6844: } /* end varevsij */
1.126 brouard 6845:
6846: /************ Variance of prevlim ******************/
1.269 brouard 6847: 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 6848: {
1.205 brouard 6849: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 6850: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 6851:
1.268 brouard 6852: double **dnewmpar,**doldm;
1.126 brouard 6853: int i, j, nhstepm, hstepm;
6854: double *xp;
6855: double *gp, *gm;
6856: double **gradg, **trgradg;
1.208 brouard 6857: double **mgm, **mgp;
1.126 brouard 6858: double age,agelim;
6859: int theta;
6860:
6861: pstamp(ficresvpl);
1.288 brouard 6862: fprintf(ficresvpl,"# Standard deviation of period (forward stable) prevalences \n");
1.241 brouard 6863: fprintf(ficresvpl,"# Age ");
6864: if(nresult >=1)
6865: fprintf(ficresvpl," Result# ");
1.126 brouard 6866: for(i=1; i<=nlstate;i++)
6867: fprintf(ficresvpl," %1d-%1d",i,i);
6868: fprintf(ficresvpl,"\n");
6869:
6870: xp=vector(1,npar);
1.268 brouard 6871: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 6872: doldm=matrix(1,nlstate,1,nlstate);
6873:
6874: hstepm=1*YEARM; /* Every year of age */
6875: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6876: agelim = AGESUP;
6877: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6878: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6879: if (stepm >= YEARM) hstepm=1;
6880: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6881: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 6882: mgp=matrix(1,npar,1,nlstate);
6883: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 6884: gp=vector(1,nlstate);
6885: gm=vector(1,nlstate);
6886:
6887: for(theta=1; theta <=npar; theta++){
6888: for(i=1; i<=npar; i++){ /* Computes gradient */
6889: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6890: }
1.288 brouard 6891: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
6892: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
6893: /* else */
6894: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6895: for(i=1;i<=nlstate;i++){
1.126 brouard 6896: gp[i] = prlim[i][i];
1.208 brouard 6897: mgp[theta][i] = prlim[i][i];
6898: }
1.126 brouard 6899: for(i=1; i<=npar; i++) /* Computes gradient */
6900: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 6901: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
6902: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
6903: /* else */
6904: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6905: for(i=1;i<=nlstate;i++){
1.126 brouard 6906: gm[i] = prlim[i][i];
1.208 brouard 6907: mgm[theta][i] = prlim[i][i];
6908: }
1.126 brouard 6909: for(i=1;i<=nlstate;i++)
6910: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 6911: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 6912: } /* End theta */
6913:
6914: trgradg =matrix(1,nlstate,1,npar);
6915:
6916: for(j=1; j<=nlstate;j++)
6917: for(theta=1; theta <=npar; theta++)
6918: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 6919: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6920: /* printf("\nmgm mgp %d ",(int)age); */
6921: /* for(j=1; j<=nlstate;j++){ */
6922: /* printf(" %d ",j); */
6923: /* for(theta=1; theta <=npar; theta++) */
6924: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6925: /* printf("\n "); */
6926: /* } */
6927: /* } */
6928: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6929: /* printf("\n gradg %d ",(int)age); */
6930: /* for(j=1; j<=nlstate;j++){ */
6931: /* printf("%d ",j); */
6932: /* for(theta=1; theta <=npar; theta++) */
6933: /* printf("%d %lf ",theta,gradg[theta][j]); */
6934: /* printf("\n "); */
6935: /* } */
6936: /* } */
1.126 brouard 6937:
6938: for(i=1;i<=nlstate;i++)
6939: varpl[i][(int)age] =0.;
1.209 brouard 6940: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 brouard 6941: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6942: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6943: }else{
1.268 brouard 6944: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6945: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6946: }
1.126 brouard 6947: for(i=1;i<=nlstate;i++)
6948: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6949:
6950: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 6951: if(nresult >=1)
6952: fprintf(ficresvpl,"%d ",nres );
1.288 brouard 6953: for(i=1; i<=nlstate;i++){
1.126 brouard 6954: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
1.288 brouard 6955: /* for(j=1;j<=nlstate;j++) */
6956: /* fprintf(ficresvpl," %d %.5f ",j,prlim[j][i]); */
6957: }
1.126 brouard 6958: fprintf(ficresvpl,"\n");
6959: free_vector(gp,1,nlstate);
6960: free_vector(gm,1,nlstate);
1.208 brouard 6961: free_matrix(mgm,1,npar,1,nlstate);
6962: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 6963: free_matrix(gradg,1,npar,1,nlstate);
6964: free_matrix(trgradg,1,nlstate,1,npar);
6965: } /* End age */
6966:
6967: free_vector(xp,1,npar);
6968: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 6969: free_matrix(dnewmpar,1,nlstate,1,nlstate);
6970:
6971: }
6972:
6973:
6974: /************ Variance of backprevalence limit ******************/
1.269 brouard 6975: 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 6976: {
6977: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
6978: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
6979:
6980: double **dnewmpar,**doldm;
6981: int i, j, nhstepm, hstepm;
6982: double *xp;
6983: double *gp, *gm;
6984: double **gradg, **trgradg;
6985: double **mgm, **mgp;
6986: double age,agelim;
6987: int theta;
6988:
6989: pstamp(ficresvbl);
6990: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
6991: fprintf(ficresvbl,"# Age ");
6992: if(nresult >=1)
6993: fprintf(ficresvbl," Result# ");
6994: for(i=1; i<=nlstate;i++)
6995: fprintf(ficresvbl," %1d-%1d",i,i);
6996: fprintf(ficresvbl,"\n");
6997:
6998: xp=vector(1,npar);
6999: dnewmpar=matrix(1,nlstate,1,npar);
7000: doldm=matrix(1,nlstate,1,nlstate);
7001:
7002: hstepm=1*YEARM; /* Every year of age */
7003: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
7004: agelim = AGEINF;
7005: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
7006: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
7007: if (stepm >= YEARM) hstepm=1;
7008: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
7009: gradg=matrix(1,npar,1,nlstate);
7010: mgp=matrix(1,npar,1,nlstate);
7011: mgm=matrix(1,npar,1,nlstate);
7012: gp=vector(1,nlstate);
7013: gm=vector(1,nlstate);
7014:
7015: for(theta=1; theta <=npar; theta++){
7016: for(i=1; i<=npar; i++){ /* Computes gradient */
7017: xp[i] = x[i] + (i==theta ?delti[theta]:0);
7018: }
7019: if(mobilavproj > 0 )
7020: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7021: else
7022: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7023: for(i=1;i<=nlstate;i++){
7024: gp[i] = bprlim[i][i];
7025: mgp[theta][i] = bprlim[i][i];
7026: }
7027: for(i=1; i<=npar; i++) /* Computes gradient */
7028: xp[i] = x[i] - (i==theta ?delti[theta]:0);
7029: if(mobilavproj > 0 )
7030: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7031: else
7032: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7033: for(i=1;i<=nlstate;i++){
7034: gm[i] = bprlim[i][i];
7035: mgm[theta][i] = bprlim[i][i];
7036: }
7037: for(i=1;i<=nlstate;i++)
7038: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
7039: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
7040: } /* End theta */
7041:
7042: trgradg =matrix(1,nlstate,1,npar);
7043:
7044: for(j=1; j<=nlstate;j++)
7045: for(theta=1; theta <=npar; theta++)
7046: trgradg[j][theta]=gradg[theta][j];
7047: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7048: /* printf("\nmgm mgp %d ",(int)age); */
7049: /* for(j=1; j<=nlstate;j++){ */
7050: /* printf(" %d ",j); */
7051: /* for(theta=1; theta <=npar; theta++) */
7052: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
7053: /* printf("\n "); */
7054: /* } */
7055: /* } */
7056: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7057: /* printf("\n gradg %d ",(int)age); */
7058: /* for(j=1; j<=nlstate;j++){ */
7059: /* printf("%d ",j); */
7060: /* for(theta=1; theta <=npar; theta++) */
7061: /* printf("%d %lf ",theta,gradg[theta][j]); */
7062: /* printf("\n "); */
7063: /* } */
7064: /* } */
7065:
7066: for(i=1;i<=nlstate;i++)
7067: varbpl[i][(int)age] =0.;
7068: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
7069: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7070: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
7071: }else{
7072: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7073: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
7074: }
7075: for(i=1;i<=nlstate;i++)
7076: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
7077:
7078: fprintf(ficresvbl,"%.0f ",age );
7079: if(nresult >=1)
7080: fprintf(ficresvbl,"%d ",nres );
7081: for(i=1; i<=nlstate;i++)
7082: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
7083: fprintf(ficresvbl,"\n");
7084: free_vector(gp,1,nlstate);
7085: free_vector(gm,1,nlstate);
7086: free_matrix(mgm,1,npar,1,nlstate);
7087: free_matrix(mgp,1,npar,1,nlstate);
7088: free_matrix(gradg,1,npar,1,nlstate);
7089: free_matrix(trgradg,1,nlstate,1,npar);
7090: } /* End age */
7091:
7092: free_vector(xp,1,npar);
7093: free_matrix(doldm,1,nlstate,1,npar);
7094: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 7095:
7096: }
7097:
7098: /************ Variance of one-step probabilities ******************/
7099: 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 7100: {
7101: int i, j=0, k1, l1, tj;
7102: int k2, l2, j1, z1;
7103: int k=0, l;
7104: int first=1, first1, first2;
1.326 brouard 7105: int nres=0; /* New */
1.222 brouard 7106: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
7107: double **dnewm,**doldm;
7108: double *xp;
7109: double *gp, *gm;
7110: double **gradg, **trgradg;
7111: double **mu;
7112: double age, cov[NCOVMAX+1];
7113: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
7114: int theta;
7115: char fileresprob[FILENAMELENGTH];
7116: char fileresprobcov[FILENAMELENGTH];
7117: char fileresprobcor[FILENAMELENGTH];
7118: double ***varpij;
7119:
7120: strcpy(fileresprob,"PROB_");
7121: strcat(fileresprob,fileres);
7122: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
7123: printf("Problem with resultfile: %s\n", fileresprob);
7124: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
7125: }
7126: strcpy(fileresprobcov,"PROBCOV_");
7127: strcat(fileresprobcov,fileresu);
7128: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
7129: printf("Problem with resultfile: %s\n", fileresprobcov);
7130: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
7131: }
7132: strcpy(fileresprobcor,"PROBCOR_");
7133: strcat(fileresprobcor,fileresu);
7134: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
7135: printf("Problem with resultfile: %s\n", fileresprobcor);
7136: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
7137: }
7138: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
7139: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
7140: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
7141: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
7142: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
7143: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
7144: pstamp(ficresprob);
7145: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
7146: fprintf(ficresprob,"# Age");
7147: pstamp(ficresprobcov);
7148: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
7149: fprintf(ficresprobcov,"# Age");
7150: pstamp(ficresprobcor);
7151: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
7152: fprintf(ficresprobcor,"# Age");
1.126 brouard 7153:
7154:
1.222 brouard 7155: for(i=1; i<=nlstate;i++)
7156: for(j=1; j<=(nlstate+ndeath);j++){
7157: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
7158: fprintf(ficresprobcov," p%1d-%1d ",i,j);
7159: fprintf(ficresprobcor," p%1d-%1d ",i,j);
7160: }
7161: /* fprintf(ficresprob,"\n");
7162: fprintf(ficresprobcov,"\n");
7163: fprintf(ficresprobcor,"\n");
7164: */
7165: xp=vector(1,npar);
7166: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
7167: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
7168: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
7169: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
7170: first=1;
7171: fprintf(ficgp,"\n# Routine varprob");
7172: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
7173: fprintf(fichtm,"\n");
7174:
1.288 brouard 7175: 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 7176: 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);
7177: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 7178: and drawn. It helps understanding how is the covariance between two incidences.\
7179: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 7180: 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 7181: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
7182: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
7183: standard deviations wide on each axis. <br>\
7184: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
7185: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
7186: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
7187:
1.222 brouard 7188: cov[1]=1;
7189: /* tj=cptcoveff; */
1.225 brouard 7190: tj = (int) pow(2,cptcoveff);
1.222 brouard 7191: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
7192: j1=0;
1.332 brouard 7193:
7194: for(nres=1;nres <=nresult; nres++){ /* For each resultline */
7195: for(j1=1; j1<=tj;j1++){ /* For any combination of dummy covariates, fixed and varying */
1.334 brouard 7196: printf("Varprob TKresult[nres]=%d j1=%d, nres=%d, cptcovn=%d, cptcoveff=%d tj=%d cptcovs=%d\n", TKresult[nres], j1, nres, cptcovn, cptcoveff, tj, cptcovs);
1.332 brouard 7197: if(tj != 1 && TKresult[nres]!= j1)
7198: continue;
7199:
7200: /* for(j1=1; j1<=tj;j1++){ /\* For each valid combination of covariates or only once*\/ */
7201: /* for(nres=1;nres <=1; nres++){ /\* For each resultline *\/ */
7202: /* /\* for(nres=1;nres <=nresult; nres++){ /\\* For each resultline *\\/ *\/ */
1.222 brouard 7203: if (cptcovn>0) {
1.334 brouard 7204: fprintf(ficresprob, "\n#********** Variable ");
7205: fprintf(ficresprobcov, "\n#********** Variable ");
7206: fprintf(ficgp, "\n#********** Variable ");
7207: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
7208: fprintf(ficresprobcor, "\n#********** Variable ");
7209:
7210: /* Including quantitative variables of the resultline to be done */
7211: for (z1=1; z1<=cptcovs; z1++){ /* Loop on each variable of this resultline */
1.338 ! brouard 7212: printf("Varprob modelresult[%d][%d]=%d model=1+age+%s \n",nres, z1, modelresult[nres][z1], model);
! 7213: fprintf(ficlog,"Varprob modelresult[%d][%d]=%d model=1+age+%s \n",nres, z1, modelresult[nres][z1], model);
! 7214: /* fprintf(ficlog,"Varprob modelresult[%d][%d]=%d model=1+age+%s resultline[%d]=%s \n",nres, z1, modelresult[nres][z1], model, nres, resultline[nres]); */
1.334 brouard 7215: if(Dummy[modelresult[nres][z1]]==0){/* Dummy variable of the variable in position modelresult in the model corresponding to z1 in resultline */
7216: if(Fixed[modelresult[nres][z1]]==0){ /* Fixed referenced to model equation */
7217: fprintf(ficresprob,"V%d=%d ",Tvresult[nres][z1],Tresult[nres][z1]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline */
7218: fprintf(ficresprobcov,"V%d=%d ",Tvresult[nres][z1],Tresult[nres][z1]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline */
7219: fprintf(ficgp,"V%d=%d ",Tvresult[nres][z1],Tresult[nres][z1]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline */
7220: fprintf(fichtmcov,"V%d=%d ",Tvresult[nres][z1],Tresult[nres][z1]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline */
7221: fprintf(ficresprobcor,"V%d=%d ",Tvresult[nres][z1],Tresult[nres][z1]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline */
7222: fprintf(ficresprob,"fixed ");
7223: fprintf(ficresprobcov,"fixed ");
7224: fprintf(ficgp,"fixed ");
7225: fprintf(fichtmcov,"fixed ");
7226: fprintf(ficresprobcor,"fixed ");
7227: }else{
7228: fprintf(ficresprob,"varyi ");
7229: fprintf(ficresprobcov,"varyi ");
7230: fprintf(ficgp,"varyi ");
7231: fprintf(fichtmcov,"varyi ");
7232: fprintf(ficresprobcor,"varyi ");
7233: }
7234: }else if(Dummy[modelresult[nres][z1]]==1){ /* Quanti variable */
7235: /* For each selected (single) quantitative value */
1.337 brouard 7236: fprintf(ficresprob," V%d=%lg ",Tvqresult[nres][z1],Tqresult[nres][z1]);
1.334 brouard 7237: if(Fixed[modelresult[nres][z1]]==0){ /* Fixed */
7238: fprintf(ficresprob,"fixed ");
7239: fprintf(ficresprobcov,"fixed ");
7240: fprintf(ficgp,"fixed ");
7241: fprintf(fichtmcov,"fixed ");
7242: fprintf(ficresprobcor,"fixed ");
7243: }else{
7244: fprintf(ficresprob,"varyi ");
7245: fprintf(ficresprobcov,"varyi ");
7246: fprintf(ficgp,"varyi ");
7247: fprintf(fichtmcov,"varyi ");
7248: fprintf(ficresprobcor,"varyi ");
7249: }
7250: }else{
7251: printf("Error in varprob() Dummy[modelresult[%d][%d]]=%d, modelresult[%d][%d]=V%d cptcovs=%d, cptcoveff=%d \n", nres, z1, Dummy[modelresult[nres][z1]],nres,z1,modelresult[nres][z1],cptcovs, cptcoveff); /* end if dummy or quanti */
7252: fprintf(ficlog,"Error in varprob() Dummy[modelresult[%d][%d]]=%d, modelresult[%d][%d]=V%d cptcovs=%d, cptcoveff=%d \n", nres, z1, Dummy[modelresult[nres][z1]],nres,z1,modelresult[nres][z1],cptcovs, cptcoveff); /* end if dummy or quanti */
7253: exit(1);
7254: }
7255: } /* End loop on variable of this resultline */
7256: /* for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]); */
1.222 brouard 7257: fprintf(ficresprob, "**********\n#\n");
7258: fprintf(ficresprobcov, "**********\n#\n");
7259: fprintf(ficgp, "**********\n#\n");
7260: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
7261: fprintf(ficresprobcor, "**********\n#");
7262: if(invalidvarcomb[j1]){
7263: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
7264: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
7265: continue;
7266: }
7267: }
7268: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
7269: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
7270: gp=vector(1,(nlstate)*(nlstate+ndeath));
7271: gm=vector(1,(nlstate)*(nlstate+ndeath));
1.334 brouard 7272: for (age=bage; age<=fage; age ++){ /* Fo each age we feed the model equation with covariates, using precov as in hpxij() ? */
1.222 brouard 7273: cov[2]=age;
7274: if(nagesqr==1)
7275: cov[3]= age*age;
1.334 brouard 7276: /* New code end of combination but for each resultline */
7277: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
7278: if(Typevar[k1]==1){ /* A product with age */
7279: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.326 brouard 7280: }else{
1.334 brouard 7281: cov[2+nagesqr+k1]=precov[nres][k1];
1.326 brouard 7282: }
1.334 brouard 7283: }/* End of loop on model equation */
7284: /* Old code */
7285: /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
7286: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)]; *\/ */
7287: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
7288: /* /\* Here comes the value of the covariate 'j1' after renumbering k with single dummy covariates *\/ */
7289: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(j1,TnsdVar[TvarsD[k]])]; */
7290: /* /\*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*\//\* j1 1 2 3 4 */
7291: /* * 1 1 1 1 1 */
7292: /* * 2 2 1 1 1 */
7293: /* * 3 1 2 1 1 */
7294: /* *\/ */
7295: /* /\* nbcode[1][1]=0 nbcode[1][2]=1;*\/ */
7296: /* } */
7297: /* /\* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1, Tage[1]=2 *\/ */
7298: /* /\* ) p nbcode[Tvar[Tage[k]]][(1 & (ij-1) >> (k-1))+1] *\/ */
7299: /* /\*for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; *\/ */
7300: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
7301: /* if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
7302: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(j1,TnsdVar[Tvar[Tage[k]]])]*cov[2]; */
7303: /* /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
7304: /* } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
7305: /* printf("Internal IMaCh error, don't know which value for quantitative covariate with age, Tage[k]%d, k=%d, Tvar[Tage[k]]=V%d, age=%d\n",Tage[k],k ,Tvar[Tage[k]], (int)cov[2]); */
7306: /* /\* cov[2+nagesqr+Tage[k]]=meanq[k]/idq[k]*cov[2];/\\* Using the mean of quantitative variable Tvar[Tage[k]] /\\* Tqresult[nres][k]; *\\/ *\/ */
7307: /* /\* exit(1); *\/ */
7308: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
7309: /* } */
7310: /* /\* cov[2+Tage[k]+nagesqr]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
7311: /* } */
7312: /* for (k=1; k<=cptcovprod;k++){/\* For product without age *\/ */
7313: /* if(Dummy[Tvard[k][1]]==0){ */
7314: /* if(Dummy[Tvard[k][2]]==0){ */
7315: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(j1,TnsdVar[Tvard[k][1]])] * nbcode[Tvard[k][2]][codtabm(j1,TnsdVar[Tvard[k][2]])]; */
7316: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
7317: /* }else{ /\* Should we use the mean of the quantitative variables? *\/ */
7318: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(j1,TnsdVar[Tvard[k][1]])] * Tqresult[nres][resultmodel[nres][k]]; */
7319: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
7320: /* } */
7321: /* }else{ */
7322: /* if(Dummy[Tvard[k][2]]==0){ */
7323: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(j1,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][TnsdVar[Tvard[k][1]]]; */
7324: /* /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
7325: /* }else{ */
7326: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][TnsdVar[Tvard[k][1]]]* Tqinvresult[nres][TnsdVar[Tvard[k][2]]]; */
7327: /* /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\/ */
7328: /* } */
7329: /* } */
7330: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
7331: /* } */
1.326 brouard 7332: /* For each age and combination of dummy covariates we slightly move the parameters of delti in order to get the gradient*/
1.222 brouard 7333: for(theta=1; theta <=npar; theta++){
7334: for(i=1; i<=npar; i++)
7335: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 7336:
1.222 brouard 7337: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 7338:
1.222 brouard 7339: k=0;
7340: for(i=1; i<= (nlstate); i++){
7341: for(j=1; j<=(nlstate+ndeath);j++){
7342: k=k+1;
7343: gp[k]=pmmij[i][j];
7344: }
7345: }
1.220 brouard 7346:
1.222 brouard 7347: for(i=1; i<=npar; i++)
7348: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 7349:
1.222 brouard 7350: pmij(pmmij,cov,ncovmodel,xp,nlstate);
7351: k=0;
7352: for(i=1; i<=(nlstate); i++){
7353: for(j=1; j<=(nlstate+ndeath);j++){
7354: k=k+1;
7355: gm[k]=pmmij[i][j];
7356: }
7357: }
1.220 brouard 7358:
1.222 brouard 7359: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
7360: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
7361: }
1.126 brouard 7362:
1.222 brouard 7363: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
7364: for(theta=1; theta <=npar; theta++)
7365: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 7366:
1.222 brouard 7367: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
7368: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 7369:
1.222 brouard 7370: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 7371:
1.222 brouard 7372: k=0;
7373: for(i=1; i<=(nlstate); i++){
7374: for(j=1; j<=(nlstate+ndeath);j++){
7375: k=k+1;
7376: mu[k][(int) age]=pmmij[i][j];
7377: }
7378: }
7379: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
7380: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
7381: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 7382:
1.222 brouard 7383: /*printf("\n%d ",(int)age);
7384: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
7385: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
7386: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
7387: }*/
1.220 brouard 7388:
1.222 brouard 7389: fprintf(ficresprob,"\n%d ",(int)age);
7390: fprintf(ficresprobcov,"\n%d ",(int)age);
7391: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 7392:
1.222 brouard 7393: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
7394: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
7395: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
7396: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
7397: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
7398: }
7399: i=0;
7400: for (k=1; k<=(nlstate);k++){
7401: for (l=1; l<=(nlstate+ndeath);l++){
7402: i++;
7403: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
7404: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
7405: for (j=1; j<=i;j++){
7406: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
7407: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
7408: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
7409: }
7410: }
7411: }/* end of loop for state */
7412: } /* end of loop for age */
7413: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
7414: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
7415: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7416: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7417:
7418: /* Confidence intervalle of pij */
7419: /*
7420: fprintf(ficgp,"\nunset parametric;unset label");
7421: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
7422: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
7423: 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);
7424: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
7425: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
7426: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
7427: */
7428:
7429: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
7430: first1=1;first2=2;
7431: for (k2=1; k2<=(nlstate);k2++){
7432: for (l2=1; l2<=(nlstate+ndeath);l2++){
7433: if(l2==k2) continue;
7434: j=(k2-1)*(nlstate+ndeath)+l2;
7435: for (k1=1; k1<=(nlstate);k1++){
7436: for (l1=1; l1<=(nlstate+ndeath);l1++){
7437: if(l1==k1) continue;
7438: i=(k1-1)*(nlstate+ndeath)+l1;
7439: if(i<=j) continue;
7440: for (age=bage; age<=fage; age ++){
7441: if ((int)age %5==0){
7442: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
7443: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
7444: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
7445: mu1=mu[i][(int) age]/stepm*YEARM ;
7446: mu2=mu[j][(int) age]/stepm*YEARM;
7447: c12=cv12/sqrt(v1*v2);
7448: /* Computing eigen value of matrix of covariance */
7449: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7450: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7451: if ((lc2 <0) || (lc1 <0) ){
7452: if(first2==1){
7453: first1=0;
7454: 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);
7455: }
7456: 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);
7457: /* lc1=fabs(lc1); */ /* If we want to have them positive */
7458: /* lc2=fabs(lc2); */
7459: }
1.220 brouard 7460:
1.222 brouard 7461: /* Eigen vectors */
1.280 brouard 7462: if(1+(v1-lc1)*(v1-lc1)/cv12/cv12 <1.e-5){
7463: printf(" Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7464: fprintf(ficlog," Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7465: v11=(1./sqrt(fabs(1+(v1-lc1)*(v1-lc1)/cv12/cv12)));
7466: }else
7467: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
1.222 brouard 7468: /*v21=sqrt(1.-v11*v11); *//* error */
7469: v21=(lc1-v1)/cv12*v11;
7470: v12=-v21;
7471: v22=v11;
7472: tnalp=v21/v11;
7473: if(first1==1){
7474: first1=0;
7475: 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);
7476: }
7477: 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);
7478: /*printf(fignu*/
7479: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
7480: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
7481: if(first==1){
7482: first=0;
7483: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
7484: fprintf(ficgp,"\nset parametric;unset label");
7485: 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);
7486: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 7487: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 7488: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 7489: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 7490: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
7491: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7492: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7493: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
7494: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7495: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
7496: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
7497: 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 7498: mu1,std,v11,sqrt(fabs(lc1)),v12,sqrt(fabs(lc2)), \
7499: mu2,std,v21,sqrt(fabs(lc1)),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 7500: }else{
7501: first=0;
7502: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
7503: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
7504: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
7505: 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 7506: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
7507: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 7508: }/* if first */
7509: } /* age mod 5 */
7510: } /* end loop age */
7511: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7512: first=1;
7513: } /*l12 */
7514: } /* k12 */
7515: } /*l1 */
7516: }/* k1 */
1.332 brouard 7517: } /* loop on combination of covariates j1 */
1.326 brouard 7518: } /* loop on nres */
1.222 brouard 7519: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
7520: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
7521: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
7522: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
7523: free_vector(xp,1,npar);
7524: fclose(ficresprob);
7525: fclose(ficresprobcov);
7526: fclose(ficresprobcor);
7527: fflush(ficgp);
7528: fflush(fichtmcov);
7529: }
1.126 brouard 7530:
7531:
7532: /******************* Printing html file ***********/
1.201 brouard 7533: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 7534: int lastpass, int stepm, int weightopt, char model[],\
7535: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.296 brouard 7536: int popforecast, int mobilav, int prevfcast, int mobilavproj, int prevbcast, int estepm , \
7537: double jprev1, double mprev1,double anprev1, double dateprev1, double dateprojd, double dateback1, \
7538: double jprev2, double mprev2,double anprev2, double dateprev2, double dateprojf, double dateback2){
1.237 brouard 7539: int jj1, k1, i1, cpt, k4, nres;
1.319 brouard 7540: /* In fact some results are already printed in fichtm which is open */
1.126 brouard 7541: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
7542: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
7543: </ul>");
1.319 brouard 7544: /* fprintf(fichtm,"<ul><li> model=1+age+%s\n \ */
7545: /* </ul>", model); */
1.214 brouard 7546: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
7547: 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",
7548: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
1.332 brouard 7549: fprintf(fichtm,"<li> - Observed prevalence (cross-sectional 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 7550: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
7551: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 7552: fprintf(fichtm,"\
7553: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 7554: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 7555: fprintf(fichtm,"\
1.217 brouard 7556: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
7557: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
7558: fprintf(fichtm,"\
1.288 brouard 7559: - Period (forward) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 7560: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 7561: fprintf(fichtm,"\
1.288 brouard 7562: - Backward prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.217 brouard 7563: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
7564: fprintf(fichtm,"\
1.211 brouard 7565: - (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 7566: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 7567: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 7568: if(prevfcast==1){
7569: fprintf(fichtm,"\
7570: - Prevalence projections by age and states: \
1.201 brouard 7571: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 7572: }
1.126 brouard 7573:
7574:
1.225 brouard 7575: m=pow(2,cptcoveff);
1.222 brouard 7576: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 7577:
1.317 brouard 7578: fprintf(fichtm," \n<ul><li><b>Graphs (first order)</b></li><p>");
1.264 brouard 7579:
7580: jj1=0;
7581:
7582: fprintf(fichtm," \n<ul>");
1.337 brouard 7583: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
7584: /* k1=nres; */
1.338 ! brouard 7585: k1=TKresult[nres];
! 7586: if(TKresult[nres]==0)k1=1; /* To be checked for no result */
1.337 brouard 7587: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
7588: /* if(m != 1 && TKresult[nres]!= k1) */
7589: /* continue; */
1.264 brouard 7590: jj1++;
7591: if (cptcovn > 0) {
7592: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
1.337 brouard 7593: for (cpt=1; cpt<=cptcovs;cpt++){ /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
7594: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 7595: }
1.337 brouard 7596: /* for (cpt=1; cpt<=cptcoveff;cpt++){ */
7597: /* fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]); */
7598: /* } */
7599: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
7600: /* fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]); */
7601: /* } */
1.264 brouard 7602: fprintf(fichtm,"\">");
7603:
7604: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
7605: fprintf(fichtm,"************ Results for covariates");
1.337 brouard 7606: for (cpt=1; cpt<=cptcovs;cpt++){
7607: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 7608: }
1.337 brouard 7609: /* fprintf(fichtm,"************ Results for covariates"); */
7610: /* for (cpt=1; cpt<=cptcoveff;cpt++){ */
7611: /* fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]); */
7612: /* } */
7613: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
7614: /* fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
7615: /* } */
1.264 brouard 7616: if(invalidvarcomb[k1]){
7617: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
7618: continue;
7619: }
7620: fprintf(fichtm,"</a></li>");
7621: } /* cptcovn >0 */
7622: }
1.317 brouard 7623: fprintf(fichtm," \n</ul>");
1.264 brouard 7624:
1.222 brouard 7625: jj1=0;
1.237 brouard 7626:
1.337 brouard 7627: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
7628: /* k1=nres; */
1.338 ! brouard 7629: k1=TKresult[nres];
! 7630: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 7631: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
7632: /* if(m != 1 && TKresult[nres]!= k1) */
7633: /* continue; */
1.220 brouard 7634:
1.222 brouard 7635: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
7636: jj1++;
7637: if (cptcovn > 0) {
1.264 brouard 7638: fprintf(fichtm,"\n<p><a name=\"rescov");
1.337 brouard 7639: for (cpt=1; cpt<=cptcovs;cpt++){
7640: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 7641: }
1.337 brouard 7642: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
7643: /* fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]); */
7644: /* } */
1.264 brouard 7645: fprintf(fichtm,"\"</a>");
7646:
1.222 brouard 7647: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.337 brouard 7648: for (cpt=1; cpt<=cptcovs;cpt++){
7649: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
7650: printf(" V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.237 brouard 7651: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
7652: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 7653: }
1.230 brouard 7654: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.338 ! brouard 7655: fprintf(fichtm," (model=1+age+%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.222 brouard 7656: if(invalidvarcomb[k1]){
7657: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
7658: printf("\nCombination (%d) ignored because no cases \n",k1);
7659: continue;
7660: }
7661: }
7662: /* aij, bij */
1.259 brouard 7663: 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 7664: <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 7665: /* Pij */
1.241 brouard 7666: 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> \
7667: <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 7668: /* Quasi-incidences */
7669: 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 7670: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 7671: 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 7672: 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> \
7673: <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 7674: /* Survival functions (period) in state j */
7675: for(cpt=1; cpt<=nlstate;cpt++){
1.329 brouard 7676: fprintf(fichtm,"<br>\n- Survival functions in state %d. And probability to be observed in state %d being in state (1 to %d) at different ages. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br>", cpt, cpt, nlstate, subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres,subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
7677: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
7678: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.222 brouard 7679: }
7680: /* State specific survival functions (period) */
7681: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 7682: fprintf(fichtm,"<br>\n- Survival functions in state %d and in any other live state (total).\
7683: And probability to be observed in various states (up to %d) being in state %d at different ages. \
1.329 brouard 7684: <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br> ", cpt, nlstate, cpt, subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres,subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
7685: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
7686: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.222 brouard 7687: }
1.288 brouard 7688: /* Period (forward stable) prevalence in each health state */
1.222 brouard 7689: for(cpt=1; cpt<=nlstate;cpt++){
1.329 brouard 7690: fprintf(fichtm,"<br>\n- Convergence to period (stable) prevalence in state %d. Or probability for a person being in state (1 to %d) at different ages, to be in state %d some years after. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br>", cpt, nlstate, cpt, subdirf2(optionfilefiname,"P_"),cpt,k1,nres,subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.338 ! brouard 7691: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
1.329 brouard 7692: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.222 brouard 7693: }
1.296 brouard 7694: if(prevbcast==1){
1.288 brouard 7695: /* Backward prevalence in each health state */
1.222 brouard 7696: for(cpt=1; cpt<=nlstate;cpt++){
1.338 ! brouard 7697: 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>", cpt, cpt, nlstate, subdirf2(optionfilefiname,"PB_"),cpt,k1,nres,subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
! 7698: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJB_"),subdirf2(optionfilefiname,"PIJB_"));
! 7699: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.222 brouard 7700: }
1.217 brouard 7701: }
1.222 brouard 7702: if(prevfcast==1){
1.288 brouard 7703: /* Projection of prevalence up to period (forward stable) prevalence in each health state */
1.222 brouard 7704: for(cpt=1; cpt<=nlstate;cpt++){
1.314 brouard 7705: 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);
7706: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"F_"),subdirf2(optionfilefiname,"F_"));
7707: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",
7708: subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.222 brouard 7709: }
7710: }
1.296 brouard 7711: if(prevbcast==1){
1.268 brouard 7712: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
7713: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 7714: fprintf(fichtm,"<br>\n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), \
7715: 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 \
7716: 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 7717: 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);
7718: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"FB_"),subdirf2(optionfilefiname,"FB_"));
7719: fprintf(fichtm," <img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
1.268 brouard 7720: }
7721: }
1.220 brouard 7722:
1.222 brouard 7723: for(cpt=1; cpt<=nlstate;cpt++) {
1.314 brouard 7724: 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);
7725: fprintf(fichtm," (data from text file <a href=\"%s.txt\"> %s.txt</a>)\n<br>",subdirf2(optionfilefiname,"E_"),subdirf2(optionfilefiname,"E_"));
7726: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres );
1.222 brouard 7727: }
7728: /* } /\* end i1 *\/ */
1.337 brouard 7729: }/* End k1=nres */
1.222 brouard 7730: fprintf(fichtm,"</ul>");
1.126 brouard 7731:
1.222 brouard 7732: fprintf(fichtm,"\
1.126 brouard 7733: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 7734: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 7735: - 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 7736: But because parameters are usually highly correlated (a higher incidence of disability \
7737: and a higher incidence of recovery can give very close observed transition) it might \
7738: be very useful to look not only at linear confidence intervals estimated from the \
7739: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
7740: (parameters) of the logistic regression, it might be more meaningful to visualize the \
7741: covariance matrix of the one-step probabilities. \
7742: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 7743:
1.222 brouard 7744: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
7745: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
7746: fprintf(fichtm,"\
1.126 brouard 7747: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 7748: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 7749:
1.222 brouard 7750: fprintf(fichtm,"\
1.126 brouard 7751: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 7752: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
7753: fprintf(fichtm,"\
1.126 brouard 7754: - 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): \
7755: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 7756: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 7757: fprintf(fichtm,"\
1.126 brouard 7758: - (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): \
7759: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 7760: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 7761: fprintf(fichtm,"\
1.288 brouard 7762: - 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 7763: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
7764: fprintf(fichtm,"\
1.128 brouard 7765: - 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 7766: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
7767: fprintf(fichtm,"\
1.288 brouard 7768: - Standard deviation of forward (period) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 7769: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 7770:
7771: /* if(popforecast==1) fprintf(fichtm,"\n */
7772: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
7773: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
7774: /* <br>",fileres,fileres,fileres,fileres); */
7775: /* else */
1.338 ! brouard 7776: /* fprintf(fichtm,"\n No population forecast: popforecast = %d (instead of 1) or stepm = %d (instead of 1) or model=1+age+%s (instead of .)<br><br></li>\n",popforecast, stepm, model); */
1.222 brouard 7777: fflush(fichtm);
1.126 brouard 7778:
1.225 brouard 7779: m=pow(2,cptcoveff);
1.222 brouard 7780: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 7781:
1.317 brouard 7782: fprintf(fichtm," <ul><li><b>Graphs (second order)</b></li><p>");
7783:
7784: jj1=0;
7785:
7786: fprintf(fichtm," \n<ul>");
1.337 brouard 7787: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
7788: /* k1=nres; */
1.338 ! brouard 7789: k1=TKresult[nres];
1.337 brouard 7790: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
7791: /* if(m != 1 && TKresult[nres]!= k1) */
7792: /* continue; */
1.317 brouard 7793: jj1++;
7794: if (cptcovn > 0) {
7795: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescovsecond");
1.337 brouard 7796: for (cpt=1; cpt<=cptcovs;cpt++){
7797: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 7798: }
7799: fprintf(fichtm,"\">");
7800:
7801: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
7802: fprintf(fichtm,"************ Results for covariates");
1.337 brouard 7803: for (cpt=1; cpt<=cptcovs;cpt++){
7804: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 7805: }
7806: if(invalidvarcomb[k1]){
7807: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
7808: continue;
7809: }
7810: fprintf(fichtm,"</a></li>");
7811: } /* cptcovn >0 */
1.337 brouard 7812: } /* End nres */
1.317 brouard 7813: fprintf(fichtm," \n</ul>");
7814:
1.222 brouard 7815: jj1=0;
1.237 brouard 7816:
1.241 brouard 7817: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 7818: /* k1=nres; */
1.338 ! brouard 7819: k1=TKresult[nres];
! 7820: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 7821: /* for(k1=1; k1<=m;k1++){ */
7822: /* if(m != 1 && TKresult[nres]!= k1) */
7823: /* continue; */
1.222 brouard 7824: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
7825: jj1++;
1.126 brouard 7826: if (cptcovn > 0) {
1.317 brouard 7827: fprintf(fichtm,"\n<p><a name=\"rescovsecond");
1.337 brouard 7828: for (cpt=1; cpt<=cptcovs;cpt++){
7829: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 7830: }
7831: fprintf(fichtm,"\"</a>");
7832:
1.126 brouard 7833: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.337 brouard 7834: for (cpt=1; cpt<=cptcovs;cpt++){ /**< cptcoveff number of variables */
7835: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
7836: printf(" V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.237 brouard 7837: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
1.317 brouard 7838: }
1.237 brouard 7839:
1.338 ! brouard 7840: fprintf(fichtm," (model=1+age+%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.220 brouard 7841:
1.222 brouard 7842: if(invalidvarcomb[k1]){
7843: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
7844: continue;
7845: }
1.337 brouard 7846: } /* If cptcovn >0 */
1.126 brouard 7847: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 7848: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.314 brouard 7849: 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);
7850: fprintf(fichtm," (data from text file <a href=\"%s\">%s</a>)\n <br>",subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
7851: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"V_"), cpt,k1,nres);
1.126 brouard 7852: }
7853: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.314 brouard 7854: health expectancies in each live states (1 to %d). If popbased=1 the smooth (due to the model) \
1.128 brouard 7855: true period expectancies (those weighted with period prevalences are also\
7856: drawn in addition to the population based expectancies computed using\
1.314 brouard 7857: 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);
7858: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>) \n<br>",subdirf2(optionfilefiname,"T_"),subdirf2(optionfilefiname,"T_"));
7859: fprintf(fichtm,"<img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 7860: /* } /\* end i1 *\/ */
1.241 brouard 7861: }/* End nres */
1.222 brouard 7862: fprintf(fichtm,"</ul>");
7863: fflush(fichtm);
1.126 brouard 7864: }
7865:
7866: /******************* Gnuplot file **************/
1.296 brouard 7867: 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 7868:
7869: char dirfileres[132],optfileres[132];
1.264 brouard 7870: char gplotcondition[132], gplotlabel[132];
1.237 brouard 7871: 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 7872: int lv=0, vlv=0, kl=0;
1.130 brouard 7873: int ng=0;
1.201 brouard 7874: int vpopbased;
1.223 brouard 7875: int ioffset; /* variable offset for columns */
1.270 brouard 7876: int iyearc=1; /* variable column for year of projection */
7877: int iagec=1; /* variable column for age of projection */
1.235 brouard 7878: int nres=0; /* Index of resultline */
1.266 brouard 7879: int istart=1; /* For starting graphs in projections */
1.219 brouard 7880:
1.126 brouard 7881: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
7882: /* printf("Problem with file %s",optionfilegnuplot); */
7883: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
7884: /* } */
7885:
7886: /*#ifdef windows */
7887: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 7888: /*#endif */
1.225 brouard 7889: m=pow(2,cptcoveff);
1.126 brouard 7890:
1.274 brouard 7891: /* diagram of the model */
7892: fprintf(ficgp,"\n#Diagram of the model \n");
7893: fprintf(ficgp,"\ndelta=0.03;delta2=0.07;unset arrow;\n");
7894: fprintf(ficgp,"yoff=(%d > 2? 0:1);\n",nlstate);
7895: 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);
7896:
7897: 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);
7898: fprintf(ficgp,"\n#show arrow\nunset label\n");
7899: 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);
7900: fprintf(ficgp,"\nset label %d+1 sprintf(\"State %%d\",%d+1) center at 0.,0. font \"helvetica, 16\" tc rgbcolor \"red\"\n",nlstate,nlstate);
7901: fprintf(ficgp,"\n#show label\nunset border;unset xtics; unset ytics;\n");
7902: fprintf(ficgp,"\n\nset ter svg size 640, 480;set out \"%s_.svg\" \n",subdirf2(optionfilefiname,"D_"));
7903: fprintf(ficgp,"unset log y; plot [-1.2:1.2][yoff-1.2:1.2] 1/0 not; set out;reset;\n");
7904:
1.202 brouard 7905: /* Contribution to likelihood */
7906: /* Plot the probability implied in the likelihood */
1.223 brouard 7907: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
7908: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
7909: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
7910: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 7911: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 7912: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
7913: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 7914: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
7915: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
7916: 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));
7917: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
7918: 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));
7919: for (i=1; i<= nlstate ; i ++) {
7920: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
7921: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
7922: 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);
7923: for (j=2; j<= nlstate+ndeath ; j ++) {
7924: 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);
7925: }
7926: fprintf(ficgp,";\nset out; unset ylabel;\n");
7927: }
7928: /* 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 */
7929: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
7930: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
7931: fprintf(ficgp,"\nset out;unset log\n");
7932: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 7933:
1.126 brouard 7934: strcpy(dirfileres,optionfilefiname);
7935: strcpy(optfileres,"vpl");
1.223 brouard 7936: /* 1eme*/
1.238 brouard 7937: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
1.337 brouard 7938: /* for (k1=1; k1<= m ; k1 ++){ /\* For each valid combination of covariate *\/ */
1.236 brouard 7939: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 7940: k1=TKresult[nres];
1.338 ! brouard 7941: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.238 brouard 7942: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.337 brouard 7943: /* if(m != 1 && TKresult[nres]!= k1) */
7944: /* continue; */
1.238 brouard 7945: /* We are interested in selected combination by the resultline */
