Annotation of imach/src/imach.c, revision 1.238
1.238 ! brouard 1: /* $Id: imach.c,v 1.237 2016/08/26 09:20:19 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.238 ! brouard 4: Revision 1.237 2016/08/26 09:20:19 brouard
! 5: Summary: to valgrind
! 6:
1.237 brouard 7: Revision 1.236 2016/08/25 10:50:18 brouard
8: *** empty log message ***
9:
1.236 brouard 10: Revision 1.235 2016/08/25 06:59:23 brouard
11: *** empty log message ***
12:
1.235 brouard 13: Revision 1.234 2016/08/23 16:51:20 brouard
14: *** empty log message ***
15:
1.234 brouard 16: Revision 1.233 2016/08/23 07:40:50 brouard
17: Summary: not working
18:
1.233 brouard 19: Revision 1.232 2016/08/22 14:20:21 brouard
20: Summary: not working
21:
1.232 brouard 22: Revision 1.231 2016/08/22 07:17:15 brouard
23: Summary: not working
24:
1.231 brouard 25: Revision 1.230 2016/08/22 06:55:53 brouard
26: Summary: Not working
27:
1.230 brouard 28: Revision 1.229 2016/07/23 09:45:53 brouard
29: Summary: Completing for func too
30:
1.229 brouard 31: Revision 1.228 2016/07/22 17:45:30 brouard
32: Summary: Fixing some arrays, still debugging
33:
1.227 brouard 34: Revision 1.226 2016/07/12 18:42:34 brouard
35: Summary: temp
36:
1.226 brouard 37: Revision 1.225 2016/07/12 08:40:03 brouard
38: Summary: saving but not running
39:
1.225 brouard 40: Revision 1.224 2016/07/01 13:16:01 brouard
41: Summary: Fixes
42:
1.224 brouard 43: Revision 1.223 2016/02/19 09:23:35 brouard
44: Summary: temporary
45:
1.223 brouard 46: Revision 1.222 2016/02/17 08:14:50 brouard
47: Summary: Probably last 0.98 stable version 0.98r6
48:
1.222 brouard 49: Revision 1.221 2016/02/15 23:35:36 brouard
50: Summary: minor bug
51:
1.220 brouard 52: Revision 1.219 2016/02/15 00:48:12 brouard
53: *** empty log message ***
54:
1.219 brouard 55: Revision 1.218 2016/02/12 11:29:23 brouard
56: Summary: 0.99 Back projections
57:
1.218 brouard 58: Revision 1.217 2015/12/23 17:18:31 brouard
59: Summary: Experimental backcast
60:
1.217 brouard 61: Revision 1.216 2015/12/18 17:32:11 brouard
62: Summary: 0.98r4 Warning and status=-2
63:
64: Version 0.98r4 is now:
65: - displaying an error when status is -1, date of interview unknown and date of death known;
66: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
67: Older changes concerning s=-2, dating from 2005 have been supersed.
68:
1.216 brouard 69: Revision 1.215 2015/12/16 08:52:24 brouard
70: Summary: 0.98r4 working
71:
1.215 brouard 72: Revision 1.214 2015/12/16 06:57:54 brouard
73: Summary: temporary not working
74:
1.214 brouard 75: Revision 1.213 2015/12/11 18:22:17 brouard
76: Summary: 0.98r4
77:
1.213 brouard 78: Revision 1.212 2015/11/21 12:47:24 brouard
79: Summary: minor typo
80:
1.212 brouard 81: Revision 1.211 2015/11/21 12:41:11 brouard
82: Summary: 0.98r3 with some graph of projected cross-sectional
83:
84: Author: Nicolas Brouard
85:
1.211 brouard 86: Revision 1.210 2015/11/18 17:41:20 brouard
87: Summary: Start working on projected prevalences
88:
1.210 brouard 89: Revision 1.209 2015/11/17 22:12:03 brouard
90: Summary: Adding ftolpl parameter
91: Author: N Brouard
92:
93: We had difficulties to get smoothed confidence intervals. It was due
94: to the period prevalence which wasn't computed accurately. The inner
95: parameter ftolpl is now an outer parameter of the .imach parameter
96: file after estepm. If ftolpl is small 1.e-4 and estepm too,
97: computation are long.
98:
1.209 brouard 99: Revision 1.208 2015/11/17 14:31:57 brouard
100: Summary: temporary
101:
1.208 brouard 102: Revision 1.207 2015/10/27 17:36:57 brouard
103: *** empty log message ***
104:
1.207 brouard 105: Revision 1.206 2015/10/24 07:14:11 brouard
106: *** empty log message ***
107:
1.206 brouard 108: Revision 1.205 2015/10/23 15:50:53 brouard
109: Summary: 0.98r3 some clarification for graphs on likelihood contributions
110:
1.205 brouard 111: Revision 1.204 2015/10/01 16:20:26 brouard
112: Summary: Some new graphs of contribution to likelihood
113:
1.204 brouard 114: Revision 1.203 2015/09/30 17:45:14 brouard
115: Summary: looking at better estimation of the hessian
116:
117: Also a better criteria for convergence to the period prevalence And
118: therefore adding the number of years needed to converge. (The
119: prevalence in any alive state shold sum to one
120:
1.203 brouard 121: Revision 1.202 2015/09/22 19:45:16 brouard
122: Summary: Adding some overall graph on contribution to likelihood. Might change
123:
1.202 brouard 124: Revision 1.201 2015/09/15 17:34:58 brouard
125: Summary: 0.98r0
126:
127: - Some new graphs like suvival functions
128: - Some bugs fixed like model=1+age+V2.
129:
1.201 brouard 130: Revision 1.200 2015/09/09 16:53:55 brouard
131: Summary: Big bug thanks to Flavia
132:
133: Even model=1+age+V2. did not work anymore
134:
1.200 brouard 135: Revision 1.199 2015/09/07 14:09:23 brouard
136: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
137:
1.199 brouard 138: Revision 1.198 2015/09/03 07:14:39 brouard
139: Summary: 0.98q5 Flavia
140:
1.198 brouard 141: Revision 1.197 2015/09/01 18:24:39 brouard
142: *** empty log message ***
143:
1.197 brouard 144: Revision 1.196 2015/08/18 23:17:52 brouard
145: Summary: 0.98q5
146:
1.196 brouard 147: Revision 1.195 2015/08/18 16:28:39 brouard
148: Summary: Adding a hack for testing purpose
149:
150: After reading the title, ftol and model lines, if the comment line has
151: a q, starting with #q, the answer at the end of the run is quit. It
152: permits to run test files in batch with ctest. The former workaround was
153: $ echo q | imach foo.imach
154:
1.195 brouard 155: Revision 1.194 2015/08/18 13:32:00 brouard
156: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
157:
1.194 brouard 158: Revision 1.193 2015/08/04 07:17:42 brouard
159: Summary: 0.98q4
160:
1.193 brouard 161: Revision 1.192 2015/07/16 16:49:02 brouard
162: Summary: Fixing some outputs
163:
1.192 brouard 164: Revision 1.191 2015/07/14 10:00:33 brouard
165: Summary: Some fixes
166:
1.191 brouard 167: Revision 1.190 2015/05/05 08:51:13 brouard
168: Summary: Adding digits in output parameters (7 digits instead of 6)
169:
170: Fix 1+age+.
171:
1.190 brouard 172: Revision 1.189 2015/04/30 14:45:16 brouard
173: Summary: 0.98q2
174:
1.189 brouard 175: Revision 1.188 2015/04/30 08:27:53 brouard
176: *** empty log message ***
177:
1.188 brouard 178: Revision 1.187 2015/04/29 09:11:15 brouard
179: *** empty log message ***
180:
1.187 brouard 181: Revision 1.186 2015/04/23 12:01:52 brouard
182: Summary: V1*age is working now, version 0.98q1
183:
184: Some codes had been disabled in order to simplify and Vn*age was
185: working in the optimization phase, ie, giving correct MLE parameters,
186: but, as usual, outputs were not correct and program core dumped.
187:
1.186 brouard 188: Revision 1.185 2015/03/11 13:26:42 brouard
189: Summary: Inclusion of compile and links command line for Intel Compiler
190:
1.185 brouard 191: Revision 1.184 2015/03/11 11:52:39 brouard
192: Summary: Back from Windows 8. Intel Compiler
193:
1.184 brouard 194: Revision 1.183 2015/03/10 20:34:32 brouard
195: Summary: 0.98q0, trying with directest, mnbrak fixed
196:
197: We use directest instead of original Powell test; probably no
198: incidence on the results, but better justifications;
199: We fixed Numerical Recipes mnbrak routine which was wrong and gave
200: wrong results.
201:
1.183 brouard 202: Revision 1.182 2015/02/12 08:19:57 brouard
203: Summary: Trying to keep directest which seems simpler and more general
204: Author: Nicolas Brouard
205:
1.182 brouard 206: Revision 1.181 2015/02/11 23:22:24 brouard
207: Summary: Comments on Powell added
208:
209: Author:
210:
1.181 brouard 211: Revision 1.180 2015/02/11 17:33:45 brouard
212: Summary: Finishing move from main to function (hpijx and prevalence_limit)
213:
1.180 brouard 214: Revision 1.179 2015/01/04 09:57:06 brouard
215: Summary: back to OS/X
216:
1.179 brouard 217: Revision 1.178 2015/01/04 09:35:48 brouard
218: *** empty log message ***
219:
1.178 brouard 220: Revision 1.177 2015/01/03 18:40:56 brouard
221: Summary: Still testing ilc32 on OSX
222:
1.177 brouard 223: Revision 1.176 2015/01/03 16:45:04 brouard
224: *** empty log message ***
225:
1.176 brouard 226: Revision 1.175 2015/01/03 16:33:42 brouard
227: *** empty log message ***
228:
1.175 brouard 229: Revision 1.174 2015/01/03 16:15:49 brouard
230: Summary: Still in cross-compilation
231:
1.174 brouard 232: Revision 1.173 2015/01/03 12:06:26 brouard
233: Summary: trying to detect cross-compilation
234:
1.173 brouard 235: Revision 1.172 2014/12/27 12:07:47 brouard
236: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
237:
1.172 brouard 238: Revision 1.171 2014/12/23 13:26:59 brouard
239: Summary: Back from Visual C
240:
241: Still problem with utsname.h on Windows
242:
1.171 brouard 243: Revision 1.170 2014/12/23 11:17:12 brouard
244: Summary: Cleaning some \%% back to %%
245:
246: The escape was mandatory for a specific compiler (which one?), but too many warnings.
247:
1.170 brouard 248: Revision 1.169 2014/12/22 23:08:31 brouard
249: Summary: 0.98p
250:
251: Outputs some informations on compiler used, OS etc. Testing on different platforms.
252:
1.169 brouard 253: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 254: Summary: update
1.169 brouard 255:
1.168 brouard 256: Revision 1.167 2014/12/22 13:50:56 brouard
257: Summary: Testing uname and compiler version and if compiled 32 or 64
258:
259: Testing on Linux 64
260:
1.167 brouard 261: Revision 1.166 2014/12/22 11:40:47 brouard
262: *** empty log message ***
263:
1.166 brouard 264: Revision 1.165 2014/12/16 11:20:36 brouard
265: Summary: After compiling on Visual C
266:
267: * imach.c (Module): Merging 1.61 to 1.162
268:
1.165 brouard 269: Revision 1.164 2014/12/16 10:52:11 brouard
270: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
271:
272: * imach.c (Module): Merging 1.61 to 1.162
273:
1.164 brouard 274: Revision 1.163 2014/12/16 10:30:11 brouard
275: * imach.c (Module): Merging 1.61 to 1.162
276:
1.163 brouard 277: Revision 1.162 2014/09/25 11:43:39 brouard
278: Summary: temporary backup 0.99!
279:
1.162 brouard 280: Revision 1.1 2014/09/16 11:06:58 brouard
281: Summary: With some code (wrong) for nlopt
282:
283: Author:
284:
285: Revision 1.161 2014/09/15 20:41:41 brouard
286: Summary: Problem with macro SQR on Intel compiler
287:
1.161 brouard 288: Revision 1.160 2014/09/02 09:24:05 brouard
289: *** empty log message ***
290:
1.160 brouard 291: Revision 1.159 2014/09/01 10:34:10 brouard
292: Summary: WIN32
293: Author: Brouard
294:
1.159 brouard 295: Revision 1.158 2014/08/27 17:11:51 brouard
296: *** empty log message ***
297:
1.158 brouard 298: Revision 1.157 2014/08/27 16:26:55 brouard
299: Summary: Preparing windows Visual studio version
300: Author: Brouard
301:
302: In order to compile on Visual studio, time.h is now correct and time_t
303: and tm struct should be used. difftime should be used but sometimes I
304: just make the differences in raw time format (time(&now).
305: Trying to suppress #ifdef LINUX
306: Add xdg-open for __linux in order to open default browser.
307:
1.157 brouard 308: Revision 1.156 2014/08/25 20:10:10 brouard
309: *** empty log message ***
310:
1.156 brouard 311: Revision 1.155 2014/08/25 18:32:34 brouard
312: Summary: New compile, minor changes
313: Author: Brouard
314:
1.155 brouard 315: Revision 1.154 2014/06/20 17:32:08 brouard
316: Summary: Outputs now all graphs of convergence to period prevalence
317:
1.154 brouard 318: Revision 1.153 2014/06/20 16:45:46 brouard
319: Summary: If 3 live state, convergence to period prevalence on same graph
320: Author: Brouard
321:
1.153 brouard 322: Revision 1.152 2014/06/18 17:54:09 brouard
323: Summary: open browser, use gnuplot on same dir than imach if not found in the path
324:
1.152 brouard 325: Revision 1.151 2014/06/18 16:43:30 brouard
326: *** empty log message ***
327:
1.151 brouard 328: Revision 1.150 2014/06/18 16:42:35 brouard
329: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
330: Author: brouard
331:
1.150 brouard 332: Revision 1.149 2014/06/18 15:51:14 brouard
333: Summary: Some fixes in parameter files errors
334: Author: Nicolas Brouard
335:
1.149 brouard 336: Revision 1.148 2014/06/17 17:38:48 brouard
337: Summary: Nothing new
338: Author: Brouard
339:
340: Just a new packaging for OS/X version 0.98nS
341:
1.148 brouard 342: Revision 1.147 2014/06/16 10:33:11 brouard
343: *** empty log message ***
344:
1.147 brouard 345: Revision 1.146 2014/06/16 10:20:28 brouard
346: Summary: Merge
347: Author: Brouard
348:
349: Merge, before building revised version.
350:
1.146 brouard 351: Revision 1.145 2014/06/10 21:23:15 brouard
352: Summary: Debugging with valgrind
353: Author: Nicolas Brouard
354:
355: Lot of changes in order to output the results with some covariates
356: After the Edimburgh REVES conference 2014, it seems mandatory to
357: improve the code.
358: No more memory valgrind error but a lot has to be done in order to
359: continue the work of splitting the code into subroutines.
360: Also, decodemodel has been improved. Tricode is still not
361: optimal. nbcode should be improved. Documentation has been added in
362: the source code.
363:
1.144 brouard 364: Revision 1.143 2014/01/26 09:45:38 brouard
365: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
366:
367: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
368: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
369:
1.143 brouard 370: Revision 1.142 2014/01/26 03:57:36 brouard
371: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
372:
373: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
374:
1.142 brouard 375: Revision 1.141 2014/01/26 02:42:01 brouard
376: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
377:
1.141 brouard 378: Revision 1.140 2011/09/02 10:37:54 brouard
379: Summary: times.h is ok with mingw32 now.
380:
1.140 brouard 381: Revision 1.139 2010/06/14 07:50:17 brouard
382: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
383: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
384:
1.139 brouard 385: Revision 1.138 2010/04/30 18:19:40 brouard
386: *** empty log message ***
387:
1.138 brouard 388: Revision 1.137 2010/04/29 18:11:38 brouard
389: (Module): Checking covariates for more complex models
390: than V1+V2. A lot of change to be done. Unstable.
391:
1.137 brouard 392: Revision 1.136 2010/04/26 20:30:53 brouard
393: (Module): merging some libgsl code. Fixing computation
394: of likelione (using inter/intrapolation if mle = 0) in order to
395: get same likelihood as if mle=1.
396: Some cleaning of code and comments added.
397:
1.136 brouard 398: Revision 1.135 2009/10/29 15:33:14 brouard
399: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
400:
1.135 brouard 401: Revision 1.134 2009/10/29 13:18:53 brouard
402: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
403:
1.134 brouard 404: Revision 1.133 2009/07/06 10:21:25 brouard
405: just nforces
406:
1.133 brouard 407: Revision 1.132 2009/07/06 08:22:05 brouard
408: Many tings
409:
1.132 brouard 410: Revision 1.131 2009/06/20 16:22:47 brouard
411: Some dimensions resccaled
412:
1.131 brouard 413: Revision 1.130 2009/05/26 06:44:34 brouard
414: (Module): Max Covariate is now set to 20 instead of 8. A
415: lot of cleaning with variables initialized to 0. Trying to make
416: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
417:
1.130 brouard 418: Revision 1.129 2007/08/31 13:49:27 lievre
419: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
420:
1.129 lievre 421: Revision 1.128 2006/06/30 13:02:05 brouard
422: (Module): Clarifications on computing e.j
423:
1.128 brouard 424: Revision 1.127 2006/04/28 18:11:50 brouard
425: (Module): Yes the sum of survivors was wrong since
426: imach-114 because nhstepm was no more computed in the age
427: loop. Now we define nhstepma in the age loop.
428: (Module): In order to speed up (in case of numerous covariates) we
429: compute health expectancies (without variances) in a first step
430: and then all the health expectancies with variances or standard
431: deviation (needs data from the Hessian matrices) which slows the
432: computation.
433: In the future we should be able to stop the program is only health
434: expectancies and graph are needed without standard deviations.
435:
1.127 brouard 436: Revision 1.126 2006/04/28 17:23:28 brouard
437: (Module): Yes the sum of survivors was wrong since
438: imach-114 because nhstepm was no more computed in the age
439: loop. Now we define nhstepma in the age loop.
440: Version 0.98h
441:
1.126 brouard 442: Revision 1.125 2006/04/04 15:20:31 lievre
443: Errors in calculation of health expectancies. Age was not initialized.
444: Forecasting file added.
445:
446: Revision 1.124 2006/03/22 17:13:53 lievre
447: Parameters are printed with %lf instead of %f (more numbers after the comma).
448: The log-likelihood is printed in the log file
449:
450: Revision 1.123 2006/03/20 10:52:43 brouard
451: * imach.c (Module): <title> changed, corresponds to .htm file
452: name. <head> headers where missing.
453:
454: * imach.c (Module): Weights can have a decimal point as for
455: English (a comma might work with a correct LC_NUMERIC environment,
456: otherwise the weight is truncated).
457: Modification of warning when the covariates values are not 0 or
458: 1.
459: Version 0.98g
460:
461: Revision 1.122 2006/03/20 09:45:41 brouard
462: (Module): Weights can have a decimal point as for
463: English (a comma might work with a correct LC_NUMERIC environment,
464: otherwise the weight is truncated).
465: Modification of warning when the covariates values are not 0 or
466: 1.
467: Version 0.98g
468:
469: Revision 1.121 2006/03/16 17:45:01 lievre
470: * imach.c (Module): Comments concerning covariates added
471:
472: * imach.c (Module): refinements in the computation of lli if
473: status=-2 in order to have more reliable computation if stepm is
474: not 1 month. Version 0.98f
475:
476: Revision 1.120 2006/03/16 15:10:38 lievre
477: (Module): refinements in the computation of lli if
478: status=-2 in order to have more reliable computation if stepm is
479: not 1 month. Version 0.98f
480:
481: Revision 1.119 2006/03/15 17:42:26 brouard
482: (Module): Bug if status = -2, the loglikelihood was
483: computed as likelihood omitting the logarithm. Version O.98e
484:
485: Revision 1.118 2006/03/14 18:20:07 brouard
486: (Module): varevsij Comments added explaining the second
487: table of variances if popbased=1 .
488: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
489: (Module): Function pstamp added
490: (Module): Version 0.98d
491:
492: Revision 1.117 2006/03/14 17:16:22 brouard
493: (Module): varevsij Comments added explaining the second
494: table of variances if popbased=1 .
495: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
496: (Module): Function pstamp added
497: (Module): Version 0.98d
498:
499: Revision 1.116 2006/03/06 10:29:27 brouard
500: (Module): Variance-covariance wrong links and
501: varian-covariance of ej. is needed (Saito).
502:
503: Revision 1.115 2006/02/27 12:17:45 brouard
504: (Module): One freematrix added in mlikeli! 0.98c
505:
506: Revision 1.114 2006/02/26 12:57:58 brouard
507: (Module): Some improvements in processing parameter
508: filename with strsep.
509:
510: Revision 1.113 2006/02/24 14:20:24 brouard
511: (Module): Memory leaks checks with valgrind and:
512: datafile was not closed, some imatrix were not freed and on matrix
513: allocation too.
514:
515: Revision 1.112 2006/01/30 09:55:26 brouard
516: (Module): Back to gnuplot.exe instead of wgnuplot.exe
517:
518: Revision 1.111 2006/01/25 20:38:18 brouard
519: (Module): Lots of cleaning and bugs added (Gompertz)
520: (Module): Comments can be added in data file. Missing date values
521: can be a simple dot '.'.
522:
523: Revision 1.110 2006/01/25 00:51:50 brouard
524: (Module): Lots of cleaning and bugs added (Gompertz)
525:
526: Revision 1.109 2006/01/24 19:37:15 brouard
527: (Module): Comments (lines starting with a #) are allowed in data.
528:
529: Revision 1.108 2006/01/19 18:05:42 lievre
530: Gnuplot problem appeared...
531: To be fixed
532:
533: Revision 1.107 2006/01/19 16:20:37 brouard
534: Test existence of gnuplot in imach path
535:
536: Revision 1.106 2006/01/19 13:24:36 brouard
537: Some cleaning and links added in html output
538:
539: Revision 1.105 2006/01/05 20:23:19 lievre
540: *** empty log message ***
541:
542: Revision 1.104 2005/09/30 16:11:43 lievre
543: (Module): sump fixed, loop imx fixed, and simplifications.
544: (Module): If the status is missing at the last wave but we know
545: that the person is alive, then we can code his/her status as -2
546: (instead of missing=-1 in earlier versions) and his/her
547: contributions to the likelihood is 1 - Prob of dying from last
548: health status (= 1-p13= p11+p12 in the easiest case of somebody in
549: the healthy state at last known wave). Version is 0.98
550:
551: Revision 1.103 2005/09/30 15:54:49 lievre
552: (Module): sump fixed, loop imx fixed, and simplifications.
553:
554: Revision 1.102 2004/09/15 17:31:30 brouard
555: Add the possibility to read data file including tab characters.
556:
557: Revision 1.101 2004/09/15 10:38:38 brouard
558: Fix on curr_time
559:
560: Revision 1.100 2004/07/12 18:29:06 brouard
561: Add version for Mac OS X. Just define UNIX in Makefile
562:
563: Revision 1.99 2004/06/05 08:57:40 brouard
564: *** empty log message ***
565:
566: Revision 1.98 2004/05/16 15:05:56 brouard
567: New version 0.97 . First attempt to estimate force of mortality
568: directly from the data i.e. without the need of knowing the health
569: state at each age, but using a Gompertz model: log u =a + b*age .
570: This is the basic analysis of mortality and should be done before any
571: other analysis, in order to test if the mortality estimated from the
572: cross-longitudinal survey is different from the mortality estimated
573: from other sources like vital statistic data.
574:
575: The same imach parameter file can be used but the option for mle should be -3.
576:
1.133 brouard 577: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 578: former routines in order to include the new code within the former code.
579:
580: The output is very simple: only an estimate of the intercept and of
581: the slope with 95% confident intervals.
582:
583: Current limitations:
584: A) Even if you enter covariates, i.e. with the
585: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
586: B) There is no computation of Life Expectancy nor Life Table.
587:
588: Revision 1.97 2004/02/20 13:25:42 lievre
589: Version 0.96d. Population forecasting command line is (temporarily)
590: suppressed.
591:
592: Revision 1.96 2003/07/15 15:38:55 brouard
593: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
594: rewritten within the same printf. Workaround: many printfs.
595:
596: Revision 1.95 2003/07/08 07:54:34 brouard
597: * imach.c (Repository):
598: (Repository): Using imachwizard code to output a more meaningful covariance
599: matrix (cov(a12,c31) instead of numbers.
600:
601: Revision 1.94 2003/06/27 13:00:02 brouard
602: Just cleaning
603:
604: Revision 1.93 2003/06/25 16:33:55 brouard
605: (Module): On windows (cygwin) function asctime_r doesn't
606: exist so I changed back to asctime which exists.
607: (Module): Version 0.96b
608:
609: Revision 1.92 2003/06/25 16:30:45 brouard
610: (Module): On windows (cygwin) function asctime_r doesn't
611: exist so I changed back to asctime which exists.
612:
613: Revision 1.91 2003/06/25 15:30:29 brouard
614: * imach.c (Repository): Duplicated warning errors corrected.
615: (Repository): Elapsed time after each iteration is now output. It
616: helps to forecast when convergence will be reached. Elapsed time
617: is stamped in powell. We created a new html file for the graphs
618: concerning matrix of covariance. It has extension -cov.htm.
619:
620: Revision 1.90 2003/06/24 12:34:15 brouard
621: (Module): Some bugs corrected for windows. Also, when
622: mle=-1 a template is output in file "or"mypar.txt with the design
623: of the covariance matrix to be input.
624:
625: Revision 1.89 2003/06/24 12:30:52 brouard
626: (Module): Some bugs corrected for windows. Also, when
627: mle=-1 a template is output in file "or"mypar.txt with the design
628: of the covariance matrix to be input.
629:
630: Revision 1.88 2003/06/23 17:54:56 brouard
631: * 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.
632:
633: Revision 1.87 2003/06/18 12:26:01 brouard
634: Version 0.96
635:
636: Revision 1.86 2003/06/17 20:04:08 brouard
637: (Module): Change position of html and gnuplot routines and added
638: routine fileappend.
639:
640: Revision 1.85 2003/06/17 13:12:43 brouard
641: * imach.c (Repository): Check when date of death was earlier that
642: current date of interview. It may happen when the death was just
643: prior to the death. In this case, dh was negative and likelihood
644: was wrong (infinity). We still send an "Error" but patch by
645: assuming that the date of death was just one stepm after the
646: interview.
647: (Repository): Because some people have very long ID (first column)
648: we changed int to long in num[] and we added a new lvector for
649: memory allocation. But we also truncated to 8 characters (left
650: truncation)
651: (Repository): No more line truncation errors.
652:
653: Revision 1.84 2003/06/13 21:44:43 brouard
654: * imach.c (Repository): Replace "freqsummary" at a correct
655: place. It differs from routine "prevalence" which may be called
656: many times. Probs is memory consuming and must be used with
657: parcimony.
658: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
659:
660: Revision 1.83 2003/06/10 13:39:11 lievre
661: *** empty log message ***
662:
663: Revision 1.82 2003/06/05 15:57:20 brouard
664: Add log in imach.c and fullversion number is now printed.
665:
666: */
667: /*
668: Interpolated Markov Chain
669:
670: Short summary of the programme:
671:
1.227 brouard 672: This program computes Healthy Life Expectancies or State-specific
673: (if states aren't health statuses) Expectancies from
674: cross-longitudinal data. Cross-longitudinal data consist in:
675:
676: -1- a first survey ("cross") where individuals from different ages
677: are interviewed on their health status or degree of disability (in
678: the case of a health survey which is our main interest)
679:
680: -2- at least a second wave of interviews ("longitudinal") which
681: measure each change (if any) in individual health status. Health
682: expectancies are computed from the time spent in each health state
683: according to a model. More health states you consider, more time is
684: necessary to reach the Maximum Likelihood of the parameters involved
685: in the model. The simplest model is the multinomial logistic model
686: where pij is the probability to be observed in state j at the second
687: wave conditional to be observed in state i at the first
688: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
689: etc , where 'age' is age and 'sex' is a covariate. If you want to
690: have a more complex model than "constant and age", you should modify
691: the program where the markup *Covariates have to be included here
692: again* invites you to do it. More covariates you add, slower the
1.126 brouard 693: convergence.
694:
695: The advantage of this computer programme, compared to a simple
696: multinomial logistic model, is clear when the delay between waves is not
697: identical for each individual. Also, if a individual missed an
698: intermediate interview, the information is lost, but taken into
699: account using an interpolation or extrapolation.
700:
701: hPijx is the probability to be observed in state i at age x+h
702: conditional to the observed state i at age x. The delay 'h' can be
703: split into an exact number (nh*stepm) of unobserved intermediate
704: states. This elementary transition (by month, quarter,
705: semester or year) is modelled as a multinomial logistic. The hPx
706: matrix is simply the matrix product of nh*stepm elementary matrices
707: and the contribution of each individual to the likelihood is simply
708: hPijx.
709:
710: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 711: of the life expectancies. It also computes the period (stable) prevalence.
712:
713: Back prevalence and projections:
1.227 brouard 714:
715: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
716: double agemaxpar, double ftolpl, int *ncvyearp, double
717: dateprev1,double dateprev2, int firstpass, int lastpass, int
718: mobilavproj)
719:
720: Computes the back prevalence limit for any combination of
721: covariate values k at any age between ageminpar and agemaxpar and
722: returns it in **bprlim. In the loops,
723:
724: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
725: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
726:
727: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 728: Computes for any combination of covariates k and any age between bage and fage
729: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
730: oldm=oldms;savm=savms;
1.227 brouard 731:
732: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k);
1.218 brouard 733: Computes the transition matrix starting at age 'age' over
734: 'nhstepm*hstepm*stepm' months (i.e. until
735: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 736: nhstepm*hstepm matrices.
737:
738: Returns p3mat[i][j][h] after calling
739: p3mat[i][j][h]=matprod2(newm,
740: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
741: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
742: oldm);
1.226 brouard 743:
744: Important routines
745:
746: - func (or funcone), computes logit (pij) distinguishing
747: o fixed variables (single or product dummies or quantitative);
748: o varying variables by:
749: (1) wave (single, product dummies, quantitative),
750: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
751: % fixed dummy (treated) or quantitative (not done because time-consuming);
752: % varying dummy (not done) or quantitative (not done);
753: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
754: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
755: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
756: o There are 2*cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
757: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 758:
1.226 brouard 759:
760:
1.133 brouard 761: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
762: Institut national d'études démographiques, Paris.
1.126 brouard 763: This software have been partly granted by Euro-REVES, a concerted action
764: from the European Union.
765: It is copyrighted identically to a GNU software product, ie programme and
766: software can be distributed freely for non commercial use. Latest version
767: can be accessed at http://euroreves.ined.fr/imach .
768:
769: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
770: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
771:
772: **********************************************************************/
773: /*
774: main
775: read parameterfile
776: read datafile
777: concatwav
778: freqsummary
779: if (mle >= 1)
780: mlikeli
781: print results files
782: if mle==1
783: computes hessian
784: read end of parameter file: agemin, agemax, bage, fage, estepm
785: begin-prev-date,...
786: open gnuplot file
787: open html file
1.145 brouard 788: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
789: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
790: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
791: freexexit2 possible for memory heap.