1.246 brouard 7946: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.288 brouard 7947: fprintf(ficgp,"\n# 1st: Forward (stable period) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 7948: strcpy(gplotlabel,"(");
1.337 brouard 7949: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
7950: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
7951: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
7952:
7953: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate k get corresponding value lv for combination k1 *\/ */
7954: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the value of the covariate corresponding to k1 combination *\\/ *\/ */
7955: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
7956: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
7957: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
7958: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
7959: /* vlv= nbcode[Tvaraff[k]][lv]; /\* vlv is the value of the covariate lv, 0 or 1 *\/ */
7960: /* /\* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv *\/ */
7961: /* /\* printf(" V%d=%d ",Tvaraff[k],vlv); *\/ */
7962: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
7963: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
7964: /* } */
7965: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
7966: /* /\* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); *\/ */
7967: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
7968: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.264 brouard 7969: }
7970: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 7971: /* printf("\n#\n"); */
1.238 brouard 7972: fprintf(ficgp,"\n#\n");
7973: if(invalidvarcomb[k1]){
1.260 brouard 7974: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 7975: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7976: continue;
7977: }
1.235 brouard 7978:
1.241 brouard 7979: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
7980: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.276 brouard 7981: /* fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel); */
1.338 ! brouard 7982: fprintf(ficgp,"set title \"Alive state %d %s model=1+age+%s\" font \"Helvetica,12\"\n",cpt,gplotlabel,model);
1.260 brouard 7983: 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);
7984: /* 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); */
7985: /* k1-1 error should be nres-1*/
1.238 brouard 7986: for (i=1; i<= nlstate ; i ++) {
7987: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7988: else fprintf(ficgp," %%*lf (%%*lf)");
7989: }
1.288 brouard 7990: 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 7991: for (i=1; i<= nlstate ; i ++) {
7992: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7993: else fprintf(ficgp," %%*lf (%%*lf)");
7994: }
1.260 brouard 7995: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 7996: for (i=1; i<= nlstate ; i ++) {
7997: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7998: else fprintf(ficgp," %%*lf (%%*lf)");
7999: }
1.265 brouard 8000: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
8001:
8002: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
8003: if(cptcoveff ==0){
1.271 brouard 8004: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+3*(cpt-1), cpt );
1.265 brouard 8005: }else{
8006: kl=0;
8007: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
1.332 brouard 8008: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
8009: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.265 brouard 8010: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8011: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8012: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8013: vlv= nbcode[Tvaraff[k]][lv];
8014: kl++;
8015: /* 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 *\/ */
8016: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8017: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8018: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
8019: if(k==cptcoveff){
8020: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
8021: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
8022: }else{
8023: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
8024: kl++;
8025: }
8026: } /* end covariate */
8027: } /* end if no covariate */
8028:
1.296 brouard 8029: if(prevbcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
1.238 brouard 8030: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 8031: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 8032: if(cptcoveff ==0){
1.245 brouard 8033: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 8034: }else{
8035: kl=0;
8036: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
1.332 brouard 8037: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
8038: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.238 brouard 8039: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8040: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8041: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 8042: /* vlv= nbcode[Tvaraff[k]][lv]; */
8043: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.223 brouard 8044: kl++;
1.238 brouard 8045: /* 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 *\/ */
8046: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8047: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8048: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
8049: if(k==cptcoveff){
1.245 brouard 8050: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 8051: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 8052: }else{
1.332 brouard 8053: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]);
1.238 brouard 8054: kl++;
8055: }
8056: } /* end covariate */
8057: } /* end if no covariate */
1.296 brouard 8058: if(prevbcast == 1){
1.268 brouard 8059: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
8060: /* k1-1 error should be nres-1*/
8061: for (i=1; i<= nlstate ; i ++) {
8062: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8063: else fprintf(ficgp," %%*lf (%%*lf)");
8064: }
1.271 brouard 8065: 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 8066: for (i=1; i<= nlstate ; i ++) {
8067: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8068: else fprintf(ficgp," %%*lf (%%*lf)");
8069: }
1.276 brouard 8070: 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 8071: for (i=1; i<= nlstate ; i ++) {
8072: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8073: else fprintf(ficgp," %%*lf (%%*lf)");
8074: }
1.274 brouard 8075: fprintf(ficgp,"\" t\"\" w l lt 4");
1.268 brouard 8076: } /* end if backprojcast */
1.296 brouard 8077: } /* end if prevbcast */
1.276 brouard 8078: /* fprintf(ficgp,"\nset out ;unset label;\n"); */
8079: fprintf(ficgp,"\nset out ;unset title;\n");
1.238 brouard 8080: } /* nres */
1.337 brouard 8081: /* } /\* k1 *\/ */
1.201 brouard 8082: } /* cpt */
1.235 brouard 8083:
8084:
1.126 brouard 8085: /*2 eme*/
1.337 brouard 8086: /* for (k1=1; k1<= m ; k1 ++){ */
1.238 brouard 8087: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8088: k1=TKresult[nres];
1.338 ! brouard 8089: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8090: /* if(m != 1 && TKresult[nres]!= k1) */
8091: /* continue; */
1.238 brouard 8092: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 8093: strcpy(gplotlabel,"(");
1.337 brouard 8094: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8095: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8096: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8097: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8098: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8099: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8100: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8101: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8102: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8103: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8104: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8105: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8106: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8107: /* } */
8108: /* /\* for(k=1; k <= ncovds; k++){ *\/ */
8109: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8110: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8111: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8112: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 8113: }
1.264 brouard 8114: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 8115: fprintf(ficgp,"\n#\n");
1.223 brouard 8116: if(invalidvarcomb[k1]){
8117: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8118: continue;
8119: }
1.219 brouard 8120:
1.241 brouard 8121: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 8122: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 8123: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
8124: if(vpopbased==0){
1.238 brouard 8125: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 8126: }else
1.238 brouard 8127: fprintf(ficgp,"\nreplot ");
8128: for (i=1; i<= nlstate+1 ; i ++) {
8129: k=2*i;
1.261 brouard 8130: 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 8131: for (j=1; j<= nlstate+1 ; j ++) {
8132: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8133: else fprintf(ficgp," %%*lf (%%*lf)");
8134: }
8135: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
8136: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
1.261 brouard 8137: 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 8138: for (j=1; j<= nlstate+1 ; j ++) {
8139: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8140: else fprintf(ficgp," %%*lf (%%*lf)");
8141: }
8142: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 8143: 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 8144: for (j=1; j<= nlstate+1 ; j ++) {
8145: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8146: else fprintf(ficgp," %%*lf (%%*lf)");
8147: }
8148: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
8149: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
8150: } /* state */
8151: } /* vpopbased */
1.264 brouard 8152: 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 8153: } /* end nres */
1.337 brouard 8154: /* } /\* k1 end 2 eme*\/ */
1.238 brouard 8155:
8156:
8157: /*3eme*/
1.337 brouard 8158: /* for (k1=1; k1<= m ; k1 ++){ */
1.238 brouard 8159: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8160: k1=TKresult[nres];
1.338 ! brouard 8161: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8162: /* if(m != 1 && TKresult[nres]!= k1) */
8163: /* continue; */
1.238 brouard 8164:
1.332 brouard 8165: for (cpt=1; cpt<= nlstate ; cpt ++) { /* Fragile no verification of covariate values */
1.261 brouard 8166: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 8167: strcpy(gplotlabel,"(");
1.337 brouard 8168: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8169: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8170: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8171: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8172: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8173: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
8174: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8175: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8176: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8177: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8178: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8179: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8180: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8181: /* } */
8182: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8183: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]); */
8184: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]); */
8185: }
1.264 brouard 8186: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8187: fprintf(ficgp,"\n#\n");
8188: if(invalidvarcomb[k1]){
8189: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8190: continue;
8191: }
8192:
8193: /* k=2+nlstate*(2*cpt-2); */
8194: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 8195: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 8196: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 8197: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 8198: 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 8199: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
8200: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
8201: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
8202: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
8203: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
8204: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 8205:
1.238 brouard 8206: */
8207: for (i=1; i< nlstate ; i ++) {
1.261 brouard 8208: 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 8209: /* 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 8210:
1.238 brouard 8211: }
1.261 brouard 8212: 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 8213: }
1.264 brouard 8214: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 8215: } /* end nres */
1.337 brouard 8216: /* } /\* end kl 3eme *\/ */
1.126 brouard 8217:
1.223 brouard 8218: /* 4eme */
1.201 brouard 8219: /* Survival functions (period) from state i in state j by initial state i */
1.337 brouard 8220: /* for (k1=1; k1<=m; k1++){ /\* For each covariate and each value *\/ */
1.238 brouard 8221: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8222: k1=TKresult[nres];
1.338 ! brouard 8223: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8224: /* if(m != 1 && TKresult[nres]!= k1) */
8225: /* continue; */
1.238 brouard 8226: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 8227: strcpy(gplotlabel,"(");
1.337 brouard 8228: fprintf(ficgp,"\n#\n#\n# Survival functions in state %d : 'LIJ_' files, cov=%d state=%d", cpt, k1, cpt);
8229: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8230: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8231: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8232: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8233: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8234: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8235: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8236: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8237: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8238: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8239: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8240: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8241: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8242: /* } */
8243: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8244: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8245: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.238 brouard 8246: }
1.264 brouard 8247: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8248: fprintf(ficgp,"\n#\n");
8249: if(invalidvarcomb[k1]){
8250: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8251: continue;
1.223 brouard 8252: }
1.238 brouard 8253:
1.241 brouard 8254: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 8255: 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 8256: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
8257: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8258: k=3;
8259: for (i=1; i<= nlstate ; i ++){
8260: if(i==1){
8261: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8262: }else{
8263: fprintf(ficgp,", '' ");
8264: }
8265: l=(nlstate+ndeath)*(i-1)+1;
8266: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
8267: for (j=2; j<= nlstate+ndeath ; j ++)
8268: fprintf(ficgp,"+$%d",k+l+j-1);
8269: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
8270: } /* nlstate */
1.264 brouard 8271: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 8272: } /* end cpt state*/
8273: } /* end nres */
1.337 brouard 8274: /* } /\* end covariate k1 *\/ */
1.238 brouard 8275:
1.220 brouard 8276: /* 5eme */
1.201 brouard 8277: /* Survival functions (period) from state i in state j by final state j */
1.337 brouard 8278: /* for (k1=1; k1<= m ; k1++){ /\* For each covariate combination if any *\/ */
1.238 brouard 8279: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8280: k1=TKresult[nres];
1.338 ! brouard 8281: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8282: /* if(m != 1 && TKresult[nres]!= k1) */
8283: /* continue; */
1.238 brouard 8284: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 8285: strcpy(gplotlabel,"(");
1.238 brouard 8286: 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);
1.337 brouard 8287: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8288: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8289: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8290: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8291: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8292: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8293: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8294: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8295: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8296: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8297: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8298: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8299: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8300: /* } */
8301: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8302: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8303: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.238 brouard 8304: }
1.264 brouard 8305: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8306: fprintf(ficgp,"\n#\n");
8307: if(invalidvarcomb[k1]){
8308: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8309: continue;
8310: }
1.227 brouard 8311:
1.241 brouard 8312: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 8313: 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 8314: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
8315: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8316: k=3;
8317: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
8318: if(j==1)
8319: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8320: else
8321: fprintf(ficgp,", '' ");
8322: l=(nlstate+ndeath)*(cpt-1) +j;
8323: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
8324: /* for (i=2; i<= nlstate+ndeath ; i ++) */
8325: /* fprintf(ficgp,"+$%d",k+l+i-1); */
8326: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
8327: } /* nlstate */
8328: fprintf(ficgp,", '' ");
8329: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
8330: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
8331: l=(nlstate+ndeath)*(cpt-1) +j;
8332: if(j < nlstate)
8333: fprintf(ficgp,"$%d +",k+l);
8334: else
8335: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
8336: }
1.264 brouard 8337: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 8338: } /* end cpt state*/
1.337 brouard 8339: /* } /\* end covariate *\/ */
1.238 brouard 8340: } /* end nres */
1.227 brouard 8341:
1.220 brouard 8342: /* 6eme */
1.202 brouard 8343: /* CV preval stable (period) for each covariate */
1.337 brouard 8344: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 8345: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8346: k1=TKresult[nres];
1.338 ! brouard 8347: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8348: /* if(m != 1 && TKresult[nres]!= k1) */
8349: /* continue; */
1.255 brouard 8350: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 8351: strcpy(gplotlabel,"(");
1.288 brouard 8352: fprintf(ficgp,"\n#\n#\n#CV preval stable (forward): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 8353: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8354: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8355: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8356: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8357: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8358: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8359: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8360: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8361: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8362: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8363: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8364: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8365: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8366: /* } */
8367: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8368: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8369: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 8370: }
1.264 brouard 8371: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 8372: fprintf(ficgp,"\n#\n");
1.223 brouard 8373: if(invalidvarcomb[k1]){
1.227 brouard 8374: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8375: continue;
1.223 brouard 8376: }
1.227 brouard 8377:
1.241 brouard 8378: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 8379: 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 8380: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 8381: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 8382: k=3; /* Offset */
1.255 brouard 8383: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 8384: if(i==1)
8385: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8386: else
8387: fprintf(ficgp,", '' ");
1.255 brouard 8388: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 8389: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
8390: for (j=2; j<= nlstate ; j ++)
8391: fprintf(ficgp,"+$%d",k+l+j-1);
8392: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 8393: } /* nlstate */
1.264 brouard 8394: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 8395: } /* end cpt state*/
8396: } /* end covariate */
1.227 brouard 8397:
8398:
1.220 brouard 8399: /* 7eme */
1.296 brouard 8400: if(prevbcast == 1){
1.288 brouard 8401: /* CV backward prevalence for each covariate */
1.337 brouard 8402: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 8403: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8404: k1=TKresult[nres];
1.338 ! brouard 8405: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8406: /* if(m != 1 && TKresult[nres]!= k1) */
8407: /* continue; */
1.268 brouard 8408: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 8409: strcpy(gplotlabel,"(");
1.288 brouard 8410: fprintf(ficgp,"\n#\n#\n#CV Backward stable prevalence: 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 8411: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8412: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8413: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8414: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8415: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8416: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8417: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8418: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8419: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8420: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8421: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8422: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8423: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8424: /* } */
8425: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8426: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8427: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 8428: }
1.264 brouard 8429: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 8430: fprintf(ficgp,"\n#\n");
8431: if(invalidvarcomb[k1]){
8432: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8433: continue;
8434: }
8435:
1.241 brouard 8436: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 8437: 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 8438: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 8439: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 8440: k=3; /* Offset */
1.268 brouard 8441: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 8442: if(i==1)
8443: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
8444: else
8445: fprintf(ficgp,", '' ");
8446: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 8447: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.324 brouard 8448: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
8449: /* 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 8450: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 8451: /* for (j=2; j<= nlstate ; j ++) */
8452: /* fprintf(ficgp,"+$%d",k+l+j-1); */
8453: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 8454: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 8455: } /* nlstate */
1.264 brouard 8456: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 8457: } /* end cpt state*/
8458: } /* end covariate */
1.296 brouard 8459: } /* End if prevbcast */
1.218 brouard 8460:
1.223 brouard 8461: /* 8eme */
1.218 brouard 8462: if(prevfcast==1){
1.288 brouard 8463: /* Projection from cross-sectional to forward stable (period) prevalence for each covariate */
1.218 brouard 8464:
1.337 brouard 8465: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 8466: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8467: k1=TKresult[nres];
1.338 ! brouard 8468: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8469: /* if(m != 1 && TKresult[nres]!= k1) */
8470: /* continue; */
1.211 brouard 8471: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 8472: strcpy(gplotlabel,"(");
1.288 brouard 8473: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to forward stable prevalence (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 8474: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8475: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8476: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8477: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
8478: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
8479: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8480: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8481: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8482: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8483: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8484: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8485: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8486: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8487: /* } */
8488: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8489: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8490: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 8491: }
1.264 brouard 8492: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 8493: fprintf(ficgp,"\n#\n");
8494: if(invalidvarcomb[k1]){
8495: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8496: continue;
8497: }
8498:
8499: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 8500: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 8501: 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 8502: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 8503: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 8504:
8505: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
8506: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
8507: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
8508: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 8509: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8510: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8511: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8512: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 8513: if(i==istart){
1.227 brouard 8514: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
8515: }else{
8516: fprintf(ficgp,",\\\n '' ");
8517: }
8518: if(cptcoveff ==0){ /* No covariate */
8519: ioffset=2; /* Age is in 2 */
8520: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8521: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8522: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8523: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8524: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 8525: if(i==nlstate+1){
1.270 brouard 8526: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 8527: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
8528: fprintf(ficgp,",\\\n '' ");
8529: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 8530: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 8531: offyear, \
1.268 brouard 8532: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 8533: }else
1.227 brouard 8534: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
8535: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
8536: }else{ /* more than 2 covariates */
1.270 brouard 8537: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
8538: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8539: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8540: iyearc=ioffset-1;
8541: iagec=ioffset;
1.227 brouard 8542: fprintf(ficgp," u %d:(",ioffset);
8543: kl=0;
8544: strcpy(gplotcondition,"(");
8545: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
1.332 brouard 8546: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
8547: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.227 brouard 8548: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8549: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8550: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 8551: /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */
8552: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.227 brouard 8553: kl++;
8554: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
8555: kl++;
8556: if(k <cptcoveff && cptcoveff>1)
8557: sprintf(gplotcondition+strlen(gplotcondition)," && ");
8558: }
8559: strcpy(gplotcondition+strlen(gplotcondition),")");
8560: /* 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 *\/ */
8561: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8562: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8563: /* '' 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*/
8564: if(i==nlstate+1){
1.270 brouard 8565: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
8566: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 8567: fprintf(ficgp,",\\\n '' ");
1.270 brouard 8568: fprintf(ficgp," u %d:(",iagec);
8569: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
8570: iyearc, iagec, offyear, \
8571: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 8572: /* '' 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 8573: }else{
8574: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
8575: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
8576: }
8577: } /* end if covariate */
8578: } /* nlstate */
1.264 brouard 8579: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 8580: } /* end cpt state*/
8581: } /* end covariate */
8582: } /* End if prevfcast */
1.227 brouard 8583:
1.296 brouard 8584: if(prevbcast==1){
1.268 brouard 8585: /* Back projection from cross-sectional to stable (mixed) for each covariate */
8586:
1.337 brouard 8587: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.268 brouard 8588: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8589: k1=TKresult[nres];
1.338 ! brouard 8590: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8591: /* if(m != 1 && TKresult[nres]!= k1) */
8592: /* continue; */
1.268 brouard 8593: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
8594: strcpy(gplotlabel,"(");
8595: fprintf(ficgp,"\n#\n#\n#Back projection of prevalence to stable (mixed) back prevalence: 'BPROJ_' files, covariatecombination#=%d originstate=%d",k1, cpt);
1.337 brouard 8596: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8597: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8598: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8599: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
8600: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
8601: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
8602: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8603: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8604: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8605: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8606: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8607: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8608: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8609: /* } */
8610: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8611: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8612: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.268 brouard 8613: }
8614: strcpy(gplotlabel+strlen(gplotlabel),")");
8615: fprintf(ficgp,"\n#\n");
8616: if(invalidvarcomb[k1]){
8617: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8618: continue;
8619: }
8620:
8621: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
8622: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
8623: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
8624: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
8625: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8626:
8627: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
8628: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
8629: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
8630: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
8631: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8632: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8633: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8634: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8635: if(i==istart){
8636: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
8637: }else{
8638: fprintf(ficgp,",\\\n '' ");
8639: }
8640: if(cptcoveff ==0){ /* No covariate */
8641: ioffset=2; /* Age is in 2 */
8642: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8643: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8644: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8645: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8646: fprintf(ficgp," u %d:(", ioffset);
8647: if(i==nlstate+1){
1.270 brouard 8648: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 8649: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
8650: fprintf(ficgp,",\\\n '' ");
8651: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 8652: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 8653: offbyear, \
8654: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
8655: }else
8656: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
8657: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
8658: }else{ /* more than 2 covariates */
1.270 brouard 8659: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
8660: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8661: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8662: iyearc=ioffset-1;
8663: iagec=ioffset;
1.268 brouard 8664: fprintf(ficgp," u %d:(",ioffset);
8665: kl=0;
8666: strcpy(gplotcondition,"(");
1.337 brouard 8667: for (k=1; k<=cptcovs; k++){ /* For each covariate k of the resultline, get corresponding value lv for combination k1 */
1.338 ! brouard 8668: if(Dummy[modelresult[nres][k]]==0){ /* To be verified */
1.337 brouard 8669: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate writing the chain of conditions *\/ */
8670: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
8671: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
8672: lv=Tvresult[nres][k];
8673: vlv=TinvDoQresult[nres][Tvresult[nres][k]];
8674: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8675: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8676: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8677: /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */
8678: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8679: kl++;
8680: /* sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]); */
8681: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%lg " ,kl,Tvresult[nres][k], kl+1,TinvDoQresult[nres][Tvresult[nres][k]]);
8682: kl++;
1.338 ! brouard 8683: if(k <cptcovs && cptcovs>1)
1.337 brouard 8684: sprintf(gplotcondition+strlen(gplotcondition)," && ");
8685: }
1.268 brouard 8686: }
8687: strcpy(gplotcondition+strlen(gplotcondition),")");
8688: /* 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 *\/ */
8689: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8690: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8691: /* '' 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*/
8692: if(i==nlstate+1){
1.270 brouard 8693: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
8694: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 8695: fprintf(ficgp,",\\\n '' ");
1.270 brouard 8696: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 8697: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 brouard 8698: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
8699: iyearc,iagec,offbyear, \
8700: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 8701: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
8702: }else{
8703: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
8704: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
8705: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
8706: }
8707: } /* end if covariate */
8708: } /* nlstate */
8709: fprintf(ficgp,"\nset out; unset label;\n");
8710: } /* end cpt state*/
8711: } /* end covariate */
1.296 brouard 8712: } /* End if prevbcast */
1.268 brouard 8713:
1.227 brouard 8714:
1.238 brouard 8715: /* 9eme writing MLE parameters */
8716: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 8717: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 8718: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 8719: for(k=1; k <=(nlstate+ndeath); k++){
8720: if (k != i) {
1.227 brouard 8721: fprintf(ficgp,"# current state %d\n",k);
8722: for(j=1; j <=ncovmodel; j++){
8723: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
8724: jk++;
8725: }
8726: fprintf(ficgp,"\n");
1.126 brouard 8727: }
8728: }
1.223 brouard 8729: }
1.187 brouard 8730: fprintf(ficgp,"##############\n#\n");
1.227 brouard 8731:
1.145 brouard 8732: /*goto avoid;*/
1.238 brouard 8733: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
8734: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 8735: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
8736: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
8737: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
8738: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
8739: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
8740: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
8741: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
8742: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
8743: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
8744: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
8745: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
8746: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
8747: fprintf(ficgp,"#\n");
1.223 brouard 8748: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 8749: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.338 ! brouard 8750: fprintf(ficgp,"#model=1+age+%s \n",model);
1.238 brouard 8751: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.264 brouard 8752: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/* to be checked */
1.337 brouard 8753: /* for(k1=1; k1 <=m; k1++) /\* For each combination of covariate *\/ */
1.237 brouard 8754: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8755: /* k1=nres; */
1.338 ! brouard 8756: k1=TKresult[nres];
! 8757: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8758: fprintf(ficgp,"\n\n# Resultline k1=%d ",k1);
1.264 brouard 8759: strcpy(gplotlabel,"(");
1.276 brouard 8760: /*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*/
1.337 brouard 8761: for (k=1; k<=cptcovs; k++){ /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
8762: /* for each resultline nres, and position k, Tvresult[nres][k] gives the name of the variable and
8763: TinvDoQresult[nres][Tvresult[nres][k]] gives its value double or integer) */
8764: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8765: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8766: }
8767: /* if(m != 1 && TKresult[nres]!= k1) */
8768: /* continue; */
8769: /* fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1); */
8770: /* strcpy(gplotlabel,"("); */
8771: /* /\*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*\/ */
8772: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
8773: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
8774: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
8775: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8776: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8777: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8778: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8779: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8780: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8781: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8782: /* } */
8783: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8784: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8785: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8786: /* } */
1.264 brouard 8787: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 8788: fprintf(ficgp,"\n#\n");
1.264 brouard 8789: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
1.276 brouard 8790: fprintf(ficgp,"\nset key outside ");
8791: /* fprintf(ficgp,"\nset label \"%s\" at graph 1.2,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel); */
8792: fprintf(ficgp,"\nset title \"%s\" font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 8793: fprintf(ficgp,"\nset ter svg size 640, 480 ");
8794: if (ng==1){
8795: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
8796: fprintf(ficgp,"\nunset log y");
8797: }else if (ng==2){
8798: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
8799: fprintf(ficgp,"\nset log y");
8800: }else if (ng==3){
8801: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
8802: fprintf(ficgp,"\nset log y");
8803: }else
8804: fprintf(ficgp,"\nunset title ");
8805: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
8806: i=1;
8807: for(k2=1; k2<=nlstate; k2++) {
8808: k3=i;
8809: for(k=1; k<=(nlstate+ndeath); k++) {
8810: if (k != k2){
8811: switch( ng) {
8812: case 1:
8813: if(nagesqr==0)
8814: fprintf(ficgp," p%d+p%d*x",i,i+1);
8815: else /* nagesqr =1 */
8816: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
8817: break;
8818: case 2: /* ng=2 */
8819: if(nagesqr==0)
8820: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
8821: else /* nagesqr =1 */
8822: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
8823: break;
8824: case 3:
8825: if(nagesqr==0)
8826: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
8827: else /* nagesqr =1 */
8828: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
8829: break;
8830: }
8831: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 8832: ijp=1; /* product no age */
8833: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
8834: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 8835: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.329 brouard 8836: switch(Typevar[j]){
8837: case 1:
8838: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
8839: if(j==Tage[ij]) { /* Product by age To be looked at!!*//* Bug valgrind */
8840: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
8841: if(DummyV[j]==0){/* Bug valgrind */
8842: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
8843: }else{ /* quantitative */
8844: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
8845: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
8846: }
8847: ij++;
1.268 brouard 8848: }
1.237 brouard 8849: }
1.329 brouard 8850: }
8851: break;
8852: case 2:
8853: if(cptcovprod >0){
8854: if(j==Tprod[ijp]) { /* */
8855: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
8856: if(ijp <=cptcovprod) { /* Product */
8857: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
8858: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
8859: /* 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)]); */
8860: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
8861: }else{ /* Vn is dummy and Vm is quanti */
8862: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
8863: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
8864: }
8865: }else{ /* Vn*Vm Vn is quanti */
8866: if(DummyV[Tvard[ijp][2]]==0){
8867: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
8868: }else{ /* Both quanti */
8869: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
8870: }
1.268 brouard 8871: }
1.329 brouard 8872: ijp++;
1.237 brouard 8873: }
1.329 brouard 8874: } /* end Tprod */
8875: }
8876: break;
8877: case 0:
8878: /* simple covariate */
1.264 brouard 8879: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 8880: if(Dummy[j]==0){
8881: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
8882: }else{ /* quantitative */
8883: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 8884: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 8885: }
1.329 brouard 8886: /* end simple */
8887: break;
8888: default:
8889: break;
8890: } /* end switch */
1.237 brouard 8891: } /* end j */
1.329 brouard 8892: }else{ /* k=k2 */
8893: if(ng !=1 ){ /* For logit formula of log p11 is more difficult to get */
8894: fprintf(ficgp," (1.");i=i-ncovmodel;
8895: }else
8896: i=i-ncovmodel;
1.223 brouard 8897: }
1.227 brouard 8898:
1.223 brouard 8899: if(ng != 1){
8900: fprintf(ficgp,")/(1");
1.227 brouard 8901:
1.264 brouard 8902: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 8903: if(nagesqr==0)
1.264 brouard 8904: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 8905: else /* nagesqr =1 */
1.264 brouard 8906: 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 8907:
1.223 brouard 8908: ij=1;
1.329 brouard 8909: ijp=1;
8910: /* for(j=3; j <=ncovmodel-nagesqr; j++){ */
8911: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
8912: switch(Typevar[j]){
8913: case 1:
8914: if(cptcovage >0){
8915: if(j==Tage[ij]) { /* Bug valgrind */
8916: if(ij <=cptcovage) { /* Bug valgrind */
8917: if(DummyV[j]==0){/* Bug valgrind */
8918: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]); */
8919: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,nbcode[Tvar[j]][codtabm(k1,j)]); */
8920: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]);
8921: /* fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);; */
8922: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
8923: }else{ /* quantitative */
8924: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
8925: fprintf(ficgp,"+p%d*%f*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
8926: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
8927: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
8928: }
8929: ij++;
8930: }
8931: }
8932: }
8933: break;
8934: case 2:
8935: if(cptcovprod >0){
8936: if(j==Tprod[ijp]) { /* */
8937: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
8938: if(ijp <=cptcovprod) { /* Product */
8939: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
8940: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
8941: /* 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)]); */
8942: fprintf(ficgp,"+p%d*%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
8943: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]); */
8944: }else{ /* Vn is dummy and Vm is quanti */
8945: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
8946: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
8947: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
8948: }
8949: }else{ /* Vn*Vm Vn is quanti */
8950: if(DummyV[Tvard[ijp][2]]==0){
8951: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
8952: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]); */
8953: }else{ /* Both quanti */
8954: fprintf(ficgp,"+p%d*%f*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
8955: /* fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
8956: }
8957: }
8958: ijp++;
8959: }
8960: } /* end Tprod */
8961: } /* end if */
8962: break;
8963: case 0:
8964: /* simple covariate */
8965: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
8966: if(Dummy[j]==0){
8967: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
8968: fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]); /* */
8969: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
8970: }else{ /* quantitative */
8971: fprintf(ficgp,"+p%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* */
8972: /* fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* *\/ */
8973: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
8974: }
8975: /* end simple */
8976: /* fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);/\* Valgrind bug nbcode *\/ */
8977: break;
8978: default:
8979: break;
8980: } /* end switch */
1.223 brouard 8981: }
8982: fprintf(ficgp,")");
8983: }
8984: fprintf(ficgp,")");
8985: if(ng ==2)
1.276 brouard 8986: 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 8987: else /* ng= 3 */
1.276 brouard 8988: fprintf(ficgp," w l lw 2 lt (%d*%d+%d)%%%d+1 dt %d t \"i%d%d\" ", nlstate+ndeath, k2, k, nlstate+ndeath, k2, k2,k);
1.329 brouard 8989: }else{ /* end ng <> 1 */
1.223 brouard 8990: if( k !=k2) /* logit p11 is hard to draw */
1.276 brouard 8991: 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 8992: }
8993: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
8994: fprintf(ficgp,",");
8995: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
8996: fprintf(ficgp,",");
8997: i=i+ncovmodel;
8998: } /* end k */
8999: } /* end k2 */
1.276 brouard 9000: /* fprintf(ficgp,"\n set out; unset label;set key default;\n"); */
9001: fprintf(ficgp,"\n set out; unset title;set key default;\n");
1.337 brouard 9002: } /* end resultline */
1.223 brouard 9003: } /* end ng */
9004: /* avoid: */
9005: fflush(ficgp);
1.126 brouard 9006: } /* end gnuplot */
9007:
9008:
9009: /*************** Moving average **************/
1.219 brouard 9010: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 9011: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 9012:
1.222 brouard 9013: int i, cpt, cptcod;
9014: int modcovmax =1;
9015: int mobilavrange, mob;
9016: int iage=0;
1.288 brouard 9017: int firstA1=0, firstA2=0;
1.222 brouard 9018:
1.266 brouard 9019: double sum=0., sumr=0.;
1.222 brouard 9020: double age;
1.266 brouard 9021: double *sumnewp, *sumnewm, *sumnewmr;
9022: double *agemingood, *agemaxgood;
9023: double *agemingoodr, *agemaxgoodr;
1.222 brouard 9024:
9025:
1.278 brouard 9026: /* modcovmax=2*cptcoveff; Max number of modalities. We suppose */
9027: /* a covariate has 2 modalities, should be equal to ncovcombmax */
1.222 brouard 9028:
9029: sumnewp = vector(1,ncovcombmax);
9030: sumnewm = vector(1,ncovcombmax);
1.266 brouard 9031: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 9032: agemingood = vector(1,ncovcombmax);
1.266 brouard 9033: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 9034: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 9035: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 9036:
9037: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 9038: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 9039: sumnewp[cptcod]=0.;
1.266 brouard 9040: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
9041: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 9042: }
9043: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
9044:
1.266 brouard 9045: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
9046: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 9047: else mobilavrange=mobilav;
9048: for (age=bage; age<=fage; age++)
9049: for (i=1; i<=nlstate;i++)
9050: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
9051: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9052: /* We keep the original values on the extreme ages bage, fage and for
9053: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
9054: we use a 5 terms etc. until the borders are no more concerned.