792:
793: h Pij x | pij_nom ficrestpij
794: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
795: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
796: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
797:
798: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
799: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
800: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
801: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
802: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
803:
1.126 brouard 804: forecasting if prevfcast==1 prevforecast call prevalence()
805: health expectancies
806: Variance-covariance of DFLE
807: prevalence()
808: movingaverage()
809: varevsij()
810: if popbased==1 varevsij(,popbased)
811: total life expectancies
812: Variance of period (stable) prevalence
813: end
814: */
815:
1.187 brouard 816: /* #define DEBUG */
817: /* #define DEBUGBRENT */
1.203 brouard 818: /* #define DEBUGLINMIN */
819: /* #define DEBUGHESS */
820: #define DEBUGHESSIJ
1.224 brouard 821: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 822: #define POWELL /* Instead of NLOPT */
1.224 brouard 823: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 824: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
825: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.126 brouard 826:
827: #include <math.h>
828: #include <stdio.h>
829: #include <stdlib.h>
830: #include <string.h>
1.226 brouard 831: #include <ctype.h>
1.159 brouard 832:
833: #ifdef _WIN32
834: #include <io.h>
1.172 brouard 835: #include <windows.h>
836: #include <tchar.h>
1.159 brouard 837: #else
1.126 brouard 838: #include <unistd.h>
1.159 brouard 839: #endif
1.126 brouard 840:
841: #include <limits.h>
842: #include <sys/types.h>
1.171 brouard 843:
844: #if defined(__GNUC__)
845: #include <sys/utsname.h> /* Doesn't work on Windows */
846: #endif
847:
1.126 brouard 848: #include <sys/stat.h>
849: #include <errno.h>
1.159 brouard 850: /* extern int errno; */
1.126 brouard 851:
1.157 brouard 852: /* #ifdef LINUX */
853: /* #include <time.h> */
854: /* #include "timeval.h" */
855: /* #else */
856: /* #include <sys/time.h> */
857: /* #endif */
858:
1.126 brouard 859: #include <time.h>
860:
1.136 brouard 861: #ifdef GSL
862: #include <gsl/gsl_errno.h>
863: #include <gsl/gsl_multimin.h>
864: #endif
865:
1.167 brouard 866:
1.162 brouard 867: #ifdef NLOPT
868: #include <nlopt.h>
869: typedef struct {
870: double (* function)(double [] );
871: } myfunc_data ;
872: #endif
873:
1.126 brouard 874: /* #include <libintl.h> */
875: /* #define _(String) gettext (String) */
876:
1.141 brouard 877: #define MAXLINE 1024 /* Was 256. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 878:
879: #define GNUPLOTPROGRAM "gnuplot"
880: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
881: #define FILENAMELENGTH 132
882:
883: #define GLOCK_ERROR_NOPATH -1 /* empty path */
884: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
885:
1.144 brouard 886: #define MAXPARM 128 /**< Maximum number of parameters for the optimization */
887: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 888:
889: #define NINTERVMAX 8
1.144 brouard 890: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
891: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
892: #define NCOVMAX 20 /**< Maximum number of covariates, including generated covariates V1*V2 */
1.197 brouard 893: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 894: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
895: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.126 brouard 896: #define MAXN 20000
1.144 brouard 897: #define YEARM 12. /**< Number of months per year */
1.218 brouard 898: /* #define AGESUP 130 */
899: #define AGESUP 150
900: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 901: #define AGEBASE 40
1.194 brouard 902: #define AGEOVERFLOW 1.e20
1.164 brouard 903: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 904: #ifdef _WIN32
905: #define DIRSEPARATOR '\\'
906: #define CHARSEPARATOR "\\"
907: #define ODIRSEPARATOR '/'
908: #else
1.126 brouard 909: #define DIRSEPARATOR '/'
910: #define CHARSEPARATOR "/"
911: #define ODIRSEPARATOR '\\'
912: #endif
913:
1.238 ! brouard 914: /* $Id: imach.c,v 1.237 2016/08/26 09:20:19 brouard Exp $ */
1.126 brouard 915: /* $State: Exp $ */
1.196 brouard 916: #include "version.h"
917: char version[]=__IMACH_VERSION__;
1.224 brouard 918: char copyright[]="February 2016,INED-EUROREVES-Institut de longevite-Japan Society for the Promotion of Science (Grant-in-Aid for Scientific Research 25293121), Intel Software 2015-2018";
1.238 ! brouard 919: char fullversion[]="$Revision: 1.237 $ $Date: 2016/08/26 09:20:19 $";
1.126 brouard 920: char strstart[80];
921: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 922: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.187 brouard 923: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.145 brouard 924: /* Number of covariates model=V2+V1+ V3*age+V2*V4 */
925: int cptcovn=0; /**< cptcovn number of covariates added in the model (excepting constant and age and age*product) */
926: int cptcovt=0; /**< cptcovt number of covariates added in the model (excepting constant and age) */
1.225 brouard 927: int cptcovs=0; /**< cptcovs number of simple covariates in the model V2+V1 =2 */
928: int cptcovsnq=0; /**< cptcovsnq number of simple covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 929: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
930: int cptcovprodnoage=0; /**< Number of covariate products without age */
931: int cptcoveff=0; /* Total number of covariates to vary for printing results */
1.233 brouard 932: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
933: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.232 brouard 934: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (dummy of quantitative) in the model */
1.234 brouard 935: int nsd=0; /**< Total number of single dummy variables (output) */
936: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 937: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 938: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 939: int ntveff=0; /**< ntveff number of effective time varying variables */
940: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 941: int cptcov=0; /* Working variable */
1.218 brouard 942: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.126 brouard 943: int npar=NPARMAX;
944: int nlstate=2; /* Number of live states */
945: int ndeath=1; /* Number of dead states */
1.130 brouard 946: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.223 brouard 947: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable */
1.126 brouard 948: int popbased=0;
949:
950: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 951: int maxwav=0; /* Maxim number of waves */
952: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
953: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
954: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 955: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 956: int mle=1, weightopt=0;
1.126 brouard 957: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
958: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
959: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
960: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 961: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 962: int selected(int kvar); /* Is covariate kvar selected for printing results */
963:
1.130 brouard 964: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 965: double **matprod2(); /* test */
1.126 brouard 966: double **oldm, **newm, **savm; /* Working pointers to matrices */
967: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 968: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
969:
1.136 brouard 970: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 971: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 972: FILE *ficlog, *ficrespow;
1.130 brouard 973: int globpr=0; /* Global variable for printing or not */
1.126 brouard 974: double fretone; /* Only one call to likelihood */
1.130 brouard 975: long ipmx=0; /* Number of contributions */
1.126 brouard 976: double sw; /* Sum of weights */
977: char filerespow[FILENAMELENGTH];
978: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
979: FILE *ficresilk;
980: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
981: FILE *ficresprobmorprev;
982: FILE *fichtm, *fichtmcov; /* Html File */
983: FILE *ficreseij;
984: char filerese[FILENAMELENGTH];
985: FILE *ficresstdeij;
986: char fileresstde[FILENAMELENGTH];
987: FILE *ficrescveij;
988: char filerescve[FILENAMELENGTH];
989: FILE *ficresvij;
990: char fileresv[FILENAMELENGTH];
991: FILE *ficresvpl;
992: char fileresvpl[FILENAMELENGTH];
993: char title[MAXLINE];
1.234 brouard 994: char model[MAXLINE]; /**< The model line */
1.217 brouard 995: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 996: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
997: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
998: char command[FILENAMELENGTH];
999: int outcmd=0;
1000:
1.217 brouard 1001: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1002: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1003: char filelog[FILENAMELENGTH]; /* Log file */
1004: char filerest[FILENAMELENGTH];
1005: char fileregp[FILENAMELENGTH];
1006: char popfile[FILENAMELENGTH];
1007:
1008: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1009:
1.157 brouard 1010: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1011: /* struct timezone tzp; */
1012: /* extern int gettimeofday(); */
1013: struct tm tml, *gmtime(), *localtime();
1014:
1015: extern time_t time();
1016:
1017: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1018: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1019: struct tm tm;
1020:
1.126 brouard 1021: char strcurr[80], strfor[80];
1022:
1023: char *endptr;
1024: long lval;
1025: double dval;
1026:
1027: #define NR_END 1
1028: #define FREE_ARG char*
1029: #define FTOL 1.0e-10
1030:
1031: #define NRANSI
1032: #define ITMAX 200
1033:
1034: #define TOL 2.0e-4
1035:
1036: #define CGOLD 0.3819660
1037: #define ZEPS 1.0e-10
1038: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1039:
1040: #define GOLD 1.618034
1041: #define GLIMIT 100.0
1042: #define TINY 1.0e-20
1043:
1044: static double maxarg1,maxarg2;
1045: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1046: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1047:
1048: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1049: #define rint(a) floor(a+0.5)
1.166 brouard 1050: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1051: #define mytinydouble 1.0e-16
1.166 brouard 1052: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1053: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1054: /* static double dsqrarg; */
1055: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1056: static double sqrarg;
1057: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1058: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1059: int agegomp= AGEGOMP;
1060:
1061: int imx;
1062: int stepm=1;
1063: /* Stepm, step in month: minimum step interpolation*/
1064:
1065: int estepm;
1066: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1067:
1068: int m,nb;
1069: long *num;
1.197 brouard 1070: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1071: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1072: covariate for which somebody answered excluding
1073: undefined. Usually 2: 0 and 1. */
1074: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1075: covariate for which somebody answered including
1076: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1077: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1078: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1079: double ***mobaverage, ***mobaverages; /* New global variable */
1.126 brouard 1080: double *ageexmed,*agecens;
1081: double dateintmean=0;
1082:
1083: double *weight;
1084: int **s; /* Status */
1.141 brouard 1085: double *agedc;
1.145 brouard 1086: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1087: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1088: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.225 brouard 1089: double **coqvar; /* Fixed quantitative covariate iqv */
1090: double ***cotvar; /* Time varying covariate itv */
1091: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1092: double idx;
1093: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.234 brouard 1094: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1095: /*k 1 2 3 4 5 6 7 8 9 */
1096: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 */
1097: /* Tndvar[k] 1 2 3 4 5 */
1098: /*TDvar 4 3 6 7 1 */ /* For outputs only; combination of dummies fixed or varying */
1099: /* Tns[k] 1 2 2 4 5 */ /* Number of single cova */
1100: /* TvarsD[k] 1 2 3 */ /* Number of single dummy cova */
1101: /* TvarsDind 2 3 9 */ /* position K of single dummy cova */
1102: /* TvarsQ[k] 1 2 */ /* Number of single quantitative cova */
1103: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1104: /* Tprod[i]=k 4 7 */
1105: /* Tage[i]=k 5 8 */
1106: /* */
1107: /* Type */
1108: /* V 1 2 3 4 5 */
1109: /* F F V V V */
1110: /* D Q D D Q */
1111: /* */
1112: int *TvarsD;
1113: int *TvarsDind;
1114: int *TvarsQ;
1115: int *TvarsQind;
1116:
1.235 brouard 1117: #define MAXRESULTLINES 10
1118: int nresult=0;
1119: int TKresult[MAXRESULTLINES];
1.237 brouard 1120: int Tresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */
1121: int Tinvresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */
1.235 brouard 1122: int Tvresult[MAXRESULTLINES][NCOVMAX]; /* For dummy variable , variable # (output) */
1123: double Tqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */
1.237 brouard 1124: double Tqinvresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */
1.235 brouard 1125: int Tvqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , variable # (output) */
1126:
1.234 brouard 1127: /* 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 1128: 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 */
1129: 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 */
1130: 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 */
1131: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1132: 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 */
1133: 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 1134: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1135: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1136: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1137: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1138: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1139: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1140: 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 */
1141: 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 */
1142:
1.230 brouard 1143: int *Tvarsel; /**< Selected covariates for output */
1144: double *Tvalsel; /**< Selected modality value of covariate for output */
1.226 brouard 1145: int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.227 brouard 1146: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1147: 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 1148: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
! 1149: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1150: int *Tage;
1.227 brouard 1151: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1152: 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 1153: 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*/
1154: 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 1155: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1156: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1157: int **Tvard;
1158: int *Tprod;/**< Gives the k position of the k1 product */
1.238 ! brouard 1159: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1160: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 ! brouard 1161: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
! 1162: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1163: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1164: double *lsurv, *lpop, *tpop;
1165:
1.231 brouard 1166: #define FD 1; /* Fixed dummy covariate */
1167: #define FQ 2; /* Fixed quantitative covariate */
1168: #define FP 3; /* Fixed product covariate */
1169: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1170: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1171: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1172: #define VD 10; /* Varying dummy covariate */
1173: #define VQ 11; /* Varying quantitative covariate */
1174: #define VP 12; /* Varying product covariate */
1175: #define VPDD 13; /* Varying product dummy*dummy covariate */
1176: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1177: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1178: #define APFD 16; /* Age product * fixed dummy covariate */
1179: #define APFQ 17; /* Age product * fixed quantitative covariate */
1180: #define APVD 18; /* Age product * varying dummy covariate */
1181: #define APVQ 19; /* Age product * varying quantitative covariate */
1182:
1183: #define FTYPE 1; /* Fixed covariate */
1184: #define VTYPE 2; /* Varying covariate (loop in wave) */
1185: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1186:
1187: struct kmodel{
1188: int maintype; /* main type */
1189: int subtype; /* subtype */
1190: };
1191: struct kmodel modell[NCOVMAX];
1192:
1.143 brouard 1193: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1194: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1195:
1196: /**************** split *************************/
1197: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1198: {
1199: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1200: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1201: */
1202: char *ss; /* pointer */
1.186 brouard 1203: int l1=0, l2=0; /* length counters */
1.126 brouard 1204:
1205: l1 = strlen(path ); /* length of path */
1206: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1207: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1208: if ( ss == NULL ) { /* no directory, so determine current directory */
1209: strcpy( name, path ); /* we got the fullname name because no directory */
1210: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1211: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1212: /* get current working directory */
1213: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1214: #ifdef WIN32
1215: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1216: #else
1217: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1218: #endif
1.126 brouard 1219: return( GLOCK_ERROR_GETCWD );
1220: }
1221: /* got dirc from getcwd*/
1222: printf(" DIRC = %s \n",dirc);
1.205 brouard 1223: } else { /* strip directory from path */
1.126 brouard 1224: ss++; /* after this, the filename */
1225: l2 = strlen( ss ); /* length of filename */
1226: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1227: strcpy( name, ss ); /* save file name */
1228: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1229: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1230: printf(" DIRC2 = %s \n",dirc);
1231: }
1232: /* We add a separator at the end of dirc if not exists */
1233: l1 = strlen( dirc ); /* length of directory */
1234: if( dirc[l1-1] != DIRSEPARATOR ){
1235: dirc[l1] = DIRSEPARATOR;
1236: dirc[l1+1] = 0;
1237: printf(" DIRC3 = %s \n",dirc);
1238: }
1239: ss = strrchr( name, '.' ); /* find last / */
1240: if (ss >0){
1241: ss++;
1242: strcpy(ext,ss); /* save extension */
1243: l1= strlen( name);
1244: l2= strlen(ss)+1;
1245: strncpy( finame, name, l1-l2);
1246: finame[l1-l2]= 0;
1247: }
1248:
1249: return( 0 ); /* we're done */
1250: }
1251:
1252:
1253: /******************************************/
1254:
1255: void replace_back_to_slash(char *s, char*t)
1256: {
1257: int i;
1258: int lg=0;
1259: i=0;
1260: lg=strlen(t);
1261: for(i=0; i<= lg; i++) {
1262: (s[i] = t[i]);
1263: if (t[i]== '\\') s[i]='/';
1264: }
1265: }
1266:
1.132 brouard 1267: char *trimbb(char *out, char *in)
1.137 brouard 1268: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1269: char *s;
1270: s=out;
1271: while (*in != '\0'){
1.137 brouard 1272: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1273: in++;
1274: }
1275: *out++ = *in++;
1276: }
1277: *out='\0';
1278: return s;
1279: }
1280:
1.187 brouard 1281: /* char *substrchaine(char *out, char *in, char *chain) */
1282: /* { */
1283: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1284: /* char *s, *t; */
1285: /* t=in;s=out; */
1286: /* while ((*in != *chain) && (*in != '\0')){ */
1287: /* *out++ = *in++; */
1288: /* } */
1289:
1290: /* /\* *in matches *chain *\/ */
1291: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1292: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1293: /* } */
1294: /* in--; chain--; */
1295: /* while ( (*in != '\0')){ */
1296: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1297: /* *out++ = *in++; */
1298: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1299: /* } */
1300: /* *out='\0'; */
1301: /* out=s; */
1302: /* return out; */
1303: /* } */
1304: char *substrchaine(char *out, char *in, char *chain)
1305: {
1306: /* Substract chain 'chain' from 'in', return and output 'out' */
1307: /* in="V1+V1*age+age*age+V2", chain="age*age" */
1308:
1309: char *strloc;
1310:
1311: strcpy (out, in);
1312: strloc = strstr(out, chain); /* strloc points to out at age*age+V2 */
1313: printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out);
1314: if(strloc != NULL){
1315: /* will affect out */ /* strloc+strlenc(chain)=+V2 */ /* Will also work in Unicode */
1316: memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1);
1317: /* strcpy (strloc, strloc +strlen(chain));*/
1318: }
1319: printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out);
1320: return out;
1321: }
1322:
1323:
1.145 brouard 1324: char *cutl(char *blocc, char *alocc, char *in, char occ)
1325: {
1.187 brouard 1326: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.145 brouard 1327: and alocc starts after first occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1.187 brouard 1328: gives blocc="abcdef" and alocc="ghi2j".
1.145 brouard 1329: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1330: */
1.160 brouard 1331: char *s, *t;
1.145 brouard 1332: t=in;s=in;
1333: while ((*in != occ) && (*in != '\0')){
1334: *alocc++ = *in++;
1335: }
1336: if( *in == occ){
1337: *(alocc)='\0';
1338: s=++in;
1339: }
1340:
1341: if (s == t) {/* occ not found */
1342: *(alocc-(in-s))='\0';
1343: in=s;
1344: }
1345: while ( *in != '\0'){
1346: *blocc++ = *in++;
1347: }
1348:
1349: *blocc='\0';
1350: return t;
1351: }
1.137 brouard 1352: char *cutv(char *blocc, char *alocc, char *in, char occ)
1353: {
1.187 brouard 1354: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1355: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1356: gives blocc="abcdef2ghi" and alocc="j".