9055: */
9056: for (mob=3;mob <=mobilavrange;mob=mob+2){
9057: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 9058: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
9059: sumnewm[cptcod]=0.;
9060: for (i=1; i<=nlstate;i++){
1.222 brouard 9061: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
9062: for (cpt=1;cpt<=(mob-1)/2;cpt++){
9063: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
9064: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
9065: }
9066: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 9067: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9068: } /* end i */
9069: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
9070: } /* end cptcod */
1.222 brouard 9071: }/* end age */
9072: }/* end mob */
1.266 brouard 9073: }else{
9074: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 9075: return -1;
1.266 brouard 9076: }
9077:
9078: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 9079: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
9080: if(invalidvarcomb[cptcod]){
9081: printf("\nCombination (%d) ignored because no cases \n",cptcod);
9082: continue;
9083: }
1.219 brouard 9084:
1.266 brouard 9085: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
9086: sumnewm[cptcod]=0.;
9087: sumnewmr[cptcod]=0.;
9088: for (i=1; i<=nlstate;i++){
9089: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9090: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9091: }
9092: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9093: agemingoodr[cptcod]=age;
9094: }
9095: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9096: agemingood[cptcod]=age;
9097: }
9098: } /* age */
9099: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 9100: sumnewm[cptcod]=0.;
1.266 brouard 9101: sumnewmr[cptcod]=0.;
1.222 brouard 9102: for (i=1; i<=nlstate;i++){
9103: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 9104: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9105: }
9106: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9107: agemaxgoodr[cptcod]=age;
1.222 brouard 9108: }
9109: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 9110: agemaxgood[cptcod]=age;
9111: }
9112: } /* age */
9113: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
9114: /* but they will change */
1.288 brouard 9115: firstA1=0;firstA2=0;
1.266 brouard 9116: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
9117: sumnewm[cptcod]=0.;
9118: sumnewmr[cptcod]=0.;
9119: for (i=1; i<=nlstate;i++){
9120: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9121: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9122: }
9123: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
9124: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9125: agemaxgoodr[cptcod]=age; /* age min */
9126: for (i=1; i<=nlstate;i++)
9127: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9128: }else{ /* bad we change the value with the values of good ages */
9129: for (i=1; i<=nlstate;i++){
9130: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
9131: } /* i */
9132: } /* end bad */
9133: }else{
9134: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9135: agemaxgood[cptcod]=age;
9136: }else{ /* bad we change the value with the values of good ages */
9137: for (i=1; i<=nlstate;i++){
9138: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
9139: } /* i */
9140: } /* end bad */
9141: }/* end else */
9142: sum=0.;sumr=0.;
9143: for (i=1; i<=nlstate;i++){
9144: sum+=mobaverage[(int)age][i][cptcod];
9145: sumr+=probs[(int)age][i][cptcod];
9146: }
9147: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.288 brouard 9148: if(!firstA1){
9149: firstA1=1;
9150: 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);
9151: }
9152: 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 9153: } /* end bad */
9154: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
9155: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.288 brouard 9156: if(!firstA2){
9157: firstA2=1;
9158: 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);
9159: }
9160: 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 9161: } /* end bad */
9162: }/* age */
1.266 brouard 9163:
9164: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 9165: sumnewm[cptcod]=0.;
1.266 brouard 9166: sumnewmr[cptcod]=0.;
1.222 brouard 9167: for (i=1; i<=nlstate;i++){
9168: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 9169: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9170: }
9171: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
9172: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
9173: agemingoodr[cptcod]=age;
9174: for (i=1; i<=nlstate;i++)
9175: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9176: }else{ /* bad we change the value with the values of good ages */
9177: for (i=1; i<=nlstate;i++){
9178: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
9179: } /* i */
9180: } /* end bad */
9181: }else{
9182: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9183: agemingood[cptcod]=age;
9184: }else{ /* bad */
9185: for (i=1; i<=nlstate;i++){
9186: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
9187: } /* i */
9188: } /* end bad */
9189: }/* end else */
9190: sum=0.;sumr=0.;
9191: for (i=1; i<=nlstate;i++){
9192: sum+=mobaverage[(int)age][i][cptcod];
9193: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 9194: }
1.266 brouard 9195: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 9196: 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 9197: } /* end bad */
9198: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
9199: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 9200: 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 9201: } /* end bad */
9202: }/* age */
1.266 brouard 9203:
1.222 brouard 9204:
9205: for (age=bage; age<=fage; age++){
1.235 brouard 9206: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 9207: sumnewp[cptcod]=0.;
9208: sumnewm[cptcod]=0.;
9209: for (i=1; i<=nlstate;i++){
9210: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
9211: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9212: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
9213: }
9214: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
9215: }
9216: /* printf("\n"); */
9217: /* } */
1.266 brouard 9218:
1.222 brouard 9219: /* brutal averaging */
1.266 brouard 9220: /* for (i=1; i<=nlstate;i++){ */
9221: /* for (age=1; age<=bage; age++){ */
9222: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
9223: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
9224: /* } */
9225: /* for (age=fage; age<=AGESUP; age++){ */
9226: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
9227: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
9228: /* } */
9229: /* } /\* end i status *\/ */
9230: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
9231: /* for (age=1; age<=AGESUP; age++){ */
9232: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
9233: /* mobaverage[(int)age][i][cptcod]=0.; */
9234: /* } */
9235: /* } */
1.222 brouard 9236: }/* end cptcod */
1.266 brouard 9237: free_vector(agemaxgoodr,1, ncovcombmax);
9238: free_vector(agemaxgood,1, ncovcombmax);
9239: free_vector(agemingood,1, ncovcombmax);
9240: free_vector(agemingoodr,1, ncovcombmax);
9241: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 9242: free_vector(sumnewm,1, ncovcombmax);
9243: free_vector(sumnewp,1, ncovcombmax);
9244: return 0;
9245: }/* End movingaverage */
1.218 brouard 9246:
1.126 brouard 9247:
1.296 brouard 9248:
1.126 brouard 9249: /************** Forecasting ******************/
1.296 brouard 9250: /* 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)*/
9251: 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){
9252: /* dateintemean, mean date of interviews
9253: dateprojd, year, month, day of starting projection
9254: dateprojf date of end of projection;year of end of projection (same day and month as proj1).
1.126 brouard 9255: agemin, agemax range of age
9256: dateprev1 dateprev2 range of dates during which prevalence is computed
9257: */
1.296 brouard 9258: /* double anprojd, mprojd, jprojd; */
9259: /* double anprojf, mprojf, jprojf; */
1.267 brouard 9260: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 9261: double agec; /* generic age */
1.296 brouard 9262: double agelim, ppij, yp,yp1,yp2;
1.126 brouard 9263: double *popeffectif,*popcount;
9264: double ***p3mat;
1.218 brouard 9265: /* double ***mobaverage; */
1.126 brouard 9266: char fileresf[FILENAMELENGTH];
9267:
9268: agelim=AGESUP;
1.211 brouard 9269: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
9270: in each health status at the date of interview (if between dateprev1 and dateprev2).
9271: We still use firstpass and lastpass as another selection.
9272: */
1.214 brouard 9273: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
9274: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 9275:
1.201 brouard 9276: strcpy(fileresf,"F_");
9277: strcat(fileresf,fileresu);
1.126 brouard 9278: if((ficresf=fopen(fileresf,"w"))==NULL) {
9279: printf("Problem with forecast resultfile: %s\n", fileresf);
9280: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
9281: }
1.235 brouard 9282: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
9283: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 9284:
1.225 brouard 9285: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 9286:
9287:
9288: stepsize=(int) (stepm+YEARM-1)/YEARM;
9289: if (stepm<=12) stepsize=1;
9290: if(estepm < stepm){
9291: printf ("Problem %d lower than %d\n",estepm, stepm);
9292: }
1.270 brouard 9293: else{
9294: hstepm=estepm;
9295: }
9296: if(estepm > stepm){ /* Yes every two year */
9297: stepsize=2;
9298: }
1.296 brouard 9299: hstepm=hstepm/stepm;
1.126 brouard 9300:
1.296 brouard 9301:
9302: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
9303: /* fractional in yp1 *\/ */
9304: /* aintmean=yp; */
9305: /* yp2=modf((yp1*12),&yp); */
9306: /* mintmean=yp; */
9307: /* yp1=modf((yp2*30.5),&yp); */
9308: /* jintmean=yp; */
9309: /* if(jintmean==0) jintmean=1; */
9310: /* if(mintmean==0) mintmean=1; */
1.126 brouard 9311:
1.296 brouard 9312:
9313: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */
9314: /* date2dmy(dateprojd,&jprojd, &mprojd, &anprojd); */
9315: /* date2dmy(dateprojf,&jprojf, &mprojf, &anprojf); */
1.227 brouard 9316: i1=pow(2,cptcoveff);
1.126 brouard 9317: if (cptcovn < 1){i1=1;}
9318:
1.296 brouard 9319: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.126 brouard 9320:
9321: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 9322:
1.126 brouard 9323: /* if (h==(int)(YEARM*yearp)){ */
1.235 brouard 9324: for(nres=1; nres <= nresult; nres++) /* For each resultline */
1.332 brouard 9325: for(k=1; k<=i1;k++){ /* We want to find the combination k corresponding to the values of the dummies given in this resut line (to be cleaned one day) */
1.253 brouard 9326: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 9327: continue;
1.227 brouard 9328: if(invalidvarcomb[k]){
9329: printf("\nCombination (%d) projection ignored because no cases \n",k);
9330: continue;
9331: }
9332: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
9333: for(j=1;j<=cptcoveff;j++) {
1.332 brouard 9334: /* fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); */
9335: fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.227 brouard 9336: }
1.235 brouard 9337: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 9338: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.235 brouard 9339: }
1.227 brouard 9340: fprintf(ficresf," yearproj age");
9341: for(j=1; j<=nlstate+ndeath;j++){
9342: for(i=1; i<=nlstate;i++)
9343: fprintf(ficresf," p%d%d",i,j);
9344: fprintf(ficresf," wp.%d",j);
9345: }
1.296 brouard 9346: for (yearp=0; yearp<=(anprojf-anprojd);yearp +=stepsize) {
1.227 brouard 9347: fprintf(ficresf,"\n");
1.296 brouard 9348: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jprojd,mprojd,anprojd+yearp);
1.270 brouard 9349: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
9350: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 9351: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
9352: nhstepm = nhstepm/hstepm;
9353: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9354: oldm=oldms;savm=savms;
1.268 brouard 9355: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 9356: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 9357: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 9358: for (h=0; h<=nhstepm; h++){
9359: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 9360: break;
9361: }
9362: }
9363: fprintf(ficresf,"\n");
9364: for(j=1;j<=cptcoveff;j++)
1.332 brouard 9365: /* fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Tvaraff not correct *\/ */
9366: fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /* TnsdVar[Tvaraff] correct */
1.296 brouard 9367: fprintf(ficresf,"%.f %.f ",anprojd+yearp,agec+h*hstepm/YEARM*stepm);
1.268 brouard 9368:
9369: for(j=1; j<=nlstate+ndeath;j++) {
9370: ppij=0.;
9371: for(i=1; i<=nlstate;i++) {
1.278 brouard 9372: if (mobilav>=1)
9373: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
9374: else { /* even if mobilav==-1 we use mobaverage, probs may not sums to 1 */
9375: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
9376: }
1.268 brouard 9377: fprintf(ficresf," %.3f", p3mat[i][j][h]);
9378: } /* end i */
9379: fprintf(ficresf," %.3f", ppij);
9380: }/* end j */
1.227 brouard 9381: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9382: } /* end agec */
1.266 brouard 9383: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
9384: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 9385: } /* end yearp */
9386: } /* end k */
1.219 brouard 9387:
1.126 brouard 9388: fclose(ficresf);
1.215 brouard 9389: printf("End of Computing forecasting \n");
9390: fprintf(ficlog,"End of Computing forecasting\n");
9391:
1.126 brouard 9392: }
9393:
1.269 brouard 9394: /************** Back Forecasting ******************/
1.296 brouard 9395: /* 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){ */
9396: 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){
9397: /* back1, year, month, day of starting backprojection
1.267 brouard 9398: agemin, agemax range of age
9399: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 9400: anback2 year of end of backprojection (same day and month as back1).
9401: prevacurrent and prev are prevalences.
1.267 brouard 9402: */
9403: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
9404: double agec; /* generic age */
1.302 brouard 9405: double agelim, ppij, ppi, yp,yp1,yp2; /* ,jintmean,mintmean,aintmean;*/
1.267 brouard 9406: double *popeffectif,*popcount;
9407: double ***p3mat;
9408: /* double ***mobaverage; */
9409: char fileresfb[FILENAMELENGTH];
9410:
1.268 brouard 9411: agelim=AGEINF;
1.267 brouard 9412: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
9413: in each health status at the date of interview (if between dateprev1 and dateprev2).
9414: We still use firstpass and lastpass as another selection.
9415: */
9416: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
9417: /* firstpass, lastpass, stepm, weightopt, model); */
9418:
9419: /*Do we need to compute prevalence again?*/
9420:
9421: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
9422:
9423: strcpy(fileresfb,"FB_");
9424: strcat(fileresfb,fileresu);
9425: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
9426: printf("Problem with back forecast resultfile: %s\n", fileresfb);
9427: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
9428: }
9429: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
9430: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
9431:
9432: if (cptcoveff==0) ncodemax[cptcoveff]=1;
9433:
9434:
9435: stepsize=(int) (stepm+YEARM-1)/YEARM;
9436: if (stepm<=12) stepsize=1;
9437: if(estepm < stepm){
9438: printf ("Problem %d lower than %d\n",estepm, stepm);
9439: }
1.270 brouard 9440: else{
9441: hstepm=estepm;
9442: }
9443: if(estepm >= stepm){ /* Yes every two year */
9444: stepsize=2;
9445: }
1.267 brouard 9446:
9447: hstepm=hstepm/stepm;
1.296 brouard 9448: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
9449: /* fractional in yp1 *\/ */
9450: /* aintmean=yp; */
9451: /* yp2=modf((yp1*12),&yp); */
9452: /* mintmean=yp; */
9453: /* yp1=modf((yp2*30.5),&yp); */
9454: /* jintmean=yp; */
9455: /* if(jintmean==0) jintmean=1; */
9456: /* if(mintmean==0) jintmean=1; */
1.267 brouard 9457:
9458: i1=pow(2,cptcoveff);
9459: if (cptcovn < 1){i1=1;}
9460:
1.296 brouard 9461: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
9462: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 9463:
9464: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
9465:
9466: for(nres=1; nres <= nresult; nres++) /* For each resultline */
9467: for(k=1; k<=i1;k++){
9468: if(i1 != 1 && TKresult[nres]!= k)
9469: continue;
9470: if(invalidvarcomb[k]){
9471: printf("\nCombination (%d) projection ignored because no cases \n",k);
9472: continue;
9473: }
1.268 brouard 9474: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.267 brouard 9475: for(j=1;j<=cptcoveff;j++) {
1.332 brouard 9476: fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.267 brouard 9477: }
9478: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
9479: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
9480: }
9481: fprintf(ficresfb," yearbproj age");
9482: for(j=1; j<=nlstate+ndeath;j++){
9483: for(i=1; i<=nlstate;i++)
1.268 brouard 9484: fprintf(ficresfb," b%d%d",i,j);
9485: fprintf(ficresfb," b.%d",j);
1.267 brouard 9486: }
1.296 brouard 9487: for (yearp=0; yearp>=(anbackf-anbackd);yearp -=stepsize) {
1.267 brouard 9488: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
9489: fprintf(ficresfb,"\n");
1.296 brouard 9490: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jbackd,mbackd,anbackd+yearp);
1.273 brouard 9491: /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
1.270 brouard 9492: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
9493: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 9494: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
1.271 brouard 9495: nhstepm=(int) (agec-agelim) *YEARM/stepm;/* nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
1.267 brouard 9496: nhstepm = nhstepm/hstepm;
9497: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9498: oldm=oldms;savm=savms;
1.268 brouard 9499: /* computes hbxij at age agec over 1 to nhstepm */
1.271 brouard 9500: /* printf("####prevbackforecast debug agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
1.267 brouard 9501: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 9502: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
9503: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
9504: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 9505: for (h=0; h<=nhstepm; h++){
1.268 brouard 9506: if (h*hstepm/YEARM*stepm ==-yearp) {
9507: break;
9508: }
9509: }
9510: fprintf(ficresfb,"\n");
9511: for(j=1;j<=cptcoveff;j++)
1.332 brouard 9512: fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.296 brouard 9513: fprintf(ficresfb,"%.f %.f ",anbackd+yearp,agec-h*hstepm/YEARM*stepm);
1.268 brouard 9514: for(i=1; i<=nlstate+ndeath;i++) {
9515: ppij=0.;ppi=0.;
9516: for(j=1; j<=nlstate;j++) {
9517: /* if (mobilav==1) */
1.269 brouard 9518: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
9519: ppi=ppi+prevacurrent[(int)agec][j][k];
9520: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
9521: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 9522: /* else { */
9523: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
9524: /* } */
1.268 brouard 9525: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
9526: } /* end j */
9527: if(ppi <0.99){
9528: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
9529: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
9530: }
9531: fprintf(ficresfb," %.3f", ppij);
9532: }/* end j */
1.267 brouard 9533: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9534: } /* end agec */
9535: } /* end yearp */
9536: } /* end k */
1.217 brouard 9537:
1.267 brouard 9538: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 9539:
1.267 brouard 9540: fclose(ficresfb);
9541: printf("End of Computing Back forecasting \n");
9542: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 9543:
1.267 brouard 9544: }
1.217 brouard 9545:
1.269 brouard 9546: /* Variance of prevalence limit: varprlim */
9547: 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 9548: /*------- Variance of forward period (stable) prevalence------*/
1.269 brouard 9549:
9550: char fileresvpl[FILENAMELENGTH];
9551: FILE *ficresvpl;
9552: double **oldm, **savm;
9553: double **varpl; /* Variances of prevalence limits by age */
9554: int i1, k, nres, j ;
9555:
9556: strcpy(fileresvpl,"VPL_");
9557: strcat(fileresvpl,fileresu);
9558: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
1.288 brouard 9559: printf("Problem with variance of forward period (stable) prevalence resultfile: %s\n", fileresvpl);
1.269 brouard 9560: exit(0);
9561: }
1.288 brouard 9562: printf("Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
9563: fprintf(ficlog, "Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
1.269 brouard 9564:
9565: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
9566: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
9567:
9568: i1=pow(2,cptcoveff);
9569: if (cptcovn < 1){i1=1;}
9570:
1.337 brouard 9571: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
9572: k=TKresult[nres];
1.338 ! brouard 9573: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 9574: /* for(k=1; k<=i1;k++){ /\* We find the combination equivalent to result line values of dummies *\/ */
1.269 brouard 9575: if(i1 != 1 && TKresult[nres]!= k)
9576: continue;
9577: fprintf(ficresvpl,"\n#****** ");
9578: printf("\n#****** ");
9579: fprintf(ficlog,"\n#****** ");
1.337 brouard 9580: for(j=1;j<=cptcovs;j++) {
9581: fprintf(ficresvpl,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
9582: fprintf(ficlog,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
9583: printf("V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
9584: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
9585: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
1.269 brouard 9586: }
1.337 brouard 9587: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
9588: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
9589: /* fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
9590: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
9591: /* } */
1.269 brouard 9592: fprintf(ficresvpl,"******\n");
9593: printf("******\n");
9594: fprintf(ficlog,"******\n");
9595:
9596: varpl=matrix(1,nlstate,(int) bage, (int) fage);
9597: oldm=oldms;savm=savms;
9598: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
9599: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
9600: /*}*/
9601: }
9602:
9603: fclose(ficresvpl);
1.288 brouard 9604: printf("done variance-covariance of forward period prevalence\n");fflush(stdout);
9605: fprintf(ficlog,"done variance-covariance of forward period prevalence\n");fflush(ficlog);
1.269 brouard 9606:
9607: }
9608: /* Variance of back prevalence: varbprlim */
9609: 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){
9610: /*------- Variance of back (stable) prevalence------*/
9611:
9612: char fileresvbl[FILENAMELENGTH];
9613: FILE *ficresvbl;
9614:
9615: double **oldm, **savm;
9616: double **varbpl; /* Variances of back prevalence limits by age */
9617: int i1, k, nres, j ;
9618:
9619: strcpy(fileresvbl,"VBL_");
9620: strcat(fileresvbl,fileresu);
9621: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
9622: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
9623: exit(0);
9624: }
9625: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
9626: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
9627:
9628:
9629: i1=pow(2,cptcoveff);
9630: if (cptcovn < 1){i1=1;}
9631:
1.337 brouard 9632: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
9633: k=TKresult[nres];
1.338 ! brouard 9634: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 9635: /* for(k=1; k<=i1;k++){ */
9636: /* if(i1 != 1 && TKresult[nres]!= k) */
9637: /* continue; */
1.269 brouard 9638: fprintf(ficresvbl,"\n#****** ");
9639: printf("\n#****** ");
9640: fprintf(ficlog,"\n#****** ");
1.337 brouard 9641: for (j=1; j<= cptcovs; j++){ /* For each selected (single) quantitative value */
1.338 ! brouard 9642: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
! 9643: fprintf(ficresvbl," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
! 9644: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
1.337 brouard 9645: /* for(j=1;j<=cptcoveff;j++) { */
9646: /* fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
9647: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
9648: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
9649: /* } */
9650: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
9651: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
9652: /* fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
9653: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
1.269 brouard 9654: }
9655: fprintf(ficresvbl,"******\n");
9656: printf("******\n");
9657: fprintf(ficlog,"******\n");
9658:
9659: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
9660: oldm=oldms;savm=savms;
9661:
9662: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
9663: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
9664: /*}*/
9665: }
9666:
9667: fclose(ficresvbl);
9668: printf("done variance-covariance of back prevalence\n");fflush(stdout);
9669: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
9670:
9671: } /* End of varbprlim */
9672:
1.126 brouard 9673: /************** Forecasting *****not tested NB*************/
1.227 brouard 9674: /* 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 9675:
1.227 brouard 9676: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
9677: /* int *popage; */
9678: /* double calagedatem, agelim, kk1, kk2; */
9679: /* double *popeffectif,*popcount; */
9680: /* double ***p3mat,***tabpop,***tabpopprev; */
9681: /* /\* double ***mobaverage; *\/ */
9682: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 9683:
1.227 brouard 9684: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9685: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9686: /* agelim=AGESUP; */
9687: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 9688:
1.227 brouard 9689: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 9690:
9691:
1.227 brouard 9692: /* strcpy(filerespop,"POP_"); */
9693: /* strcat(filerespop,fileresu); */
9694: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
9695: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
9696: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
9697: /* } */
9698: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
9699: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 9700:
1.227 brouard 9701: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 9702:
1.227 brouard 9703: /* /\* if (mobilav!=0) { *\/ */
9704: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
9705: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
9706: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
9707: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
9708: /* /\* } *\/ */
9709: /* /\* } *\/ */
1.126 brouard 9710:
1.227 brouard 9711: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
9712: /* if (stepm<=12) stepsize=1; */
1.126 brouard 9713:
1.227 brouard 9714: /* agelim=AGESUP; */
1.126 brouard 9715:
1.227 brouard 9716: /* hstepm=1; */
9717: /* hstepm=hstepm/stepm; */
1.218 brouard 9718:
1.227 brouard 9719: /* if (popforecast==1) { */
9720: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
9721: /* printf("Problem with population file : %s\n",popfile);exit(0); */
9722: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
9723: /* } */
9724: /* popage=ivector(0,AGESUP); */
9725: /* popeffectif=vector(0,AGESUP); */
9726: /* popcount=vector(0,AGESUP); */
1.126 brouard 9727:
1.227 brouard 9728: /* i=1; */
9729: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 9730:
1.227 brouard 9731: /* imx=i; */
9732: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
9733: /* } */
1.218 brouard 9734:
1.227 brouard 9735: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
9736: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
9737: /* k=k+1; */
9738: /* fprintf(ficrespop,"\n#******"); */
9739: /* for(j=1;j<=cptcoveff;j++) { */
9740: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
9741: /* } */
9742: /* fprintf(ficrespop,"******\n"); */
9743: /* fprintf(ficrespop,"# Age"); */
9744: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
9745: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 9746:
1.227 brouard 9747: /* for (cpt=0; cpt<=0;cpt++) { */
9748: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 9749:
1.227 brouard 9750: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
9751: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
9752: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 9753:
1.227 brouard 9754: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9755: /* oldm=oldms;savm=savms; */
9756: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 9757:
1.227 brouard 9758: /* for (h=0; h<=nhstepm; h++){ */
9759: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
9760: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
9761: /* } */
9762: /* for(j=1; j<=nlstate+ndeath;j++) { */
9763: /* kk1=0.;kk2=0; */
9764: /* for(i=1; i<=nlstate;i++) { */
9765: /* if (mobilav==1) */
9766: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
9767: /* else { */
9768: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
9769: /* } */
9770: /* } */
9771: /* if (h==(int)(calagedatem+12*cpt)){ */
9772: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
9773: /* /\*fprintf(ficrespop," %.3f", kk1); */
9774: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
9775: /* } */
9776: /* } */
9777: /* for(i=1; i<=nlstate;i++){ */
9778: /* kk1=0.; */
9779: /* for(j=1; j<=nlstate;j++){ */
9780: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
9781: /* } */
9782: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
9783: /* } */
1.218 brouard 9784:
1.227 brouard 9785: /* if (h==(int)(calagedatem+12*cpt)) */
9786: /* for(j=1; j<=nlstate;j++) */
9787: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
9788: /* } */
9789: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9790: /* } */
9791: /* } */
1.218 brouard 9792:
1.227 brouard 9793: /* /\******\/ */
1.218 brouard 9794:
1.227 brouard 9795: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
9796: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
9797: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
9798: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
9799: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 9800:
1.227 brouard 9801: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9802: /* oldm=oldms;savm=savms; */
9803: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
9804: /* for (h=0; h<=nhstepm; h++){ */
9805: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
9806: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
9807: /* } */
9808: /* for(j=1; j<=nlstate+ndeath;j++) { */
9809: /* kk1=0.;kk2=0; */
9810: /* for(i=1; i<=nlstate;i++) { */
9811: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
9812: /* } */
9813: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
9814: /* } */
9815: /* } */
9816: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9817: /* } */
9818: /* } */
9819: /* } */
9820: /* } */
1.218 brouard 9821:
1.227 brouard 9822: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 9823:
1.227 brouard 9824: /* if (popforecast==1) { */
9825: /* free_ivector(popage,0,AGESUP); */
9826: /* free_vector(popeffectif,0,AGESUP); */
9827: /* free_vector(popcount,0,AGESUP); */
9828: /* } */
9829: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9830: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9831: /* fclose(ficrespop); */
9832: /* } /\* End of popforecast *\/ */
1.218 brouard 9833:
1.126 brouard 9834: int fileappend(FILE *fichier, char *optionfich)
9835: {
9836: if((fichier=fopen(optionfich,"a"))==NULL) {
9837: printf("Problem with file: %s\n", optionfich);
9838: fprintf(ficlog,"Problem with file: %s\n", optionfich);
9839: return (0);
9840: }
9841: fflush(fichier);
9842: return (1);
9843: }
9844:
9845:
9846: /**************** function prwizard **********************/
9847: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
9848: {
9849:
9850: /* Wizard to print covariance matrix template */
9851:
1.164 brouard 9852: char ca[32], cb[32];
9853: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 9854: int numlinepar;
9855:
9856: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
9857: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
9858: for(i=1; i <=nlstate; i++){
9859: jj=0;
9860: for(j=1; j <=nlstate+ndeath; j++){
9861: if(j==i) continue;
9862: jj++;
9863: /*ca[0]= k+'a'-1;ca[1]='\0';*/
9864: printf("%1d%1d",i,j);
9865: fprintf(ficparo,"%1d%1d",i,j);
9866: for(k=1; k<=ncovmodel;k++){
9867: /* printf(" %lf",param[i][j][k]); */
9868: /* fprintf(ficparo," %lf",param[i][j][k]); */
9869: printf(" 0.");
9870: fprintf(ficparo," 0.");
9871: }
9872: printf("\n");
9873: fprintf(ficparo,"\n");
9874: }
9875: }
9876: printf("# Scales (for hessian or gradient estimation)\n");
9877: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
9878: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
9879: for(i=1; i <=nlstate; i++){
9880: jj=0;
9881: for(j=1; j <=nlstate+ndeath; j++){
9882: if(j==i) continue;
9883: jj++;
9884: fprintf(ficparo,"%1d%1d",i,j);
9885: printf("%1d%1d",i,j);
9886: fflush(stdout);
9887: for(k=1; k<=ncovmodel;k++){
9888: /* printf(" %le",delti3[i][j][k]); */
9889: /* fprintf(ficparo," %le",delti3[i][j][k]); */
9890: printf(" 0.");
9891: fprintf(ficparo," 0.");
9892: }
9893: numlinepar++;
9894: printf("\n");
9895: fprintf(ficparo,"\n");
9896: }
9897: }
9898: printf("# Covariance matrix\n");
9899: /* # 121 Var(a12)\n\ */
9900: /* # 122 Cov(b12,a12) Var(b12)\n\ */
9901: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
9902: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
9903: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
9904: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
9905: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
9906: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
9907: fflush(stdout);
9908: fprintf(ficparo,"# Covariance matrix\n");
9909: /* # 121 Var(a12)\n\ */
9910: /* # 122 Cov(b12,a12) Var(b12)\n\ */
9911: /* # ...\n\ */
9912: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
9913:
9914: for(itimes=1;itimes<=2;itimes++){
9915: jj=0;
9916: for(i=1; i <=nlstate; i++){
9917: for(j=1; j <=nlstate+ndeath; j++){
9918: if(j==i) continue;
9919: for(k=1; k<=ncovmodel;k++){
9920: jj++;
9921: ca[0]= k+'a'-1;ca[1]='\0';
9922: if(itimes==1){
9923: printf("#%1d%1d%d",i,j,k);
9924: fprintf(ficparo,"#%1d%1d%d",i,j,k);
9925: }else{
9926: printf("%1d%1d%d",i,j,k);
9927: fprintf(ficparo,"%1d%1d%d",i,j,k);
9928: /* printf(" %.5le",matcov[i][j]); */
9929: }
9930: ll=0;
9931: for(li=1;li <=nlstate; li++){
9932: for(lj=1;lj <=nlstate+ndeath; lj++){
9933: if(lj==li) continue;
9934: for(lk=1;lk<=ncovmodel;lk++){
9935: ll++;
9936: if(ll<=jj){
9937: cb[0]= lk +'a'-1;cb[1]='\0';
9938: if(ll<jj){
9939: if(itimes==1){
9940: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
9941: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
9942: }else{
9943: printf(" 0.");
9944: fprintf(ficparo," 0.");
9945: }
9946: }else{
9947: if(itimes==1){
9948: printf(" Var(%s%1d%1d)",ca,i,j);
9949: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
9950: }else{
9951: printf(" 0.");
9952: fprintf(ficparo," 0.");
9953: }
9954: }
9955: }
9956: } /* end lk */
9957: } /* end lj */
9958: } /* end li */
9959: printf("\n");
9960: fprintf(ficparo,"\n");
9961: numlinepar++;
9962: } /* end k*/
9963: } /*end j */
9964: } /* end i */
9965: } /* end itimes */
9966:
9967: } /* end of prwizard */
9968: /******************* Gompertz Likelihood ******************************/
9969: double gompertz(double x[])
9970: {
1.302 brouard 9971: double A=0.0,B=0.,L=0.0,sump=0.,num=0.;
1.126 brouard 9972: int i,n=0; /* n is the size of the sample */
9973:
1.220 brouard 9974: for (i=1;i<=imx ; i++) {
1.126 brouard 9975: sump=sump+weight[i];
9976: /* sump=sump+1;*/
9977: num=num+1;
9978: }
1.302 brouard 9979: L=0.0;
9980: /* agegomp=AGEGOMP; */
1.126 brouard 9981: /* for (i=0; i<=imx; i++)
9982: 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]);*/
9983:
1.302 brouard 9984: for (i=1;i<=imx ; i++) {
9985: /* mu(a)=mu(agecomp)*exp(teta*(age-agegomp))
9986: mu(a)=x[1]*exp(x[2]*(age-agegomp)); x[1] and x[2] are per year.
9987: * L= Product mu(agedeces)exp(-\int_ageexam^agedc mu(u) du ) for a death between agedc (in month)
9988: * and agedc +1 month, cens[i]=0: log(x[1]/YEARM)
9989: * +
9990: * exp(-\int_ageexam^agecens mu(u) du ) when censored, cens[i]=1
9991: */
9992: if (wav[i] > 1 || agedc[i] < AGESUP) {
9993: if (cens[i] == 1){
9994: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
9995: } else if (cens[i] == 0){
1.126 brouard 9996: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
1.302 brouard 9997: +log(x[1]/YEARM) +x[2]*(agedc[i]-agegomp)+log(YEARM);
9998: } else
9999: printf("Gompertz cens[%d] neither 1 nor 0\n",i);
1.126 brouard 10000: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
1.302 brouard 10001: L=L+A*weight[i];
1.126 brouard 10002: /* 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 10003: }
10004: }
1.126 brouard 10005:
1.302 brouard 10006: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
1.126 brouard 10007:
10008: return -2*L*num/sump;
10009: }
10010:
1.136 brouard 10011: #ifdef GSL
10012: /******************* Gompertz_f Likelihood ******************************/
10013: double gompertz_f(const gsl_vector *v, void *params)
10014: {
1.302 brouard 10015: double A=0.,B=0.,LL=0.0,sump=0.,num=0.;
1.136 brouard 10016: double *x= (double *) v->data;
10017: int i,n=0; /* n is the size of the sample */
10018:
10019: for (i=0;i<=imx-1 ; i++) {
10020: sump=sump+weight[i];
10021: /* sump=sump+1;*/
10022: num=num+1;
10023: }
10024:
10025:
10026: /* for (i=0; i<=imx; i++)
10027: 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]);*/
10028: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
10029: for (i=1;i<=imx ; i++)
10030: {
10031: if (cens[i] == 1 && wav[i]>1)
10032: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
10033:
10034: if (cens[i] == 0 && wav[i]>1)
10035: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
10036: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
10037:
10038: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
10039: if (wav[i] > 1 ) { /* ??? */
10040: LL=LL+A*weight[i];
10041: /* 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]);*/
10042: }
10043: }
10044:
10045: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
10046: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
10047:
10048: return -2*LL*num/sump;
10049: }
10050: #endif
10051:
1.126 brouard 10052: /******************* Printing html file ***********/
1.201 brouard 10053: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 10054: int lastpass, int stepm, int weightopt, char model[],\
10055: int imx, double p[],double **matcov,double agemortsup){
10056: int i,k;
10057:
10058: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
10059: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
10060: for (i=1;i<=2;i++)
10061: 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 10062: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 10063: fprintf(fichtm,"</ul>");
10064:
10065: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
10066:
10067: 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>");
10068:
10069: for (k=agegomp;k<(agemortsup-2);k++)
10070: 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]);
10071:
10072:
10073: fflush(fichtm);
10074: }
10075:
10076: /******************* Gnuplot file **************/
1.201 brouard 10077: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 10078:
10079: char dirfileres[132],optfileres[132];
1.164 brouard 10080:
1.126 brouard 10081: int ng;
10082:
10083:
10084: /*#ifdef windows */
10085: fprintf(ficgp,"cd \"%s\" \n",pathc);
10086: /*#endif */
10087:
10088:
10089: strcpy(dirfileres,optionfilefiname);
10090: strcpy(optfileres,"vpl");
1.199 brouard 10091: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 10092: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 10093: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 10094: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 10095: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
10096:
10097: }
10098:
1.136 brouard 10099: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
10100: {
1.126 brouard 10101:
1.136 brouard 10102: /*-------- data file ----------*/
10103: FILE *fic;
10104: char dummy[]=" ";
1.240 brouard 10105: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 10106: int lstra;
1.136 brouard 10107: int linei, month, year,iout;
1.302 brouard 10108: int noffset=0; /* This is the offset if BOM data file */
1.136 brouard 10109: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 10110: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 10111: char *stratrunc;
1.223 brouard 10112:
1.240 brouard 10113: DummyV=ivector(1,NCOVMAX); /* 1 to 3 */
10114: FixedV=ivector(1,NCOVMAX); /* 1 to 3 */
1.328 brouard 10115: for(v=1;v<NCOVMAX;v++){
10116: DummyV[v]=0;
10117: FixedV[v]=0;
10118: }
1.126 brouard 10119:
1.240 brouard 10120: for(v=1; v <=ncovcol;v++){
10121: DummyV[v]=0;
10122: FixedV[v]=0;
10123: }
10124: for(v=ncovcol+1; v <=ncovcol+nqv;v++){
10125: DummyV[v]=1;
10126: FixedV[v]=0;
10127: }
10128: for(v=ncovcol+nqv+1; v <=ncovcol+nqv+ntv;v++){
10129: DummyV[v]=0;
10130: FixedV[v]=1;
10131: }
10132: for(v=ncovcol+nqv+ntv+1; v <=ncovcol+nqv+ntv+nqtv;v++){
10133: DummyV[v]=1;
10134: FixedV[v]=1;
10135: }
10136: for(v=1; v <=ncovcol+nqv+ntv+nqtv;v++){
10137: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",v,v,DummyV[v],v,FixedV[v]);
10138: 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]);
10139: }
1.126 brouard 10140:
1.136 brouard 10141: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 10142: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
10143: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 10144: }
1.126 brouard 10145:
1.302 brouard 10146: /* Is it a BOM UTF-8 Windows file? */
10147: /* First data line */
10148: linei=0;
10149: while(fgets(line, MAXLINE, fic)) {
10150: noffset=0;
10151: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
10152: {
10153: noffset=noffset+3;
10154: printf("# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);fflush(stdout);
10155: fprintf(ficlog,"# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);
10156: fflush(ficlog); return 1;
10157: }
10158: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
10159: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
10160: {
10161: noffset=noffset+2;
1.304 brouard 10162: 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);
10163: 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 10164: fflush(ficlog); return 1;
10165: }
10166: else if( line[0] == 0 && line[1] == 0)
10167: {
10168: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
10169: noffset=noffset+4;
1.304 brouard 10170: 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);
10171: 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 10172: fflush(ficlog); return 1;
10173: }
10174: } else{
10175: ;/*printf(" Not a BOM file\n");*/
10176: }
10177: /* If line starts with a # it is a comment */
10178: if (line[noffset] == '#') {
10179: linei=linei+1;
10180: break;
10181: }else{
10182: break;
10183: }
10184: }
10185: fclose(fic);
10186: if((fic=fopen(datafile,"r"))==NULL) {
10187: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
10188: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
10189: }
10190: /* Not a Bom file */
10191:
1.136 brouard 10192: i=1;
10193: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
10194: linei=linei+1;
10195: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
10196: if(line[j] == '\t')
10197: line[j] = ' ';
10198: }
10199: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
10200: ;
10201: };
10202: line[j+1]=0; /* Trims blanks at end of line */
10203: if(line[0]=='#'){
10204: fprintf(ficlog,"Comment line\n%s\n",line);
10205: printf("Comment line\n%s\n",line);
10206: continue;
10207: }
10208: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 10209: strcpy(line, linetmp);
1.223 brouard 10210:
10211: /* Loops on waves */
10212: for (j=maxwav;j>=1;j--){
10213: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 10214: cutv(stra, strb, line, ' ');
10215: if(strb[0]=='.') { /* Missing value */
10216: lval=-1;
10217: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
10218: cotvar[j][ntv+iv][i]=-1; /* For performance reasons */
10219: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
10220: 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);
10221: 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);
10222: return 1;
10223: }
10224: }else{
10225: errno=0;
10226: /* what_kind_of_number(strb); */
10227: dval=strtod(strb,&endptr);
10228: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
10229: /* if(strb != endptr && *endptr == '\0') */
10230: /* dval=dlval; */
10231: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
10232: if( strb[0]=='\0' || (*endptr != '\0')){
10233: 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);
10234: 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);
10235: return 1;
10236: }
10237: cotqvar[j][iv][i]=dval;
10238: cotvar[j][ntv+iv][i]=dval;
10239: }
10240: strcpy(line,stra);
1.223 brouard 10241: }/* end loop ntqv */
1.225 brouard 10242:
1.223 brouard 10243: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 10244: cutv(stra, strb, line, ' ');
10245: if(strb[0]=='.') { /* Missing value */
10246: lval=-1;
10247: }else{
10248: errno=0;
10249: lval=strtol(strb,&endptr,10);
10250: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
10251: if( strb[0]=='\0' || (*endptr != '\0')){
10252: 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);
10253: 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);
10254: return 1;
10255: }
10256: }
10257: if(lval <-1 || lval >1){
10258: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 10259: Should be a value of %d(nth) covariate of wave %d (0 should be the value for the reference and 1\n \
1.223 brouard 10260: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 10261: For example, for multinomial values like 1, 2 and 3,\n \
10262: build V1=0 V2=0 for the reference value (1),\n \
10263: V1=1 V2=0 for (2) \n \
1.223 brouard 10264: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 10265: output of IMaCh is often meaningless.\n \
1.319 brouard 10266: Exiting.\n",lval,linei, i,line,iv,j);
1.238 brouard 10267: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 10268: Should be a value of %d(nth) covariate of wave %d (0 should be the value for the reference and 1\n \
1.223 brouard 10269: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 10270: For example, for multinomial values like 1, 2 and 3,\n \
10271: build V1=0 V2=0 for the reference value (1),\n \
10272: V1=1 V2=0 for (2) \n \
1.223 brouard 10273: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 10274: output of IMaCh is often meaningless.\n \
1.319 brouard 10275: Exiting.\n",lval,linei, i,line,iv,j);fflush(ficlog);
1.238 brouard 10276: return 1;
10277: }
10278: cotvar[j][iv][i]=(double)(lval);
10279: strcpy(line,stra);
1.223 brouard 10280: }/* end loop ntv */
1.225 brouard 10281:
1.223 brouard 10282: /* Statuses at wave */
1.137 brouard 10283: cutv(stra, strb, line, ' ');
1.223 brouard 10284: if(strb[0]=='.') { /* Missing value */
1.238 brouard 10285: lval=-1;
1.136 brouard 10286: }else{
1.238 brouard 10287: errno=0;
10288: lval=strtol(strb,&endptr,10);
10289: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
10290: if( strb[0]=='\0' || (*endptr != '\0')){
10291: 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);
10292: 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);
10293: return 1;
10294: }
1.136 brouard 10295: }
1.225 brouard 10296:
1.136 brouard 10297: s[j][i]=lval;
1.225 brouard 10298:
1.223 brouard 10299: /* Date of Interview */
1.136 brouard 10300: strcpy(line,stra);
10301: cutv(stra, strb,line,' ');
1.169 brouard 10302: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10303: }
1.169 brouard 10304: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 10305: month=99;
10306: year=9999;
1.136 brouard 10307: }else{
1.225 brouard 10308: 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);
10309: 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);
10310: return 1;
1.136 brouard 10311: }
10312: anint[j][i]= (double) year;
1.302 brouard 10313: mint[j][i]= (double)month;
10314: /* if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){ */
10315: /* 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]); */
10316: /* 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]); */
10317: /* } */
1.136 brouard 10318: strcpy(line,stra);
1.223 brouard 10319: } /* End loop on waves */
1.225 brouard 10320:
1.223 brouard 10321: /* Date of death */
1.136 brouard 10322: cutv(stra, strb,line,' ');
1.169 brouard 10323: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10324: }
1.169 brouard 10325: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 10326: month=99;
10327: year=9999;
10328: }else{
1.141 brouard 10329: 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 10330: 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);
10331: return 1;
1.136 brouard 10332: }
10333: andc[i]=(double) year;
10334: moisdc[i]=(double) month;
10335: strcpy(line,stra);
10336:
1.223 brouard 10337: /* Date of birth */
1.136 brouard 10338: cutv(stra, strb,line,' ');
1.169 brouard 10339: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10340: }
1.169 brouard 10341: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 10342: month=99;
10343: year=9999;
10344: }else{
1.141 brouard 10345: 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);
10346: 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 10347: return 1;
1.136 brouard 10348: }
10349: if (year==9999) {
1.141 brouard 10350: 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);
10351: 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 10352: return 1;
10353:
1.136 brouard 10354: }
10355: annais[i]=(double)(year);
1.302 brouard 10356: moisnais[i]=(double)(month);
10357: for (j=1;j<=maxwav;j++){
10358: if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){
10359: 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]);
10360: 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]);
10361: }
10362: }
10363:
1.136 brouard 10364: strcpy(line,stra);
1.225 brouard 10365:
1.223 brouard 10366: /* Sample weight */
1.136 brouard 10367: cutv(stra, strb,line,' ');
10368: errno=0;
10369: dval=strtod(strb,&endptr);
10370: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 10371: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
10372: 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 10373: fflush(ficlog);
10374: return 1;
10375: }
10376: weight[i]=dval;
10377: strcpy(line,stra);
1.225 brouard 10378:
1.223 brouard 10379: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
10380: cutv(stra, strb, line, ' ');
10381: if(strb[0]=='.') { /* Missing value */
1.225 brouard 10382: lval=-1;
1.311 brouard 10383: coqvar[iv][i]=NAN;
10384: covar[ncovcol+iv][i]=NAN; /* including qvar in standard covar for performance reasons */
1.223 brouard 10385: }else{
1.225 brouard 10386: errno=0;
10387: /* what_kind_of_number(strb); */
10388: dval=strtod(strb,&endptr);
10389: /* if(strb != endptr && *endptr == '\0') */
10390: /* dval=dlval; */
10391: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
10392: if( strb[0]=='\0' || (*endptr != '\0')){
10393: 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);
10394: 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);
10395: return 1;
10396: }
10397: coqvar[iv][i]=dval;
1.226 brouard 10398: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 10399: }
10400: strcpy(line,stra);
10401: }/* end loop nqv */
1.136 brouard 10402:
1.223 brouard 10403: /* Covariate values */
1.136 brouard 10404: for (j=ncovcol;j>=1;j--){
10405: cutv(stra, strb,line,' ');
1.223 brouard 10406: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 10407: lval=-1;
1.136 brouard 10408: }else{
1.225 brouard 10409: errno=0;
10410: lval=strtol(strb,&endptr,10);
10411: if( strb[0]=='\0' || (*endptr != '\0')){
10412: 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);
10413: 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);
10414: return 1;
10415: }
1.136 brouard 10416: }
10417: if(lval <-1 || lval >1){
1.225 brouard 10418: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 10419: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
10420: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 10421: For example, for multinomial values like 1, 2 and 3,\n \
10422: build V1=0 V2=0 for the reference value (1),\n \
10423: V1=1 V2=0 for (2) \n \
1.136 brouard 10424: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 10425: output of IMaCh is often meaningless.\n \
1.136 brouard 10426: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 10427: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 10428: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
10429: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 10430: For example, for multinomial values like 1, 2 and 3,\n \
10431: build V1=0 V2=0 for the reference value (1),\n \
10432: V1=1 V2=0 for (2) \n \
1.136 brouard 10433: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 10434: output of IMaCh is often meaningless.\n \
1.136 brouard 10435: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 10436: return 1;
1.136 brouard 10437: }
10438: covar[j][i]=(double)(lval);
10439: strcpy(line,stra);
10440: }
10441: lstra=strlen(stra);
1.225 brouard 10442:
1.136 brouard 10443: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
10444: stratrunc = &(stra[lstra-9]);
10445: num[i]=atol(stratrunc);
10446: }
10447: else
10448: num[i]=atol(stra);
10449: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
10450: 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;}*/
10451:
10452: i=i+1;
10453: } /* End loop reading data */
1.225 brouard 10454:
1.136 brouard 10455: *imax=i-1; /* Number of individuals */
10456: fclose(fic);
1.225 brouard 10457:
1.136 brouard 10458: return (0);
1.164 brouard 10459: /* endread: */
1.225 brouard 10460: printf("Exiting readdata: ");
10461: fclose(fic);
10462: return (1);
1.223 brouard 10463: }
1.126 brouard 10464:
1.234 brouard 10465: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 10466: char *p1 = *stri, *p2 = *stri;
1.235 brouard 10467: while (*p2 == ' ')
1.234 brouard 10468: p2++;
10469: /* while ((*p1++ = *p2++) !=0) */
10470: /* ; */
10471: /* do */
10472: /* while (*p2 == ' ') */
10473: /* p2++; */
10474: /* while (*p1++ == *p2++); */
10475: *stri=p2;
1.145 brouard 10476: }
10477:
1.330 brouard 10478: int decoderesult( char resultline[], int nres)
1.230 brouard 10479: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
10480: {
1.235 brouard 10481: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 10482: char resultsav[MAXLINE];
1.330 brouard 10483: /* int resultmodel[MAXLINE]; */
1.334 brouard 10484: /* int modelresult[MAXLINE]; */
1.230 brouard 10485: char stra[80], strb[80], strc[80], strd[80],stre[80];
10486:
1.234 brouard 10487: removefirstspace(&resultline);
1.332 brouard 10488: printf("decoderesult:%s\n",resultline);
1.230 brouard 10489:
1.332 brouard 10490: strcpy(resultsav,resultline);
10491: printf("Decoderesult resultsav=\"%s\" resultline=\"%s\"\n", resultsav, resultline);
1.230 brouard 10492: if (strlen(resultsav) >1){
1.334 brouard 10493: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' in this resultline */
1.230 brouard 10494: }
1.253 brouard 10495: if(j == 0){ /* Resultline but no = */
10496: TKresult[nres]=0; /* Combination for the nresult and the model */
10497: return (0);
10498: }
1.234 brouard 10499: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
1.334 brouard 10500: printf("ERROR: the number of variables in the resultline which is %d, differs from the number %d of single variables used in the model line, %s.\n",j, cptcovs, model);
10501: fprintf(ficlog,"ERROR: the number of variables in the resultline which is %d, differs from the number %d of single variables used in the model line, %s.\n",j, cptcovs, model);
1.332 brouard 10502: /* return 1;*/
1.234 brouard 10503: }
1.334 brouard 10504: for(k=1; k<=j;k++){ /* Loop on any covariate of the RESULT LINE */
1.234 brouard 10505: if(nbocc(resultsav,'=') >1){
1.318 brouard 10506: 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" */
1.332 brouard 10507: /* If resultsav= "V4= 1 V5=25.1 V3=0" with a blank then strb="V4=" and stra="1 V5=25.1 V3=0" */
1.318 brouard 10508: cutl(strc,strd,strb,'='); /* strb:"V4=1" strc="1" strd="V4" */
1.332 brouard 10509: /* If a blank, then strc="V4=" and strd='\0' */
10510: if(strc[0]=='\0'){
10511: printf("Error in resultline, probably a blank after the \"%s\", \"result:%s\", stra=\"%s\" resultsav=\"%s\"\n",strb,resultline, stra, resultsav);
10512: fprintf(ficlog,"Error in resultline, probably a blank after the \"V%s=\", resultline=%s\n",strb,resultline);
10513: return 1;
10514: }
1.234 brouard 10515: }else
10516: cutl(strc,strd,resultsav,'=');
1.318 brouard 10517: Tvalsel[k]=atof(strc); /* 1 */ /* Tvalsel of k is the float value of the kth covariate appearing in this result line */
1.234 brouard 10518:
1.230 brouard 10519: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
1.318 brouard 10520: 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 10521: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
10522: /* cptcovsel++; */
10523: if (nbocc(stra,'=') >0)
10524: strcpy(resultsav,stra); /* and analyzes it */
10525: }
1.235 brouard 10526: /* Checking for missing or useless values in comparison of current model needs */
1.332 brouard 10527: /* Feeds resultmodel[nres][k1]=k2 for k1th product covariate with age in the model equation fed by the index k2 of the resutline*/
1.334 brouard 10528: for(k1=1; k1<= cptcovt ;k1++){ /* Loop on MODEL LINE V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.332 brouard 10529: if(Typevar[k1]==0){ /* Single covariate in model */
10530: /* 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.234 brouard 10531: match=0;
1.318 brouard 10532: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
10533: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.334 brouard 10534: modelresult[nres][k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.318 brouard 10535: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
1.234 brouard 10536: break;
10537: }
10538: }
10539: if(match == 0){
1.338 ! brouard 10540: printf("Error in result line (Dummy single): V%d is missing in result: %s according to model=1+age+%s. Tvar[k1=%d]=%d is different from Tvarsel[k2=%d]=%d.\n",Tvar[k1], resultline, model,k1, Tvar[k1], k2, Tvarsel[k2]);
! 10541: fprintf(ficlog,"Error in result line (Dummy single): V%d is missing in result: %s according to model=1+age+%s\n",Tvar[k1], resultline, model);
1.310 brouard 10542: return 1;
1.234 brouard 10543: }
1.332 brouard 10544: }else if(Typevar[k1]==1){ /* Product with age We want to get the position k2 in the resultline of the product k1 in the model line*/
10545: /* We feed resultmodel[k1]=k2; */
10546: match=0;
10547: for(k2=1; k2 <=j;k2++){/* Loop on resultline. jth occurence of = signs in the result line. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
10548: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.334 brouard 10549: modelresult[nres][k2]=k1;/* we found a Vn=1 corrresponding to Vn*age in the model modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.332 brouard 10550: resultmodel[nres][k1]=k2; /* Added here */
10551: printf("Decoderesult first modelresult[k2=%d]=%d (k1) V%d*AGE\n",k2,k1,Tvar[k1]);
10552: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
10553: break;
10554: }
10555: }
10556: if(match == 0){
1.338 ! brouard 10557: printf("Error in result line (Product with age): V%d is missing in result: %s according to model=1+age+%s (Tvarsel[k2=%d]=%d)\n",Tvar[k1], resultline, model, k2, Tvarsel[k2]);
! 10558: fprintf(ficlog,"Error in result line (Product with age): V%d is missing in result: %s according to model=1+age+%s (Tvarsel[k2=%d]=%d)\n",Tvar[k1], resultline, model, k2, Tvarsel[k2]);
1.332 brouard 10559: return 1;
10560: }
10561: }else if(Typevar[k1]==2){ /* Product No age We want to get the position in the resultline of the product in the model line*/
10562: /* resultmodel[nres][of such a Vn * Vm product k1] is not unique, so can't exist, we feed Tvard[k1][1] and [2] */
10563: match=0;
10564: printf("Decoderesult very first Product Tvardk[k1=%d][1]=%d Tvardk[k1=%d][2]=%d V%d * V%d\n",k1,Tvardk[k1][1],k1,Tvardk[k1][2],Tvardk[k1][1],Tvardk[k1][2]);
10565: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
10566: if(Tvardk[k1][1]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
10567: /* modelresult[k2]=k1; */
10568: printf("Decoderesult first Product modelresult[k2=%d]=%d (k1) V%d * \n",k2,k1,Tvarsel[k2]);
10569: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
10570: }
10571: }
10572: if(match == 0){
1.338 ! brouard 10573: printf("Error in result line (Product without age first variable): V%d is missing in result: %s according to model=1+age+%s\n",Tvardk[k1][1], resultline, model);
! 10574: fprintf(ficlog,"Error in result line (Product without age first variable): V%d is missing in result: %s according to model=1+age+%s\n",Tvardk[k1][1], resultline, model);
1.332 brouard 10575: return 1;
10576: }
10577: match=0;
10578: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
10579: if(Tvardk[k1][2]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
10580: /* modelresult[k2]=k1;*/
10581: printf("Decoderesult second Product modelresult[k2=%d]=%d (k1) * V%d \n ",k2,k1,Tvarsel[k2]);
10582: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
10583: break;
10584: }
10585: }
10586: if(match == 0){
1.338 ! brouard 10587: printf("Error in result line (Product without age second variable): V%d is missing in result: %s according to model=1+age+%s\n",Tvardk[k1][2], resultline, model);
! 10588: fprintf(ficlog,"Error in result line (Product without age second variable): V%d is missing in result : %s according to model=1+age+%s\n",Tvardk[k1][2], resultline, model);
1.332 brouard 10589: return 1;
10590: }
10591: }/* End of testing */
1.333 brouard 10592: }/* End loop cptcovt */
1.235 brouard 10593: /* Checking for missing or useless values in comparison of current model needs */
1.332 brouard 10594: /* Feeds resultmodel[nres][k1]=k2 for single covariate (k1) in the model equation */
1.334 brouard 10595: for(k2=1; k2 <=j;k2++){ /* j or cptcovs is the number of single covariates used either in the model line as well as in the result line (dummy or quantitative)
10596: * Loop on resultline variables: result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 10597: match=0;
1.318 brouard 10598: for(k1=1; k1<= cptcovt ;k1++){ /* loop on model: model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.332 brouard 10599: if(Typevar[k1]==0){ /* Single only */
1.237 brouard 10600: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 */
1.330 brouard 10601: resultmodel[nres][k1]=k2; /* k1th position in the model equation corresponds to k2th position in the result line. resultmodel[2]=1 resultmodel[1]=2 resultmodel[3]=3 resultmodel[6]=4 resultmodel[9]=5 */
1.334 brouard 10602: modelresult[nres][k2]=k1; /* k1th position in the model equation corresponds to k2th position in the result line. modelresult[1]=2 modelresult[2]=1 modelresult[3]=3 remodelresult[4]=6 modelresult[5]=9 */
1.234 brouard 10603: ++match;
10604: }
10605: }
10606: }
10607: if(match == 0){
1.338 ! brouard 10608: printf("Error in result line: variable V%d is missing in model; result: %s, model=1+age+%s\n",Tvarsel[k2], resultline, model);
! 10609: fprintf(ficlog,"Error in result line: variable V%d is missing in model; result: %s, model=1+age+%s\n",Tvarsel[k2], resultline, model);
1.310 brouard 10610: return 1;
1.234 brouard 10611: }else if(match > 1){
1.338 ! brouard 10612: printf("Error in result line: %d doubled; result: %s, model=1+age+%s\n",k2, resultline, model);
! 10613: fprintf(ficlog,"Error in result line: %d doubled; result: %s, model=1+age+%s\n",k2, resultline, model);
1.310 brouard 10614: return 1;
1.234 brouard 10615: }
10616: }
1.334 brouard 10617: /* cptcovres=j /\* Number of variables in the resultline is equal to cptcovs and thus useless *\/ */
1.234 brouard 10618: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 10619: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.330 brouard 10620: /* nres=1st result line: V4=1 V5=25.1 V3=0 V2=8 V1=1 */
10621: /* should correspond to the combination 6 of dummy: V4=1, V3=0, V1=1 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 1*1 + 0*2 + 1*4 = 5 + (1offset) = 6*/
10622: /* nres=2nd result line: V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.235 brouard 10623: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
10624: /* 1 0 0 0 */
10625: /* 2 1 0 0 */
10626: /* 3 0 1 0 */
1.330 brouard 10627: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 (nres=2)*/
1.235 brouard 10628: /* 5 0 0 1 */
1.330 brouard 10629: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 (nres=1)*/
1.235 brouard 10630: /* 7 0 1 1 */
10631: /* 8 1 1 1 */
1.237 brouard 10632: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
10633: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
10634: /* V5*age V5 known which value for nres? */
10635: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.334 brouard 10636: for(k1=1, k=0, k4=0, k4q=0; k1 <=cptcovt;k1++){ /* cptcovt number of covariates (excluding 1 and age or age*age) in the MODEL equation.
10637: * loop on position k1 in the MODEL LINE */
1.331 brouard 10638: /* k counting number of combination of single dummies in the equation model */
10639: /* k4 counting single dummies in the equation model */
10640: /* k4q counting single quantitatives in the equation model */
1.334 brouard 10641: if( Dummy[k1]==0 && Typevar[k1]==0 ){ /* Dummy and Single, k1 is sorting according to MODEL, but k3 to resultline */
10642: /* k4+1= (not always if quant in model) position in the resultline V(Tvarsel)=Tvalsel=Tresult[nres][pos](value); V(Tvresult[nres][pos] (variable): V(variable)=value) */
1.332 brouard 10643: /* modelresult[k3]=k1: k3th position in the result line corresponds to the k1 position in the model line (doesn't work with products)*/
1.330 brouard 10644: /* Value in the (current nres) resultline of the variable at the k1th position in the model equation resultmodel[nres][k1]= k3 */
1.332 brouard 10645: /* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline */
10646: /* k3 is the position in the nres result line of the k1th variable of the model equation */
10647: /* Tvarsel[k3]: Name of the variable at the k3th position in the result line. */
10648: /* Tvalsel[k3]: Value of the variable at the k3th position in the result line. */
10649: /* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
1.334 brouard 10650: /* Tvresult[nres][result_position]= name of the dummy variable at the result_position in the nres resultline */
1.332 brouard 10651: /* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
1.330 brouard 10652: /* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
1.332 brouard 10653: k3= resultmodel[nres][k1]; /* From position k1 in model get position k3 in result line */
10654: /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
10655: k2=(int)Tvarsel[k3]; /* from position k3 in resultline get name k2: nres=1 k1=2=>k3=1 Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 (V4); k1=3=>k3=2 Tvarsel[2]=3 (V3)*/
1.330 brouard 10656: k+=Tvalsel[k3]*pow(2,k4); /* nres=1 k1=2 Tvalsel[1]=1 (V4=1); k1=3 k3=2 Tvalsel[2]=0 (V3=0) */
1.334 brouard 10657: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][Name]=Value; stores the value into the name of the variable. */
1.332 brouard 10658: /* Tinvresult[nres][4]=1 */
1.334 brouard 10659: /* Tresult[nres][k4+1]=Tvalsel[k3];/\* Tresult[nres=2][1]=1(V4=1) Tresult[nres=2][2]=0(V3=0) *\/ */
10660: Tresult[nres][k3]=Tvalsel[k3];/* Tresult[nres=2][1]=1(V4=1) Tresult[nres=2][2]=0(V3=0) */
10661: /* Tvresult[nres][k4+1]=(int)Tvarsel[k3];/\* Tvresult[nres][1]=4 Tvresult[nres][3]=1 *\/ */
10662: Tvresult[nres][k3]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
1.237 brouard 10663: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.334 brouard 10664: precov[nres][k1]=Tvalsel[k3]; /* Value from resultline of the variable at the k1 position in the model */
1.332 brouard 10665: printf("Decoderesult Dummy k=%d, k1=%d precov[nres=%d][k1=%d]=%.f V(k2=V%d)= Tvalsel[%d]=%d, 2**(%d)\n",k, k1, nres, k1,precov[nres][k1], k2, k3, (int)Tvalsel[k3], k4);
1.235 brouard 10666: k4++;;
1.331 brouard 10667: }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Quantitative and single */
1.330 brouard 10668: /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
1.332 brouard 10669: /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
1.330 brouard 10670: /* Tqinvresult[nres][Name of a quantitative variable]= value of the variable in the result line */
1.332 brouard 10671: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 5 =k3q */
10672: k2q=(int)Tvarsel[k3q]; /* Name of variable at k3q th position in the resultline */
10673: /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
1.334 brouard 10674: /* Tqresult[nres][k4q+1]=Tvalsel[k3q]; /\* Tqresult[nres][1]=25.1 *\/ */
10675: /* Tvresult[nres][k4q+1]=(int)Tvarsel[k3q];/\* Tvresult[nres][1]=4 Tvresult[nres][3]=1 *\/ */
10676: /* Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /\* Tvqresult[nres][1]=5 *\/ */
10677: Tqresult[nres][k3q]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
10678: Tvresult[nres][k3q]=(int)Tvarsel[k3q];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
10679: Tvqresult[nres][k3q]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
1.237 brouard 10680: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.330 brouard 10681: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.332 brouard 10682: precov[nres][k1]=Tvalsel[k3q];
10683: printf("Decoderesult Quantitative nres=%d,precov[nres=%d][k1=%d]=%.f V(k2q=V%d)= Tvalsel[%d]=%d, Tvarsel[%d]=%f\n",nres, nres, k1,precov[nres][k1], k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]);
1.235 brouard 10684: k4q++;;
1.331 brouard 10685: }else if( Dummy[k1]==2 ){ /* For dummy with age product */
10686: /* Tvar[k1]; */ /* Age variable */
1.332 brouard 10687: /* Wrong we want the value of variable name Tvar[k1] */
10688:
10689: k3= resultmodel[nres][k1]; /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
1.331 brouard 10690: k2=(int)Tvarsel[k3]; /* nres=1 k1=2=>k3=1 Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 (V4); k1=3=>k3=2 Tvarsel[2]=3 (V3)*/
1.334 brouard 10691: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][4]=1 */
1.332 brouard 10692: precov[nres][k1]=Tvalsel[k3];
10693: printf("Decoderesult Dummy with age k=%d, k1=%d precov[nres=%d][k1=%d]=%.f Tvar[%d]=V%d k2=Tvarsel[%d]=%d Tvalsel[%d]=%d\n",k, k1, nres, k1,precov[nres][k1], k1, Tvar[k1], k3,(int)Tvarsel[k3], k3, (int)Tvalsel[k3]);
1.331 brouard 10694: }else if( Dummy[k1]==3 ){ /* For quant with age product */
1.332 brouard 10695: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 25.1=k3q */
1.331 brouard 10696: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
1.334 brouard 10697: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* TinvDoQresult[nres][5]=25.1 */
1.332 brouard 10698: precov[nres][k1]=Tvalsel[k3q];
1.334 brouard 10699: printf("Decoderesult Quantitative with age nres=%d, k1=%d, precov[nres=%d][k1=%d]=%f Tvar[%d]=V%d V(k2q=%d)= Tvarsel[%d]=%d, Tvalsel[%d]=%f\n",nres, k1, nres, k1,precov[nres][k1], k1, Tvar[k1], k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]);
1.331 brouard 10700: }else if(Typevar[k1]==2 ){ /* For product quant or dummy (not with age) */
1.332 brouard 10701: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
10702: printf("Decoderesult Quantitative or Dummy (not with age) nres=%d k1=%d precov[nres=%d][k1=%d]=%.f V%d(=%.f) * V%d(=%.f) \n",nres, k1, nres, k1,precov[nres][k1], Tvardk[k1][1], TinvDoQresult[nres][Tvardk[k1][1]], Tvardk[k1][2], TinvDoQresult[nres][Tvardk[k1][2]]);
1.330 brouard 10703: }else{
1.332 brouard 10704: printf("Error Decoderesult probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
10705: fprintf(ficlog,"Error Decoderesult probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
1.235 brouard 10706: }
10707: }
1.234 brouard 10708:
1.334 brouard 10709: TKresult[nres]=++k; /* Number of combinations of dummies for the nresult and the model =Tvalsel[k3]*pow(2,k4) + 1*/
1.230 brouard 10710: return (0);
10711: }
1.235 brouard 10712:
1.230 brouard 10713: int decodemodel( char model[], int lastobs)
10714: /**< This routine decodes the model and returns:
1.224 brouard 10715: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
10716: * - nagesqr = 1 if age*age in the model, otherwise 0.