1357: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1358: */
1359: char *s, *t;
1360: t=in;s=in;
1361: while (*in != '\0'){
1362: while( *in == occ){
1363: *blocc++ = *in++;
1364: s=in;
1365: }
1366: *blocc++ = *in++;
1367: }
1368: if (s == t) /* occ not found */
1369: *(blocc-(in-s))='\0';
1370: else
1371: *(blocc-(in-s)-1)='\0';
1372: in=s;
1373: while ( *in != '\0'){
1374: *alocc++ = *in++;
1375: }
1376:
1377: *alocc='\0';
1378: return s;
1379: }
1380:
1.126 brouard 1381: int nbocc(char *s, char occ)
1382: {
1383: int i,j=0;
1384: int lg=20;
1385: i=0;
1386: lg=strlen(s);
1387: for(i=0; i<= lg; i++) {
1.234 brouard 1388: if (s[i] == occ ) j++;
1.126 brouard 1389: }
1390: return j;
1391: }
1392:
1.137 brouard 1393: /* void cutv(char *u,char *v, char*t, char occ) */
1394: /* { */
1395: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1396: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1397: /* gives u="abcdef2ghi" and v="j" *\/ */
1398: /* int i,lg,j,p=0; */
1399: /* i=0; */
1400: /* lg=strlen(t); */
1401: /* for(j=0; j<=lg-1; j++) { */
1402: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1403: /* } */
1.126 brouard 1404:
1.137 brouard 1405: /* for(j=0; j<p; j++) { */
1406: /* (u[j] = t[j]); */
1407: /* } */
1408: /* u[p]='\0'; */
1.126 brouard 1409:
1.137 brouard 1410: /* for(j=0; j<= lg; j++) { */
1411: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1412: /* } */
1413: /* } */
1.126 brouard 1414:
1.160 brouard 1415: #ifdef _WIN32
1416: char * strsep(char **pp, const char *delim)
1417: {
1418: char *p, *q;
1419:
1420: if ((p = *pp) == NULL)
1421: return 0;
1422: if ((q = strpbrk (p, delim)) != NULL)
1423: {
1424: *pp = q + 1;
1425: *q = '\0';
1426: }
1427: else
1428: *pp = 0;
1429: return p;
1430: }
1431: #endif
1432:
1.126 brouard 1433: /********************** nrerror ********************/
1434:
1435: void nrerror(char error_text[])
1436: {
1437: fprintf(stderr,"ERREUR ...\n");
1438: fprintf(stderr,"%s\n",error_text);
1439: exit(EXIT_FAILURE);
1440: }
1441: /*********************** vector *******************/
1442: double *vector(int nl, int nh)
1443: {
1444: double *v;
1445: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
1446: if (!v) nrerror("allocation failure in vector");
1447: return v-nl+NR_END;
1448: }
1449:
1450: /************************ free vector ******************/
1451: void free_vector(double*v, int nl, int nh)
1452: {
1453: free((FREE_ARG)(v+nl-NR_END));
1454: }
1455:
1456: /************************ivector *******************************/
1457: int *ivector(long nl,long nh)
1458: {
1459: int *v;
1460: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
1461: if (!v) nrerror("allocation failure in ivector");
1462: return v-nl+NR_END;
1463: }
1464:
1465: /******************free ivector **************************/
1466: void free_ivector(int *v, long nl, long nh)
1467: {
1468: free((FREE_ARG)(v+nl-NR_END));
1469: }
1470:
1471: /************************lvector *******************************/
1472: long *lvector(long nl,long nh)
1473: {
1474: long *v;
1475: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
1476: if (!v) nrerror("allocation failure in ivector");
1477: return v-nl+NR_END;
1478: }
1479:
1480: /******************free lvector **************************/
1481: void free_lvector(long *v, long nl, long nh)
1482: {
1483: free((FREE_ARG)(v+nl-NR_END));
1484: }
1485:
1486: /******************* imatrix *******************************/
1487: int **imatrix(long nrl, long nrh, long ncl, long nch)
1488: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
1489: {
1490: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
1491: int **m;
1492:
1493: /* allocate pointers to rows */
1494: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
1495: if (!m) nrerror("allocation failure 1 in matrix()");
1496: m += NR_END;
1497: m -= nrl;
1498:
1499:
1500: /* allocate rows and set pointers to them */
1501: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
1502: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1503: m[nrl] += NR_END;
1504: m[nrl] -= ncl;
1505:
1506: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
1507:
1508: /* return pointer to array of pointers to rows */
1509: return m;
1510: }
1511:
1512: /****************** free_imatrix *************************/
1513: void free_imatrix(m,nrl,nrh,ncl,nch)
1514: int **m;
1515: long nch,ncl,nrh,nrl;
1516: /* free an int matrix allocated by imatrix() */
1517: {
1518: free((FREE_ARG) (m[nrl]+ncl-NR_END));
1519: free((FREE_ARG) (m+nrl-NR_END));
1520: }
1521:
1522: /******************* matrix *******************************/
1523: double **matrix(long nrl, long nrh, long ncl, long nch)
1524: {
1525: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
1526: double **m;
1527:
1528: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1529: if (!m) nrerror("allocation failure 1 in matrix()");
1530: m += NR_END;
1531: m -= nrl;
1532:
1533: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1534: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1535: m[nrl] += NR_END;
1536: m[nrl] -= ncl;
1537:
1538: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1539: return m;
1.145 brouard 1540: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
1541: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
1542: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 1543: */
1544: }
1545:
1546: /*************************free matrix ************************/
1547: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
1548: {
1549: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1550: free((FREE_ARG)(m+nrl-NR_END));
1551: }
1552:
1553: /******************* ma3x *******************************/
1554: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
1555: {
1556: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
1557: double ***m;
1558:
1559: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1560: if (!m) nrerror("allocation failure 1 in matrix()");
1561: m += NR_END;
1562: m -= nrl;
1563:
1564: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1565: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1566: m[nrl] += NR_END;
1567: m[nrl] -= ncl;
1568:
1569: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1570:
1571: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
1572: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
1573: m[nrl][ncl] += NR_END;
1574: m[nrl][ncl] -= nll;
1575: for (j=ncl+1; j<=nch; j++)
1576: m[nrl][j]=m[nrl][j-1]+nlay;
1577:
1578: for (i=nrl+1; i<=nrh; i++) {
1579: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
1580: for (j=ncl+1; j<=nch; j++)
1581: m[i][j]=m[i][j-1]+nlay;
1582: }
1583: return m;
1584: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
1585: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
1586: */
1587: }
1588:
1589: /*************************free ma3x ************************/
1590: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
1591: {
1592: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
1593: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1594: free((FREE_ARG)(m+nrl-NR_END));
1595: }
1596:
1597: /*************** function subdirf ***********/
1598: char *subdirf(char fileres[])
1599: {
1600: /* Caution optionfilefiname is hidden */
1601: strcpy(tmpout,optionfilefiname);
1602: strcat(tmpout,"/"); /* Add to the right */
1603: strcat(tmpout,fileres);
1604: return tmpout;
1605: }
1606:
1607: /*************** function subdirf2 ***********/
1608: char *subdirf2(char fileres[], char *preop)
1609: {
1610:
1611: /* Caution optionfilefiname is hidden */
1612: strcpy(tmpout,optionfilefiname);
1613: strcat(tmpout,"/");
1614: strcat(tmpout,preop);
1615: strcat(tmpout,fileres);
1616: return tmpout;
1617: }
1618:
1619: /*************** function subdirf3 ***********/
1620: char *subdirf3(char fileres[], char *preop, char *preop2)
1621: {
1622:
1623: /* Caution optionfilefiname is hidden */
1624: strcpy(tmpout,optionfilefiname);
1625: strcat(tmpout,"/");
1626: strcat(tmpout,preop);
1627: strcat(tmpout,preop2);
1628: strcat(tmpout,fileres);
1629: return tmpout;
1630: }
1.213 brouard 1631:
1632: /*************** function subdirfext ***********/
1633: char *subdirfext(char fileres[], char *preop, char *postop)
1634: {
1635:
1636: strcpy(tmpout,preop);
1637: strcat(tmpout,fileres);
1638: strcat(tmpout,postop);
1639: return tmpout;
1640: }
1.126 brouard 1641:
1.213 brouard 1642: /*************** function subdirfext3 ***********/
1643: char *subdirfext3(char fileres[], char *preop, char *postop)
1644: {
1645:
1646: /* Caution optionfilefiname is hidden */
1647: strcpy(tmpout,optionfilefiname);
1648: strcat(tmpout,"/");
1649: strcat(tmpout,preop);
1650: strcat(tmpout,fileres);
1651: strcat(tmpout,postop);
1652: return tmpout;
1653: }
1654:
1.162 brouard 1655: char *asc_diff_time(long time_sec, char ascdiff[])
1656: {
1657: long sec_left, days, hours, minutes;
1658: days = (time_sec) / (60*60*24);
1659: sec_left = (time_sec) % (60*60*24);
1660: hours = (sec_left) / (60*60) ;
1661: sec_left = (sec_left) %(60*60);
1662: minutes = (sec_left) /60;
1663: sec_left = (sec_left) % (60);
1664: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
1665: return ascdiff;
1666: }
1667:
1.126 brouard 1668: /***************** f1dim *************************/
1669: extern int ncom;
1670: extern double *pcom,*xicom;
1671: extern double (*nrfunc)(double []);
1672:
1673: double f1dim(double x)
1674: {
1675: int j;
1676: double f;
1677: double *xt;
1678:
1679: xt=vector(1,ncom);
1680: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
1681: f=(*nrfunc)(xt);
1682: free_vector(xt,1,ncom);
1683: return f;
1684: }
1685:
1686: /*****************brent *************************/
1687: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 1688: {
1689: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
1690: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
1691: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
1692: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
1693: * returned function value.
1694: */
1.126 brouard 1695: int iter;
1696: double a,b,d,etemp;
1.159 brouard 1697: double fu=0,fv,fw,fx;
1.164 brouard 1698: double ftemp=0.;
1.126 brouard 1699: double p,q,r,tol1,tol2,u,v,w,x,xm;
1700: double e=0.0;
1701:
1702: a=(ax < cx ? ax : cx);
1703: b=(ax > cx ? ax : cx);
1704: x=w=v=bx;
1705: fw=fv=fx=(*f)(x);
1706: for (iter=1;iter<=ITMAX;iter++) {
1707: xm=0.5*(a+b);
1708: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
1709: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
1710: printf(".");fflush(stdout);
1711: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 1712: #ifdef DEBUGBRENT
1.126 brouard 1713: 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);
1714: 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);
1715: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
1716: #endif
1717: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
1718: *xmin=x;
1719: return fx;
1720: }
1721: ftemp=fu;
1722: if (fabs(e) > tol1) {
1723: r=(x-w)*(fx-fv);
1724: q=(x-v)*(fx-fw);
1725: p=(x-v)*q-(x-w)*r;
1726: q=2.0*(q-r);
1727: if (q > 0.0) p = -p;
1728: q=fabs(q);
1729: etemp=e;
1730: e=d;
1731: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 1732: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 1733: else {
1.224 brouard 1734: d=p/q;
1735: u=x+d;
1736: if (u-a < tol2 || b-u < tol2)
1737: d=SIGN(tol1,xm-x);
1.126 brouard 1738: }
1739: } else {
1740: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1741: }
1742: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
1743: fu=(*f)(u);
1744: if (fu <= fx) {
1745: if (u >= x) a=x; else b=x;
1746: SHFT(v,w,x,u)
1.183 brouard 1747: SHFT(fv,fw,fx,fu)
1748: } else {
1749: if (u < x) a=u; else b=u;
1750: if (fu <= fw || w == x) {
1.224 brouard 1751: v=w;
1752: w=u;
1753: fv=fw;
1754: fw=fu;
1.183 brouard 1755: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 1756: v=u;
1757: fv=fu;
1.183 brouard 1758: }
1759: }
1.126 brouard 1760: }
1761: nrerror("Too many iterations in brent");
1762: *xmin=x;
1763: return fx;
1764: }
1765:
1766: /****************** mnbrak ***********************/
1767:
1768: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
1769: double (*func)(double))
1.183 brouard 1770: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
1771: the downhill direction (defined by the function as evaluated at the initial points) and returns
1772: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
1773: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
1774: */
1.126 brouard 1775: double ulim,u,r,q, dum;
1776: double fu;
1.187 brouard 1777:
1778: double scale=10.;
1779: int iterscale=0;
1780:
1781: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
1782: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
1783:
1784:
1785: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
1786: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
1787: /* *bx = *ax - (*ax - *bx)/scale; */
1788: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
1789: /* } */
1790:
1.126 brouard 1791: if (*fb > *fa) {
1792: SHFT(dum,*ax,*bx,dum)
1.183 brouard 1793: SHFT(dum,*fb,*fa,dum)
1794: }
1.126 brouard 1795: *cx=(*bx)+GOLD*(*bx-*ax);
1796: *fc=(*func)(*cx);
1.183 brouard 1797: #ifdef DEBUG
1.224 brouard 1798: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
1799: 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 1800: #endif
1.224 brouard 1801: 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 1802: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 1803: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 1804: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 1805: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
1806: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
1807: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 1808: fu=(*func)(u);
1.163 brouard 1809: #ifdef DEBUG
1810: /* f(x)=A(x-u)**2+f(u) */
1811: double A, fparabu;
1812: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
1813: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 1814: 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);
1815: 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 1816: /* And thus,it can be that fu > *fc even if fparabu < *fc */
1817: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
1818: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
1819: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 1820: #endif
1.184 brouard 1821: #ifdef MNBRAKORIGINAL
1.183 brouard 1822: #else
1.191 brouard 1823: /* if (fu > *fc) { */
1824: /* #ifdef DEBUG */
1825: /* printf("mnbrak4 fu > fc \n"); */
1826: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
1827: /* #endif */
1828: /* /\* 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 *\\/ *\/ */
1829: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
1830: /* dum=u; /\* Shifting c and u *\/ */
1831: /* u = *cx; */
1832: /* *cx = dum; */
1833: /* dum = fu; */
1834: /* fu = *fc; */
1835: /* *fc =dum; */
1836: /* } else { /\* end *\/ */
1837: /* #ifdef DEBUG */
1838: /* printf("mnbrak3 fu < fc \n"); */
1839: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
1840: /* #endif */
1841: /* dum=u; /\* Shifting c and u *\/ */
1842: /* u = *cx; */
1843: /* *cx = dum; */
1844: /* dum = fu; */
1845: /* fu = *fc; */
1846: /* *fc =dum; */
1847: /* } */
1.224 brouard 1848: #ifdef DEBUGMNBRAK
1849: double A, fparabu;
1850: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
1851: fparabu= *fa - A*(*ax-u)*(*ax-u);
1852: 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);
1853: 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 1854: #endif
1.191 brouard 1855: dum=u; /* Shifting c and u */
1856: u = *cx;
1857: *cx = dum;
1858: dum = fu;
1859: fu = *fc;
1860: *fc =dum;
1.183 brouard 1861: #endif
1.162 brouard 1862: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 1863: #ifdef DEBUG
1.224 brouard 1864: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1865: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 1866: #endif
1.126 brouard 1867: fu=(*func)(u);
1868: if (fu < *fc) {
1.183 brouard 1869: #ifdef DEBUG
1.224 brouard 1870: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
1871: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
1872: #endif
1873: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
1874: SHFT(*fb,*fc,fu,(*func)(u))
1875: #ifdef DEBUG
1876: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 1877: #endif
1878: }
1.162 brouard 1879: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 1880: #ifdef DEBUG
1.224 brouard 1881: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1882: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 1883: #endif
1.126 brouard 1884: u=ulim;
1885: fu=(*func)(u);
1.183 brouard 1886: } else { /* u could be left to b (if r > q parabola has a maximum) */
1887: #ifdef DEBUG
1.224 brouard 1888: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
1889: 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 1890: #endif
1.126 brouard 1891: u=(*cx)+GOLD*(*cx-*bx);
1892: fu=(*func)(u);
1.224 brouard 1893: #ifdef DEBUG
1894: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
1895: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
1896: #endif
1.183 brouard 1897: } /* end tests */
1.126 brouard 1898: SHFT(*ax,*bx,*cx,u)
1.183 brouard 1899: SHFT(*fa,*fb,*fc,fu)
1900: #ifdef DEBUG
1.224 brouard 1901: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
1902: 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 1903: #endif
1904: } /* 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 1905: }
1906:
1907: /*************** linmin ************************/
1.162 brouard 1908: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
1909: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
1910: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
1911: the value of func at the returned location p . This is actually all accomplished by calling the
1912: routines mnbrak and brent .*/
1.126 brouard 1913: int ncom;
1914: double *pcom,*xicom;
1915: double (*nrfunc)(double []);
1916:
1.224 brouard 1917: #ifdef LINMINORIGINAL
1.126 brouard 1918: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 1919: #else
1920: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
1921: #endif
1.126 brouard 1922: {
1923: double brent(double ax, double bx, double cx,
1924: double (*f)(double), double tol, double *xmin);
1925: double f1dim(double x);
1926: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
1927: double *fc, double (*func)(double));
1928: int j;
1929: double xx,xmin,bx,ax;
1930: double fx,fb,fa;
1.187 brouard 1931:
1.203 brouard 1932: #ifdef LINMINORIGINAL
1933: #else
1934: double scale=10., axs, xxs; /* Scale added for infinity */
1935: #endif
1936:
1.126 brouard 1937: ncom=n;
1938: pcom=vector(1,n);
1939: xicom=vector(1,n);
1940: nrfunc=func;
1941: for (j=1;j<=n;j++) {
1942: pcom[j]=p[j];
1.202 brouard 1943: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 1944: }
1.187 brouard 1945:
1.203 brouard 1946: #ifdef LINMINORIGINAL
1947: xx=1.;
1948: #else
1949: axs=0.0;
1950: xxs=1.;
1951: do{
1952: xx= xxs;
1953: #endif
1.187 brouard 1954: ax=0.;
1955: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
1956: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
1957: /* 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)) */
1958: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
1959: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
1960: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
1961: /* 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 1962: #ifdef LINMINORIGINAL
1963: #else
1964: if (fx != fx){
1.224 brouard 1965: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
1966: printf("|");
1967: fprintf(ficlog,"|");
1.203 brouard 1968: #ifdef DEBUGLINMIN
1.224 brouard 1969: 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 1970: #endif
1971: }
1.224 brouard 1972: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 1973: #endif
1974:
1.191 brouard 1975: #ifdef DEBUGLINMIN
1976: 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 1977: 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 1978: #endif
1.224 brouard 1979: #ifdef LINMINORIGINAL
1980: #else
1981: if(fb == fx){ /* Flat function in the direction */
1982: xmin=xx;
1983: *flat=1;
1984: }else{
1985: *flat=0;
1986: #endif
1987: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 1988: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
1989: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
1990: /* fmin = f(p[j] + xmin * xi[j]) */
1991: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
1992: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 1993: #ifdef DEBUG
1.224 brouard 1994: 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);
1995: 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);
1996: #endif
1997: #ifdef LINMINORIGINAL
1998: #else
1999: }
1.126 brouard 2000: #endif
1.191 brouard 2001: #ifdef DEBUGLINMIN
2002: printf("linmin end ");
1.202 brouard 2003: fprintf(ficlog,"linmin end ");
1.191 brouard 2004: #endif
1.126 brouard 2005: for (j=1;j<=n;j++) {
1.203 brouard 2006: #ifdef LINMINORIGINAL
2007: xi[j] *= xmin;
2008: #else
2009: #ifdef DEBUGLINMIN
2010: if(xxs <1.0)
2011: printf(" before xi[%d]=%12.8f", j,xi[j]);
2012: #endif
2013: 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) */
2014: #ifdef DEBUGLINMIN
2015: if(xxs <1.0)
2016: 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 );
2017: #endif
2018: #endif
1.187 brouard 2019: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2020: }
1.191 brouard 2021: #ifdef DEBUGLINMIN
1.203 brouard 2022: printf("\n");
1.191 brouard 2023: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2024: 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 2025: for (j=1;j<=n;j++) {
1.202 brouard 2026: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2027: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2028: if(j % ncovmodel == 0){
1.191 brouard 2029: printf("\n");
1.202 brouard 2030: fprintf(ficlog,"\n");
2031: }
1.191 brouard 2032: }
1.203 brouard 2033: #else
1.191 brouard 2034: #endif
1.126 brouard 2035: free_vector(xicom,1,n);
2036: free_vector(pcom,1,n);
2037: }
2038:
2039:
2040: /*************** powell ************************/
1.162 brouard 2041: /*
2042: Minimization of a function func of n variables. Input consists of an initial starting point
2043: p[1..n] ; an initial matrix xi[1..n][1..n] , whose columns contain the initial set of di-
2044: rections (usually the n unit vectors); and ftol , the fractional tolerance in the function value
2045: such that failure to decrease by more than this amount on one iteration signals doneness. On
2046: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2047: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2048: */
1.224 brouard 2049: #ifdef LINMINORIGINAL
2050: #else
2051: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2052: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2053: #endif
1.126 brouard 2054: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2055: double (*func)(double []))
2056: {
1.224 brouard 2057: #ifdef LINMINORIGINAL
2058: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2059: double (*func)(double []));
1.224 brouard 2060: #else
2061: void linmin(double p[], double xi[], int n, double *fret,
2062: double (*func)(double []),int *flat);
2063: #endif
1.126 brouard 2064: int i,ibig,j;
2065: double del,t,*pt,*ptt,*xit;
1.181 brouard 2066: double directest;
1.126 brouard 2067: double fp,fptt;
2068: double *xits;
2069: int niterf, itmp;
1.224 brouard 2070: #ifdef LINMINORIGINAL
2071: #else
2072:
2073: flatdir=ivector(1,n);
2074: for (j=1;j<=n;j++) flatdir[j]=0;
2075: #endif
1.126 brouard 2076:
2077: pt=vector(1,n);
2078: ptt=vector(1,n);
2079: xit=vector(1,n);
2080: xits=vector(1,n);