10717: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
10718: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
10719: * - cptcovage number of covariates with age*products =2
10720: * - cptcovs number of simple covariates
10721: * - 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
10722: * which is a new column after the 9 (ncovcol) variables.
1.319 brouard 10723: * - if k is a product Vn*Vm, covar[k][i] is filled with correct values for each individual
1.224 brouard 10724: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
10725: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
10726: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
10727: */
1.319 brouard 10728: /* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1, Tage[1]=2 */
1.136 brouard 10729: {
1.238 brouard 10730: int i, j, k, ks, v;
1.227 brouard 10731: int j1, k1, k2, k3, k4;
1.136 brouard 10732: char modelsav[80];
1.145 brouard 10733: char stra[80], strb[80], strc[80], strd[80],stre[80];
1.187 brouard 10734: char *strpt;
1.136 brouard 10735:
1.145 brouard 10736: /*removespace(model);*/
1.136 brouard 10737: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.145 brouard 10738: j=0, j1=0, k1=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 10739: if (strstr(model,"AGE") !=0){
1.192 brouard 10740: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
10741: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 10742: return 1;
10743: }
1.141 brouard 10744: if (strstr(model,"v") !=0){
1.338 ! brouard 10745: printf("Error. 'v' must be in upper case 'V' model=1+age+%s ",model);
! 10746: fprintf(ficlog,"Error. 'v' must be in upper case model=1+age+%s ",model);fflush(ficlog);
1.141 brouard 10747: return 1;
10748: }
1.187 brouard 10749: strcpy(modelsav,model);
10750: if ((strpt=strstr(model,"age*age")) !=0){
1.338 ! brouard 10751: printf(" strpt=%s, model=1+age+%s\n",strpt, model);
1.187 brouard 10752: if(strpt != model){
1.338 ! brouard 10753: printf("Error in model: 'model=1+age+%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 10754: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 10755: corresponding column of parameters.\n",model);
1.338 ! brouard 10756: fprintf(ficlog,"Error in model: 'model=1+age+%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 10757: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 10758: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 10759: return 1;
1.225 brouard 10760: }
1.187 brouard 10761: nagesqr=1;
10762: if (strstr(model,"+age*age") !=0)
1.234 brouard 10763: substrchaine(modelsav, model, "+age*age");
1.187 brouard 10764: else if (strstr(model,"age*age+") !=0)
1.234 brouard 10765: substrchaine(modelsav, model, "age*age+");
1.187 brouard 10766: else
1.234 brouard 10767: substrchaine(modelsav, model, "age*age");
1.187 brouard 10768: }else
10769: nagesqr=0;
10770: if (strlen(modelsav) >1){
10771: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
10772: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.224 brouard 10773: cptcovs=j+1-j1; /**< Number of simple covariates V1+V1*age+V3 +V3*V4+age*age=> V1 + V3 =5-3=2 */
1.187 brouard 10774: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 10775: * cst, age and age*age
10776: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
10777: /* including age products which are counted in cptcovage.
10778: * but the covariates which are products must be treated
10779: * separately: ncovn=4- 2=2 (V1+V3). */
1.187 brouard 10780: cptcovprod=j1; /**< Number of products V1*V2 +v3*age = 2 */
10781: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.225 brouard 10782:
10783:
1.187 brouard 10784: /* Design
10785: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
10786: * < ncovcol=8 >
10787: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
10788: * k= 1 2 3 4 5 6 7 8
10789: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
10790: * covar[k,i], value of kth covariate if not including age for individual i:
1.224 brouard 10791: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
10792: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 10793: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
10794: * Tage[++cptcovage]=k
10795: * if products, new covar are created after ncovcol with k1
10796: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
10797: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
10798: * 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
10799: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
10800: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
10801: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
10802: * < ncovcol=8 >
10803: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
10804: * k= 1 2 3 4 5 6 7 8 9 10 11 12
10805: * Tvar[k]= 2 1 3 3 10 11 8 8 5 6 7 8
1.319 brouard 10806: * p Tvar[1]@12={2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
1.187 brouard 10807: * p Tprod[1]@2={ 6, 5}
10808: *p Tvard[1][1]@4= {7, 8, 5, 6}
10809: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
10810: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
1.319 brouard 10811: *How to reorganize? Tvars(orted)
1.187 brouard 10812: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
10813: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
10814: * {2, 1, 4, 8, 5, 6, 3, 7}
10815: * Struct []
10816: */
1.225 brouard 10817:
1.187 brouard 10818: /* This loop fills the array Tvar from the string 'model'.*/
10819: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
10820: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
10821: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
10822: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
10823: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
10824: /* k=1 Tvar[1]=2 (from V2) */
10825: /* k=5 Tvar[5] */
10826: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 10827: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 10828: /* } */
1.198 brouard 10829: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 10830: /*
10831: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 10832: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
10833: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
10834: }
1.187 brouard 10835: cptcovage=0;
1.319 brouard 10836: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model line */
10837: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+' cutl from left to right
10838: modelsav==V2+V1+V5*age+V4+V3*age strb=V3*age stra=V2+V1V5*age+V4 */ /* <model> "V5+V4+V3+V4*V3+V5*age+V1*age+V1" strb="V5" stra="V4+V3+V4*V3+V5*age+V1*age+V1" */
10839: if (nbocc(modelsav,'+')==0)
10840: strcpy(strb,modelsav); /* and analyzes it */
1.234 brouard 10841: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
10842: /*scanf("%d",i);*/
1.319 brouard 10843: if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V5*age+ V4+V3*age strb=V3*age */
10844: cutl(strc,strd,strb,'*'); /**< k=1 strd*strc Vm*Vn: strb=V3*age(input) strc=age strd=V3 ; V3*V2 strc=V2, strd=V3 */
1.234 brouard 10845: if (strcmp(strc,"age")==0) { /**< Model includes age: Vn*age */
10846: /* covar is not filled and then is empty */
10847: cptcovprod--;
10848: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
1.319 brouard 10849: Tvar[k]=atoi(stre); /* V2+V1+V5*age+V4+V3*age Tvar[5]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1 */
1.234 brouard 10850: Typevar[k]=1; /* 1 for age product */
1.319 brouard 10851: cptcovage++; /* Counts the number of covariates which include age as a product */
10852: Tage[cptcovage]=k; /* V2+V1+V4+V3*age Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */
1.234 brouard 10853: /*printf("stre=%s ", stre);*/
10854: } else if (strcmp(strd,"age")==0) { /* or age*Vn */
10855: cptcovprod--;
10856: cutl(stre,strb,strc,'V');
10857: Tvar[k]=atoi(stre);
10858: Typevar[k]=1; /* 1 for age product */
10859: cptcovage++;
10860: Tage[cptcovage]=k;
10861: } else { /* Age is not in the model product V2+V1+V1*V4+V3*age+V3*V2 strb=V3*V2*/
10862: /* loops on k1=1 (V3*V2) and k1=2 V4*V3 */
10863: cptcovn++;
10864: cptcovprodnoage++;k1++;
10865: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
10866: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* For model-covariate k tells which data-covariate to use but
10867: because this model-covariate is a construction we invent a new column
10868: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
1.335 brouard 10869: If already ncovcol=4 and model= V2 + V1 + V1*V4 + age*V3 + V3*V2
1.319 brouard 10870: thus after V4 we invent V5 and V6 because age*V3 will be computed in 4
10871: Tvar[3=V1*V4]=4+1=5 Tvar[5=V3*V2]=4 + 2= 6, Tvar[4=age*V3]=4 etc */
1.335 brouard 10872: /* Please remark that the new variables are model dependent */
10873: /* If we have 4 variable but the model uses only 3, like in
10874: * model= V1 + age*V1 + V2 + V3 + age*V2 + age*V3 + V1*V2 + V1*V3
10875: * k= 1 2 3 4 5 6 7 8
10876: * Tvar[k]=1 1 2 3 2 3 (5 6) (and not 4 5 because of V4 missing)
10877: * Tage[kk] [1]= 2 [2]=5 [3]=6 kk=1 to cptcovage=3
10878: * Tvar[Tage[kk]][1]=2 [2]=2 [3]=3
10879: */
1.234 brouard 10880: Typevar[k]=2; /* 2 for double fixed dummy covariates */
10881: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
10882: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 */
1.319 brouard 10883: Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 */
1.234 brouard 10884: Tvard[k1][1] =atoi(strc); /* m 1 for V1*/
1.330 brouard 10885: Tvardk[k][1] =atoi(strc); /* m 1 for V1*/
1.234 brouard 10886: Tvard[k1][2] =atoi(stre); /* n 4 for V4*/
1.330 brouard 10887: Tvardk[k][2] =atoi(stre); /* n 4 for V4*/
1.234 brouard 10888: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
10889: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
10890: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
1.225 brouard 10891: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
1.234 brouard 10892: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
10893: for (i=1; i<=lastobs;i++){
10894: /* Computes the new covariate which is a product of
10895: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
10896: covar[ncovcol+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
10897: }
10898: } /* End age is not in the model */
10899: } /* End if model includes a product */
1.319 brouard 10900: else { /* not a product */
1.234 brouard 10901: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
10902: /* scanf("%d",i);*/
10903: cutl(strd,strc,strb,'V');
10904: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
10905: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
10906: Tvar[k]=atoi(strd);
10907: Typevar[k]=0; /* 0 for simple covariates */
10908: }
10909: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 10910: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 10911: scanf("%d",i);*/
1.187 brouard 10912: } /* end of loop + on total covariates */
10913: } /* end if strlen(modelsave == 0) age*age might exist */
10914: } /* end if strlen(model == 0) */
1.136 brouard 10915:
10916: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
10917: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 10918:
1.136 brouard 10919: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 10920: printf("cptcovprod=%d ", cptcovprod);
10921: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
10922: scanf("%d ",i);*/
10923:
10924:
1.230 brouard 10925: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
10926: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 10927: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
10928: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
10929: k = 1 2 3 4 5 6 7 8 9
10930: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
1.319 brouard 10931: Typevar[k]= 0 0 0 2 1 0 2 1 0
1.227 brouard 10932: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
10933: Dummy[k] 1 0 0 0 3 1 1 2 3
10934: Tmodelind[combination of covar]=k;
1.225 brouard 10935: */
10936: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 10937: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 10938: /* 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 10939: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.318 brouard 10940: printf("Model=1+age+%s\n\
1.227 brouard 10941: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
10942: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
10943: 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 10944: fprintf(ficlog,"Model=1+age+%s\n\
1.227 brouard 10945: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
10946: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
10947: 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 10948: for(k=-1;k<=cptcovt; k++){ Fixed[k]=0; Dummy[k]=0;}
1.234 brouard 10949: 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 */
10950: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 10951: Fixed[k]= 0;
10952: Dummy[k]= 0;
1.225 brouard 10953: ncoveff++;
1.232 brouard 10954: ncovf++;
1.234 brouard 10955: nsd++;
10956: modell[k].maintype= FTYPE;
10957: TvarsD[nsd]=Tvar[k];
10958: TvarsDind[nsd]=k;
1.330 brouard 10959: TnsdVar[Tvar[k]]=nsd;
1.234 brouard 10960: TvarF[ncovf]=Tvar[k];
10961: TvarFind[ncovf]=k;
10962: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
10963: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
10964: }else if( Tvar[k] <=ncovcol && Typevar[k]==2){ /* Product of fixed dummy (<=ncovcol) covariates */
10965: Fixed[k]= 0;
10966: Dummy[k]= 0;
10967: ncoveff++;
10968: ncovf++;
10969: modell[k].maintype= FTYPE;
10970: TvarF[ncovf]=Tvar[k];
1.330 brouard 10971: /* TnsdVar[Tvar[k]]=nsd; */ /* To be done */
1.234 brouard 10972: TvarFind[ncovf]=k;
1.230 brouard 10973: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.231 brouard 10974: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.240 brouard 10975: }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 10976: Fixed[k]= 0;
10977: Dummy[k]= 1;
1.230 brouard 10978: nqfveff++;
1.234 brouard 10979: modell[k].maintype= FTYPE;
10980: modell[k].subtype= FQ;
10981: nsq++;
1.334 brouard 10982: TvarsQ[nsq]=Tvar[k]; /* Gives the variable name (extended to products) of first nsq simple quantitative covariates (fixed or time vary see below */
10983: TvarsQind[nsq]=k; /* Gives the position in the model equation of the first nsq simple quantitative covariates (fixed or time vary) */
1.232 brouard 10984: ncovf++;
1.234 brouard 10985: TvarF[ncovf]=Tvar[k];
10986: TvarFind[ncovf]=k;
1.231 brouard 10987: 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 10988: 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 10989: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.227 brouard 10990: Fixed[k]= 1;
10991: Dummy[k]= 0;
1.225 brouard 10992: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 10993: modell[k].maintype= VTYPE;
10994: modell[k].subtype= VD;
10995: nsd++;
10996: TvarsD[nsd]=Tvar[k];
10997: TvarsDind[nsd]=k;
1.330 brouard 10998: TnsdVar[Tvar[k]]=nsd; /* To be verified */
1.234 brouard 10999: ncovv++; /* Only simple time varying variables */
11000: TvarV[ncovv]=Tvar[k];
1.242 brouard 11001: 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 11002: 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 */
11003: 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 11004: 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);
11005: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 11006: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.234 brouard 11007: Fixed[k]= 1;
11008: Dummy[k]= 1;
11009: nqtveff++;
11010: modell[k].maintype= VTYPE;
11011: modell[k].subtype= VQ;
11012: ncovv++; /* Only simple time varying variables */
11013: nsq++;
1.334 brouard 11014: TvarsQ[nsq]=Tvar[k]; /* k=1 Tvar=5 nsq=1 TvarsQ[1]=5 */ /* Gives the variable name (extended to products) of first nsq simple quantitative covariates (fixed or time vary here) */
11015: TvarsQind[nsq]=k; /* For single quantitative covariate gives the model position of each single quantitative covariate *//* Gives the position in the model equation of the first nsq simple quantitative covariates (fixed or time vary) */
1.234 brouard 11016: TvarV[ncovv]=Tvar[k];
1.242 brouard 11017: 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 11018: 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 */
11019: 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 11020: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
11021: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
11022: 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 11023: printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv);
1.227 brouard 11024: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 11025: ncova++;
11026: TvarA[ncova]=Tvar[k];
11027: TvarAind[ncova]=k;
1.231 brouard 11028: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 11029: Fixed[k]= 2;
11030: Dummy[k]= 2;
11031: modell[k].maintype= ATYPE;
11032: modell[k].subtype= APFD;
11033: /* ncoveff++; */
1.227 brouard 11034: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 11035: Fixed[k]= 2;
11036: Dummy[k]= 3;
11037: modell[k].maintype= ATYPE;
11038: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
11039: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 11040: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 11041: Fixed[k]= 3;
11042: Dummy[k]= 2;
11043: modell[k].maintype= ATYPE;
11044: modell[k].subtype= APVD; /* Product age * varying dummy */
11045: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 11046: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 11047: Fixed[k]= 3;
11048: Dummy[k]= 3;
11049: modell[k].maintype= ATYPE;
11050: modell[k].subtype= APVQ; /* Product age * varying quantitative */
11051: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 11052: }
11053: }else if (Typevar[k] == 2) { /* product without age */
11054: k1=Tposprod[k];
11055: if(Tvard[k1][1] <=ncovcol){
1.240 brouard 11056: if(Tvard[k1][2] <=ncovcol){
11057: Fixed[k]= 1;
11058: Dummy[k]= 0;
11059: modell[k].maintype= FTYPE;
11060: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
11061: ncovf++; /* Fixed variables without age */
11062: TvarF[ncovf]=Tvar[k];
11063: TvarFind[ncovf]=k;
11064: }else if(Tvard[k1][2] <=ncovcol+nqv){
11065: Fixed[k]= 0; /* or 2 ?*/
11066: Dummy[k]= 1;
11067: modell[k].maintype= FTYPE;
11068: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
11069: ncovf++; /* Varying variables without age */
11070: TvarF[ncovf]=Tvar[k];
11071: TvarFind[ncovf]=k;
11072: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
11073: Fixed[k]= 1;
11074: Dummy[k]= 0;
11075: modell[k].maintype= VTYPE;
11076: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
11077: ncovv++; /* Varying variables without age */
11078: TvarV[ncovv]=Tvar[k];
11079: TvarVind[ncovv]=k;
11080: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
11081: Fixed[k]= 1;
11082: Dummy[k]= 1;
11083: modell[k].maintype= VTYPE;
11084: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
11085: ncovv++; /* Varying variables without age */
11086: TvarV[ncovv]=Tvar[k];
11087: TvarVind[ncovv]=k;
11088: }
1.227 brouard 11089: }else if(Tvard[k1][1] <=ncovcol+nqv){
1.240 brouard 11090: if(Tvard[k1][2] <=ncovcol){
11091: Fixed[k]= 0; /* or 2 ?*/
11092: Dummy[k]= 1;
11093: modell[k].maintype= FTYPE;
11094: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
11095: ncovf++; /* Fixed variables without age */
11096: TvarF[ncovf]=Tvar[k];
11097: TvarFind[ncovf]=k;
11098: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
11099: Fixed[k]= 1;
11100: Dummy[k]= 1;
11101: modell[k].maintype= VTYPE;
11102: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
11103: ncovv++; /* Varying variables without age */
11104: TvarV[ncovv]=Tvar[k];
11105: TvarVind[ncovv]=k;
11106: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
11107: Fixed[k]= 1;
11108: Dummy[k]= 1;
11109: modell[k].maintype= VTYPE;
11110: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
11111: ncovv++; /* Varying variables without age */
11112: TvarV[ncovv]=Tvar[k];
11113: TvarVind[ncovv]=k;
11114: ncovv++; /* Varying variables without age */
11115: TvarV[ncovv]=Tvar[k];
11116: TvarVind[ncovv]=k;
11117: }
1.227 brouard 11118: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){
1.240 brouard 11119: if(Tvard[k1][2] <=ncovcol){
11120: Fixed[k]= 1;
11121: Dummy[k]= 1;
11122: modell[k].maintype= VTYPE;
11123: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
11124: ncovv++; /* Varying variables without age */
11125: TvarV[ncovv]=Tvar[k];
11126: TvarVind[ncovv]=k;
11127: }else if(Tvard[k1][2] <=ncovcol+nqv){
11128: Fixed[k]= 1;
11129: Dummy[k]= 1;
11130: modell[k].maintype= VTYPE;
11131: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
11132: ncovv++; /* Varying variables without age */
11133: TvarV[ncovv]=Tvar[k];
11134: TvarVind[ncovv]=k;
11135: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
11136: Fixed[k]= 1;
11137: Dummy[k]= 0;
11138: modell[k].maintype= VTYPE;
11139: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
11140: ncovv++; /* Varying variables without age */
11141: TvarV[ncovv]=Tvar[k];
11142: TvarVind[ncovv]=k;
11143: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
11144: Fixed[k]= 1;
11145: Dummy[k]= 1;
11146: modell[k].maintype= VTYPE;
11147: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
11148: ncovv++; /* Varying variables without age */
11149: TvarV[ncovv]=Tvar[k];
11150: TvarVind[ncovv]=k;
11151: }
1.227 brouard 11152: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 11153: if(Tvard[k1][2] <=ncovcol){
11154: Fixed[k]= 1;
11155: Dummy[k]= 1;
11156: modell[k].maintype= VTYPE;
11157: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
11158: ncovv++; /* Varying variables without age */
11159: TvarV[ncovv]=Tvar[k];
11160: TvarVind[ncovv]=k;
11161: }else if(Tvard[k1][2] <=ncovcol+nqv){
11162: Fixed[k]= 1;
11163: Dummy[k]= 1;
11164: modell[k].maintype= VTYPE;
11165: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
11166: ncovv++; /* Varying variables without age */
11167: TvarV[ncovv]=Tvar[k];
11168: TvarVind[ncovv]=k;
11169: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
11170: Fixed[k]= 1;
11171: Dummy[k]= 1;
11172: modell[k].maintype= VTYPE;
11173: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
11174: ncovv++; /* Varying variables without age */
11175: TvarV[ncovv]=Tvar[k];
11176: TvarVind[ncovv]=k;
11177: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
11178: Fixed[k]= 1;
11179: Dummy[k]= 1;
11180: modell[k].maintype= VTYPE;
11181: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
11182: ncovv++; /* Varying variables without age */
11183: TvarV[ncovv]=Tvar[k];
11184: TvarVind[ncovv]=k;
11185: }
1.227 brouard 11186: }else{
1.240 brouard 11187: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
11188: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
11189: } /*end k1*/
1.225 brouard 11190: }else{
1.226 brouard 11191: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
11192: 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 11193: }
1.227 brouard 11194: 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 11195: printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype);
1.227 brouard 11196: 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]);
11197: }
11198: /* Searching for doublons in the model */
11199: for(k1=1; k1<= cptcovt;k1++){
11200: for(k2=1; k2 <k1;k2++){
1.285 brouard 11201: /* if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){ */
11202: if((Typevar[k1]==Typevar[k2]) && (Fixed[k1]==Fixed[k2]) && (Dummy[k1]==Dummy[k2] )){
1.234 brouard 11203: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
11204: if(Tvar[k1]==Tvar[k2]){
1.338 ! brouard 11205: printf("Error duplication in the model=1+age+%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]);
! 11206: fprintf(ficlog,"Error duplication in the model=1+age+%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 11207: return(1);
11208: }
11209: }else if (Typevar[k1] ==2){
11210: k3=Tposprod[k1];
11211: k4=Tposprod[k2];
11212: 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])) ){
1.338 ! brouard 11213: printf("Error duplication in the model=1+age+%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]]);
! 11214: fprintf(ficlog,"Error duplication in the model=1+age+%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);
1.234 brouard 11215: return(1);
11216: }
11217: }
1.227 brouard 11218: }
11219: }
1.225 brouard 11220: }
11221: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
11222: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 11223: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
11224: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.137 brouard 11225: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 11226: /*endread:*/
1.225 brouard 11227: printf("Exiting decodemodel: ");
11228: return (1);
1.136 brouard 11229: }
11230:
1.169 brouard 11231: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 11232: {/* Check ages at death */
1.136 brouard 11233: int i, m;
1.218 brouard 11234: int firstone=0;
11235:
1.136 brouard 11236: for (i=1; i<=imx; i++) {
11237: for(m=2; (m<= maxwav); m++) {
11238: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
11239: anint[m][i]=9999;
1.216 brouard 11240: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
11241: s[m][i]=-1;
1.136 brouard 11242: }
11243: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 11244: *nberr = *nberr + 1;
1.218 brouard 11245: if(firstone == 0){
11246: firstone=1;
1.260 brouard 11247: 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 11248: }
1.262 brouard 11249: 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 11250: s[m][i]=-1; /* Droping the death status */
1.136 brouard 11251: }
11252: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 11253: (*nberr)++;
1.259 brouard 11254: 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 11255: 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 11256: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 11257: }
11258: }
11259: }
11260:
11261: for (i=1; i<=imx; i++) {
11262: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
11263: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 11264: 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 11265: if (s[m][i] >= nlstate+1) {
1.169 brouard 11266: if(agedc[i]>0){
11267: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 11268: agev[m][i]=agedc[i];
1.214 brouard 11269: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 11270: }else {
1.136 brouard 11271: if ((int)andc[i]!=9999){
11272: nbwarn++;
11273: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
11274: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
11275: agev[m][i]=-1;
11276: }
11277: }
1.169 brouard 11278: } /* agedc > 0 */
1.214 brouard 11279: } /* end if */
1.136 brouard 11280: else if(s[m][i] !=9){ /* Standard case, age in fractional
11281: years but with the precision of a month */
11282: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
11283: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
11284: agev[m][i]=1;
11285: else if(agev[m][i] < *agemin){
11286: *agemin=agev[m][i];
11287: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
11288: }
11289: else if(agev[m][i] >*agemax){
11290: *agemax=agev[m][i];
1.156 brouard 11291: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 11292: }
11293: /*agev[m][i]=anint[m][i]-annais[i];*/
11294: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 11295: } /* en if 9*/
1.136 brouard 11296: else { /* =9 */
1.214 brouard 11297: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 11298: agev[m][i]=1;
11299: s[m][i]=-1;
11300: }
11301: }
1.214 brouard 11302: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 11303: agev[m][i]=1;
1.214 brouard 11304: else{
11305: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
11306: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
11307: agev[m][i]=0;
11308: }
11309: } /* End for lastpass */
11310: }
1.136 brouard 11311:
11312: for (i=1; i<=imx; i++) {
11313: for(m=firstpass; (m<=lastpass); m++){
11314: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 11315: (*nberr)++;
1.136 brouard 11316: 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);
11317: 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);
11318: return 1;
11319: }
11320: }
11321: }
11322:
11323: /*for (i=1; i<=imx; i++){
11324: for (m=firstpass; (m<lastpass); m++){
11325: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
11326: }
11327:
11328: }*/
11329:
11330:
1.139 brouard 11331: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
11332: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 11333:
11334: return (0);
1.164 brouard 11335: /* endread:*/
1.136 brouard 11336: printf("Exiting calandcheckages: ");
11337: return (1);
11338: }
11339:
1.172 brouard 11340: #if defined(_MSC_VER)
11341: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
11342: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
11343: //#include "stdafx.h"
11344: //#include <stdio.h>
11345: //#include <tchar.h>
11346: //#include <windows.h>
11347: //#include <iostream>
11348: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
11349:
11350: LPFN_ISWOW64PROCESS fnIsWow64Process;
11351:
11352: BOOL IsWow64()
11353: {
11354: BOOL bIsWow64 = FALSE;
11355:
11356: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
11357: // (HANDLE, PBOOL);
11358:
11359: //LPFN_ISWOW64PROCESS fnIsWow64Process;
11360:
11361: HMODULE module = GetModuleHandle(_T("kernel32"));
11362: const char funcName[] = "IsWow64Process";
11363: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
11364: GetProcAddress(module, funcName);
11365:
11366: if (NULL != fnIsWow64Process)
11367: {
11368: if (!fnIsWow64Process(GetCurrentProcess(),
11369: &bIsWow64))
11370: //throw std::exception("Unknown error");
11371: printf("Unknown error\n");
11372: }
11373: return bIsWow64 != FALSE;
11374: }
11375: #endif
1.177 brouard 11376:
1.191 brouard 11377: void syscompilerinfo(int logged)
1.292 brouard 11378: {
11379: #include <stdint.h>
11380:
11381: /* #include "syscompilerinfo.h"*/
1.185 brouard 11382: /* command line Intel compiler 32bit windows, XP compatible:*/
11383: /* /GS /W3 /Gy
11384: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
11385: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
11386: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 11387: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
11388: */
11389: /* 64 bits */
1.185 brouard 11390: /*
11391: /GS /W3 /Gy
11392: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
11393: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
11394: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
11395: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
11396: /* Optimization are useless and O3 is slower than O2 */
11397: /*
11398: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
11399: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
11400: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
11401: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
11402: */
1.186 brouard 11403: /* Link is */ /* /OUT:"visual studio
1.185 brouard 11404: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
11405: /PDB:"visual studio
11406: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
11407: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
11408: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
11409: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
11410: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
11411: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
11412: uiAccess='false'"
11413: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
11414: /NOLOGO /TLBID:1
11415: */
1.292 brouard 11416:
11417:
1.177 brouard 11418: #if defined __INTEL_COMPILER
1.178 brouard 11419: #if defined(__GNUC__)
11420: struct utsname sysInfo; /* For Intel on Linux and OS/X */
11421: #endif
1.177 brouard 11422: #elif defined(__GNUC__)
1.179 brouard 11423: #ifndef __APPLE__
1.174 brouard 11424: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 11425: #endif
1.177 brouard 11426: struct utsname sysInfo;
1.178 brouard 11427: int cross = CROSS;
11428: if (cross){
11429: printf("Cross-");
1.191 brouard 11430: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 11431: }
1.174 brouard 11432: #endif
11433:
1.191 brouard 11434: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 11435: #if defined(__clang__)
1.191 brouard 11436: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 11437: #endif
11438: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 11439: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 11440: #endif
11441: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 11442: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 11443: #endif
11444: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 11445: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 11446: #endif
11447: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 11448: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 11449: #endif
11450: #if defined(_MSC_VER)
1.191 brouard 11451: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 11452: #endif
11453: #if defined(__PGI)
1.191 brouard 11454: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 11455: #endif
11456: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 11457: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 11458: #endif
1.191 brouard 11459: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 11460:
1.167 brouard 11461: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
11462: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
11463: // Windows (x64 and x86)
1.191 brouard 11464: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 11465: #elif __unix__ // all unices, not all compilers
11466: // Unix
1.191 brouard 11467: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 11468: #elif __linux__
11469: // linux
1.191 brouard 11470: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 11471: #elif __APPLE__
1.174 brouard 11472: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 11473: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 11474: #endif
11475:
11476: /* __MINGW32__ */
11477: /* __CYGWIN__ */
11478: /* __MINGW64__ */
11479: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
11480: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
11481: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
11482: /* _WIN64 // Defined for applications for Win64. */
11483: /* _M_X64 // Defined for compilations that target x64 processors. */
11484: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 11485:
1.167 brouard 11486: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 11487: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 11488: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 11489: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 11490: #else
1.191 brouard 11491: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 11492: #endif
11493:
1.169 brouard 11494: #if defined(__GNUC__)
11495: # if defined(__GNUC_PATCHLEVEL__)
11496: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
11497: + __GNUC_MINOR__ * 100 \
11498: + __GNUC_PATCHLEVEL__)
11499: # else
11500: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
11501: + __GNUC_MINOR__ * 100)
11502: # endif
1.174 brouard 11503: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 11504: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 11505:
11506: if (uname(&sysInfo) != -1) {
11507: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 11508: 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 11509: }
11510: else
11511: perror("uname() error");
1.179 brouard 11512: //#ifndef __INTEL_COMPILER
11513: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 11514: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 11515: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 11516: #endif
1.169 brouard 11517: #endif
1.172 brouard 11518:
1.286 brouard 11519: // void main ()
1.172 brouard 11520: // {
1.169 brouard 11521: #if defined(_MSC_VER)
1.174 brouard 11522: if (IsWow64()){
1.191 brouard 11523: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
11524: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 11525: }
11526: else{
1.191 brouard 11527: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
11528: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 11529: }
1.172 brouard 11530: // printf("\nPress Enter to continue...");
11531: // getchar();
11532: // }
11533:
1.169 brouard 11534: #endif
11535:
1.167 brouard 11536:
1.219 brouard 11537: }
1.136 brouard 11538:
1.219 brouard 11539: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.288 brouard 11540: /*--------------- Prevalence limit (forward period or forward stable prevalence) --------------*/
1.332 brouard 11541: /* Computes the prevalence limit for each combination of the dummy covariates */
1.235 brouard 11542: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 11543: /* double ftolpl = 1.e-10; */
1.180 brouard 11544: double age, agebase, agelim;
1.203 brouard 11545: double tot;
1.180 brouard 11546:
1.202 brouard 11547: strcpy(filerespl,"PL_");
11548: strcat(filerespl,fileresu);
11549: if((ficrespl=fopen(filerespl,"w"))==NULL) {
1.288 brouard 11550: printf("Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
11551: fprintf(ficlog,"Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
1.202 brouard 11552: }
1.288 brouard 11553: printf("\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
11554: fprintf(ficlog,"\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 11555: pstamp(ficrespl);
1.288 brouard 11556: fprintf(ficrespl,"# Forward period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 11557: fprintf(ficrespl,"#Age ");
11558: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
11559: fprintf(ficrespl,"\n");
1.180 brouard 11560:
1.219 brouard 11561: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 11562:
1.219 brouard 11563: agebase=ageminpar;
11564: agelim=agemaxpar;
1.180 brouard 11565:
1.227 brouard 11566: /* i1=pow(2,ncoveff); */
1.234 brouard 11567: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 11568: if (cptcovn < 1){i1=1;}
1.180 brouard 11569:
1.337 brouard 11570: /* for(k=1; k<=i1;k++){ /\* For each combination k of dummy covariates in the model *\/ */
1.238 brouard 11571: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 11572: k=TKresult[nres];
1.338 ! brouard 11573: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 11574: /* if(i1 != 1 && TKresult[nres]!= k) /\* We found the combination k corresponding to the resultline value of dummies *\/ */
11575: /* continue; */
1.235 brouard 11576:
1.238 brouard 11577: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
11578: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
11579: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
11580: /* k=k+1; */
11581: /* to clean */
1.332 brouard 11582: /*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*/
1.238 brouard 11583: fprintf(ficrespl,"#******");
11584: printf("#******");
11585: fprintf(ficlog,"#******");
1.337 brouard 11586: for(j=1;j<=cptcovs ;j++) {/**< cptcovs number of SIMPLE covariates in the model or resultline V2+V1 =2 (dummy or quantit or time varying) */
1.332 brouard 11587: /* fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Here problem for varying dummy*\/ */
1.337 brouard 11588: /* printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11589: /* fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11590: fprintf(ficrespl," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
11591: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
11592: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
11593: }
11594: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
11595: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
11596: /* fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
11597: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
11598: /* } */
1.238 brouard 11599: fprintf(ficrespl,"******\n");
11600: printf("******\n");
11601: fprintf(ficlog,"******\n");
11602: if(invalidvarcomb[k]){
11603: printf("\nCombination (%d) ignored because no case \n",k);
11604: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
11605: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
11606: continue;
11607: }
1.219 brouard 11608:
1.238 brouard 11609: fprintf(ficrespl,"#Age ");
1.337 brouard 11610: /* for(j=1;j<=cptcoveff;j++) { */
11611: /* fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11612: /* } */
11613: for(j=1;j<=cptcovs;j++) { /* New the quanti variable is added */
11614: fprintf(ficrespl,"V%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 11615: }
11616: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
11617: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 11618:
1.238 brouard 11619: for (age=agebase; age<=agelim; age++){
11620: /* for (age=agebase; age<=agebase; age++){ */
1.337 brouard 11621: /**< Computes the prevalence limit in each live state at age x and for covariate combination (k and) nres */
11622: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres); /* Nicely done */
1.238 brouard 11623: fprintf(ficrespl,"%.0f ",age );
1.337 brouard 11624: /* for(j=1;j<=cptcoveff;j++) */
11625: /* fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11626: for(j=1;j<=cptcovs;j++)
11627: fprintf(ficrespl,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 11628: tot=0.;
11629: for(i=1; i<=nlstate;i++){
11630: tot += prlim[i][i];
11631: fprintf(ficrespl," %.5f", prlim[i][i]);
11632: }
11633: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
11634: } /* Age */
11635: /* was end of cptcod */
1.337 brouard 11636: } /* nres */
11637: /* } /\* for each combination *\/ */
1.219 brouard 11638: return 0;
1.180 brouard 11639: }
11640:
1.218 brouard 11641: 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 11642: /*--------------- Back Prevalence limit (backward stable prevalence) --------------*/
1.218 brouard 11643:
11644: /* Computes the back prevalence limit for any combination of covariate values
11645: * at any age between ageminpar and agemaxpar
11646: */
1.235 brouard 11647: int i, j, k, i1, nres=0 ;
1.217 brouard 11648: /* double ftolpl = 1.e-10; */
11649: double age, agebase, agelim;
11650: double tot;
1.218 brouard 11651: /* double ***mobaverage; */
11652: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 11653:
11654: strcpy(fileresplb,"PLB_");
11655: strcat(fileresplb,fileresu);
11656: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
1.288 brouard 11657: printf("Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
11658: fprintf(ficlog,"Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
1.217 brouard 11659: }
1.288 brouard 11660: printf("Computing backward prevalence: result on file '%s' \n", fileresplb);
11661: fprintf(ficlog,"Computing backward prevalence: result on file '%s' \n", fileresplb);
1.217 brouard 11662: pstamp(ficresplb);
1.288 brouard 11663: fprintf(ficresplb,"# Backward prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.217 brouard 11664: fprintf(ficresplb,"#Age ");
11665: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
11666: fprintf(ficresplb,"\n");
11667:
1.218 brouard 11668:
11669: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
11670:
11671: agebase=ageminpar;
11672: agelim=agemaxpar;
11673:
11674:
1.227 brouard 11675: i1=pow(2,cptcoveff);
1.218 brouard 11676: if (cptcovn < 1){i1=1;}
1.227 brouard 11677:
1.238 brouard 11678: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.338 ! brouard 11679: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
! 11680: k=TKresult[nres];
! 11681: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
! 11682: /* if(i1 != 1 && TKresult[nres]!= k) */
! 11683: /* continue; */
! 11684: /* /\*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*\/ */
1.238 brouard 11685: fprintf(ficresplb,"#******");
11686: printf("#******");
11687: fprintf(ficlog,"#******");
1.338 ! brouard 11688: for(j=1;j<=cptcovs ;j++) {/**< cptcovs number of SIMPLE covariates in the model or resultline V2+V1 =2 (dummy or quantit or time varying) */
! 11689: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
! 11690: fprintf(ficresplb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
! 11691: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 11692: }
1.338 ! brouard 11693: /* for(j=1;j<=cptcoveff ;j++) {/\* all covariates *\/ */
! 11694: /* fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
! 11695: /* printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
! 11696: /* fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
! 11697: /* } */
! 11698: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
! 11699: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
! 11700: /* fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
! 11701: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
! 11702: /* } */
1.238 brouard 11703: fprintf(ficresplb,"******\n");
11704: printf("******\n");
11705: fprintf(ficlog,"******\n");
11706: if(invalidvarcomb[k]){
11707: printf("\nCombination (%d) ignored because no cases \n",k);
11708: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
11709: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
11710: continue;
11711: }
1.218 brouard 11712:
1.238 brouard 11713: fprintf(ficresplb,"#Age ");
1.338 ! brouard 11714: for(j=1;j<=cptcovs;j++) {
! 11715: fprintf(ficresplb,"V%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 11716: }
11717: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
11718: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 11719:
11720:
1.238 brouard 11721: for (age=agebase; age<=agelim; age++){
11722: /* for (age=agebase; age<=agebase; age++){ */
11723: if(mobilavproj > 0){
11724: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
11725: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 11726: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 11727: }else if (mobilavproj == 0){
11728: 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);
11729: 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);
11730: exit(1);
11731: }else{
11732: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 11733: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 11734: /* printf("TOTOT\n"); */
11735: /* exit(1); */
1.238 brouard 11736: }
11737: fprintf(ficresplb,"%.0f ",age );
1.338 ! brouard 11738: for(j=1;j<=cptcovs;j++)
! 11739: fprintf(ficresplb,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 11740: tot=0.;
11741: for(i=1; i<=nlstate;i++){
11742: tot += bprlim[i][i];
11743: fprintf(ficresplb," %.5f", bprlim[i][i]);
11744: }
11745: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
11746: } /* Age */
11747: /* was end of cptcod */
1.255 brouard 11748: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.338 ! brouard 11749: /* } /\* end of any combination *\/ */
1.238 brouard 11750: } /* end of nres */
1.218 brouard 11751: /* hBijx(p, bage, fage); */
11752: /* fclose(ficrespijb); */
11753:
11754: return 0;
1.217 brouard 11755: }
1.218 brouard 11756:
1.180 brouard 11757: int hPijx(double *p, int bage, int fage){
11758: /*------------- h Pij x at various ages ------------*/
1.336 brouard 11759: /* to be optimized with precov */
1.180 brouard 11760: int stepsize;
11761: int agelim;
11762: int hstepm;
11763: int nhstepm;
1.235 brouard 11764: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 11765:
11766: double agedeb;
11767: double ***p3mat;
11768:
1.337 brouard 11769: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
11770: if((ficrespij=fopen(filerespij,"w"))==NULL) {
11771: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
11772: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
11773: }
11774: printf("Computing pij: result on file '%s' \n", filerespij);
11775: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
11776:
11777: stepsize=(int) (stepm+YEARM-1)/YEARM;
11778: /*if (stepm<=24) stepsize=2;*/
11779:
11780: agelim=AGESUP;
11781: hstepm=stepsize*YEARM; /* Every year of age */
11782: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
11783:
11784: /* hstepm=1; aff par mois*/
11785: pstamp(ficrespij);
11786: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
11787: i1= pow(2,cptcoveff);
11788: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
11789: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
11790: /* k=k+1; */
11791: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
11792: k=TKresult[nres];
1.338 ! brouard 11793: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 11794: /* for(k=1; k<=i1;k++){ */
11795: /* if(i1 != 1 && TKresult[nres]!= k) */
11796: /* continue; */
11797: fprintf(ficrespij,"\n#****** ");
11798: for(j=1;j<=cptcovs;j++){
11799: fprintf(ficrespij," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
11800: /* fprintf(ficrespij,"@wV%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11801: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
11802: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
11803: /* fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
11804: }
11805: fprintf(ficrespij,"******\n");
11806:
11807: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
11808: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
11809: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
11810:
11811: /* nhstepm=nhstepm*YEARM; aff par mois*/
11812:
11813: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11814: oldm=oldms;savm=savms;
11815: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
11816: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
11817: for(i=1; i<=nlstate;i++)
11818: for(j=1; j<=nlstate+ndeath;j++)
11819: fprintf(ficrespij," %1d-%1d",i,j);
11820: fprintf(ficrespij,"\n");
11821: for (h=0; h<=nhstepm; h++){
11822: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
11823: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.183 brouard 11824: for(i=1; i<=nlstate;i++)
11825: for(j=1; j<=nlstate+ndeath;j++)
1.337 brouard 11826: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.183 brouard 11827: fprintf(ficrespij,"\n");
11828: }
1.337 brouard 11829: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11830: fprintf(ficrespij,"\n");
1.180 brouard 11831: }
1.337 brouard 11832: }
11833: /*}*/
11834: return 0;
1.180 brouard 11835: }
1.218 brouard 11836:
11837: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 11838: /*------------- h Bij x at various ages ------------*/
1.336 brouard 11839: /* To be optimized with precov */
1.217 brouard 11840: int stepsize;
1.218 brouard 11841: /* int agelim; */
11842: int ageminl;
1.217 brouard 11843: int hstepm;
11844: int nhstepm;
1.238 brouard 11845: int h, i, i1, j, k, nres;
1.218 brouard 11846:
1.217 brouard 11847: double agedeb;
11848: double ***p3mat;
1.218 brouard 11849:
11850: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
11851: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
11852: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
11853: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
11854: }
11855: printf("Computing pij back: result on file '%s' \n", filerespijb);
11856: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
11857:
11858: stepsize=(int) (stepm+YEARM-1)/YEARM;
11859: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 11860:
1.218 brouard 11861: /* agelim=AGESUP; */
1.289 brouard 11862: ageminl=AGEINF; /* was 30 */
1.218 brouard 11863: hstepm=stepsize*YEARM; /* Every year of age */
11864: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
11865:
11866: /* hstepm=1; aff par mois*/
11867: pstamp(ficrespijb);
1.255 brouard 11868: 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 11869: i1= pow(2,cptcoveff);
1.218 brouard 11870: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
11871: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
11872: /* k=k+1; */
1.238 brouard 11873: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 11874: k=TKresult[nres];
1.338 ! brouard 11875: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 11876: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
11877: /* if(i1 != 1 && TKresult[nres]!= k) */
11878: /* continue; */
11879: fprintf(ficrespijb,"\n#****** ");
11880: for(j=1;j<=cptcovs;j++){
1.338 ! brouard 11881: fprintf(ficrespijb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.337 brouard 11882: /* for(j=1;j<=cptcoveff;j++) */
11883: /* fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11884: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
11885: /* fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
11886: }
11887: fprintf(ficrespijb,"******\n");
11888: if(invalidvarcomb[k]){ /* Is it necessary here? */
11889: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
11890: continue;
11891: }
11892:
11893: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
11894: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
11895: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
11896: 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 */
11897: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 or 28*/
11898:
11899: /* nhstepm=nhstepm*YEARM; aff par mois*/
11900:
11901: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
11902: /* and memory limitations if stepm is small */
11903:
11904: /* oldm=oldms;savm=savms; */
11905: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
11906: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);/* Bug valgrind */
11907: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
11908: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
11909: for(i=1; i<=nlstate;i++)
11910: for(j=1; j<=nlstate+ndeath;j++)
11911: fprintf(ficrespijb," %1d-%1d",i,j);
11912: fprintf(ficrespijb,"\n");
11913: for (h=0; h<=nhstepm; h++){
11914: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
11915: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
11916: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
1.217 brouard 11917: for(i=1; i<=nlstate;i++)
11918: for(j=1; j<=nlstate+ndeath;j++)
1.337 brouard 11919: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);/* Bug valgrind */
1.217 brouard 11920: fprintf(ficrespijb,"\n");
1.337 brouard 11921: }
11922: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11923: fprintf(ficrespijb,"\n");
11924: } /* end age deb */
11925: /* } /\* end combination *\/ */
1.238 brouard 11926: } /* end nres */
1.218 brouard 11927: return 0;
11928: } /* hBijx */
1.217 brouard 11929:
1.180 brouard 11930:
1.136 brouard 11931: /***********************************************/
11932: /**************** Main Program *****************/
11933: /***********************************************/
11934:
11935: int main(int argc, char *argv[])
11936: {
11937: #ifdef GSL
11938: const gsl_multimin_fminimizer_type *T;
11939: size_t iteri = 0, it;
11940: int rval = GSL_CONTINUE;
11941: int status = GSL_SUCCESS;
11942: double ssval;
11943: #endif
11944: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.290 brouard 11945: int i,j, k, iter=0,m,size=100, cptcod; /* Suppressing because nobs */
11946: /* int i,j, k, n=MAXN,iter=0,m,size=100, cptcod; */
1.209 brouard 11947: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 11948: int jj, ll, li, lj, lk;
1.136 brouard 11949: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 11950: int num_filled;
1.136 brouard 11951: int itimes;
11952: int NDIM=2;
11953: int vpopbased=0;
1.235 brouard 11954: int nres=0;
1.258 brouard 11955: int endishere=0;
1.277 brouard 11956: int noffset=0;
1.274 brouard 11957: int ncurrv=0; /* Temporary variable */
11958:
1.164 brouard 11959: char ca[32], cb[32];
1.136 brouard 11960: /* FILE *fichtm; *//* Html File */
11961: /* FILE *ficgp;*/ /*Gnuplot File */
11962: struct stat info;
1.191 brouard 11963: double agedeb=0.;
1.194 brouard 11964:
11965: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 11966: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 11967:
1.165 brouard 11968: double fret;
1.191 brouard 11969: double dum=0.; /* Dummy variable */
1.136 brouard 11970: double ***p3mat;
1.218 brouard 11971: /* double ***mobaverage; */
1.319 brouard 11972: double wald;
1.164 brouard 11973:
11974: char line[MAXLINE];
1.197 brouard 11975: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
11976:
1.234 brouard 11977: char modeltemp[MAXLINE];
1.332 brouard 11978: char resultline[MAXLINE], resultlineori[MAXLINE];
1.230 brouard 11979:
1.136 brouard 11980: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 11981: char *tok, *val; /* pathtot */
1.334 brouard 11982: /* int firstobs=1, lastobs=10; /\* nobs = lastobs-firstobs declared globally ;*\/ */
1.195 brouard 11983: int c, h , cpt, c2;
1.191 brouard 11984: int jl=0;
11985: int i1, j1, jk, stepsize=0;
1.194 brouard 11986: int count=0;
11987:
1.164 brouard 11988: int *tab;
1.136 brouard 11989: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.296 brouard 11990: /* double anprojd, mprojd, jprojd; /\* For eventual projections *\/ */
11991: /* double anprojf, mprojf, jprojf; */
11992: /* double jintmean,mintmean,aintmean; */
11993: int prvforecast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
11994: int prvbackcast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
11995: double yrfproj= 10.0; /* Number of years of forward projections */
11996: double yrbproj= 10.0; /* Number of years of backward projections */
11997: int prevbcast=0; /* defined as global for mlikeli and mle, replacing backcast */
1.136 brouard 11998: int mobilav=0,popforecast=0;
1.191 brouard 11999: int hstepm=0, nhstepm=0;
1.136 brouard 12000: int agemortsup;
12001: float sumlpop=0.;
12002: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
12003: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
12004:
1.191 brouard 12005: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 12006: double ftolpl=FTOL;
12007: double **prlim;
1.217 brouard 12008: double **bprlim;
1.317 brouard 12009: double ***param; /* Matrix of parameters, param[i][j][k] param=ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel)
12010: state of origin, state of destination including death, for each covariate: constante, age, and V1 V2 etc. */
1.251 brouard 12011: double ***paramstart; /* Matrix of starting parameter values */
12012: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 12013: double **matcov; /* Matrix of covariance */
1.203 brouard 12014: double **hess; /* Hessian matrix */
1.136 brouard 12015: double ***delti3; /* Scale */
12016: double *delti; /* Scale */
12017: double ***eij, ***vareij;
12018: double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 12019:
1.136 brouard 12020: double *epj, vepp;
1.164 brouard 12021:
1.273 brouard 12022: double dateprev1, dateprev2;
1.296 brouard 12023: double jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000, dateproj1=0, dateproj2=0, dateprojd=0, dateprojf=0;
12024: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000, dateback1=0, dateback2=0, datebackd=0, datebackf=0;
12025:
1.217 brouard 12026:
1.136 brouard 12027: double **ximort;
1.145 brouard 12028: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 12029: int *dcwave;
12030:
1.164 brouard 12031: char z[1]="c";
1.136 brouard 12032:
12033: /*char *strt;*/
12034: char strtend[80];
1.126 brouard 12035:
1.164 brouard 12036:
1.126 brouard 12037: /* setlocale (LC_ALL, ""); */
12038: /* bindtextdomain (PACKAGE, LOCALEDIR); */
12039: /* textdomain (PACKAGE); */
12040: /* setlocale (LC_CTYPE, ""); */
12041: /* setlocale (LC_MESSAGES, ""); */
12042:
12043: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 12044: rstart_time = time(NULL);
12045: /* (void) gettimeofday(&start_time,&tzp);*/
12046: start_time = *localtime(&rstart_time);
1.126 brouard 12047: curr_time=start_time;
1.157 brouard 12048: /*tml = *localtime(&start_time.tm_sec);*/
12049: /* strcpy(strstart,asctime(&tml)); */
12050: strcpy(strstart,asctime(&start_time));
1.126 brouard 12051:
12052: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 12053: /* tp.tm_sec = tp.tm_sec +86400; */
12054: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 12055: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
12056: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
12057: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 12058: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 12059: /* strt=asctime(&tmg); */
12060: /* printf("Time(after) =%s",strstart); */
12061: /* (void) time (&time_value);
12062: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
12063: * tm = *localtime(&time_value);
12064: * strstart=asctime(&tm);
12065: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
12066: */
12067:
12068: nberr=0; /* Number of errors and warnings */
12069: nbwarn=0;
1.184 brouard 12070: #ifdef WIN32
12071: _getcwd(pathcd, size);
12072: #else
1.126 brouard 12073: getcwd(pathcd, size);
1.184 brouard 12074: #endif
1.191 brouard 12075: syscompilerinfo(0);
1.196 brouard 12076: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 12077: if(argc <=1){
12078: printf("\nEnter the parameter file name: ");
1.205 brouard 12079: if(!fgets(pathr,FILENAMELENGTH,stdin)){
12080: printf("ERROR Empty parameter file name\n");
12081: goto end;
12082: }
1.126 brouard 12083: i=strlen(pathr);
12084: if(pathr[i-1]=='\n')
12085: pathr[i-1]='\0';
1.156 brouard 12086: i=strlen(pathr);
1.205 brouard 12087: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 12088: pathr[i-1]='\0';
1.205 brouard 12089: }
12090: i=strlen(pathr);
12091: if( i==0 ){
12092: printf("ERROR Empty parameter file name\n");
12093: goto end;
12094: }
12095: for (tok = pathr; tok != NULL; ){
1.126 brouard 12096: printf("Pathr |%s|\n",pathr);
12097: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
12098: printf("val= |%s| pathr=%s\n",val,pathr);
12099: strcpy (pathtot, val);
12100: if(pathr[0] == '\0') break; /* Dirty */
12101: }
12102: }
1.281 brouard 12103: else if (argc<=2){
12104: strcpy(pathtot,argv[1]);
12105: }
1.126 brouard 12106: else{
12107: strcpy(pathtot,argv[1]);
1.281 brouard 12108: strcpy(z,argv[2]);
12109: printf("\nargv[2]=%s z=%c\n",argv[2],z[0]);
1.126 brouard 12110: }
12111: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
12112: /*cygwin_split_path(pathtot,path,optionfile);
12113: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
12114: /* cutv(path,optionfile,pathtot,'\\');*/
12115:
12116: /* Split argv[0], imach program to get pathimach */
12117: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
12118: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
12119: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
12120: /* strcpy(pathimach,argv[0]); */
12121: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
12122: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
12123: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 12124: #ifdef WIN32
12125: _chdir(path); /* Can be a relative path */
12126: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
12127: #else
1.126 brouard 12128: chdir(path); /* Can be a relative path */
1.184 brouard 12129: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
12130: #endif
12131: printf("Current directory %s!\n",pathcd);
1.126 brouard 12132: strcpy(command,"mkdir ");
12133: strcat(command,optionfilefiname);
12134: if((outcmd=system(command)) != 0){
1.169 brouard 12135: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 12136: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
12137: /* fclose(ficlog); */
12138: /* exit(1); */
12139: }
12140: /* if((imk=mkdir(optionfilefiname))<0){ */
12141: /* perror("mkdir"); */
12142: /* } */
12143:
12144: /*-------- arguments in the command line --------*/
12145:
1.186 brouard 12146: /* Main Log file */
1.126 brouard 12147: strcat(filelog, optionfilefiname);
12148: strcat(filelog,".log"); /* */
12149: if((ficlog=fopen(filelog,"w"))==NULL) {
12150: printf("Problem with logfile %s\n",filelog);
12151: goto end;
12152: }
12153: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 12154: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 12155: fprintf(ficlog,"\nEnter the parameter file name: \n");
12156: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
12157: path=%s \n\
12158: optionfile=%s\n\
12159: optionfilext=%s\n\
1.156 brouard 12160: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 12161:
1.197 brouard 12162: syscompilerinfo(1);
1.167 brouard 12163:
1.126 brouard 12164: printf("Local time (at start):%s",strstart);
12165: fprintf(ficlog,"Local time (at start): %s",strstart);
12166: fflush(ficlog);
12167: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 12168: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 12169:
12170: /* */
12171: strcpy(fileres,"r");
12172: strcat(fileres, optionfilefiname);
1.201 brouard 12173: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 12174: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 12175: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 12176:
1.186 brouard 12177: /* Main ---------arguments file --------*/
1.126 brouard 12178:
12179: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 12180: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
12181: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 12182: fflush(ficlog);
1.149 brouard 12183: /* goto end; */
12184: exit(70);
1.126 brouard 12185: }
12186:
12187: strcpy(filereso,"o");
1.201 brouard 12188: strcat(filereso,fileresu);
1.126 brouard 12189: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
12190: printf("Problem with Output resultfile: %s\n", filereso);
12191: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
12192: fflush(ficlog);
12193: goto end;
12194: }
1.278 brouard 12195: /*-------- Rewriting parameter file ----------*/
12196: strcpy(rfileres,"r"); /* "Rparameterfile */
12197: strcat(rfileres,optionfilefiname); /* Parameter file first name */
12198: strcat(rfileres,"."); /* */
12199: strcat(rfileres,optionfilext); /* Other files have txt extension */
12200: if((ficres =fopen(rfileres,"w"))==NULL) {
12201: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
12202: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
12203: fflush(ficlog);
12204: goto end;
12205: }
12206: fprintf(ficres,"#IMaCh %s\n",version);
1.126 brouard 12207:
1.278 brouard 12208:
1.126 brouard 12209: /* Reads comments: lines beginning with '#' */
12210: numlinepar=0;
1.277 brouard 12211: /* Is it a BOM UTF-8 Windows file? */
12212: /* First parameter line */
1.197 brouard 12213: while(fgets(line, MAXLINE, ficpar)) {
1.277 brouard 12214: noffset=0;
12215: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
12216: {
12217: noffset=noffset+3;
12218: printf("# File is an UTF8 Bom.\n"); // 0xBF
12219: }
1.302 brouard 12220: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
12221: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
1.277 brouard 12222: {
12223: noffset=noffset+2;
12224: printf("# File is an UTF16BE BOM file\n");
12225: }
12226: else if( line[0] == 0 && line[1] == 0)
12227: {
12228: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
12229: noffset=noffset+4;
12230: printf("# File is an UTF16BE BOM file\n");
12231: }
12232: } else{
12233: ;/*printf(" Not a BOM file\n");*/
12234: }
12235:
1.197 brouard 12236: /* If line starts with a # it is a comment */
1.277 brouard 12237: if (line[noffset] == '#') {
1.197 brouard 12238: numlinepar++;
12239: fputs(line,stdout);
12240: fputs(line,ficparo);
1.278 brouard 12241: fputs(line,ficres);
1.197 brouard 12242: fputs(line,ficlog);
12243: continue;
12244: }else
12245: break;
12246: }
12247: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
12248: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
12249: if (num_filled != 5) {
12250: printf("Should be 5 parameters\n");
1.283 brouard 12251: fprintf(ficlog,"Should be 5 parameters\n");
1.197 brouard 12252: }
1.126 brouard 12253: numlinepar++;
1.197 brouard 12254: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.283 brouard 12255: fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
12256: fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
12257: fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.197 brouard 12258: }
12259: /* Second parameter line */
12260: while(fgets(line, MAXLINE, ficpar)) {
1.283 brouard 12261: /* while(fscanf(ficpar,"%[^\n]", line)) { */
12262: /* If line starts with a # it is a comment. Strangely fgets reads the EOL and fputs doesn't */
1.197 brouard 12263: if (line[0] == '#') {
12264: numlinepar++;
1.283 brouard 12265: printf("%s",line);
12266: fprintf(ficres,"%s",line);
12267: fprintf(ficparo,"%s",line);
12268: fprintf(ficlog,"%s",line);
1.197 brouard 12269: continue;
12270: }else
12271: break;
12272: }
1.223 brouard 12273: 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", \
12274: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
12275: if (num_filled != 11) {
12276: 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 12277: printf("but line=%s\n",line);
1.283 brouard 12278: 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");
12279: fprintf(ficlog,"but line=%s\n",line);
1.197 brouard 12280: }
1.286 brouard 12281: if( lastpass > maxwav){
12282: printf("Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
12283: fprintf(ficlog,"Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
12284: fflush(ficlog);
12285: goto end;
12286: }
12287: 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 12288: 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 12289: 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 12290: 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 12291: }
1.203 brouard 12292: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 12293: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 12294: /* Third parameter line */
12295: while(fgets(line, MAXLINE, ficpar)) {
12296: /* If line starts with a # it is a comment */
12297: if (line[0] == '#') {
12298: numlinepar++;
1.283 brouard 12299: printf("%s",line);
12300: fprintf(ficres,"%s",line);
12301: fprintf(ficparo,"%s",line);
12302: fprintf(ficlog,"%s",line);
1.197 brouard 12303: continue;
12304: }else
12305: break;
12306: }
1.201 brouard 12307: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){
1.279 brouard 12308: if (num_filled != 1){
1.302 brouard 12309: printf("ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
12310: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
1.197 brouard 12311: model[0]='\0';
12312: goto end;
12313: }
12314: else{
12315: if (model[0]=='+'){
12316: for(i=1; i<=strlen(model);i++)
12317: modeltemp[i-1]=model[i];
1.201 brouard 12318: strcpy(model,modeltemp);
1.197 brouard 12319: }
12320: }
1.338 ! brouard 12321: /* printf(" model=1+age%s modeltemp= %s, model=1+age+%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 12322: printf("model=1+age+%s\n",model);fflush(stdout);
1.283 brouard 12323: fprintf(ficparo,"model=1+age+%s\n",model);fflush(stdout);
12324: fprintf(ficres,"model=1+age+%s\n",model);fflush(stdout);
12325: fprintf(ficlog,"model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 12326: }
12327: /* 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); */
12328: /* numlinepar=numlinepar+3; /\* In general *\/ */
12329: /* 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 12330: /* 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); */
12331: /* 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 12332: fflush(ficlog);
1.190 brouard 12333: /* if(model[0]=='#'|| model[0]== '\0'){ */
12334: if(model[0]=='#'){
1.279 brouard 12335: printf("Error in 'model' line: model should start with 'model=1+age+' and end without space \n \
12336: 'model=1+age+' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age' or \n \
12337: 'model=1+age+V1+V2' or 'model=1+age+V1+V2+V1*V2' etc. \n"); \
1.187 brouard 12338: if(mle != -1){
1.279 brouard 12339: 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 12340: exit(1);
12341: }
12342: }
1.126 brouard 12343: while((c=getc(ficpar))=='#' && c!= EOF){
12344: ungetc(c,ficpar);
12345: fgets(line, MAXLINE, ficpar);
12346: numlinepar++;
1.195 brouard 12347: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
12348: z[0]=line[1];
12349: }
12350: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 12351: fputs(line, stdout);
12352: //puts(line);
1.126 brouard 12353: fputs(line,ficparo);
12354: fputs(line,ficlog);
12355: }
12356: ungetc(c,ficpar);
12357:
12358:
1.290 brouard 12359: covar=matrix(0,NCOVMAX,firstobs,lastobs); /**< used in readdata */
12360: if(nqv>=1)coqvar=matrix(1,nqv,firstobs,lastobs); /**< Fixed quantitative covariate */
12361: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,firstobs,lastobs); /**< Time varying quantitative covariate */
12362: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,firstobs,lastobs); /**< Time varying covariate (dummy and quantitative)*/
1.136 brouard 12363: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
12364: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
12365: v1+v2*age+v2*v3 makes cptcovn = 3
12366: */
12367: if (strlen(model)>1)
1.187 brouard 12368: 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 12369: else
1.187 brouard 12370: ncovmodel=2; /* Constant and age */
1.133 brouard 12371: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
12372: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 12373: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
12374: 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);
12375: 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);
12376: fflush(stdout);
12377: fclose (ficlog);
12378: goto end;
12379: }
1.126 brouard 12380: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
12381: delti=delti3[1][1];
12382: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
12383: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 12384: /* We could also provide initial parameters values giving by simple logistic regression
12385: * only one way, that is without matrix product. We will have nlstate maximizations */
12386: /* for(i=1;i<nlstate;i++){ */
12387: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
12388: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
12389: /* } */
1.126 brouard 12390: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 12391: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
12392: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 12393: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
12394: fclose (ficparo);
12395: fclose (ficlog);
12396: goto end;
12397: exit(0);
1.220 brouard 12398: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 12399: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 12400: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
12401: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 12402: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
12403: matcov=matrix(1,npar,1,npar);
1.203 brouard 12404: hess=matrix(1,npar,1,npar);
1.220 brouard 12405: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 12406: /* Read guessed parameters */
1.126 brouard 12407: /* Reads comments: lines beginning with '#' */
12408: while((c=getc(ficpar))=='#' && c!= EOF){
12409: ungetc(c,ficpar);
12410: fgets(line, MAXLINE, ficpar);
12411: numlinepar++;
1.141 brouard 12412: fputs(line,stdout);
1.126 brouard 12413: fputs(line,ficparo);
12414: fputs(line,ficlog);
12415: }
12416: ungetc(c,ficpar);
12417:
12418: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 12419: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 12420: for(i=1; i <=nlstate; i++){
1.234 brouard 12421: j=0;
1.126 brouard 12422: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 12423: if(jj==i) continue;
12424: j++;
1.292 brouard 12425: while((c=getc(ficpar))=='#' && c!= EOF){
12426: ungetc(c,ficpar);
12427: fgets(line, MAXLINE, ficpar);
12428: numlinepar++;
12429: fputs(line,stdout);
12430: fputs(line,ficparo);
12431: fputs(line,ficlog);
12432: }
12433: ungetc(c,ficpar);
1.234 brouard 12434: fscanf(ficpar,"%1d%1d",&i1,&j1);
12435: if ((i1 != i) || (j1 != jj)){
12436: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 12437: It might be a problem of design; if ncovcol and the model are correct\n \
12438: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 12439: exit(1);
12440: }
12441: fprintf(ficparo,"%1d%1d",i1,j1);
12442: if(mle==1)
12443: printf("%1d%1d",i,jj);
12444: fprintf(ficlog,"%1d%1d",i,jj);
12445: for(k=1; k<=ncovmodel;k++){
12446: fscanf(ficpar," %lf",¶m[i][j][k]);
12447: if(mle==1){
12448: printf(" %lf",param[i][j][k]);
12449: fprintf(ficlog," %lf",param[i][j][k]);
12450: }
12451: else
12452: fprintf(ficlog," %lf",param[i][j][k]);
12453: fprintf(ficparo," %lf",param[i][j][k]);
12454: }
12455: fscanf(ficpar,"\n");
12456: numlinepar++;
12457: if(mle==1)
12458: printf("\n");
12459: fprintf(ficlog,"\n");
12460: fprintf(ficparo,"\n");
1.126 brouard 12461: }
12462: }
12463: fflush(ficlog);
1.234 brouard 12464:
1.251 brouard 12465: /* Reads parameters values */
1.126 brouard 12466: p=param[1][1];
1.251 brouard 12467: pstart=paramstart[1][1];
1.126 brouard 12468:
12469: /* Reads comments: lines beginning with '#' */
12470: while((c=getc(ficpar))=='#' && c!= EOF){
12471: ungetc(c,ficpar);
12472: fgets(line, MAXLINE, ficpar);
12473: numlinepar++;
1.141 brouard 12474: fputs(line,stdout);
1.126 brouard 12475: fputs(line,ficparo);
12476: fputs(line,ficlog);
12477: }
12478: ungetc(c,ficpar);
12479:
12480: for(i=1; i <=nlstate; i++){
12481: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 12482: fscanf(ficpar,"%1d%1d",&i1,&j1);
12483: if ( (i1-i) * (j1-j) != 0){
12484: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
12485: exit(1);
12486: }
12487: printf("%1d%1d",i,j);
12488: fprintf(ficparo,"%1d%1d",i1,j1);
12489: fprintf(ficlog,"%1d%1d",i1,j1);
12490: for(k=1; k<=ncovmodel;k++){
12491: fscanf(ficpar,"%le",&delti3[i][j][k]);
12492: printf(" %le",delti3[i][j][k]);
12493: fprintf(ficparo," %le",delti3[i][j][k]);
12494: fprintf(ficlog," %le",delti3[i][j][k]);
12495: }
12496: fscanf(ficpar,"\n");
12497: numlinepar++;
12498: printf("\n");
12499: fprintf(ficparo,"\n");
12500: fprintf(ficlog,"\n");
1.126 brouard 12501: }
12502: }
12503: fflush(ficlog);
1.234 brouard 12504:
1.145 brouard 12505: /* Reads covariance matrix */
1.126 brouard 12506: delti=delti3[1][1];
1.220 brouard 12507:
12508:
1.126 brouard 12509: /* 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 12510:
1.126 brouard 12511: /* Reads comments: lines beginning with '#' */
12512: while((c=getc(ficpar))=='#' && c!= EOF){
12513: ungetc(c,ficpar);
12514: fgets(line, MAXLINE, ficpar);
12515: numlinepar++;
1.141 brouard 12516: fputs(line,stdout);
1.126 brouard 12517: fputs(line,ficparo);
12518: fputs(line,ficlog);
12519: }
12520: ungetc(c,ficpar);
1.220 brouard 12521:
1.126 brouard 12522: matcov=matrix(1,npar,1,npar);
1.203 brouard 12523: hess=matrix(1,npar,1,npar);
1.131 brouard 12524: for(i=1; i <=npar; i++)
12525: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 12526:
1.194 brouard 12527: /* Scans npar lines */
1.126 brouard 12528: for(i=1; i <=npar; i++){
1.226 brouard 12529: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 12530: if(count != 3){
1.226 brouard 12531: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 12532: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
12533: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 12534: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 12535: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
12536: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 12537: exit(1);
1.220 brouard 12538: }else{
1.226 brouard 12539: if(mle==1)
12540: printf("%1d%1d%d",i1,j1,jk);
12541: }
12542: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
12543: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 12544: for(j=1; j <=i; j++){
1.226 brouard 12545: fscanf(ficpar," %le",&matcov[i][j]);
12546: if(mle==1){
12547: printf(" %.5le",matcov[i][j]);
12548: }
12549: fprintf(ficlog," %.5le",matcov[i][j]);
12550: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 12551: }
12552: fscanf(ficpar,"\n");
12553: numlinepar++;
12554: if(mle==1)
1.220 brouard 12555: printf("\n");
1.126 brouard 12556: fprintf(ficlog,"\n");
12557: fprintf(ficparo,"\n");
12558: }
1.194 brouard 12559: /* End of read covariance matrix npar lines */
1.126 brouard 12560: for(i=1; i <=npar; i++)
12561: for(j=i+1;j<=npar;j++)
1.226 brouard 12562: matcov[i][j]=matcov[j][i];
1.126 brouard 12563:
12564: if(mle==1)
12565: printf("\n");
12566: fprintf(ficlog,"\n");
12567:
12568: fflush(ficlog);
12569:
12570: } /* End of mle != -3 */
1.218 brouard 12571:
1.186 brouard 12572: /* Main data
12573: */
1.290 brouard 12574: nobs=lastobs-firstobs+1; /* was = lastobs;*/
12575: /* num=lvector(1,n); */
12576: /* moisnais=vector(1,n); */
12577: /* annais=vector(1,n); */
12578: /* moisdc=vector(1,n); */
12579: /* andc=vector(1,n); */
12580: /* weight=vector(1,n); */
12581: /* agedc=vector(1,n); */
12582: /* cod=ivector(1,n); */
12583: /* for(i=1;i<=n;i++){ */
12584: num=lvector(firstobs,lastobs);
12585: moisnais=vector(firstobs,lastobs);
12586: annais=vector(firstobs,lastobs);
12587: moisdc=vector(firstobs,lastobs);
12588: andc=vector(firstobs,lastobs);
12589: weight=vector(firstobs,lastobs);
12590: agedc=vector(firstobs,lastobs);
12591: cod=ivector(firstobs,lastobs);
12592: for(i=firstobs;i<=lastobs;i++){
1.234 brouard 12593: num[i]=0;
12594: moisnais[i]=0;
12595: annais[i]=0;
12596: moisdc[i]=0;
12597: andc[i]=0;
12598: agedc[i]=0;
12599: cod[i]=0;
12600: weight[i]=1.0; /* Equal weights, 1 by default */
12601: }
1.290 brouard 12602: mint=matrix(1,maxwav,firstobs,lastobs);
12603: anint=matrix(1,maxwav,firstobs,lastobs);
1.325 brouard 12604: s=imatrix(1,maxwav+1,firstobs,lastobs); /* s[i][j] health state for wave i and individual j */
1.336 brouard 12605: /* printf("BUG ncovmodel=%d NCOVMAX=%d 2**ncovmodel=%f BUG\n",ncovmodel,NCOVMAX,pow(2,ncovmodel)); */
1.126 brouard 12606: tab=ivector(1,NCOVMAX);
1.144 brouard 12607: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 12608: 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 12609:
1.136 brouard 12610: /* Reads data from file datafile */
12611: if (readdata(datafile, firstobs, lastobs, &imx)==1)
12612: goto end;
12613:
12614: /* Calculation of the number of parameters from char model */
1.234 brouard 12615: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 12616: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
12617: k=3 V4 Tvar[k=3]= 4 (from V4)
12618: k=2 V1 Tvar[k=2]= 1 (from V1)
12619: k=1 Tvar[1]=2 (from V2)
1.234 brouard 12620: */
12621:
12622: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
12623: TvarsDind=ivector(1,NCOVMAX); /* */
1.330 brouard 12624: TnsdVar=ivector(1,NCOVMAX); /* */
1.335 brouard 12625: /* for(i=1; i<=NCOVMAX;i++) TnsdVar[i]=3; */
1.234 brouard 12626: TvarsD=ivector(1,NCOVMAX); /* */
12627: TvarsQind=ivector(1,NCOVMAX); /* */
12628: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 12629: TvarF=ivector(1,NCOVMAX); /* */
12630: TvarFind=ivector(1,NCOVMAX); /* */
12631: TvarV=ivector(1,NCOVMAX); /* */
12632: TvarVind=ivector(1,NCOVMAX); /* */
12633: TvarA=ivector(1,NCOVMAX); /* */
12634: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 12635: TvarFD=ivector(1,NCOVMAX); /* */
12636: TvarFDind=ivector(1,NCOVMAX); /* */
12637: TvarFQ=ivector(1,NCOVMAX); /* */
12638: TvarFQind=ivector(1,NCOVMAX); /* */
12639: TvarVD=ivector(1,NCOVMAX); /* */
12640: TvarVDind=ivector(1,NCOVMAX); /* */
12641: TvarVQ=ivector(1,NCOVMAX); /* */
12642: TvarVQind=ivector(1,NCOVMAX); /* */
12643:
1.230 brouard 12644: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 12645: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 12646: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
12647: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
12648: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.137 brouard 12649: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
12650: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
12651: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
12652: */
12653: /* For model-covariate k tells which data-covariate to use but
12654: because this model-covariate is a construction we invent a new column
12655: ncovcol + k1
12656: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
12657: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 12658: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
12659: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 12660: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
12661: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 12662: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 12663: */
1.145 brouard 12664: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
12665: 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 12666: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
12667: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.330 brouard 12668: Tvardk=imatrix(1,NCOVMAX,1,2);
1.145 brouard 12669: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 12670: 4 covariates (3 plus signs)
12671: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
1.328 brouard 12672: */
12673: for(i=1;i<NCOVMAX;i++)
12674: Tage[i]=0;
1.230 brouard 12675: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 12676: * individual dummy, fixed or varying:
12677: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
12678: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 12679: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
12680: * V1 df, V2 qf, V3 & V4 dv, V5 qv
12681: * Tmodelind[1]@9={9,0,3,2,}*/
12682: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
12683: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 12684: * individual quantitative, fixed or varying:
12685: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
12686: * 3, 1, 0, 0, 0, 0, 0, 0},
12687: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.186 brouard 12688: /* Main decodemodel */
12689:
1.187 brouard 12690:
1.223 brouard 12691: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 12692: goto end;
12693:
1.137 brouard 12694: if((double)(lastobs-imx)/(double)imx > 1.10){
12695: nbwarn++;
12696: 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);
12697: 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);
12698: }
1.136 brouard 12699: /* if(mle==1){*/
1.137 brouard 12700: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
12701: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 12702: }
12703:
12704: /*-calculation of age at interview from date of interview and age at death -*/
12705: agev=matrix(1,maxwav,1,imx);
12706:
12707: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
12708: goto end;
12709:
1.126 brouard 12710:
1.136 brouard 12711: agegomp=(int)agemin;
1.290 brouard 12712: free_vector(moisnais,firstobs,lastobs);
12713: free_vector(annais,firstobs,lastobs);
1.126 brouard 12714: /* free_matrix(mint,1,maxwav,1,n);
12715: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 12716: /* free_vector(moisdc,1,n); */
12717: /* free_vector(andc,1,n); */
1.145 brouard 12718: /* */
12719:
1.126 brouard 12720: wav=ivector(1,imx);
1.214 brouard 12721: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
12722: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
12723: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
12724: 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.*/
12725: bh=imatrix(1,lastpass-firstpass+2,1,imx);
12726: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 12727:
12728: /* Concatenates waves */
1.214 brouard 12729: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
12730: Death is a valid wave (if date is known).