2081: *fret=(*func)(p);
2082: for (j=1;j<=n;j++) pt[j]=p[j];
1.202 brouard 2083: rcurr_time = time(NULL);
1.126 brouard 2084: for (*iter=1;;++(*iter)) {
1.187 brouard 2085: fp=(*fret); /* From former iteration or initial value */
1.126 brouard 2086: ibig=0;
2087: del=0.0;
1.157 brouard 2088: rlast_time=rcurr_time;
2089: /* (void) gettimeofday(&curr_time,&tzp); */
2090: rcurr_time = time(NULL);
2091: curr_time = *localtime(&rcurr_time);
2092: printf("\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout);
2093: fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog);
2094: /* fprintf(ficrespow,"%d %.12f %ld",*iter,*fret,curr_time.tm_sec-start_time.tm_sec); */
1.192 brouard 2095: for (i=1;i<=n;i++) {
1.126 brouard 2096: printf(" %d %.12f",i, p[i]);
2097: fprintf(ficlog," %d %.12lf",i, p[i]);
2098: fprintf(ficrespow," %.12lf", p[i]);
2099: }
2100: printf("\n");
2101: fprintf(ficlog,"\n");
2102: fprintf(ficrespow,"\n");fflush(ficrespow);
2103: if(*iter <=3){
1.157 brouard 2104: tml = *localtime(&rcurr_time);
2105: strcpy(strcurr,asctime(&tml));
2106: rforecast_time=rcurr_time;
1.126 brouard 2107: itmp = strlen(strcurr);
2108: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.224 brouard 2109: strcurr[itmp-1]='\0';
1.162 brouard 2110: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2111: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.126 brouard 2112: for(niterf=10;niterf<=30;niterf+=10){
1.224 brouard 2113: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2114: forecast_time = *localtime(&rforecast_time);
2115: strcpy(strfor,asctime(&forecast_time));
2116: itmp = strlen(strfor);
2117: if(strfor[itmp-1]=='\n')
2118: strfor[itmp-1]='\0';
2119: 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);
2120: 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 2121: }
2122: }
1.187 brouard 2123: for (i=1;i<=n;i++) { /* For each direction i */
2124: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2125: fptt=(*fret);
2126: #ifdef DEBUG
1.203 brouard 2127: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2128: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2129: #endif
1.203 brouard 2130: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2131: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2132: #ifdef LINMINORIGINAL
1.188 brouard 2133: linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.224 brouard 2134: #else
2135: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2136: flatdir[i]=flat; /* Function is vanishing in that direction i */
2137: #endif
2138: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2139: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2140: /* because that direction will be replaced unless the gain del is small */
2141: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2142: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2143: /* with the new direction. */
2144: del=fabs(fptt-(*fret));
2145: ibig=i;
1.126 brouard 2146: }
2147: #ifdef DEBUG
2148: printf("%d %.12e",i,(*fret));
2149: fprintf(ficlog,"%d %.12e",i,(*fret));
2150: for (j=1;j<=n;j++) {
1.224 brouard 2151: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2152: printf(" x(%d)=%.12e",j,xit[j]);
2153: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2154: }
2155: for(j=1;j<=n;j++) {
1.225 brouard 2156: printf(" p(%d)=%.12e",j,p[j]);
2157: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2158: }
2159: printf("\n");
2160: fprintf(ficlog,"\n");
2161: #endif
1.187 brouard 2162: } /* end loop on each direction i */
2163: /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
1.188 brouard 2164: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.187 brouard 2165: /* New value of last point Pn is not computed, P(n-1) */
1.224 brouard 2166: for(j=1;j<=n;j++) {
1.225 brouard 2167: if(flatdir[j] >0){
2168: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2169: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2170: }
2171: /* printf("\n"); */
2172: /* fprintf(ficlog,"\n"); */
2173: }
1.182 brouard 2174: if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /* Did we reach enough precision? */
1.188 brouard 2175: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2176: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2177: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2178: /* decreased of more than 3.84 */
2179: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2180: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2181: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2182:
1.188 brouard 2183: /* Starting the program with initial values given by a former maximization will simply change */
2184: /* the scales of the directions and the directions, because the are reset to canonical directions */
2185: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2186: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2187: #ifdef DEBUG
2188: int k[2],l;
2189: k[0]=1;
2190: k[1]=-1;
2191: printf("Max: %.12e",(*func)(p));
2192: fprintf(ficlog,"Max: %.12e",(*func)(p));
2193: for (j=1;j<=n;j++) {
2194: printf(" %.12e",p[j]);
2195: fprintf(ficlog," %.12e",p[j]);
2196: }
2197: printf("\n");
2198: fprintf(ficlog,"\n");
2199: for(l=0;l<=1;l++) {
2200: for (j=1;j<=n;j++) {
2201: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2202: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2203: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2204: }
2205: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2206: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2207: }
2208: #endif
2209:
1.224 brouard 2210: #ifdef LINMINORIGINAL
2211: #else
2212: free_ivector(flatdir,1,n);
2213: #endif
1.126 brouard 2214: free_vector(xit,1,n);
2215: free_vector(xits,1,n);
2216: free_vector(ptt,1,n);
2217: free_vector(pt,1,n);
2218: return;
1.192 brouard 2219: } /* enough precision */
1.126 brouard 2220: if (*iter == ITMAX) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2221: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2222: ptt[j]=2.0*p[j]-pt[j];
2223: xit[j]=p[j]-pt[j];
2224: pt[j]=p[j];
2225: }
1.181 brouard 2226: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2227: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2228: if (*iter <=4) {
1.225 brouard 2229: #else
2230: #endif
1.224 brouard 2231: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2232: #else
1.161 brouard 2233: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2234: #endif
1.162 brouard 2235: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2236: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2237: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2238: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2239: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2240: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2241: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2242: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2243: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2244: /* Even if f3 <f1, directest can be negative and t >0 */
2245: /* mu² and del² are equal when f3=f1 */
2246: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2247: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2248: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2249: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2250: #ifdef NRCORIGINAL
2251: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2252: #else
2253: 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 2254: t= t- del*SQR(fp-fptt);
1.183 brouard 2255: #endif
1.202 brouard 2256: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2257: #ifdef DEBUG
1.181 brouard 2258: 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);
2259: 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 2260: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2261: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2262: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2263: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2264: 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);
2265: 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);
2266: #endif
1.183 brouard 2267: #ifdef POWELLORIGINAL
2268: if (t < 0.0) { /* Then we use it for new direction */
2269: #else
1.182 brouard 2270: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2271: 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 2272: 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 2273: 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 2274: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2275: }
1.181 brouard 2276: if (directest < 0.0) { /* Then we use it for new direction */
2277: #endif
1.191 brouard 2278: #ifdef DEBUGLINMIN
1.234 brouard 2279: printf("Before linmin in direction P%d-P0\n",n);
2280: for (j=1;j<=n;j++) {
2281: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2282: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2283: if(j % ncovmodel == 0){
2284: printf("\n");
2285: fprintf(ficlog,"\n");
2286: }
2287: }
1.224 brouard 2288: #endif
2289: #ifdef LINMINORIGINAL
1.234 brouard 2290: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2291: #else
1.234 brouard 2292: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2293: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2294: #endif
1.234 brouard 2295:
1.191 brouard 2296: #ifdef DEBUGLINMIN
1.234 brouard 2297: for (j=1;j<=n;j++) {
2298: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2299: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2300: if(j % ncovmodel == 0){
2301: printf("\n");
2302: fprintf(ficlog,"\n");
2303: }
2304: }
1.224 brouard 2305: #endif
1.234 brouard 2306: for (j=1;j<=n;j++) {
2307: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2308: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2309: }
1.224 brouard 2310: #ifdef LINMINORIGINAL
2311: #else
1.234 brouard 2312: for (j=1, flatd=0;j<=n;j++) {
2313: if(flatdir[j]>0)
2314: flatd++;
2315: }
2316: if(flatd >0){
2317: printf("%d flat directions\n",flatd);
2318: fprintf(ficlog,"%d flat directions\n",flatd);
2319: for (j=1;j<=n;j++) {
2320: if(flatdir[j]>0){
2321: printf("%d ",j);
2322: fprintf(ficlog,"%d ",j);
2323: }
2324: }
2325: printf("\n");
2326: fprintf(ficlog,"\n");
2327: }
1.191 brouard 2328: #endif
1.234 brouard 2329: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2330: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2331:
1.126 brouard 2332: #ifdef DEBUG
1.234 brouard 2333: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2334: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2335: for(j=1;j<=n;j++){
2336: printf(" %lf",xit[j]);
2337: fprintf(ficlog," %lf",xit[j]);
2338: }
2339: printf("\n");
2340: fprintf(ficlog,"\n");
1.126 brouard 2341: #endif
1.192 brouard 2342: } /* end of t or directest negative */
1.224 brouard 2343: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2344: #else
1.234 brouard 2345: } /* end if (fptt < fp) */
1.192 brouard 2346: #endif
1.225 brouard 2347: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2348: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2349: #else
1.224 brouard 2350: #endif
1.234 brouard 2351: } /* loop iteration */
1.126 brouard 2352: }
1.234 brouard 2353:
1.126 brouard 2354: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 2355:
1.235 brouard 2356: 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 2357: {
1.235 brouard 2358: /* Computes the prevalence limit in each live state at age x and for covariate combination ij
2359: (and selected quantitative values in nres)
2360: by left multiplying the unit
1.234 brouard 2361: matrix by transitions matrix until convergence is reached with precision ftolpl */
1.206 brouard 2362: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
2363: /* Wx is row vector: population in state 1, population in state 2, population dead */
2364: /* or prevalence in state 1, prevalence in state 2, 0 */
2365: /* newm is the matrix after multiplications, its rows are identical at a factor */
2366: /* Initial matrix pimij */
2367: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2368: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2369: /* 0, 0 , 1} */
2370: /*
2371: * and after some iteration: */
2372: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2373: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2374: /* 0, 0 , 1} */
2375: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2376: /* {0.51571254859325999, 0.4842874514067399, */
2377: /* 0.51326036147820708, 0.48673963852179264} */
2378: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 2379:
1.126 brouard 2380: int i, ii,j,k;
1.209 brouard 2381: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 2382: /* double **matprod2(); */ /* test */
1.218 brouard 2383: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 2384: double **newm;
1.209 brouard 2385: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 2386: int ncvloop=0;
1.169 brouard 2387:
1.209 brouard 2388: min=vector(1,nlstate);
2389: max=vector(1,nlstate);
2390: meandiff=vector(1,nlstate);
2391:
1.218 brouard 2392: /* Starting with matrix unity */
1.126 brouard 2393: for (ii=1;ii<=nlstate+ndeath;ii++)
2394: for (j=1;j<=nlstate+ndeath;j++){
2395: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2396: }
1.169 brouard 2397:
2398: cov[1]=1.;
2399:
2400: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 2401: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 2402: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 2403: ncvloop++;
1.126 brouard 2404: newm=savm;
2405: /* Covariates have to be included here again */
1.138 brouard 2406: cov[2]=agefin;
1.187 brouard 2407: if(nagesqr==1)
2408: cov[3]= agefin*agefin;;
1.234 brouard 2409: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2410: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2411: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.235 brouard 2412: /* printf("prevalim Dummy combi=%d k=%d TvarsD[%d]=V%d TvarsDind[%d]=%d nbcode=%d cov=%lf codtabm(%d,Tvar[%d])=%d \n",ij,k, k, TvarsD[k],k,TvarsDind[k],nbcode[TvarsD[k]][codtabm(ij,k)],cov[2+nagesqr+TvarsDind[k]], ij, k, codtabm(ij,k)); */
1.234 brouard 2413: }
2414: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2415: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
1.235 brouard 2416: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2417: /* printf("prevalim Quantitative k=%d TvarsQind[%d]=%d, TvarsQ[%d]=V%d,Tqresult[%d][%d]=%f\n",k,k,TvarsQind[k],k,TvarsQ[k],nres,k,Tqresult[nres][k]); */
1.138 brouard 2418: }
1.237 brouard 2419: for (k=1; k<=cptcovage;k++){ /* For product with age */
1.234 brouard 2420: if(Dummy[Tvar[Tage[k]]]){
2421: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
2422: } else{
1.235 brouard 2423: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
1.234 brouard 2424: }
1.235 brouard 2425: /* printf("prevalim Age combi=%d k=%d Tage[%d]=V%d Tqresult[%d][%d]=%f\n",ij,k,k,Tage[k],nres,k,Tqresult[nres][k]); */
1.234 brouard 2426: }
1.237 brouard 2427: for (k=1; k<=cptcovprod;k++){ /* For product without age */
1.235 brouard 2428: /* printf("prevalim Prod ij=%d k=%d Tprod[%d]=%d Tvard[%d][1]=V%d, Tvard[%d][2]=V%d\n",ij,k,k,Tprod[k], k,Tvard[k][1], k,Tvard[k][2]); */
1.237 brouard 2429: if(Dummy[Tvard[k][1]==0]){
2430: if(Dummy[Tvard[k][2]==0]){
2431: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2432: }else{
2433: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2434: }
2435: }else{
2436: if(Dummy[Tvard[k][2]==0]){
2437: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2438: }else{
2439: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2440: }
2441: }
1.234 brouard 2442: }
1.138 brouard 2443: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2444: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2445: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 2446: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2447: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2448: /* age and covariate values of ij are in 'cov' */
1.142 brouard 2449: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 2450:
1.126 brouard 2451: savm=oldm;
2452: oldm=newm;
1.209 brouard 2453:
2454: for(j=1; j<=nlstate; j++){
2455: max[j]=0.;
2456: min[j]=1.;
2457: }
2458: for(i=1;i<=nlstate;i++){
2459: sumnew=0;
2460: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
2461: for(j=1; j<=nlstate; j++){
2462: prlim[i][j]= newm[i][j]/(1-sumnew);
2463: max[j]=FMAX(max[j],prlim[i][j]);
2464: min[j]=FMIN(min[j],prlim[i][j]);
2465: }
2466: }
2467:
1.126 brouard 2468: maxmax=0.;
1.209 brouard 2469: for(j=1; j<=nlstate; j++){
2470: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
2471: maxmax=FMAX(maxmax,meandiff[j]);
2472: /* 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 2473: } /* j loop */
1.203 brouard 2474: *ncvyear= (int)age- (int)agefin;
1.208 brouard 2475: /* 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 2476: if(maxmax < ftolpl){
1.209 brouard 2477: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
2478: free_vector(min,1,nlstate);
2479: free_vector(max,1,nlstate);
2480: free_vector(meandiff,1,nlstate);
1.126 brouard 2481: return prlim;
2482: }
1.169 brouard 2483: } /* age loop */
1.208 brouard 2484: /* After some age loop it doesn't converge */
1.209 brouard 2485: printf("Warning: the stable prevalence at age %d did not converge with the required precision (%g > ftolpl=%g) within %.0f years. Try to lower 'ftolpl'. \n\
1.208 brouard 2486: Earliest 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);
1.209 brouard 2487: /* 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); */
2488: free_vector(min,1,nlstate);
2489: free_vector(max,1,nlstate);
2490: free_vector(meandiff,1,nlstate);
1.208 brouard 2491:
1.169 brouard 2492: return prlim; /* should not reach here */
1.126 brouard 2493: }
2494:
1.217 brouard 2495:
2496: /**** Back Prevalence limit (stable or period prevalence) ****************/
2497:
1.218 brouard 2498: /* 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) */
2499: /* 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) */
2500: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij)
1.217 brouard 2501: {
1.218 brouard 2502: /* Computes the prevalence limit in each live state at age x and covariate ij by left multiplying the unit
1.217 brouard 2503: matrix by transitions matrix until convergence is reached with precision ftolpl */
2504: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
2505: /* Wx is row vector: population in state 1, population in state 2, population dead */
2506: /* or prevalence in state 1, prevalence in state 2, 0 */
2507: /* newm is the matrix after multiplications, its rows are identical at a factor */
2508: /* Initial matrix pimij */
2509: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2510: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2511: /* 0, 0 , 1} */
2512: /*
2513: * and after some iteration: */
2514: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2515: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2516: /* 0, 0 , 1} */
2517: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2518: /* {0.51571254859325999, 0.4842874514067399, */
2519: /* 0.51326036147820708, 0.48673963852179264} */
2520: /* If we start from prlim again, prlim tends to a constant matrix */
2521:
2522: int i, ii,j,k;
2523: double *min, *max, *meandiff, maxmax,sumnew=0.;
2524: /* double **matprod2(); */ /* test */
2525: double **out, cov[NCOVMAX+1], **bmij();
2526: double **newm;
1.218 brouard 2527: double **dnewm, **doldm, **dsavm; /* for use */
2528: double **oldm, **savm; /* for use */
2529:
1.217 brouard 2530: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
2531: int ncvloop=0;
2532:
2533: min=vector(1,nlstate);
2534: max=vector(1,nlstate);
2535: meandiff=vector(1,nlstate);
2536:
1.218 brouard 2537: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
2538: oldm=oldms; savm=savms;
2539:
2540: /* Starting with matrix unity */
2541: for (ii=1;ii<=nlstate+ndeath;ii++)
2542: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 2543: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2544: }
2545:
2546: cov[1]=1.;
2547:
2548: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
2549: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 2550: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
2551: for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 2552: ncvloop++;
1.218 brouard 2553: newm=savm; /* oldm should be kept from previous iteration or unity at start */
2554: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 2555: /* Covariates have to be included here again */
2556: cov[2]=agefin;
2557: if(nagesqr==1)
2558: cov[3]= agefin*agefin;;
2559: for (k=1; k<=cptcovn;k++) {
2560: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
2561: cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)];
2562: /* 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])]); */
2563: }
2564: for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2];
2565: for (k=1; k<=cptcovprod;k++) /* Useless */
2566: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
2567: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2568:
2569: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2570: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2571: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
2572: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2573: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2574: /* ij should be linked to the correct index of cov */
2575: /* age and covariate values ij are in 'cov', but we need to pass
2576: * ij for the observed prevalence at age and status and covariate
2577: * number: prevacurrent[(int)agefin][ii][ij]
2578: */
2579: /* 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 *\/ */
2580: /* 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 *\/ */
2581: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij)); /* Bug Valgrind */
1.217 brouard 2582: savm=oldm;
2583: oldm=newm;
2584: for(j=1; j<=nlstate; j++){
2585: max[j]=0.;
2586: min[j]=1.;
2587: }
2588: for(j=1; j<=nlstate; j++){
2589: for(i=1;i<=nlstate;i++){
1.234 brouard 2590: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
2591: bprlim[i][j]= newm[i][j];
2592: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
2593: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 2594: }
2595: }
1.218 brouard 2596:
1.217 brouard 2597: maxmax=0.;
2598: for(i=1; i<=nlstate; i++){
2599: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column */
2600: maxmax=FMAX(maxmax,meandiff[i]);
2601: /* 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); */
2602: } /* j loop */
2603: *ncvyear= -( (int)age- (int)agefin);
1.218 brouard 2604: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear);*/
1.217 brouard 2605: if(maxmax < ftolpl){
1.220 brouard 2606: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 2607: free_vector(min,1,nlstate);
2608: free_vector(max,1,nlstate);
2609: free_vector(meandiff,1,nlstate);
2610: return bprlim;
2611: }
2612: } /* age loop */
2613: /* After some age loop it doesn't converge */
2614: 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'. \n\
2615: 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);
2616: /* 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); */
2617: free_vector(min,1,nlstate);
2618: free_vector(max,1,nlstate);
2619: free_vector(meandiff,1,nlstate);
2620:
2621: return bprlim; /* should not reach here */
2622: }
2623:
1.126 brouard 2624: /*************** transition probabilities ***************/
2625:
2626: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
2627: {
1.138 brouard 2628: /* According to parameters values stored in x and the covariate's values stored in cov,
2629: computes the probability to be observed in state j being in state i by appying the
2630: model to the ncovmodel covariates (including constant and age).