12731: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
12732: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
12733: and mw[mi+1][i]. dh depends on stepm.
12734: */
12735:
1.126 brouard 12736: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 12737: /* Concatenates waves */
1.145 brouard 12738:
1.290 brouard 12739: free_vector(moisdc,firstobs,lastobs);
12740: free_vector(andc,firstobs,lastobs);
1.215 brouard 12741:
1.126 brouard 12742: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
12743: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
12744: ncodemax[1]=1;
1.145 brouard 12745: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 12746: cptcoveff=0;
1.220 brouard 12747: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
1.335 brouard 12748: tricode(&cptcoveff,Tvar,nbcode,imx, Ndum); /**< Fills nbcode[Tvar[j]][l]; as well as calculate cptcoveff or number of total effective dummy covariates*/
1.227 brouard 12749: }
12750:
12751: ncovcombmax=pow(2,cptcoveff);
1.338 ! brouard 12752: invalidvarcomb=ivector(0, ncovcombmax);
! 12753: for(i=0;i<ncovcombmax;i++)
1.227 brouard 12754: invalidvarcomb[i]=0;
12755:
1.211 brouard 12756: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 12757: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 12758: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 12759:
1.200 brouard 12760: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 12761: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 12762: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 12763: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
12764: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
12765: * (currently 0 or 1) in the data.
12766: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
12767: * corresponding modality (h,j).
12768: */
12769:
1.145 brouard 12770: h=0;
12771: /*if (cptcovn > 0) */
1.126 brouard 12772: m=pow(2,cptcoveff);
12773:
1.144 brouard 12774: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 12775: * For k=4 covariates, h goes from 1 to m=2**k
12776: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
12777: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.329 brouard 12778: * h\k 1 2 3 4 * h-1\k-1 4 3 2 1
12779: *______________________________ *______________________
12780: * 1 i=1 1 i=1 1 i=1 1 i=1 1 * 0 0 0 0 0
12781: * 2 2 1 1 1 * 1 0 0 0 1
12782: * 3 i=2 1 2 1 1 * 2 0 0 1 0
12783: * 4 2 2 1 1 * 3 0 0 1 1
12784: * 5 i=3 1 i=2 1 2 1 * 4 0 1 0 0
12785: * 6 2 1 2 1 * 5 0 1 0 1
12786: * 7 i=4 1 2 2 1 * 6 0 1 1 0
12787: * 8 2 2 2 1 * 7 0 1 1 1
12788: * 9 i=5 1 i=3 1 i=2 1 2 * 8 1 0 0 0
12789: * 10 2 1 1 2 * 9 1 0 0 1
12790: * 11 i=6 1 2 1 2 * 10 1 0 1 0
12791: * 12 2 2 1 2 * 11 1 0 1 1
12792: * 13 i=7 1 i=4 1 2 2 * 12 1 1 0 0
12793: * 14 2 1 2 2 * 13 1 1 0 1
12794: * 15 i=8 1 2 2 2 * 14 1 1 1 0
12795: * 16 2 2 2 2 * 15 1 1 1 1
12796: */
1.212 brouard 12797: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 12798: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
12799: * and the value of each covariate?
12800: * V1=1, V2=1, V3=2, V4=1 ?
12801: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
12802: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
12803: * In order to get the real value in the data, we use nbcode
12804: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
12805: * We are keeping this crazy system in order to be able (in the future?)
12806: * to have more than 2 values (0 or 1) for a covariate.
12807: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
12808: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
12809: * bbbbbbbb
12810: * 76543210
12811: * h-1 00000101 (6-1=5)
1.219 brouard 12812: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 12813: * &
12814: * 1 00000001 (1)
1.219 brouard 12815: * 00000000 = 1 & ((h-1) >> (k-1))
12816: * +1= 00000001 =1
1.211 brouard 12817: *
12818: * h=14, k=3 => h'=h-1=13, k'=k-1=2
12819: * h' 1101 =2^3+2^2+0x2^1+2^0
12820: * >>k' 11
12821: * & 00000001
12822: * = 00000001
12823: * +1 = 00000010=2 = codtabm(14,3)
12824: * Reverse h=6 and m=16?
12825: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
12826: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
12827: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
12828: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
12829: * V3=decodtabm(14,3,2**4)=2
12830: * h'=13 1101 =2^3+2^2+0x2^1+2^0
12831: *(h-1) >> (j-1) 0011 =13 >> 2
12832: * &1 000000001
12833: * = 000000001
12834: * +1= 000000010 =2
12835: * 2211
12836: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
12837: * V3=2
1.220 brouard 12838: * codtabm and decodtabm are identical
1.211 brouard 12839: */
12840:
1.145 brouard 12841:
12842: free_ivector(Ndum,-1,NCOVMAX);
12843:
12844:
1.126 brouard 12845:
1.186 brouard 12846: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 12847: strcpy(optionfilegnuplot,optionfilefiname);
12848: if(mle==-3)
1.201 brouard 12849: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 12850: strcat(optionfilegnuplot,".gp");
12851:
12852: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
12853: printf("Problem with file %s",optionfilegnuplot);
12854: }
12855: else{
1.204 brouard 12856: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 12857: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 12858: //fprintf(ficgp,"set missing 'NaNq'\n");
12859: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 12860: }
12861: /* fclose(ficgp);*/
1.186 brouard 12862:
12863:
12864: /* Initialisation of --------- index.htm --------*/
1.126 brouard 12865:
12866: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
12867: if(mle==-3)
1.201 brouard 12868: strcat(optionfilehtm,"-MORT_");
1.126 brouard 12869: strcat(optionfilehtm,".htm");
12870: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 12871: printf("Problem with %s \n",optionfilehtm);
12872: exit(0);
1.126 brouard 12873: }
12874:
12875: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
12876: strcat(optionfilehtmcov,"-cov.htm");
12877: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
12878: printf("Problem with %s \n",optionfilehtmcov), exit(0);
12879: }
12880: else{
12881: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
12882: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 12883: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 12884: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
12885: }
12886:
1.335 brouard 12887: fprintf(fichtm,"<html><head>\n<meta charset=\"utf-8\"/><meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n\
12888: <title>IMaCh %s</title></head>\n\
12889: <body><font size=\"7\"><a href=http:/euroreves.ined.fr/imach>IMaCh for Interpolated Markov Chain</a> </font><br>\n\
12890: <font size=\"3\">Sponsored by Copyright (C) 2002-2015 <a href=http://www.ined.fr>INED</a>\
12891: -EUROREVES-Institut de longévité-2013-2022-Japan Society for the Promotion of Sciences 日本学術振興会 \
12892: (<a href=https://www.jsps.go.jp/english/e-grants/>Grant-in-Aid for Scientific Research 25293121</a>) - \
12893: <a href=https://software.intel.com/en-us>Intel Software 2015-2018</a></font><br> \n", optionfilehtm);
12894:
12895: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 12896: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 12897: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.337 brouard 12898: This file: <a href=\"%s\">%s</a></br>Title=%s <br>Datafile=<a href=\"%s\">%s</a> Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n\
1.126 brouard 12899: \n\
12900: <hr size=\"2\" color=\"#EC5E5E\">\
12901: <ul><li><h4>Parameter files</h4>\n\
12902: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
12903: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
12904: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
12905: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
12906: - Date and time at start: %s</ul>\n",\
1.335 brouard 12907: version,fullversion,optionfilehtm,optionfilehtm,title,datafile,datafile,firstpass,lastpass,stepm, weightopt, model, \
1.126 brouard 12908: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
12909: fileres,fileres,\
12910: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
12911: fflush(fichtm);
12912:
12913: strcpy(pathr,path);
12914: strcat(pathr,optionfilefiname);
1.184 brouard 12915: #ifdef WIN32
12916: _chdir(optionfilefiname); /* Move to directory named optionfile */
12917: #else
1.126 brouard 12918: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 12919: #endif
12920:
1.126 brouard 12921:
1.220 brouard 12922: /* Calculates basic frequencies. Computes observed prevalence at single age
12923: and for any valid combination of covariates
1.126 brouard 12924: and prints on file fileres'p'. */
1.251 brouard 12925: freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 12926: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 12927:
12928: fprintf(fichtm,"\n");
1.286 brouard 12929: 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 12930: ftol, stepm);
12931: fprintf(fichtm,"\n<li>Number of fixed dummy covariates: ncovcol=%d ", ncovcol);
12932: ncurrv=1;
12933: for(i=ncurrv; i <=ncovcol; i++) fprintf(fichtm,"V%d ", i);
12934: fprintf(fichtm,"\n<li> Number of fixed quantitative variables: nqv=%d ", nqv);
12935: ncurrv=i;
12936: for(i=ncurrv; i <=ncurrv-1+nqv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 12937: fprintf(fichtm,"\n<li> Number of time varying (wave varying) dummy covariates: ntv=%d ", ntv);
1.274 brouard 12938: ncurrv=i;
12939: for(i=ncurrv; i <=ncurrv-1+ntv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 12940: fprintf(fichtm,"\n<li>Number of time varying quantitative covariates: nqtv=%d ", nqtv);
1.274 brouard 12941: ncurrv=i;
12942: for(i=ncurrv; i <=ncurrv-1+nqtv; i++) fprintf(fichtm,"V%d ", i);
12943: 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", \
12944: nlstate, ndeath, maxwav, mle, weightopt);
12945:
12946: fprintf(fichtm,"<h4> Diagram of states <a href=\"%s_.svg\">%s_.svg</a></h4> \n\
12947: <img src=\"%s_.svg\">", subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"));
12948:
12949:
1.317 brouard 12950: fprintf(fichtm,"\n<h4>Some descriptive statistics </h4>\n<br>Number of (used) observations=%d <br>\n\
1.126 brouard 12951: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
12952: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
1.274 brouard 12953: imx,agemin,agemax,jmin,jmax,jmean);
1.126 brouard 12954: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 12955: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
12956: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
12957: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
12958: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 12959:
1.126 brouard 12960: /* For Powell, parameters are in a vector p[] starting at p[1]
12961: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
12962: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
12963:
12964: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 12965: /* For mortality only */
1.126 brouard 12966: if (mle==-3){
1.136 brouard 12967: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 12968: for(i=1;i<=NDIM;i++)
12969: for(j=1;j<=NDIM;j++)
12970: ximort[i][j]=0.;
1.186 brouard 12971: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.290 brouard 12972: cens=ivector(firstobs,lastobs);
12973: ageexmed=vector(firstobs,lastobs);
12974: agecens=vector(firstobs,lastobs);
12975: dcwave=ivector(firstobs,lastobs);
1.223 brouard 12976:
1.126 brouard 12977: for (i=1; i<=imx; i++){
12978: dcwave[i]=-1;
12979: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 12980: if (s[m][i]>nlstate) {
12981: dcwave[i]=m;
12982: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
12983: break;
12984: }
1.126 brouard 12985: }
1.226 brouard 12986:
1.126 brouard 12987: for (i=1; i<=imx; i++) {
12988: if (wav[i]>0){
1.226 brouard 12989: ageexmed[i]=agev[mw[1][i]][i];
12990: j=wav[i];
12991: agecens[i]=1.;
12992:
12993: if (ageexmed[i]> 1 && wav[i] > 0){
12994: agecens[i]=agev[mw[j][i]][i];
12995: cens[i]= 1;
12996: }else if (ageexmed[i]< 1)
12997: cens[i]= -1;
12998: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
12999: cens[i]=0 ;
1.126 brouard 13000: }
13001: else cens[i]=-1;
13002: }
13003:
13004: for (i=1;i<=NDIM;i++) {
13005: for (j=1;j<=NDIM;j++)
1.226 brouard 13006: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 13007: }
13008:
1.302 brouard 13009: p[1]=0.0268; p[NDIM]=0.083;
13010: /* printf("%lf %lf", p[1], p[2]); */
1.126 brouard 13011:
13012:
1.136 brouard 13013: #ifdef GSL
13014: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 13015: #else
1.126 brouard 13016: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 13017: #endif
1.201 brouard 13018: strcpy(filerespow,"POW-MORT_");
13019: strcat(filerespow,fileresu);
1.126 brouard 13020: if((ficrespow=fopen(filerespow,"w"))==NULL) {
13021: printf("Problem with resultfile: %s\n", filerespow);
13022: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
13023: }
1.136 brouard 13024: #ifdef GSL
13025: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 13026: #else
1.126 brouard 13027: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 13028: #endif
1.126 brouard 13029: /* for (i=1;i<=nlstate;i++)
13030: for(j=1;j<=nlstate+ndeath;j++)
13031: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
13032: */
13033: fprintf(ficrespow,"\n");
1.136 brouard 13034: #ifdef GSL
13035: /* gsl starts here */
13036: T = gsl_multimin_fminimizer_nmsimplex;
13037: gsl_multimin_fminimizer *sfm = NULL;
13038: gsl_vector *ss, *x;
13039: gsl_multimin_function minex_func;
13040:
13041: /* Initial vertex size vector */
13042: ss = gsl_vector_alloc (NDIM);
13043:
13044: if (ss == NULL){
13045: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
13046: }
13047: /* Set all step sizes to 1 */
13048: gsl_vector_set_all (ss, 0.001);
13049:
13050: /* Starting point */
1.126 brouard 13051:
1.136 brouard 13052: x = gsl_vector_alloc (NDIM);
13053:
13054: if (x == NULL){
13055: gsl_vector_free(ss);
13056: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
13057: }
13058:
13059: /* Initialize method and iterate */
13060: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 13061: /* gsl_vector_set(x, 0, 0.0268); */
13062: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 13063: gsl_vector_set(x, 0, p[1]);
13064: gsl_vector_set(x, 1, p[2]);
13065:
13066: minex_func.f = &gompertz_f;
13067: minex_func.n = NDIM;
13068: minex_func.params = (void *)&p; /* ??? */
13069:
13070: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
13071: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
13072:
13073: printf("Iterations beginning .....\n\n");
13074: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
13075:
13076: iteri=0;
13077: while (rval == GSL_CONTINUE){
13078: iteri++;
13079: status = gsl_multimin_fminimizer_iterate(sfm);
13080:
13081: if (status) printf("error: %s\n", gsl_strerror (status));
13082: fflush(0);
13083:
13084: if (status)
13085: break;
13086:
13087: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
13088: ssval = gsl_multimin_fminimizer_size (sfm);
13089:
13090: if (rval == GSL_SUCCESS)
13091: printf ("converged to a local maximum at\n");
13092:
13093: printf("%5d ", iteri);
13094: for (it = 0; it < NDIM; it++){
13095: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
13096: }
13097: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
13098: }
13099:
13100: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
13101:
13102: gsl_vector_free(x); /* initial values */
13103: gsl_vector_free(ss); /* inital step size */
13104: for (it=0; it<NDIM; it++){
13105: p[it+1]=gsl_vector_get(sfm->x,it);
13106: fprintf(ficrespow," %.12lf", p[it]);
13107: }
13108: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
13109: #endif
13110: #ifdef POWELL
13111: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
13112: #endif
1.126 brouard 13113: fclose(ficrespow);
13114:
1.203 brouard 13115: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 13116:
13117: for(i=1; i <=NDIM; i++)
13118: for(j=i+1;j<=NDIM;j++)
1.220 brouard 13119: matcov[i][j]=matcov[j][i];
1.126 brouard 13120:
13121: printf("\nCovariance matrix\n ");
1.203 brouard 13122: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 13123: for(i=1; i <=NDIM; i++) {
13124: for(j=1;j<=NDIM;j++){
1.220 brouard 13125: printf("%f ",matcov[i][j]);
13126: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 13127: }
1.203 brouard 13128: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 13129: }
13130:
13131: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 13132: for (i=1;i<=NDIM;i++) {
1.126 brouard 13133: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 13134: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
13135: }
1.302 brouard 13136: lsurv=vector(agegomp,AGESUP);
13137: lpop=vector(agegomp,AGESUP);
13138: tpop=vector(agegomp,AGESUP);
1.126 brouard 13139: lsurv[agegomp]=100000;
13140:
13141: for (k=agegomp;k<=AGESUP;k++) {
13142: agemortsup=k;
13143: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
13144: }
13145:
13146: for (k=agegomp;k<agemortsup;k++)
13147: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
13148:
13149: for (k=agegomp;k<agemortsup;k++){
13150: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
13151: sumlpop=sumlpop+lpop[k];
13152: }
13153:
13154: tpop[agegomp]=sumlpop;
13155: for (k=agegomp;k<(agemortsup-3);k++){
13156: /* tpop[k+1]=2;*/
13157: tpop[k+1]=tpop[k]-lpop[k];
13158: }
13159:
13160:
13161: printf("\nAge lx qx dx Lx Tx e(x)\n");
13162: for (k=agegomp;k<(agemortsup-2);k++)
13163: 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]);
13164:
13165:
13166: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 13167: ageminpar=50;
13168: agemaxpar=100;
1.194 brouard 13169: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
13170: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
13171: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
13172: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
13173: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
13174: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
13175: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 13176: }else{
13177: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
13178: 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 13179: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 13180: }
1.201 brouard 13181: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 13182: stepm, weightopt,\
13183: model,imx,p,matcov,agemortsup);
13184:
1.302 brouard 13185: free_vector(lsurv,agegomp,AGESUP);
13186: free_vector(lpop,agegomp,AGESUP);
13187: free_vector(tpop,agegomp,AGESUP);
1.220 brouard 13188: free_matrix(ximort,1,NDIM,1,NDIM);
1.290 brouard 13189: free_ivector(dcwave,firstobs,lastobs);
13190: free_vector(agecens,firstobs,lastobs);
13191: free_vector(ageexmed,firstobs,lastobs);
13192: free_ivector(cens,firstobs,lastobs);
1.220 brouard 13193: #ifdef GSL
1.136 brouard 13194: #endif
1.186 brouard 13195: } /* Endof if mle==-3 mortality only */
1.205 brouard 13196: /* Standard */
13197: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
13198: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
13199: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 13200: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 13201: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
13202: for (k=1; k<=npar;k++)
13203: printf(" %d %8.5f",k,p[k]);
13204: printf("\n");
1.205 brouard 13205: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
13206: /* mlikeli uses func not funcone */
1.247 brouard 13207: /* for(i=1;i<nlstate;i++){ */
13208: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
13209: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
13210: /* } */
1.205 brouard 13211: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
13212: }
13213: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
13214: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
13215: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
13216: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
13217: }
13218: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 13219: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
13220: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
1.335 brouard 13221: /* exit(0); */
1.126 brouard 13222: for (k=1; k<=npar;k++)
13223: printf(" %d %8.5f",k,p[k]);
13224: printf("\n");
13225:
13226: /*--------- results files --------------*/
1.283 brouard 13227: /* 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 13228:
13229:
13230: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 13231: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n"); /* Printing model equation */
1.126 brouard 13232: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 13233:
13234: printf("#model= 1 + age ");
13235: fprintf(ficres,"#model= 1 + age ");
13236: fprintf(ficlog,"#model= 1 + age ");
13237: fprintf(fichtm,"\n<ul><li> model=1+age+%s\n \
13238: </ul>", model);
13239:
13240: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">\n");
13241: fprintf(fichtm, "<tr><th>Model=</th><th>1</th><th>+ age</th>");
13242: if(nagesqr==1){
13243: printf(" + age*age ");
13244: fprintf(ficres," + age*age ");
13245: fprintf(ficlog," + age*age ");
13246: fprintf(fichtm, "<th>+ age*age</th>");
13247: }
13248: for(j=1;j <=ncovmodel-2;j++){
13249: if(Typevar[j]==0) {
13250: printf(" + V%d ",Tvar[j]);
13251: fprintf(ficres," + V%d ",Tvar[j]);
13252: fprintf(ficlog," + V%d ",Tvar[j]);
13253: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
13254: }else if(Typevar[j]==1) {
13255: printf(" + V%d*age ",Tvar[j]);
13256: fprintf(ficres," + V%d*age ",Tvar[j]);
13257: fprintf(ficlog," + V%d*age ",Tvar[j]);
13258: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
13259: }else if(Typevar[j]==2) {
13260: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
13261: fprintf(ficres," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
13262: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
13263: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
13264: }
13265: }
13266: printf("\n");
13267: fprintf(ficres,"\n");
13268: fprintf(ficlog,"\n");
13269: fprintf(fichtm, "</tr>");
13270: fprintf(fichtm, "\n");
13271:
13272:
1.126 brouard 13273: for(i=1,jk=1; i <=nlstate; i++){
13274: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 13275: if (k != i) {
1.319 brouard 13276: fprintf(fichtm, "<tr>");
1.225 brouard 13277: printf("%d%d ",i,k);
13278: fprintf(ficlog,"%d%d ",i,k);
13279: fprintf(ficres,"%1d%1d ",i,k);
1.319 brouard 13280: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 13281: for(j=1; j <=ncovmodel; j++){
13282: printf("%12.7f ",p[jk]);
13283: fprintf(ficlog,"%12.7f ",p[jk]);
13284: fprintf(ficres,"%12.7f ",p[jk]);
1.319 brouard 13285: fprintf(fichtm, "<td>%12.7f</td>",p[jk]);
1.225 brouard 13286: jk++;
13287: }
13288: printf("\n");
13289: fprintf(ficlog,"\n");
13290: fprintf(ficres,"\n");
1.319 brouard 13291: fprintf(fichtm, "</tr>\n");
1.225 brouard 13292: }
1.126 brouard 13293: }
13294: }
1.319 brouard 13295: /* fprintf(fichtm,"</tr>\n"); */
13296: fprintf(fichtm,"</table>\n");
13297: fprintf(fichtm, "\n");
13298:
1.203 brouard 13299: if(mle != 0){
13300: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 13301: ftolhess=ftol; /* Usually correct */
1.203 brouard 13302: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
13303: 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");
13304: fprintf(ficlog, "Parameters, Wald tests and Wald-based confidence intervals\n W is simply the result of the division of the parameter by the square root of covariance of the parameter.\n And Wald-based confidence intervals plus and minus 1.96 * W \n It might be better to visualize the covariance matrix. See the page 'Matrix of variance-covariance of one-step probabilities' and its graphs.\n");
1.322 brouard 13305: fprintf(fichtm, "\n<p>The Wald test results are output only if the maximimzation of the Likelihood is performed (mle=1)\n</br>Parameters, Wald tests and Wald-based confidence intervals\n</br> W is simply the result of the division of the parameter by the square root of covariance of the parameter.\n</br> And Wald-based confidence intervals plus and minus 1.96 * W \n </br> It might be better to visualize the covariance matrix. See the page '<a href=\"%s\">Matrix of variance-covariance of one-step probabilities and its graphs</a>'.\n</br>",optionfilehtmcov);
1.319 brouard 13306: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">");
13307: fprintf(fichtm, "\n<tr><th>Model=</th><th>1</th><th>+ age</th>");
13308: if(nagesqr==1){
13309: printf(" + age*age ");
13310: fprintf(ficres," + age*age ");
13311: fprintf(ficlog," + age*age ");
13312: fprintf(fichtm, "<th>+ age*age</th>");
13313: }
13314: for(j=1;j <=ncovmodel-2;j++){
13315: if(Typevar[j]==0) {
13316: printf(" + V%d ",Tvar[j]);
13317: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
13318: }else if(Typevar[j]==1) {
13319: printf(" + V%d*age ",Tvar[j]);
13320: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
13321: }else if(Typevar[j]==2) {
13322: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
13323: }
13324: }
13325: fprintf(fichtm, "</tr>\n");
13326:
1.203 brouard 13327: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 13328: for(k=1; k <=(nlstate+ndeath); k++){
13329: if (k != i) {
1.319 brouard 13330: fprintf(fichtm, "<tr valign=top>");
1.225 brouard 13331: printf("%d%d ",i,k);
13332: fprintf(ficlog,"%d%d ",i,k);
1.319 brouard 13333: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 13334: for(j=1; j <=ncovmodel; j++){
1.319 brouard 13335: wald=p[jk]/sqrt(matcov[jk][jk]);
1.324 brouard 13336: printf("%12.7f(%12.7f) W=%8.3f CI=[%12.7f ; %12.7f] ",p[jk],sqrt(matcov[jk][jk]), p[jk]/sqrt(matcov[jk][jk]), p[jk]-1.96*sqrt(matcov[jk][jk]),p[jk]+1.96*sqrt(matcov[jk][jk]));
13337: fprintf(ficlog,"%12.7f(%12.7f) W=%8.3f CI=[%12.7f ; %12.7f] ",p[jk],sqrt(matcov[jk][jk]), p[jk]/sqrt(matcov[jk][jk]), p[jk]-1.96*sqrt(matcov[jk][jk]),p[jk]+1.96*sqrt(matcov[jk][jk]));
1.319 brouard 13338: if(fabs(wald) > 1.96){
1.321 brouard 13339: fprintf(fichtm, "<td><b>%12.7f</b></br> (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
1.319 brouard 13340: }else{
13341: fprintf(fichtm, "<td>%12.7f (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
13342: }
1.324 brouard 13343: fprintf(fichtm,"W=%8.3f</br>",wald);
1.319 brouard 13344: fprintf(fichtm,"[%12.7f;%12.7f]</br></td>", p[jk]-1.96*sqrt(matcov[jk][jk]),p[jk]+1.96*sqrt(matcov[jk][jk]));
1.225 brouard 13345: jk++;
13346: }
13347: printf("\n");
13348: fprintf(ficlog,"\n");
1.319 brouard 13349: fprintf(fichtm, "</tr>\n");
1.225 brouard 13350: }
13351: }
1.193 brouard 13352: }
1.203 brouard 13353: } /* end of hesscov and Wald tests */
1.319 brouard 13354: fprintf(fichtm,"</table>\n");
1.225 brouard 13355:
1.203 brouard 13356: /* */
1.126 brouard 13357: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
13358: printf("# Scales (for hessian or gradient estimation)\n");
13359: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
13360: for(i=1,jk=1; i <=nlstate; i++){
13361: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 13362: if (j!=i) {
13363: fprintf(ficres,"%1d%1d",i,j);
13364: printf("%1d%1d",i,j);
13365: fprintf(ficlog,"%1d%1d",i,j);
13366: for(k=1; k<=ncovmodel;k++){
13367: printf(" %.5e",delti[jk]);
13368: fprintf(ficlog," %.5e",delti[jk]);
13369: fprintf(ficres," %.5e",delti[jk]);
13370: jk++;
13371: }
13372: printf("\n");
13373: fprintf(ficlog,"\n");
13374: fprintf(ficres,"\n");
13375: }
1.126 brouard 13376: }
13377: }
13378:
13379: 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 13380: if(mle >= 1) /* To big for the screen */
1.126 brouard 13381: 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");
13382: 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");
13383: /* # 121 Var(a12)\n\ */
13384: /* # 122 Cov(b12,a12) Var(b12)\n\ */
13385: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
13386: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
13387: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
13388: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
13389: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
13390: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
13391:
13392:
13393: /* Just to have a covariance matrix which will be more understandable
13394: even is we still don't want to manage dictionary of variables
13395: */
13396: for(itimes=1;itimes<=2;itimes++){
13397: jj=0;
13398: for(i=1; i <=nlstate; i++){
1.225 brouard 13399: for(j=1; j <=nlstate+ndeath; j++){
13400: if(j==i) continue;
13401: for(k=1; k<=ncovmodel;k++){
13402: jj++;
13403: ca[0]= k+'a'-1;ca[1]='\0';
13404: if(itimes==1){
13405: if(mle>=1)
13406: printf("#%1d%1d%d",i,j,k);
13407: fprintf(ficlog,"#%1d%1d%d",i,j,k);
13408: fprintf(ficres,"#%1d%1d%d",i,j,k);
13409: }else{
13410: if(mle>=1)
13411: printf("%1d%1d%d",i,j,k);
13412: fprintf(ficlog,"%1d%1d%d",i,j,k);
13413: fprintf(ficres,"%1d%1d%d",i,j,k);
13414: }
13415: ll=0;
13416: for(li=1;li <=nlstate; li++){
13417: for(lj=1;lj <=nlstate+ndeath; lj++){
13418: if(lj==li) continue;
13419: for(lk=1;lk<=ncovmodel;lk++){
13420: ll++;
13421: if(ll<=jj){
13422: cb[0]= lk +'a'-1;cb[1]='\0';
13423: if(ll<jj){
13424: if(itimes==1){
13425: if(mle>=1)
13426: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
13427: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
13428: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
13429: }else{
13430: if(mle>=1)
13431: printf(" %.5e",matcov[jj][ll]);
13432: fprintf(ficlog," %.5e",matcov[jj][ll]);
13433: fprintf(ficres," %.5e",matcov[jj][ll]);
13434: }
13435: }else{
13436: if(itimes==1){
13437: if(mle>=1)
13438: printf(" Var(%s%1d%1d)",ca,i,j);
13439: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
13440: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
13441: }else{
13442: if(mle>=1)
13443: printf(" %.7e",matcov[jj][ll]);
13444: fprintf(ficlog," %.7e",matcov[jj][ll]);
13445: fprintf(ficres," %.7e",matcov[jj][ll]);
13446: }
13447: }
13448: }
13449: } /* end lk */
13450: } /* end lj */
13451: } /* end li */
13452: if(mle>=1)
13453: printf("\n");
13454: fprintf(ficlog,"\n");
13455: fprintf(ficres,"\n");
13456: numlinepar++;
13457: } /* end k*/
13458: } /*end j */
1.126 brouard 13459: } /* end i */
13460: } /* end itimes */
13461:
13462: fflush(ficlog);
13463: fflush(ficres);
1.225 brouard 13464: while(fgets(line, MAXLINE, ficpar)) {
13465: /* If line starts with a # it is a comment */
13466: if (line[0] == '#') {
13467: numlinepar++;
13468: fputs(line,stdout);
13469: fputs(line,ficparo);
13470: fputs(line,ficlog);
1.299 brouard 13471: fputs(line,ficres);
1.225 brouard 13472: continue;
13473: }else
13474: break;
13475: }
13476:
1.209 brouard 13477: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
13478: /* ungetc(c,ficpar); */
13479: /* fgets(line, MAXLINE, ficpar); */
13480: /* fputs(line,stdout); */
13481: /* fputs(line,ficparo); */
13482: /* } */
13483: /* ungetc(c,ficpar); */
1.126 brouard 13484:
13485: estepm=0;
1.209 brouard 13486: 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 13487:
13488: if (num_filled != 6) {
13489: 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);
13490: 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);
13491: goto end;
13492: }
13493: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
13494: }
13495: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
13496: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
13497:
1.209 brouard 13498: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 13499: if (estepm==0 || estepm < stepm) estepm=stepm;
13500: if (fage <= 2) {
13501: bage = ageminpar;
13502: fage = agemaxpar;
13503: }
13504:
13505: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 13506: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
13507: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 13508:
1.186 brouard 13509: /* Other stuffs, more or less useful */
1.254 brouard 13510: while(fgets(line, MAXLINE, ficpar)) {
13511: /* If line starts with a # it is a comment */
13512: if (line[0] == '#') {
13513: numlinepar++;
13514: fputs(line,stdout);
13515: fputs(line,ficparo);
13516: fputs(line,ficlog);
1.299 brouard 13517: fputs(line,ficres);
1.254 brouard 13518: continue;
13519: }else
13520: break;
13521: }
13522:
13523: 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){
13524:
13525: if (num_filled != 7) {
13526: 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);
13527: 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);
13528: goto end;
13529: }
13530: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
13531: 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);
13532: 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);
13533: 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 13534: }
1.254 brouard 13535:
13536: while(fgets(line, MAXLINE, ficpar)) {
13537: /* If line starts with a # it is a comment */
13538: if (line[0] == '#') {
13539: numlinepar++;
13540: fputs(line,stdout);
13541: fputs(line,ficparo);
13542: fputs(line,ficlog);
1.299 brouard 13543: fputs(line,ficres);
1.254 brouard 13544: continue;
13545: }else
13546: break;
1.126 brouard 13547: }
13548:
13549:
13550: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
13551: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
13552:
1.254 brouard 13553: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
13554: if (num_filled != 1) {
13555: 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);
13556: 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);
13557: goto end;
13558: }
13559: printf("pop_based=%d\n",popbased);
13560: fprintf(ficlog,"pop_based=%d\n",popbased);
13561: fprintf(ficparo,"pop_based=%d\n",popbased);
13562: fprintf(ficres,"pop_based=%d\n",popbased);
13563: }
13564:
1.258 brouard 13565: /* Results */
1.332 brouard 13566: /* Value of covariate in each resultine will be compututed (if product) and sorted according to model rank */
13567: /* It is precov[] because we need the varying age in order to compute the real cov[] of the model equation */
13568: precov=matrix(1,MAXRESULTLINESPONE,1,NCOVMAX+1);
1.307 brouard 13569: endishere=0;
1.258 brouard 13570: nresult=0;
1.308 brouard 13571: parameterline=0;
1.258 brouard 13572: do{
13573: if(!fgets(line, MAXLINE, ficpar)){
13574: endishere=1;
1.308 brouard 13575: parameterline=15;
1.258 brouard 13576: }else if (line[0] == '#') {
13577: /* If line starts with a # it is a comment */
1.254 brouard 13578: numlinepar++;
13579: fputs(line,stdout);
13580: fputs(line,ficparo);
13581: fputs(line,ficlog);
1.299 brouard 13582: fputs(line,ficres);
1.254 brouard 13583: continue;
1.258 brouard 13584: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
13585: parameterline=11;
1.296 brouard 13586: else if(sscanf(line,"prevbackcast=%[^\n]\n",modeltemp))
1.258 brouard 13587: parameterline=12;
1.307 brouard 13588: else if(sscanf(line,"result:%[^\n]\n",modeltemp)){
1.258 brouard 13589: parameterline=13;
1.307 brouard 13590: }
1.258 brouard 13591: else{
13592: parameterline=14;
1.254 brouard 13593: }
1.308 brouard 13594: switch (parameterline){ /* =0 only if only comments */
1.258 brouard 13595: case 11:
1.296 brouard 13596: 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)){
13597: 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 13598: 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);
13599: 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);
13600: 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);
13601: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 13602: dateproj1=anproj1+(mproj1-1)/12.+(jproj1-1)/365.;
13603: dateproj2=anproj2+(mproj2-1)/12.+(jproj2-1)/365.;
1.296 brouard 13604: prvforecast = 1;
13605: }
13606: else if((num_filled=sscanf(line,"prevforecast=%d yearsfproj=%lf mobil_average=%d\n",&prevfcast,&yrfproj,&mobilavproj)) !=EOF){/* && (num_filled == 3))*/