2631: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
2632: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
2633: ncth covariate in the global vector x is given by the formula:
2634: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
2635: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
2636: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
2637: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
2638: Outputs ps[i][j] the probability to be observed in j being in j according to
2639: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
2640: */
2641: double s1, lnpijopii;
1.126 brouard 2642: /*double t34;*/
1.164 brouard 2643: int i,j, nc, ii, jj;
1.126 brouard 2644:
1.223 brouard 2645: for(i=1; i<= nlstate; i++){
2646: for(j=1; j<i;j++){
2647: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2648: /*lnpijopii += param[i][j][nc]*cov[nc];*/
2649: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
2650: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2651: }
2652: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2653: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2654: }
2655: for(j=i+1; j<=nlstate+ndeath;j++){
2656: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2657: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
2658: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
2659: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
2660: }
2661: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2662: }
2663: }
1.218 brouard 2664:
1.223 brouard 2665: for(i=1; i<= nlstate; i++){
2666: s1=0;
2667: for(j=1; j<i; j++){
2668: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2669: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2670: }
2671: for(j=i+1; j<=nlstate+ndeath; j++){
2672: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2673: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2674: }
2675: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
2676: ps[i][i]=1./(s1+1.);
2677: /* Computing other pijs */
2678: for(j=1; j<i; j++)
2679: ps[i][j]= exp(ps[i][j])*ps[i][i];
2680: for(j=i+1; j<=nlstate+ndeath; j++)
2681: ps[i][j]= exp(ps[i][j])*ps[i][i];
2682: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
2683: } /* end i */
1.218 brouard 2684:
1.223 brouard 2685: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
2686: for(jj=1; jj<= nlstate+ndeath; jj++){
2687: ps[ii][jj]=0;
2688: ps[ii][ii]=1;
2689: }
2690: }
1.218 brouard 2691:
2692:
1.223 brouard 2693: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
2694: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
2695: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
2696: /* } */
2697: /* printf("\n "); */
2698: /* } */
2699: /* printf("\n ");printf("%lf ",cov[2]);*/
2700: /*
2701: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 2702: goto end;*/
1.223 brouard 2703: return ps;
1.126 brouard 2704: }
2705:
1.218 brouard 2706: /*************** backward transition probabilities ***************/
2707:
2708: /* 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 ) */
2709: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
2710: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
2711: {
1.222 brouard 2712: /* Computes the backward probability at age agefin and covariate ij
2713: * and returns in **ps as well as **bmij.
2714: */
1.218 brouard 2715: int i, ii, j,k;
1.222 brouard 2716:
2717: double **out, **pmij();
2718: double sumnew=0.;
1.218 brouard 2719: double agefin;
1.222 brouard 2720:
2721: double **dnewm, **dsavm, **doldm;
2722: double **bbmij;
2723:
1.218 brouard 2724: doldm=ddoldms; /* global pointers */
1.222 brouard 2725: dnewm=ddnewms;
2726: dsavm=ddsavms;
2727:
2728: agefin=cov[2];
2729: /* bmij *//* age is cov[2], ij is included in cov, but we need for
2730: the observed prevalence (with this covariate ij) */
2731: dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate);
2732: /* We do have the matrix Px in savm and we need pij */
2733: for (j=1;j<=nlstate+ndeath;j++){
2734: sumnew=0.; /* w1 p11 + w2 p21 only on live states */
2735: for (ii=1;ii<=nlstate;ii++){
2736: sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij];
2737: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
2738: for (ii=1;ii<=nlstate+ndeath;ii++){
2739: if(sumnew >= 1.e-10){
2740: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
2741: /* doldm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
2742: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
2743: /* doldm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
2744: /* }else */
2745: doldm[ii][j]=(ii==j ? 1./sumnew : 0.0);
2746: }else{
2747: printf("ii=%d, i=%d, doldm=%lf dsavm=%lf, probs=%lf, sumnew=%lf,agefin=%d\n",ii,j,doldm[ii][j],dsavm[ii][j],prevacurrent[(int)agefin][ii][ij],sumnew, (int)agefin);
2748: }
2749: } /*End ii */
2750: } /* End j, At the end doldm is diag[1/(w_1p1i+w_2 p2i)] */
2751: /* left Product of this diag matrix by dsavm=Px (newm=dsavm*doldm) */
2752: bbmij=matprod2(dnewm, dsavm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, doldm); /* Bug Valgrind */
2753: /* dsavm=doldm; /\* dsavm is now diag [1/(w_1p1i+w_2 p2i)] but can be overwritten*\/ */
2754: /* doldm=dnewm; /\* doldm is now Px * diag [1/(w_1p1i+w_2 p2i)] *\/ */
2755: /* dnewm=dsavm; /\* doldm is now Px * diag [1/(w_1p1i+w_2 p2i)] *\/ */
2756: /* left Product of this matrix by diag matrix of prevalences (savm) */
2757: for (j=1;j<=nlstate+ndeath;j++){
2758: for (ii=1;ii<=nlstate+ndeath;ii++){
2759: dsavm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij] : 0.0);
2760: }
2761: } /* End j, At the end oldm is diag[1/(w_1p1i+w_2 p2i)] */
2762: ps=matprod2(doldm, dsavm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dnewm); /* Bug Valgrind */
2763: /* newm or out is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
2764: /* end bmij */
2765: return ps;
1.218 brouard 2766: }
1.217 brouard 2767: /*************** transition probabilities ***************/
2768:
1.218 brouard 2769: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 2770: {
2771: /* According to parameters values stored in x and the covariate's values stored in cov,
2772: computes the probability to be observed in state j being in state i by appying the
2773: model to the ncovmodel covariates (including constant and age).
2774: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
2775: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
2776: ncth covariate in the global vector x is given by the formula:
2777: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
2778: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
2779: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
2780: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
2781: Outputs ps[i][j] the probability to be observed in j being in j according to
2782: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
2783: */
2784: double s1, lnpijopii;
2785: /*double t34;*/
2786: int i,j, nc, ii, jj;
2787:
1.234 brouard 2788: for(i=1; i<= nlstate; i++){
2789: for(j=1; j<i;j++){
2790: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2791: /*lnpijopii += param[i][j][nc]*cov[nc];*/
2792: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
2793: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2794: }
2795: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2796: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2797: }
2798: for(j=i+1; j<=nlstate+ndeath;j++){
2799: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2800: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
2801: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
2802: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
2803: }
2804: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2805: }
2806: }
2807:
2808: for(i=1; i<= nlstate; i++){
2809: s1=0;
2810: for(j=1; j<i; j++){
2811: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2812: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2813: }
2814: for(j=i+1; j<=nlstate+ndeath; j++){
2815: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2816: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2817: }
2818: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
2819: ps[i][i]=1./(s1+1.);
2820: /* Computing other pijs */
2821: for(j=1; j<i; j++)
2822: ps[i][j]= exp(ps[i][j])*ps[i][i];
2823: for(j=i+1; j<=nlstate+ndeath; j++)
2824: ps[i][j]= exp(ps[i][j])*ps[i][i];
2825: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
2826: } /* end i */
2827:
2828: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
2829: for(jj=1; jj<= nlstate+ndeath; jj++){
2830: ps[ii][jj]=0;
2831: ps[ii][ii]=1;
2832: }
2833: }
2834: /* Added for backcast */ /* Transposed matrix too */
2835: for(jj=1; jj<= nlstate+ndeath; jj++){
2836: s1=0.;
2837: for(ii=1; ii<= nlstate+ndeath; ii++){
2838: s1+=ps[ii][jj];
2839: }
2840: for(ii=1; ii<= nlstate; ii++){
2841: ps[ii][jj]=ps[ii][jj]/s1;
2842: }
2843: }
2844: /* Transposition */
2845: for(jj=1; jj<= nlstate+ndeath; jj++){
2846: for(ii=jj; ii<= nlstate+ndeath; ii++){
2847: s1=ps[ii][jj];
2848: ps[ii][jj]=ps[jj][ii];
2849: ps[jj][ii]=s1;
2850: }
2851: }
2852: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
2853: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
2854: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
2855: /* } */
2856: /* printf("\n "); */
2857: /* } */
2858: /* printf("\n ");printf("%lf ",cov[2]);*/
2859: /*
2860: for(i=1; i<= npar; i++) printf("%f ",x[i]);
2861: goto end;*/
2862: return ps;
1.217 brouard 2863: }
2864:
2865:
1.126 brouard 2866: /**************** Product of 2 matrices ******************/
2867:
1.145 brouard 2868: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 2869: {
2870: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
2871: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
2872: /* in, b, out are matrice of pointers which should have been initialized
2873: before: only the contents of out is modified. The function returns
2874: a pointer to pointers identical to out */
1.145 brouard 2875: int i, j, k;
1.126 brouard 2876: for(i=nrl; i<= nrh; i++)
1.145 brouard 2877: for(k=ncolol; k<=ncoloh; k++){
2878: out[i][k]=0.;
2879: for(j=ncl; j<=nch; j++)
2880: out[i][k] +=in[i][j]*b[j][k];
2881: }
1.126 brouard 2882: return out;
2883: }
2884:
2885:
2886: /************* Higher Matrix Product ***************/
2887:
1.235 brouard 2888: 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 2889: {
1.218 brouard 2890: /* Computes the transition matrix starting at age 'age' and combination of covariate values corresponding to ij over
1.126 brouard 2891: 'nhstepm*hstepm*stepm' months (i.e. until
2892: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
2893: nhstepm*hstepm matrices.
2894: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
2895: (typically every 2 years instead of every month which is too big
2896: for the memory).
2897: Model is determined by parameters x and covariates have to be
2898: included manually here.
2899:
2900: */
2901:
2902: int i, j, d, h, k;
1.131 brouard 2903: double **out, cov[NCOVMAX+1];
1.126 brouard 2904: double **newm;
1.187 brouard 2905: double agexact;
1.214 brouard 2906: double agebegin, ageend;
1.126 brouard 2907:
2908: /* Hstepm could be zero and should return the unit matrix */
2909: for (i=1;i<=nlstate+ndeath;i++)
2910: for (j=1;j<=nlstate+ndeath;j++){
2911: oldm[i][j]=(i==j ? 1.0 : 0.0);
2912: po[i][j][0]=(i==j ? 1.0 : 0.0);
2913: }
2914: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
2915: for(h=1; h <=nhstepm; h++){
2916: for(d=1; d <=hstepm; d++){
2917: newm=savm;
2918: /* Covariates have to be included here again */
2919: cov[1]=1.;
1.214 brouard 2920: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 2921: cov[2]=agexact;
2922: if(nagesqr==1)
1.227 brouard 2923: cov[3]= agexact*agexact;
1.235 brouard 2924: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2925: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2926: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
2927: /* printf("hpxij Dummy combi=%d k=%d TvarsD[%d]=V%d TvarsDind[%d]=%d nbcode=%d cov=%lf codtabm(%d,Tvar[%d])=%d \n",ij,k, k, TvarsD[k],k,TvarsDind[k],nbcode[TvarsD[k]][codtabm(ij,k)],cov[2+nagesqr+TvarsDind[k]], ij, k, codtabm(ij,k)); */
2928: }
2929: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2930: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
2931: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2932: /* 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]); */
2933: }
2934: for (k=1; k<=cptcovage;k++){
2935: if(Dummy[Tvar[Tage[k]]]){
2936: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
2937: } else{
2938: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
2939: }
2940: /* 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]); */
2941: }
2942: for (k=1; k<=cptcovprod;k++){ /* */
2943: /* printf("hPxij Prod ij=%d k=%d Tprod[%d]=%d Tvard[%d][1]=V%d, Tvard[%d][2]=V%d\n",ij,k,k,Tprod[k], k,Tvard[k][1], k,Tvard[k][2]); */
2944: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2945: }
2946: /* for (k=1; k<=cptcovn;k++) */
2947: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
2948: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
2949: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
2950: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
2951: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 2952:
2953:
1.126 brouard 2954: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
2955: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.218 brouard 2956: /* right multiplication of oldm by the current matrix */
1.126 brouard 2957: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
2958: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 2959: /* if((int)age == 70){ */
2960: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
2961: /* for(i=1; i<=nlstate+ndeath; i++) { */
2962: /* printf("%d pmmij ",i); */
2963: /* for(j=1;j<=nlstate+ndeath;j++) { */
2964: /* printf("%f ",pmmij[i][j]); */
2965: /* } */
2966: /* printf(" oldm "); */
2967: /* for(j=1;j<=nlstate+ndeath;j++) { */
2968: /* printf("%f ",oldm[i][j]); */
2969: /* } */
2970: /* printf("\n"); */
2971: /* } */
2972: /* } */
1.126 brouard 2973: savm=oldm;
2974: oldm=newm;
2975: }
2976: for(i=1; i<=nlstate+ndeath; i++)
2977: for(j=1;j<=nlstate+ndeath;j++) {
1.218 brouard 2978: po[i][j][h]=newm[i][j];
2979: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 2980: }
1.128 brouard 2981: /*printf("h=%d ",h);*/
1.126 brouard 2982: } /* end h */
1.218 brouard 2983: /* printf("\n H=%d \n",h); */
1.126 brouard 2984: return po;
2985: }
2986:
1.217 brouard 2987: /************* Higher Back Matrix Product ***************/
1.218 brouard 2988: /* 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 ) */
1.222 brouard 2989: double ***hbxij(double ***po, int nhstepm, double age, int hstepm, double *x, double ***prevacurrent, int nlstate, int stepm, int ij )
1.217 brouard 2990: {
1.218 brouard 2991: /* Computes the transition matrix starting at age 'age' over
1.217 brouard 2992: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 2993: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
2994: nhstepm*hstepm matrices.
2995: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
2996: (typically every 2 years instead of every month which is too big
1.217 brouard 2997: for the memory).
1.218 brouard 2998: Model is determined by parameters x and covariates have to be
2999: included manually here.
1.217 brouard 3000:
1.222 brouard 3001: */
1.217 brouard 3002:
3003: int i, j, d, h, k;
3004: double **out, cov[NCOVMAX+1];
3005: double **newm;
3006: double agexact;
3007: double agebegin, ageend;
1.222 brouard 3008: double **oldm, **savm;
1.217 brouard 3009:
1.222 brouard 3010: oldm=oldms;savm=savms;
1.217 brouard 3011: /* Hstepm could be zero and should return the unit matrix */
3012: for (i=1;i<=nlstate+ndeath;i++)
3013: for (j=1;j<=nlstate+ndeath;j++){
3014: oldm[i][j]=(i==j ? 1.0 : 0.0);
3015: po[i][j][0]=(i==j ? 1.0 : 0.0);
3016: }
3017: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3018: for(h=1; h <=nhstepm; h++){
3019: for(d=1; d <=hstepm; d++){
3020: newm=savm;
3021: /* Covariates have to be included here again */
3022: cov[1]=1.;
3023: agexact=age-((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
3024: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
3025: cov[2]=agexact;
3026: if(nagesqr==1)
1.222 brouard 3027: cov[3]= agexact*agexact;
1.218 brouard 3028: for (k=1; k<=cptcovn;k++)
1.222 brouard 3029: cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)];
3030: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.217 brouard 3031: for (k=1; k<=cptcovage;k++) /* Should start at cptcovn+1 */
1.222 brouard 3032: /* cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; */
3033: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
3034: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
1.217 brouard 3035: for (k=1; k<=cptcovprod;k++) /* Useless because included in cptcovn */
1.222 brouard 3036: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
3037: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])]*nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
1.218 brouard 3038:
3039:
1.217 brouard 3040: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3041: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.218 brouard 3042: /* Careful transposed matrix */
1.222 brouard 3043: /* age is in cov[2] */
1.218 brouard 3044: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3045: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3046: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.222 brouard 3047: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);
1.217 brouard 3048: /* if((int)age == 70){ */
3049: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3050: /* for(i=1; i<=nlstate+ndeath; i++) { */
3051: /* printf("%d pmmij ",i); */
3052: /* for(j=1;j<=nlstate+ndeath;j++) { */
3053: /* printf("%f ",pmmij[i][j]); */
3054: /* } */
3055: /* printf(" oldm "); */
3056: /* for(j=1;j<=nlstate+ndeath;j++) { */
3057: /* printf("%f ",oldm[i][j]); */
3058: /* } */
3059: /* printf("\n"); */
3060: /* } */
3061: /* } */
3062: savm=oldm;
3063: oldm=newm;
3064: }
3065: for(i=1; i<=nlstate+ndeath; i++)
3066: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 3067: po[i][j][h]=newm[i][j];
3068: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.217 brouard 3069: }
3070: /*printf("h=%d ",h);*/
3071: } /* end h */
1.222 brouard 3072: /* printf("\n H=%d \n",h); */
1.217 brouard 3073: return po;
3074: }
3075:
3076:
1.162 brouard 3077: #ifdef NLOPT
3078: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
3079: double fret;
3080: double *xt;
3081: int j;
3082: myfunc_data *d2 = (myfunc_data *) pd;
3083: /* xt = (p1-1); */
3084: xt=vector(1,n);
3085: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
3086:
3087: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
3088: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
3089: printf("Function = %.12lf ",fret);
3090: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
3091: printf("\n");
3092: free_vector(xt,1,n);
3093: return fret;
3094: }
3095: #endif
1.126 brouard 3096:
3097: /*************** log-likelihood *************/
3098: double func( double *x)
3099: {
1.226 brouard 3100: int i, ii, j, k, mi, d, kk;
3101: int ioffset=0;
3102: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
3103: double **out;
3104: double lli; /* Individual log likelihood */
3105: int s1, s2;
1.228 brouard 3106: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
1.226 brouard 3107: double bbh, survp;
3108: long ipmx;
3109: double agexact;
3110: /*extern weight */
3111: /* We are differentiating ll according to initial status */
3112: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3113: /*for(i=1;i<imx;i++)
3114: printf(" %d\n",s[4][i]);
3115: */
1.162 brouard 3116:
1.226 brouard 3117: ++countcallfunc;
1.162 brouard 3118:
1.226 brouard 3119: cov[1]=1.;
1.126 brouard 3120:
1.226 brouard 3121: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3122: ioffset=0;
1.226 brouard 3123: if(mle==1){
3124: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3125: /* Computes the values of the ncovmodel covariates of the model
3126: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
3127: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
3128: to be observed in j being in i according to the model.
3129: */
3130: ioffset=2+nagesqr+cptcovage;
1.233 brouard 3131: /* Fixed */
1.234 brouard 3132: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */
3133: cov[ioffset+TvarFind[k]]=covar[Tvar[TvarFind[k]]][i];/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, only V1 is fixed (k=6)*/
3134: }
1.226 brouard 3135: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
3136: is 6, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]
3137: has been calculated etc */
3138: /* For an individual i, wav[i] gives the number of effective waves */
3139: /* We compute the contribution to Likelihood of each effective transition
3140: mw[mi][i] is real wave of the mi th effectve wave */
3141: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
3142: s2=s[mw[mi+1][i]][i];
3143: And the iv th varying covariate is the cotvar[mw[mi+1][i]][iv][i]
3144: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
3145: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
3146: */
3147: for(mi=1; mi<= wav[i]-1; mi++){
1.234 brouard 3148: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
3149: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i];
3150: }
3151: for (ii=1;ii<=nlstate+ndeath;ii++)
3152: for (j=1;j<=nlstate+ndeath;j++){
3153: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3154: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3155: }
3156: for(d=0; d<dh[mi][i]; d++){
3157: newm=savm;
3158: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3159: cov[2]=agexact;
3160: if(nagesqr==1)
3161: cov[3]= agexact*agexact; /* Should be changed here */
3162: for (kk=1; kk<=cptcovage;kk++) {
3163: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
3164: }
3165: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3166: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3167: savm=oldm;
3168: oldm=newm;
3169: } /* end mult */
3170:
3171: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
3172: /* But now since version 0.9 we anticipate for bias at large stepm.
3173: * If stepm is larger than one month (smallest stepm) and if the exact delay
3174: * (in months) between two waves is not a multiple of stepm, we rounded to
3175: * the nearest (and in case of equal distance, to the lowest) interval but now
3176: * we keep into memory the bias bh[mi][i] and also the previous matrix product
3177: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
3178: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 3179: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
3180: * -stepm/2 to stepm/2 .
3181: * For stepm=1 the results are the same as for previous versions of Imach.
3182: * For stepm > 1 the results are less biased than in previous versions.
3183: */
1.234 brouard 3184: s1=s[mw[mi][i]][i];
3185: s2=s[mw[mi+1][i]][i];
3186: bbh=(double)bh[mi][i]/(double)stepm;
3187: /* bias bh is positive if real duration
3188: * is higher than the multiple of stepm and negative otherwise.
3189: */
3190: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
3191: if( s2 > nlstate){
3192: /* i.e. if s2 is a death state and if the date of death is known
3193: then the contribution to the likelihood is the probability to
3194: die between last step unit time and current step unit time,
3195: which is also equal to probability to die before dh
3196: minus probability to die before dh-stepm .
3197: In version up to 0.92 likelihood was computed
3198: as if date of death was unknown. Death was treated as any other
3199: health state: the date of the interview describes the actual state
3200: and not the date of a change in health state. The former idea was
3201: to consider that at each interview the state was recorded
3202: (healthy, disable or death) and IMaCh was corrected; but when we
3203: introduced the exact date of death then we should have modified
3204: the contribution of an exact death to the likelihood. This new
3205: contribution is smaller and very dependent of the step unit
3206: stepm. It is no more the probability to die between last interview
3207: and month of death but the probability to survive from last
3208: interview up to one month before death multiplied by the
3209: probability to die within a month. Thanks to Chris
3210: Jackson for correcting this bug. Former versions increased
3211: mortality artificially. The bad side is that we add another loop
3212: which slows down the processing. The difference can be up to 10%
3213: lower mortality.
3214: */
3215: /* If, at the beginning of the maximization mostly, the
3216: cumulative probability or probability to be dead is
3217: constant (ie = 1) over time d, the difference is equal to
3218: 0. out[s1][3] = savm[s1][3]: probability, being at state
3219: s1 at precedent wave, to be dead a month before current
3220: wave is equal to probability, being at state s1 at
3221: precedent wave, to be dead at mont of the current
3222: wave. Then the observed probability (that this person died)
3223: is null according to current estimated parameter. In fact,
3224: it should be very low but not zero otherwise the log go to
3225: infinity.
3226: */
1.183 brouard 3227: /* #ifdef INFINITYORIGINAL */
3228: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3229: /* #else */
3230: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
3231: /* lli=log(mytinydouble); */
3232: /* else */
3233: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3234: /* #endif */
1.226 brouard 3235: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3236:
1.226 brouard 3237: } else if ( s2==-1 ) { /* alive */
3238: for (j=1,survp=0. ; j<=nlstate; j++)
3239: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3240: /*survp += out[s1][j]; */
3241: lli= log(survp);
3242: }
3243: else if (s2==-4) {
3244: for (j=3,survp=0. ; j<=nlstate; j++)
3245: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3246: lli= log(survp);
3247: }
3248: else if (s2==-5) {
3249: for (j=1,survp=0. ; j<=2; j++)
3250: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3251: lli= log(survp);
3252: }
3253: else{
3254: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3255: /* 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 */
3256: }
3257: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
3258: /*if(lli ==000.0)*/
3259: /*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); */
3260: ipmx +=1;
3261: sw += weight[i];
3262: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3263: /* if (lli < log(mytinydouble)){ */
3264: /* 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); */
3265: /* 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]); */
3266: /* } */
3267: } /* end of wave */
3268: } /* end of individual */
3269: } else if(mle==2){
3270: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3271: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3272: for(mi=1; mi<= wav[i]-1; mi++){
3273: for (ii=1;ii<=nlstate+ndeath;ii++)
3274: for (j=1;j<=nlstate+ndeath;j++){
3275: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3276: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3277: }
3278: for(d=0; d<=dh[mi][i]; d++){
3279: newm=savm;
3280: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3281: cov[2]=agexact;
3282: if(nagesqr==1)
3283: cov[3]= agexact*agexact;
3284: for (kk=1; kk<=cptcovage;kk++) {
3285: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3286: }
3287: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3288: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3289: savm=oldm;
3290: oldm=newm;
3291: } /* end mult */
3292:
3293: s1=s[mw[mi][i]][i];
3294: s2=s[mw[mi+1][i]][i];
3295: bbh=(double)bh[mi][i]/(double)stepm;
3296: 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 */
3297: ipmx +=1;
3298: sw += weight[i];
3299: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3300: } /* end of wave */
3301: } /* end of individual */
3302: } else if(mle==3){ /* exponential inter-extrapolation */
3303: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3304: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3305: for(mi=1; mi<= wav[i]-1; mi++){
3306: for (ii=1;ii<=nlstate+ndeath;ii++)
3307: for (j=1;j<=nlstate+ndeath;j++){
3308: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3309: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3310: }
3311: for(d=0; d<dh[mi][i]; d++){
3312: newm=savm;
3313: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3314: cov[2]=agexact;
3315: if(nagesqr==1)
3316: cov[3]= agexact*agexact;
3317: for (kk=1; kk<=cptcovage;kk++) {
3318: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3319: }
3320: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3321: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3322: savm=oldm;
3323: oldm=newm;
3324: } /* end mult */
3325:
3326: s1=s[mw[mi][i]][i];
3327: s2=s[mw[mi+1][i]][i];
3328: bbh=(double)bh[mi][i]/(double)stepm;
3329: 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 */
3330: ipmx +=1;
3331: sw += weight[i];
3332: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3333: } /* end of wave */
3334: } /* end of individual */
3335: }else if (mle==4){ /* ml=4 no inter-extrapolation */
3336: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3337: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3338: for(mi=1; mi<= wav[i]-1; mi++){
3339: for (ii=1;ii<=nlstate+ndeath;ii++)
3340: for (j=1;j<=nlstate+ndeath;j++){
3341: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3342: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3343: }
3344: for(d=0; d<dh[mi][i]; d++){
3345: newm=savm;
3346: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3347: cov[2]=agexact;
3348: if(nagesqr==1)
3349: cov[3]= agexact*agexact;
3350: for (kk=1; kk<=cptcovage;kk++) {
3351: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3352: }
1.126 brouard 3353:
1.226 brouard 3354: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3355: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3356: savm=oldm;
3357: oldm=newm;
3358: } /* end mult */
3359:
3360: s1=s[mw[mi][i]][i];
3361: s2=s[mw[mi+1][i]][i];
3362: if( s2 > nlstate){
3363: lli=log(out[s1][s2] - savm[s1][s2]);
3364: } else if ( s2==-1 ) { /* alive */
3365: for (j=1,survp=0. ; j<=nlstate; j++)
3366: survp += out[s1][j];
3367: lli= log(survp);
3368: }else{
3369: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3370: }
3371: ipmx +=1;
3372: sw += weight[i];
3373: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.126 brouard 3374: /* 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 3375: } /* end of wave */
3376: } /* end of individual */
3377: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
3378: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3379: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3380: for(mi=1; mi<= wav[i]-1; mi++){
3381: for (ii=1;ii<=nlstate+ndeath;ii++)
3382: for (j=1;j<=nlstate+ndeath;j++){
3383: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3384: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3385: }
3386: for(d=0; d<dh[mi][i]; d++){
3387: newm=savm;
3388: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3389: cov[2]=agexact;
3390: if(nagesqr==1)
3391: cov[3]= agexact*agexact;
3392: for (kk=1; kk<=cptcovage;kk++) {
3393: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3394: }
1.126 brouard 3395:
1.226 brouard 3396: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3397: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3398: savm=oldm;
3399: oldm=newm;
3400: } /* end mult */
3401:
3402: s1=s[mw[mi][i]][i];
3403: s2=s[mw[mi+1][i]][i];
3404: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3405: ipmx +=1;
3406: sw += weight[i];
3407: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3408: /*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]);*/
3409: } /* end of wave */
3410: } /* end of individual */
3411: } /* End of if */
3412: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3413: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3414: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3415: return -l;
1.126 brouard 3416: }
3417:
3418: /*************** log-likelihood *************/
3419: double funcone( double *x)
3420: {
1.228 brouard 3421: /* Same as func but slower because of a lot of printf and if */
1.126 brouard 3422: int i, ii, j, k, mi, d, kk;
1.228 brouard 3423: int ioffset=0;
1.131 brouard 3424: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 3425: double **out;
3426: double lli; /* Individual log likelihood */
3427: double llt;
3428: int s1, s2;
1.228 brouard 3429: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
3430:
1.126 brouard 3431: double bbh, survp;
1.187 brouard 3432: double agexact;
1.214 brouard 3433: double agebegin, ageend;
1.126 brouard 3434: /*extern weight */
3435: /* We are differentiating ll according to initial status */
3436: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3437: /*for(i=1;i<imx;i++)
3438: printf(" %d\n",s[4][i]);
3439: */
3440: cov[1]=1.;
3441:
3442: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3443: ioffset=0;
3444: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.225 brouard 3445: ioffset=2+nagesqr+cptcovage;
1.232 brouard 3446: /* Fixed */
1.224 brouard 3447: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 3448: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
3449: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */
3450: cov[ioffset+TvarFind[k]]=covar[Tvar[TvarFind[k]]][i];/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, only V1 is fixed (k=6)*/
3451: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
3452: /* cov[2+6]=covar[Tvar[6]][i]; */
3453: /* cov[2+6]=covar[2][i]; V2 */
3454: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
3455: /* cov[2+7]=covar[Tvar[7]][i]; */
3456: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
3457: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
3458: /* cov[2+9]=covar[Tvar[9]][i]; */
3459: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 3460: }
1.232 brouard 3461: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
3462: /* 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?)*\/ */
3463: /* } */
1.231 brouard 3464: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
3465: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
3466: /* } */
1.225 brouard 3467:
1.233 brouard 3468:
3469: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.232 brouard 3470: /* Wave varying (but not age varying) */
3471: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.233 brouard 3472: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i];
1.232 brouard 3473: }
3474: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates (single??)*\/ */
1.231 brouard 3475: /* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3476: /* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; */
1.232 brouard 3477: /* k=ioffset-2-nagesqr-cptcovage+itv; /\* position in simple model *\/ */
3478: /* cov[ioffset+itv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; */
1.231 brouard 3479: /* 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 3480: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
3481: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3482: /* /\* 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]); *\/ */
3483: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
3484: /* } */
1.126 brouard 3485: for (ii=1;ii<=nlstate+ndeath;ii++)
1.231 brouard 3486: for (j=1;j<=nlstate+ndeath;j++){
3487: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3488: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3489: }
1.214 brouard 3490:
3491: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
3492: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
3493: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.231 brouard 3494: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
3495: and mw[mi+1][i]. dh depends on stepm.*/
3496: newm=savm;
3497: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3498: cov[2]=agexact;
3499: if(nagesqr==1)
3500: cov[3]= agexact*agexact;
3501: for (kk=1; kk<=cptcovage;kk++) {
3502: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3503: }
3504: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
3505: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3506: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3507: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3508: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
3509: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
3510: savm=oldm;
3511: oldm=newm;
1.126 brouard 3512: } /* end mult */
3513:
3514: s1=s[mw[mi][i]][i];
3515: s2=s[mw[mi+1][i]][i];
1.217 brouard 3516: /* if(s2==-1){ */
3517: /* printf(" s1=%d, s2=%d i=%d \n", s1, s2, i); */
3518: /* /\* exit(1); *\/ */
3519: /* } */
1.126 brouard 3520: bbh=(double)bh[mi][i]/(double)stepm;
3521: /* bias is positive if real duration
3522: * is higher than the multiple of stepm and negative otherwise.
3523: */
3524: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.232 brouard 3525: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3526: } else if ( s2==-1 ) { /* alive */
1.232 brouard 3527: for (j=1,survp=0. ; j<=nlstate; j++)
3528: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3529: lli= log(survp);
1.126 brouard 3530: }else if (mle==1){
1.232 brouard 3531: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 3532: } else if(mle==2){
1.232 brouard 3533: 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 3534: } else if(mle==3){ /* exponential inter-extrapolation */
1.232 brouard 3535: 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 3536: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.232 brouard 3537: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 3538: } else{ /* mle=0 back to 1 */
1.232 brouard 3539: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3540: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 3541: } /* End of if */
3542: ipmx +=1;
3543: sw += weight[i];
3544: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.132 brouard 3545: /*printf("i=%6d s1=%1d s2=%1d mi=%1d mw=%1d dh=%3d prob=%10.6f w=%6.4f out=%10.6f sav=%10.6f\n",i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],out[s1][s2],savm[s1][s2]); */
1.126 brouard 3546: if(globpr){
1.232 brouard 3547: fprintf(ficresilk,"%9ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 3548: %11.6f %11.6f %11.6f ", \
1.232 brouard 3549: num[i], agebegin, ageend, i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],weight[i]*gipmx/gsw,
3550: 2*weight[i]*lli,out[s1][s2],savm[s1][s2]);
3551: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
3552: llt +=ll[k]*gipmx/gsw;
3553: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
3554: }
3555: fprintf(ficresilk," %10.6f\n", -llt);
1.126 brouard 3556: }
1.232 brouard 3557: } /* end of wave */
3558: } /* end of individual */
3559: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3560: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3561: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3562: if(globpr==0){ /* First time we count the contributions and weights */
3563: gipmx=ipmx;
3564: gsw=sw;
3565: }
3566: return -l;
1.126 brouard 3567: }
3568:
3569:
3570: /*************** function likelione ***********/
3571: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*funcone)(double []))
3572: {
3573: /* This routine should help understanding what is done with
3574: the selection of individuals/waves and
3575: to check the exact contribution to the likelihood.
3576: Plotting could be done.