1.313 brouard 13607: printf("prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
13608: fprintf(ficlog,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
13609: fprintf(ficres,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
1.296 brouard 13610: prvforecast = 2;
13611: }
13612: else {
13613: 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);
13614: 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);
13615: goto end;
1.258 brouard 13616: }
1.254 brouard 13617: break;
1.258 brouard 13618: case 12:
1.296 brouard 13619: 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)){
13620: 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);
13621: 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);
13622: 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);
13623: 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);
13624: /* day and month of back2 are not used but only year anback2.*/
1.273 brouard 13625: dateback1=anback1+(mback1-1)/12.+(jback1-1)/365.;
13626: dateback2=anback2+(mback2-1)/12.+(jback2-1)/365.;
1.296 brouard 13627: prvbackcast = 1;
13628: }
13629: else if((num_filled=sscanf(line,"prevbackcast=%d yearsbproj=%lf mobil_average=%d\n",&prevbcast,&yrbproj,&mobilavproj)) ==3){/* && (num_filled == 3))*/
1.313 brouard 13630: printf("prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
13631: fprintf(ficlog,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
13632: fprintf(ficres,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
1.296 brouard 13633: prvbackcast = 2;
13634: }
13635: else {
13636: 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);
13637: 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);
13638: goto end;
1.258 brouard 13639: }
1.230 brouard 13640: break;
1.258 brouard 13641: case 13:
1.332 brouard 13642: num_filled=sscanf(line,"result:%[^\n]\n",resultlineori);
1.307 brouard 13643: nresult++; /* Sum of resultlines */
1.332 brouard 13644: printf("Result %d: result:%s\n",nresult, resultlineori);
13645: /* removefirstspace(&resultlineori); */
13646:
13647: if(strstr(resultlineori,"v") !=0){
13648: printf("Error. 'v' must be in upper case 'V' result: %s ",resultlineori);
13649: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultlineori);fflush(ficlog);
13650: return 1;
13651: }
13652: trimbb(resultline, resultlineori); /* Suppressing double blank in the resultline */
13653: printf("Decoderesult resultline=\"%s\" resultlineori=\"%s\"\n", resultline, resultlineori);
1.318 brouard 13654: if(nresult > MAXRESULTLINESPONE-1){
13655: 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);
13656: 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 13657: goto end;
13658: }
1.332 brouard 13659:
1.310 brouard 13660: if(!decoderesult(resultline, nresult)){ /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
1.314 brouard 13661: fprintf(ficparo,"result: %s\n",resultline);
13662: fprintf(ficres,"result: %s\n",resultline);
13663: fprintf(ficlog,"result: %s\n",resultline);
1.310 brouard 13664: } else
13665: goto end;
1.307 brouard 13666: break;
13667: case 14:
13668: printf("Error: Unknown command '%s'\n",line);
13669: fprintf(ficlog,"Error: Unknown command '%s'\n",line);
1.314 brouard 13670: if(line[0] == ' ' || line[0] == '\n'){
13671: printf("It should not be an empty line '%s'\n",line);
13672: fprintf(ficlog,"It should not be an empty line '%s'\n",line);
13673: }
1.307 brouard 13674: if(ncovmodel >=2 && nresult==0 ){
13675: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
13676: fprintf(ficlog,"ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 13677: }
1.307 brouard 13678: /* goto end; */
13679: break;
1.308 brouard 13680: case 15:
13681: printf("End of resultlines.\n");
13682: fprintf(ficlog,"End of resultlines.\n");
13683: break;
13684: default: /* parameterline =0 */
1.307 brouard 13685: nresult=1;
13686: decoderesult(".",nresult ); /* No covariate */
1.258 brouard 13687: } /* End switch parameterline */
13688: }while(endishere==0); /* End do */
1.126 brouard 13689:
1.230 brouard 13690: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 13691: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 13692:
13693: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 13694: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 13695: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 13696: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
13697: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 13698: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 13699: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
13700: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 13701: }else{
1.270 brouard 13702: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
1.296 brouard 13703: /* It seems that anprojd which is computed from the mean year at interview which is known yet because of freqsummary */
13704: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */ /* Done in freqsummary */
13705: if(prvforecast==1){
13706: dateprojd=(jproj1+12*mproj1+365*anproj1)/365;
13707: jprojd=jproj1;
13708: mprojd=mproj1;
13709: anprojd=anproj1;
13710: dateprojf=(jproj2+12*mproj2+365*anproj2)/365;
13711: jprojf=jproj2;
13712: mprojf=mproj2;
13713: anprojf=anproj2;
13714: } else if(prvforecast == 2){
13715: dateprojd=dateintmean;
13716: date2dmy(dateprojd,&jprojd, &mprojd, &anprojd);
13717: dateprojf=dateintmean+yrfproj;
13718: date2dmy(dateprojf,&jprojf, &mprojf, &anprojf);
13719: }
13720: if(prvbackcast==1){
13721: datebackd=(jback1+12*mback1+365*anback1)/365;
13722: jbackd=jback1;
13723: mbackd=mback1;
13724: anbackd=anback1;
13725: datebackf=(jback2+12*mback2+365*anback2)/365;
13726: jbackf=jback2;
13727: mbackf=mback2;
13728: anbackf=anback2;
13729: } else if(prvbackcast == 2){
13730: datebackd=dateintmean;
13731: date2dmy(datebackd,&jbackd, &mbackd, &anbackd);
13732: datebackf=dateintmean-yrbproj;
13733: date2dmy(datebackf,&jbackf, &mbackf, &anbackf);
13734: }
13735:
13736: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, prevbcast, pathc,p, (int)anprojd-bage, (int)anbackd-fage);
1.220 brouard 13737: }
13738: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.296 brouard 13739: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,prevbcast, estepm, \
13740: jprev1,mprev1,anprev1,dateprev1, dateprojd, datebackd,jprev2,mprev2,anprev2,dateprev2,dateprojf, datebackf);
1.220 brouard 13741:
1.225 brouard 13742: /*------------ free_vector -------------*/
13743: /* chdir(path); */
1.220 brouard 13744:
1.215 brouard 13745: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
13746: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
13747: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
13748: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.290 brouard 13749: free_lvector(num,firstobs,lastobs);
13750: free_vector(agedc,firstobs,lastobs);
1.126 brouard 13751: /*free_matrix(covar,0,NCOVMAX,1,n);*/
13752: /*free_matrix(covar,1,NCOVMAX,1,n);*/
13753: fclose(ficparo);
13754: fclose(ficres);
1.220 brouard 13755:
13756:
1.186 brouard 13757: /* Other results (useful)*/
1.220 brouard 13758:
13759:
1.126 brouard 13760: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 13761: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
13762: prlim=matrix(1,nlstate,1,nlstate);
1.332 brouard 13763: /* Computes the prevalence limit for each combination k of the dummy covariates by calling prevalim(k) */
1.209 brouard 13764: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 13765: fclose(ficrespl);
13766:
13767: /*------------- h Pij x at various ages ------------*/
1.180 brouard 13768: /*#include "hpijx.h"*/
1.332 brouard 13769: /** h Pij x Probability to be in state j at age x+h being in i at x, for each combination k of dummies in the model line or to nres?*/
13770: /* calls hpxij with combination k */
1.180 brouard 13771: hPijx(p, bage, fage);
1.145 brouard 13772: fclose(ficrespij);
1.227 brouard 13773:
1.220 brouard 13774: /* ncovcombmax= pow(2,cptcoveff); */
1.332 brouard 13775: /*-------------- Variance of one-step probabilities for a combination ij or for nres ?---*/
1.145 brouard 13776: k=1;
1.126 brouard 13777: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 13778:
1.269 brouard 13779: /* Prevalence for each covariate combination in probs[age][status][cov] */
13780: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
13781: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 13782: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 13783: for(k=1;k<=ncovcombmax;k++)
13784: probs[i][j][k]=0.;
1.269 brouard 13785: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
13786: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 13787: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 13788: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
13789: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 13790: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 13791: for(k=1;k<=ncovcombmax;k++)
13792: mobaverages[i][j][k]=0.;
1.219 brouard 13793: mobaverage=mobaverages;
13794: if (mobilav!=0) {
1.235 brouard 13795: printf("Movingaveraging observed prevalence\n");
1.258 brouard 13796: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 13797: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
13798: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
13799: printf(" Error in movingaverage mobilav=%d\n",mobilav);
13800: }
1.269 brouard 13801: } else if (mobilavproj !=0) {
1.235 brouard 13802: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 13803: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 13804: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
13805: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
13806: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
13807: }
1.269 brouard 13808: }else{
13809: printf("Internal error moving average\n");
13810: fflush(stdout);
13811: exit(1);
1.219 brouard 13812: }
13813: }/* end if moving average */
1.227 brouard 13814:
1.126 brouard 13815: /*---------- Forecasting ------------------*/
1.296 brouard 13816: if(prevfcast==1){
13817: /* /\* if(stepm ==1){*\/ */
13818: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
13819: /*This done previously after freqsummary.*/
13820: /* dateprojd=(jproj1+12*mproj1+365*anproj1)/365; */
13821: /* dateprojf=(jproj2+12*mproj2+365*anproj2)/365; */
13822:
13823: /* } else if (prvforecast==2){ */
13824: /* /\* if(stepm ==1){*\/ */
13825: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
13826: /* } */
13827: /*prevforecast(fileresu, dateintmean, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);*/
13828: prevforecast(fileresu,dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, p, cptcoveff);
1.126 brouard 13829: }
1.269 brouard 13830:
1.296 brouard 13831: /* Prevbcasting */
13832: if(prevbcast==1){
1.219 brouard 13833: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
13834: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
13835: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
13836:
13837: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
13838:
13839: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 13840:
1.219 brouard 13841: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
13842: fclose(ficresplb);
13843:
1.222 brouard 13844: hBijx(p, bage, fage, mobaverage);
13845: fclose(ficrespijb);
1.219 brouard 13846:
1.296 brouard 13847: /* /\* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, *\/ */
13848: /* /\* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); *\/ */
13849: /* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, */
13850: /* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); */
13851: prevbackforecast(fileresu, mobaverage, dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2,
13852: mobilavproj, bage, fage, firstpass, lastpass, p, cptcoveff);
13853:
13854:
1.269 brouard 13855: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 13856:
13857:
1.269 brouard 13858: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 13859: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
13860: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
13861: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.296 brouard 13862: } /* end Prevbcasting */
1.268 brouard 13863:
1.186 brouard 13864:
13865: /* ------ Other prevalence ratios------------ */
1.126 brouard 13866:
1.215 brouard 13867: free_ivector(wav,1,imx);
13868: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
13869: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
13870: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 13871:
13872:
1.127 brouard 13873: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 13874:
1.201 brouard 13875: strcpy(filerese,"E_");
13876: strcat(filerese,fileresu);
1.126 brouard 13877: if((ficreseij=fopen(filerese,"w"))==NULL) {
13878: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
13879: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
13880: }
1.208 brouard 13881: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
13882: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 13883:
13884: pstamp(ficreseij);
1.219 brouard 13885:
1.235 brouard 13886: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
13887: if (cptcovn < 1){i1=1;}
13888:
13889: for(nres=1; nres <= nresult; nres++) /* For each resultline */
13890: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 13891: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 13892: continue;
1.219 brouard 13893: fprintf(ficreseij,"\n#****** ");
1.235 brouard 13894: printf("\n#****** ");
1.225 brouard 13895: for(j=1;j<=cptcoveff;j++) {
1.332 brouard 13896: fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
13897: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.235 brouard 13898: }
13899: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.337 brouard 13900: printf(" V%d=%lg ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]); /* TvarsQ[j] gives the name of the jth quantitative (fixed or time v) */
13901: fprintf(ficreseij,"V%d=%lg ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]);
1.219 brouard 13902: }
13903: fprintf(ficreseij,"******\n");
1.235 brouard 13904: printf("******\n");
1.219 brouard 13905:
13906: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
13907: oldm=oldms;savm=savms;
1.330 brouard 13908: /* printf("HELLO Entering evsij bage=%d fage=%d k=%d estepm=%d nres=%d\n",(int) bage, (int)fage, k, estepm, nres); */
1.235 brouard 13909: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 13910:
1.219 brouard 13911: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 13912: }
13913: fclose(ficreseij);
1.208 brouard 13914: printf("done evsij\n");fflush(stdout);
13915: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 13916:
1.218 brouard 13917:
1.227 brouard 13918: /*---------- State-specific expectancies and variances ------------*/
1.336 brouard 13919: /* Should be moved in a function */
1.201 brouard 13920: strcpy(filerest,"T_");
13921: strcat(filerest,fileresu);
1.127 brouard 13922: if((ficrest=fopen(filerest,"w"))==NULL) {
13923: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
13924: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
13925: }
1.208 brouard 13926: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
13927: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 13928: strcpy(fileresstde,"STDE_");
13929: strcat(fileresstde,fileresu);
1.126 brouard 13930: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 13931: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
13932: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 13933: }
1.227 brouard 13934: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
13935: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 13936:
1.201 brouard 13937: strcpy(filerescve,"CVE_");
13938: strcat(filerescve,fileresu);
1.126 brouard 13939: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 13940: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
13941: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 13942: }
1.227 brouard 13943: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
13944: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 13945:
1.201 brouard 13946: strcpy(fileresv,"V_");
13947: strcat(fileresv,fileresu);
1.126 brouard 13948: if((ficresvij=fopen(fileresv,"w"))==NULL) {
13949: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
13950: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
13951: }
1.227 brouard 13952: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
13953: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 13954:
1.235 brouard 13955: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
13956: if (cptcovn < 1){i1=1;}
13957:
1.334 brouard 13958: for(nres=1; nres <= nresult; nres++) /* For each resultline, find the combination and output results according to the values of dummies and then quanti. */
13959: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying. For each nres and each value at position k
13960: * we know Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline
13961: * Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline
13962: * and Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
13963: /* */
13964: if(i1 != 1 && TKresult[nres]!= k) /* TKresult[nres] is the combination of this nres resultline. All the i1 combinations are not output */
1.235 brouard 13965: continue;
1.321 brouard 13966: printf("\n# model %s \n#****** Result for:", model);
13967: fprintf(ficrest,"\n# model %s \n#****** Result for:", model);
13968: fprintf(ficlog,"\n# model %s \n#****** Result for:", model);
1.334 brouard 13969: /* It might not be a good idea to mix dummies and quantitative */
13970: /* for(j=1;j<=cptcoveff;j++){ /\* j=resultpos. Could be a loop on cptcovs: number of single dummy covariate in the result line as well as in the model *\/ */
13971: for(j=1;j<=cptcovs;j++){ /* j=resultpos. Could be a loop on cptcovs: number of single covariate (dummy or quantitative) in the result line as well as in the model */
13972: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /\* Output by variables in the resultline *\/ */
13973: /* Tvaraff[j] is the name of the dummy variable in position j in the equation model:
13974: * Tvaraff[1]@9={4, 3, 0, 0, 0, 0, 0, 0, 0}, in model=V5+V4+V3+V4*V3+V5*age
13975: * (V5 is quanti) V4 and V3 are dummies
13976: * TnsdVar[4] is the position 1 and TnsdVar[3]=2 in codtabm(k,l)(V4 V3)=V4 V3
13977: * l=1 l=2
13978: * k=1 1 1 0 0
13979: * k=2 2 1 1 0
13980: * k=3 [1] [2] 0 1
13981: * k=4 2 2 1 1
13982: * If nres=1 result: V3=1 V4=0 then k=3 and outputs
13983: * If nres=2 result: V4=1 V3=0 then k=2 and outputs
13984: * nres=1 =>k=3 j=1 V4= nbcode[4][codtabm(3,1)=1)=0; j=2 V3= nbcode[3][codtabm(3,2)=2]=1
13985: * nres=2 =>k=2 j=1 V4= nbcode[4][codtabm(2,1)=2)=1; j=2 V3= nbcode[3][codtabm(2,2)=1]=0
13986: */
13987: /* Tvresult[nres][j] Name of the variable at position j in this resultline */
13988: /* Tresult[nres][j] Value of this variable at position j could be a float if quantitative */
13989: /* We give up with the combinations!! */
13990: printf("\n j=%d In computing T_ Dummy[modelresult[%d][%d]]=%d, modelresult[%d][%d]=%d cptcovs=%d, cptcoveff=%d Fixed[modelresult[nres][j]]=%d\n", j, nres, j, Dummy[modelresult[nres][j]],nres,j,modelresult[nres][j],cptcovs, cptcoveff,Fixed[modelresult[nres][j]]); /* end if dummy or quanti */
13991:
13992: if(Dummy[modelresult[nres][j]]==0){/* Dummy variable of the variable in position modelresult in the model corresponding to j in resultline */
1.337 brouard 13993: printf("V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][j]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline */
13994: fprintf(ficlog,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][j]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline */
13995: fprintf(ficrest,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][j]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline */
1.334 brouard 13996: if(Fixed[modelresult[nres][j]]==0){ /* Fixed */
13997: printf("fixed ");fprintf(ficlog,"fixed ");fprintf(ficrest,"fixed ");
13998: }else{
13999: printf("varyi ");fprintf(ficlog,"varyi ");fprintf(ficrest,"varyi ");
14000: }
14001: /* fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14002: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14003: }else if(Dummy[modelresult[nres][j]]==1){ /* Quanti variable */
14004: /* For each selected (single) quantitative value */
1.337 brouard 14005: printf(" V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
14006: fprintf(ficlog," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
14007: fprintf(ficrest," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
1.334 brouard 14008: if(Fixed[modelresult[nres][j]]==0){ /* Fixed */
14009: printf("fixed ");fprintf(ficlog,"fixed ");fprintf(ficrest,"fixed ");
14010: }else{
14011: printf("varyi ");fprintf(ficlog,"varyi ");fprintf(ficrest,"varyi ");
14012: }
14013: }else{
14014: printf("Error in computing T_ Dummy[modelresult[%d][%d]]=%d, modelresult[%d][%d]=%d cptcovs=%d, cptcoveff=%d \n", nres, j, Dummy[modelresult[nres][j]],nres,j,modelresult[nres][j],cptcovs, cptcoveff); /* end if dummy or quanti */
14015: fprintf(ficlog,"Error in computing T_ Dummy[modelresult[%d][%d]]=%d, modelresult[%d][%d]=%d cptcovs=%d, cptcoveff=%d \n", nres, j, Dummy[modelresult[nres][j]],nres,j,modelresult[nres][j],cptcovs, cptcoveff); /* end if dummy or quanti */
14016: exit(1);
14017: }
1.335 brouard 14018: } /* End loop for each variable in the resultline */
1.334 brouard 14019: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
14020: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /\* Wrong j is not in the equation model *\/ */
14021: /* fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
14022: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
14023: /* } */
1.208 brouard 14024: fprintf(ficrest,"******\n");
1.227 brouard 14025: fprintf(ficlog,"******\n");
14026: printf("******\n");
1.208 brouard 14027:
14028: fprintf(ficresstdeij,"\n#****** ");
14029: fprintf(ficrescveij,"\n#****** ");
1.337 brouard 14030: /* It could have been: for(j=1;j<=cptcoveff;j++) {printf("V=%d=%lg",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);} */
14031: /* But it won't be sorted and depends on how the resultline is ordered */
1.225 brouard 14032: for(j=1;j<=cptcoveff;j++) {
1.334 brouard 14033: fprintf(ficresstdeij,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]);
14034: /* fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14035: /* fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14036: }
14037: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value, TvarsQind gives the position of a quantitative in model equation */
1.337 brouard 14038: fprintf(ficresstdeij," V%d=%lg ",Tvar[TvarsQind[j]],Tqresult[nres][resultmodel[nres][TvarsQind[j]]]);
14039: fprintf(ficrescveij," V%d=%lg ",Tvar[TvarsQind[j]],Tqresult[nres][resultmodel[nres][TvarsQind[j]]]);
1.235 brouard 14040: }
1.208 brouard 14041: fprintf(ficresstdeij,"******\n");
14042: fprintf(ficrescveij,"******\n");
14043:
14044: fprintf(ficresvij,"\n#****** ");
1.238 brouard 14045: /* pstamp(ficresvij); */
1.225 brouard 14046: for(j=1;j<=cptcoveff;j++)
1.335 brouard 14047: fprintf(ficresvij,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]);
14048: /* fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[TnsdVar[Tvaraff[j]]])]); */
1.235 brouard 14049: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.332 brouard 14050: /* fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]); /\* To solve *\/ */
1.337 brouard 14051: fprintf(ficresvij," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /* Solved */
1.235 brouard 14052: }
1.208 brouard 14053: fprintf(ficresvij,"******\n");
14054:
14055: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
14056: oldm=oldms;savm=savms;
1.235 brouard 14057: printf(" cvevsij ");
14058: fprintf(ficlog, " cvevsij ");
14059: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 14060: printf(" end cvevsij \n ");
14061: fprintf(ficlog, " end cvevsij \n ");
14062:
14063: /*
14064: */
14065: /* goto endfree; */
14066:
14067: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
14068: pstamp(ficrest);
14069:
1.269 brouard 14070: epj=vector(1,nlstate+1);
1.208 brouard 14071: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 14072: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
14073: cptcod= 0; /* To be deleted */
14074: printf("varevsij vpopbased=%d \n",vpopbased);
14075: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 14076: 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 14077: 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 ");
14078: if(vpopbased==1)
14079: 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);
14080: else
1.288 brouard 14081: fprintf(ficrest,"the age specific forward period (stable) prevalences in each health state \n");
1.335 brouard 14082: fprintf(ficrest,"# Age popbased mobilav e.. (std) "); /* Adding covariate values? */
1.227 brouard 14083: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
14084: fprintf(ficrest,"\n");
14085: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
1.288 brouard 14086: printf("Computing age specific forward period (stable) prevalences in each health state \n");
14087: fprintf(ficlog,"Computing age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 14088: for(age=bage; age <=fage ;age++){
1.235 brouard 14089: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 14090: if (vpopbased==1) {
14091: if(mobilav ==0){
14092: for(i=1; i<=nlstate;i++)
14093: prlim[i][i]=probs[(int)age][i][k];
14094: }else{ /* mobilav */
14095: for(i=1; i<=nlstate;i++)
14096: prlim[i][i]=mobaverage[(int)age][i][k];
14097: }
14098: }
1.219 brouard 14099:
1.227 brouard 14100: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
14101: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
14102: /* printf(" age %4.0f ",age); */
14103: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
14104: for(i=1, epj[j]=0.;i <=nlstate;i++) {
14105: epj[j] += prlim[i][i]*eij[i][j][(int)age];
14106: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
14107: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
14108: }
14109: epj[nlstate+1] +=epj[j];
14110: }
14111: /* printf(" age %4.0f \n",age); */
1.219 brouard 14112:
1.227 brouard 14113: for(i=1, vepp=0.;i <=nlstate;i++)
14114: for(j=1;j <=nlstate;j++)
14115: vepp += vareij[i][j][(int)age];
14116: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
14117: for(j=1;j <=nlstate;j++){
14118: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
14119: }
14120: fprintf(ficrest,"\n");
14121: }
1.208 brouard 14122: } /* End vpopbased */
1.269 brouard 14123: free_vector(epj,1,nlstate+1);
1.208 brouard 14124: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
14125: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 14126: printf("done selection\n");fflush(stdout);
14127: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 14128:
1.335 brouard 14129: } /* End k selection or end covariate selection for nres */
1.227 brouard 14130:
14131: printf("done State-specific expectancies\n");fflush(stdout);
14132: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
14133:
1.335 brouard 14134: /* variance-covariance of forward period prevalence */
1.269 brouard 14135: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 14136:
1.227 brouard 14137:
1.290 brouard 14138: free_vector(weight,firstobs,lastobs);
1.330 brouard 14139: free_imatrix(Tvardk,1,NCOVMAX,1,2);
1.227 brouard 14140: free_imatrix(Tvard,1,NCOVMAX,1,2);
1.290 brouard 14141: free_imatrix(s,1,maxwav+1,firstobs,lastobs);
14142: free_matrix(anint,1,maxwav,firstobs,lastobs);
14143: free_matrix(mint,1,maxwav,firstobs,lastobs);
14144: free_ivector(cod,firstobs,lastobs);
1.227 brouard 14145: free_ivector(tab,1,NCOVMAX);
14146: fclose(ficresstdeij);
14147: fclose(ficrescveij);
14148: fclose(ficresvij);
14149: fclose(ficrest);
14150: fclose(ficpar);
14151:
14152:
1.126 brouard 14153: /*---------- End : free ----------------*/
1.219 brouard 14154: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 14155: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
14156: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 14157: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
14158: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 14159: } /* mle==-3 arrives here for freeing */
1.227 brouard 14160: /* endfree:*/
14161: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
14162: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
14163: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.290 brouard 14164: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,firstobs,lastobs);
14165: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,firstobs,lastobs);
14166: if(nqv>=1)free_matrix(coqvar,1,nqv,firstobs,lastobs);
14167: free_matrix(covar,0,NCOVMAX,firstobs,lastobs);
1.227 brouard 14168: free_matrix(matcov,1,npar,1,npar);
14169: free_matrix(hess,1,npar,1,npar);
14170: /*free_vector(delti,1,npar);*/
14171: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
14172: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 14173: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 14174: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
14175:
14176: free_ivector(ncodemax,1,NCOVMAX);
14177: free_ivector(ncodemaxwundef,1,NCOVMAX);
14178: free_ivector(Dummy,-1,NCOVMAX);
14179: free_ivector(Fixed,-1,NCOVMAX);
1.238 brouard 14180: free_ivector(DummyV,1,NCOVMAX);
14181: free_ivector(FixedV,1,NCOVMAX);
1.227 brouard 14182: free_ivector(Typevar,-1,NCOVMAX);
14183: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 14184: free_ivector(TvarsQ,1,NCOVMAX);
14185: free_ivector(TvarsQind,1,NCOVMAX);
14186: free_ivector(TvarsD,1,NCOVMAX);
1.330 brouard 14187: free_ivector(TnsdVar,1,NCOVMAX);
1.234 brouard 14188: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 14189: free_ivector(TvarFD,1,NCOVMAX);
14190: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 14191: free_ivector(TvarF,1,NCOVMAX);
14192: free_ivector(TvarFind,1,NCOVMAX);
14193: free_ivector(TvarV,1,NCOVMAX);
14194: free_ivector(TvarVind,1,NCOVMAX);
14195: free_ivector(TvarA,1,NCOVMAX);
14196: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 14197: free_ivector(TvarFQ,1,NCOVMAX);
14198: free_ivector(TvarFQind,1,NCOVMAX);
14199: free_ivector(TvarVD,1,NCOVMAX);
14200: free_ivector(TvarVDind,1,NCOVMAX);
14201: free_ivector(TvarVQ,1,NCOVMAX);
14202: free_ivector(TvarVQind,1,NCOVMAX);
1.230 brouard 14203: free_ivector(Tvarsel,1,NCOVMAX);
14204: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 14205: free_ivector(Tposprod,1,NCOVMAX);
14206: free_ivector(Tprod,1,NCOVMAX);
14207: free_ivector(Tvaraff,1,NCOVMAX);
1.338 ! brouard 14208: free_ivector(invalidvarcomb,0,ncovcombmax);
1.227 brouard 14209: free_ivector(Tage,1,NCOVMAX);
14210: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 14211: free_ivector(TmodelInvind,1,NCOVMAX);
14212: free_ivector(TmodelInvQind,1,NCOVMAX);
1.332 brouard 14213:
14214: free_matrix(precov, 1,MAXRESULTLINESPONE,1,NCOVMAX+1); /* Could be elsewhere ?*/
14215:
1.227 brouard 14216: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
14217: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 14218: fflush(fichtm);
14219: fflush(ficgp);
14220:
1.227 brouard 14221:
1.126 brouard 14222: if((nberr >0) || (nbwarn>0)){
1.216 brouard 14223: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
14224: 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 14225: }else{
14226: printf("End of Imach\n");
14227: fprintf(ficlog,"End of Imach\n");
14228: }
14229: printf("See log file on %s\n",filelog);
14230: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 14231: /*(void) gettimeofday(&end_time,&tzp);*/
14232: rend_time = time(NULL);
14233: end_time = *localtime(&rend_time);
14234: /* tml = *localtime(&end_time.tm_sec); */
14235: strcpy(strtend,asctime(&end_time));
1.126 brouard 14236: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
14237: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 14238: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 14239:
1.157 brouard 14240: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
14241: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
14242: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 14243: /* printf("Total time was %d uSec.\n", total_usecs);*/
14244: /* if(fileappend(fichtm,optionfilehtm)){ */
14245: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
14246: fclose(fichtm);
14247: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
14248: fclose(fichtmcov);
14249: fclose(ficgp);
14250: fclose(ficlog);
14251: /*------ End -----------*/
1.227 brouard 14252:
1.281 brouard 14253:
14254: /* Executes gnuplot */
1.227 brouard 14255:
14256: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 14257: #ifdef WIN32
1.227 brouard 14258: if (_chdir(pathcd) != 0)
14259: printf("Can't move to directory %s!\n",path);
14260: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 14261: #else
1.227 brouard 14262: if(chdir(pathcd) != 0)
14263: printf("Can't move to directory %s!\n", path);
14264: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 14265: #endif
1.126 brouard 14266: printf("Current directory %s!\n",pathcd);
14267: /*strcat(plotcmd,CHARSEPARATOR);*/
14268: sprintf(plotcmd,"gnuplot");
1.157 brouard 14269: #ifdef _WIN32
1.126 brouard 14270: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
14271: #endif
14272: if(!stat(plotcmd,&info)){
1.158 brouard 14273: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 14274: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 14275: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 14276: }else
14277: strcpy(pplotcmd,plotcmd);
1.157 brouard 14278: #ifdef __unix
1.126 brouard 14279: strcpy(plotcmd,GNUPLOTPROGRAM);
14280: if(!stat(plotcmd,&info)){
1.158 brouard 14281: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 14282: }else
14283: strcpy(pplotcmd,plotcmd);
14284: #endif
14285: }else
14286: strcpy(pplotcmd,plotcmd);
14287:
14288: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 14289: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.292 brouard 14290: strcpy(pplotcmd,plotcmd);
1.227 brouard 14291:
1.126 brouard 14292: if((outcmd=system(plotcmd)) != 0){
1.292 brouard 14293: printf("Error in gnuplot, command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 14294: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 14295: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.292 brouard 14296: if((outcmd=system(plotcmd)) != 0){
1.153 brouard 14297: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.292 brouard 14298: strcpy(plotcmd,pplotcmd);
14299: }
1.126 brouard 14300: }
1.158 brouard 14301: printf(" Successful, please wait...");
1.126 brouard 14302: while (z[0] != 'q') {
14303: /* chdir(path); */
1.154 brouard 14304: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 14305: scanf("%s",z);
14306: /* if (z[0] == 'c') system("./imach"); */
14307: if (z[0] == 'e') {
1.158 brouard 14308: #ifdef __APPLE__
1.152 brouard 14309: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 14310: #elif __linux
14311: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 14312: #else
1.152 brouard 14313: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 14314: #endif
14315: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
14316: system(pplotcmd);
1.126 brouard 14317: }
14318: else if (z[0] == 'g') system(plotcmd);
14319: else if (z[0] == 'q') exit(0);
14320: }
1.227 brouard 14321: end:
1.126 brouard 14322: while (z[0] != 'q') {
1.195 brouard 14323: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 14324: scanf("%s",z);
14325: }
1.283 brouard 14326: printf("End\n");
1.282 brouard 14327: exit(0);
1.126 brouard 14328: }
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