3577: */
3578: int k;
3579:
3580: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 3581: strcpy(fileresilk,"ILK_");
1.202 brouard 3582: strcat(fileresilk,fileresu);
1.126 brouard 3583: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
3584: printf("Problem with resultfile: %s\n", fileresilk);
3585: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
3586: }
1.214 brouard 3587: 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");
3588: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 3589: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
3590: for(k=1; k<=nlstate; k++)
3591: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
3592: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total)\n");
3593: }
3594:
3595: *fretone=(*funcone)(p);
3596: if(*globpri !=0){
3597: fclose(ficresilk);
1.205 brouard 3598: if (mle ==0)
3599: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
3600: else if(mle >=1)
3601: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
3602: 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));
1.207 brouard 3603:
1.208 brouard 3604:
3605: for (k=1; k<= nlstate ; k++) {
1.211 brouard 3606: 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 3607: <img src=\"%s-p%dj.png\">",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
3608: }
1.207 brouard 3609: 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 3610: <img src=\"%s-ori.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 3611: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.204 brouard 3612: <img src=\"%s-dest.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 3613: fflush(fichtm);
1.205 brouard 3614: }
1.126 brouard 3615: return;
3616: }
3617:
3618:
3619: /*********** Maximum Likelihood Estimation ***************/
3620:
3621: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
3622: {
1.165 brouard 3623: int i,j, iter=0;
1.126 brouard 3624: double **xi;
3625: double fret;
3626: double fretone; /* Only one call to likelihood */
3627: /* char filerespow[FILENAMELENGTH];*/
1.162 brouard 3628:
3629: #ifdef NLOPT
3630: int creturn;
3631: nlopt_opt opt;
3632: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
3633: double *lb;
3634: double minf; /* the minimum objective value, upon return */
3635: double * p1; /* Shifted parameters from 0 instead of 1 */
3636: myfunc_data dinst, *d = &dinst;
3637: #endif
3638:
3639:
1.126 brouard 3640: xi=matrix(1,npar,1,npar);
3641: for (i=1;i<=npar;i++)
3642: for (j=1;j<=npar;j++)
3643: xi[i][j]=(i==j ? 1.0 : 0.0);
3644: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 3645: strcpy(filerespow,"POW_");
1.126 brouard 3646: strcat(filerespow,fileres);
3647: if((ficrespow=fopen(filerespow,"w"))==NULL) {
3648: printf("Problem with resultfile: %s\n", filerespow);
3649: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
3650: }
3651: fprintf(ficrespow,"# Powell\n# iter -2*LL");
3652: for (i=1;i<=nlstate;i++)
3653: for(j=1;j<=nlstate+ndeath;j++)
3654: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
3655: fprintf(ficrespow,"\n");
1.162 brouard 3656: #ifdef POWELL
1.126 brouard 3657: powell(p,xi,npar,ftol,&iter,&fret,func);
1.162 brouard 3658: #endif
1.126 brouard 3659:
1.162 brouard 3660: #ifdef NLOPT
3661: #ifdef NEWUOA
3662: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
3663: #else
3664: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
3665: #endif
3666: lb=vector(0,npar-1);
3667: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
3668: nlopt_set_lower_bounds(opt, lb);
3669: nlopt_set_initial_step1(opt, 0.1);
3670:
3671: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
3672: d->function = func;
3673: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
3674: nlopt_set_min_objective(opt, myfunc, d);
3675: nlopt_set_xtol_rel(opt, ftol);
3676: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
3677: printf("nlopt failed! %d\n",creturn);
3678: }
3679: else {
3680: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
3681: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
3682: iter=1; /* not equal */
3683: }
3684: nlopt_destroy(opt);
3685: #endif
1.126 brouard 3686: free_matrix(xi,1,npar,1,npar);
3687: fclose(ficrespow);
1.203 brouard 3688: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
3689: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 3690: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 3691:
3692: }
3693:
3694: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 3695: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 3696: {
3697: double **a,**y,*x,pd;
1.203 brouard 3698: /* double **hess; */
1.164 brouard 3699: int i, j;
1.126 brouard 3700: int *indx;
3701:
3702: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 3703: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 3704: void lubksb(double **a, int npar, int *indx, double b[]) ;
3705: void ludcmp(double **a, int npar, int *indx, double *d) ;
3706: double gompertz(double p[]);
1.203 brouard 3707: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 3708:
3709: printf("\nCalculation of the hessian matrix. Wait...\n");
3710: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
3711: for (i=1;i<=npar;i++){
1.203 brouard 3712: printf("%d-",i);fflush(stdout);
3713: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 3714:
3715: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
3716:
3717: /* printf(" %f ",p[i]);
3718: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
3719: }
3720:
3721: for (i=1;i<=npar;i++) {
3722: for (j=1;j<=npar;j++) {
3723: if (j>i) {
1.203 brouard 3724: printf(".%d-%d",i,j);fflush(stdout);
3725: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
3726: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 3727:
3728: hess[j][i]=hess[i][j];
3729: /*printf(" %lf ",hess[i][j]);*/
3730: }
3731: }
3732: }
3733: printf("\n");
3734: fprintf(ficlog,"\n");
3735:
3736: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
3737: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
3738:
3739: a=matrix(1,npar,1,npar);
3740: y=matrix(1,npar,1,npar);
3741: x=vector(1,npar);
3742: indx=ivector(1,npar);
3743: for (i=1;i<=npar;i++)
3744: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
3745: ludcmp(a,npar,indx,&pd);
3746:
3747: for (j=1;j<=npar;j++) {
3748: for (i=1;i<=npar;i++) x[i]=0;
3749: x[j]=1;
3750: lubksb(a,npar,indx,x);
3751: for (i=1;i<=npar;i++){
3752: matcov[i][j]=x[i];
3753: }
3754: }
3755:
3756: printf("\n#Hessian matrix#\n");
3757: fprintf(ficlog,"\n#Hessian matrix#\n");
3758: for (i=1;i<=npar;i++) {
3759: for (j=1;j<=npar;j++) {
1.203 brouard 3760: printf("%.6e ",hess[i][j]);
3761: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 3762: }
3763: printf("\n");
3764: fprintf(ficlog,"\n");
3765: }
3766:
1.203 brouard 3767: /* printf("\n#Covariance matrix#\n"); */
3768: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
3769: /* for (i=1;i<=npar;i++) { */
3770: /* for (j=1;j<=npar;j++) { */
3771: /* printf("%.6e ",matcov[i][j]); */
3772: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
3773: /* } */
3774: /* printf("\n"); */
3775: /* fprintf(ficlog,"\n"); */
3776: /* } */
3777:
1.126 brouard 3778: /* Recompute Inverse */
1.203 brouard 3779: /* for (i=1;i<=npar;i++) */
3780: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
3781: /* ludcmp(a,npar,indx,&pd); */
3782:
3783: /* printf("\n#Hessian matrix recomputed#\n"); */
3784:
3785: /* for (j=1;j<=npar;j++) { */
3786: /* for (i=1;i<=npar;i++) x[i]=0; */
3787: /* x[j]=1; */
3788: /* lubksb(a,npar,indx,x); */
3789: /* for (i=1;i<=npar;i++){ */
3790: /* y[i][j]=x[i]; */
3791: /* printf("%.3e ",y[i][j]); */
3792: /* fprintf(ficlog,"%.3e ",y[i][j]); */
3793: /* } */
3794: /* printf("\n"); */
3795: /* fprintf(ficlog,"\n"); */
3796: /* } */
3797:
3798: /* Verifying the inverse matrix */
3799: #ifdef DEBUGHESS
3800: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 3801:
1.203 brouard 3802: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
3803: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 3804:
3805: for (j=1;j<=npar;j++) {
3806: for (i=1;i<=npar;i++){
1.203 brouard 3807: printf("%.2f ",y[i][j]);
3808: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 3809: }
3810: printf("\n");
3811: fprintf(ficlog,"\n");
3812: }
1.203 brouard 3813: #endif
1.126 brouard 3814:
3815: free_matrix(a,1,npar,1,npar);
3816: free_matrix(y,1,npar,1,npar);
3817: free_vector(x,1,npar);
3818: free_ivector(indx,1,npar);
1.203 brouard 3819: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 3820:
3821:
3822: }
3823:
3824: /*************** hessian matrix ****************/
3825: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 3826: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 3827: int i;
3828: int l=1, lmax=20;
1.203 brouard 3829: double k1,k2, res, fx;
1.132 brouard 3830: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 3831: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
3832: int k=0,kmax=10;
3833: double l1;
3834:
3835: fx=func(x);
3836: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 3837: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 3838: l1=pow(10,l);
3839: delts=delt;
3840: for(k=1 ; k <kmax; k=k+1){
3841: delt = delta*(l1*k);
3842: p2[theta]=x[theta] +delt;
1.145 brouard 3843: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 3844: p2[theta]=x[theta]-delt;
3845: k2=func(p2)-fx;
3846: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 3847: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 3848:
1.203 brouard 3849: #ifdef DEBUGHESSII
1.126 brouard 3850: 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);
3851: 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);
3852: #endif
3853: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
3854: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
3855: k=kmax;
3856: }
3857: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 3858: k=kmax; l=lmax*10;
1.126 brouard 3859: }
3860: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
3861: delts=delt;
3862: }
1.203 brouard 3863: } /* End loop k */
1.126 brouard 3864: }
3865: delti[theta]=delts;
3866: return res;
3867:
3868: }
3869:
1.203 brouard 3870: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 3871: {
3872: int i;
1.164 brouard 3873: int l=1, lmax=20;
1.126 brouard 3874: double k1,k2,k3,k4,res,fx;
1.132 brouard 3875: double p2[MAXPARM+1];
1.203 brouard 3876: int k, kmax=1;
3877: double v1, v2, cv12, lc1, lc2;
1.208 brouard 3878:
3879: int firstime=0;
1.203 brouard 3880:
1.126 brouard 3881: fx=func(x);
1.203 brouard 3882: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 3883: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 3884: p2[thetai]=x[thetai]+delti[thetai]*k;
3885: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 3886: k1=func(p2)-fx;
3887:
1.203 brouard 3888: p2[thetai]=x[thetai]+delti[thetai]*k;
3889: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 3890: k2=func(p2)-fx;
3891:
1.203 brouard 3892: p2[thetai]=x[thetai]-delti[thetai]*k;
3893: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 3894: k3=func(p2)-fx;
3895:
1.203 brouard 3896: p2[thetai]=x[thetai]-delti[thetai]*k;
3897: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 3898: k4=func(p2)-fx;
1.203 brouard 3899: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
3900: if(k1*k2*k3*k4 <0.){
1.208 brouard 3901: firstime=1;
1.203 brouard 3902: kmax=kmax+10;
1.208 brouard 3903: }
3904: if(kmax >=10 || firstime ==1){
1.218 brouard 3905: printf("Warning: directions %d-%d, you are not estimating the Hessian at the exact maximum likelihood; you may increase ftol=%.2e\n",thetai,thetaj, ftol);
3906: fprintf(ficlog,"Warning: directions %d-%d, you are not estimating the Hessian at the exact maximum likelihood; you may increase ftol=%.2e\n",thetai,thetaj, ftol);
1.203 brouard 3907: 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);
3908: 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);
3909: }
3910: #ifdef DEBUGHESSIJ
3911: v1=hess[thetai][thetai];
3912: v2=hess[thetaj][thetaj];
3913: cv12=res;
3914: /* Computing eigen value of Hessian matrix */
3915: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
3916: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
3917: if ((lc2 <0) || (lc1 <0) ){
3918: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
3919: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
3920: 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);
3921: 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);
3922: }
1.126 brouard 3923: #endif
3924: }
3925: return res;
3926: }
3927:
1.203 brouard 3928: /* Not done yet: Was supposed to fix if not exactly at the maximum */
3929: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
3930: /* { */
3931: /* int i; */
3932: /* int l=1, lmax=20; */
3933: /* double k1,k2,k3,k4,res,fx; */
3934: /* double p2[MAXPARM+1]; */
3935: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
3936: /* int k=0,kmax=10; */
3937: /* double l1; */
3938:
3939: /* fx=func(x); */
3940: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
3941: /* l1=pow(10,l); */
3942: /* delts=delt; */
3943: /* for(k=1 ; k <kmax; k=k+1){ */
3944: /* delt = delti*(l1*k); */
3945: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
3946: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
3947: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
3948: /* k1=func(p2)-fx; */
3949:
3950: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
3951: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
3952: /* k2=func(p2)-fx; */
3953:
3954: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
3955: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
3956: /* k3=func(p2)-fx; */
3957:
3958: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
3959: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
3960: /* k4=func(p2)-fx; */
3961: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
3962: /* #ifdef DEBUGHESSIJ */
3963: /* 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); */
3964: /* 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); */
3965: /* #endif */
3966: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
3967: /* k=kmax; */
3968: /* } */
3969: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
3970: /* k=kmax; l=lmax*10; */
3971: /* } */
3972: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
3973: /* delts=delt; */
3974: /* } */
3975: /* } /\* End loop k *\/ */
3976: /* } */
3977: /* delti[theta]=delts; */
3978: /* return res; */
3979: /* } */
3980:
3981:
1.126 brouard 3982: /************** Inverse of matrix **************/
3983: void ludcmp(double **a, int n, int *indx, double *d)
3984: {
3985: int i,imax,j,k;
3986: double big,dum,sum,temp;
3987: double *vv;
3988:
3989: vv=vector(1,n);
3990: *d=1.0;
3991: for (i=1;i<=n;i++) {
3992: big=0.0;
3993: for (j=1;j<=n;j++)
3994: if ((temp=fabs(a[i][j])) > big) big=temp;
3995: if (big == 0.0) nrerror("Singular matrix in routine ludcmp");
3996: vv[i]=1.0/big;
3997: }
3998: for (j=1;j<=n;j++) {
3999: for (i=1;i<j;i++) {
4000: sum=a[i][j];
4001: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
4002: a[i][j]=sum;
4003: }
4004: big=0.0;
4005: for (i=j;i<=n;i++) {
4006: sum=a[i][j];
4007: for (k=1;k<j;k++)
4008: sum -= a[i][k]*a[k][j];
4009: a[i][j]=sum;
4010: if ( (dum=vv[i]*fabs(sum)) >= big) {
4011: big=dum;
4012: imax=i;
4013: }
4014: }
4015: if (j != imax) {
4016: for (k=1;k<=n;k++) {
4017: dum=a[imax][k];
4018: a[imax][k]=a[j][k];
4019: a[j][k]=dum;
4020: }
4021: *d = -(*d);
4022: vv[imax]=vv[j];
4023: }
4024: indx[j]=imax;
4025: if (a[j][j] == 0.0) a[j][j]=TINY;
4026: if (j != n) {
4027: dum=1.0/(a[j][j]);
4028: for (i=j+1;i<=n;i++) a[i][j] *= dum;
4029: }
4030: }
4031: free_vector(vv,1,n); /* Doesn't work */
4032: ;
4033: }
4034:
4035: void lubksb(double **a, int n, int *indx, double b[])
4036: {
4037: int i,ii=0,ip,j;
4038: double sum;
4039:
4040: for (i=1;i<=n;i++) {
4041: ip=indx[i];
4042: sum=b[ip];
4043: b[ip]=b[i];
4044: if (ii)
4045: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
4046: else if (sum) ii=i;
4047: b[i]=sum;
4048: }
4049: for (i=n;i>=1;i--) {
4050: sum=b[i];
4051: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
4052: b[i]=sum/a[i][i];
4053: }
4054: }
4055:
4056: void pstamp(FILE *fichier)
4057: {
1.196 brouard 4058: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 4059: }
4060:
4061: /************ Frequencies ********************/
1.226 brouard 4062: void freqsummary(char fileres[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
4063: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
4064: int firstpass, int lastpass, int stepm, int weightopt, char model[])
4065: { /* Some frequencies */
4066:
1.227 brouard 4067: int i, m, jk, j1, bool, z1,j, k, iv;
1.226 brouard 4068: int iind=0, iage=0;
4069: int mi; /* Effective wave */
4070: int first;
4071: double ***freq; /* Frequencies */
4072: double *meanq;
4073: double **meanqt;
4074: double *pp, **prop, *posprop, *pospropt;
4075: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
4076: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
4077: double agebegin, ageend;
4078:
4079: pp=vector(1,nlstate);
4080: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+3+AGEMARGE);
4081: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
4082: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
4083: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
4084: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
4085: meanqt=matrix(1,lastpass,1,nqtveff);
4086: strcpy(fileresp,"P_");
4087: strcat(fileresp,fileresu);
4088: /*strcat(fileresphtm,fileresu);*/
4089: if((ficresp=fopen(fileresp,"w"))==NULL) {
4090: printf("Problem with prevalence resultfile: %s\n", fileresp);
4091: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
4092: exit(0);
4093: }
1.214 brouard 4094:
1.226 brouard 4095: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
4096: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
4097: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4098: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4099: fflush(ficlog);
4100: exit(70);
4101: }
4102: else{
4103: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.214 brouard 4104: <hr size=\"2\" color=\"#EC5E5E\"> \n\
4105: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4106: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4107: }
1.237 brouard 4108: fprintf(ficresphtm,"Current page is file <a href=\"%s\">%s</a><br>\n\n<h4>Frequencies and prevalence by age at begin of transition and dummy covariate value at beginning of transition</h4>\n",fileresphtm, fileresphtm);
1.214 brouard 4109:
1.226 brouard 4110: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
4111: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
4112: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4113: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4114: fflush(ficlog);
4115: exit(70);
4116: }
4117: else{
4118: fprintf(ficresphtmfr,"<html><head>\n<title>IMaCh PHTM_Frequency table %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.214 brouard 4119: <hr size=\"2\" color=\"#EC5E5E\"> \n\
4120: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4121: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4122: }
4123: fprintf(ficresphtmfr,"Current page is file <a href=\"%s\">%s</a><br>\n\n<h4>Frequencies of all effective transitions by age at begin of transition </h4>Unknown status is -1<br/>\n",fileresphtmfr, fileresphtmfr);
1.214 brouard 4124:
1.226 brouard 4125: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+3+AGEMARGE);
4126: j1=0;
1.126 brouard 4127:
1.227 brouard 4128: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
4129: j=cptcoveff; /* Only dummy covariates of the model */
1.226 brouard 4130: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.220 brouard 4131:
1.226 brouard 4132: first=1;
1.220 brouard 4133:
1.226 brouard 4134: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
4135: reference=low_education V1=0,V2=0
4136: med_educ V1=1 V2=0,
4137: high_educ V1=0 V2=1
4138: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcoveff
4139: */
1.126 brouard 4140:
1.227 brouard 4141: for (j1 = 1; j1 <= (int) pow(2,j); j1++){ /* Loop on covariates combination in order of model, excluding quantitatives V4=0, V3=0 for example, fixed or varying covariates */
1.226 brouard 4142: posproptt=0.;
4143: /*printf("cptcoveff=%d Tvaraff=%d", cptcoveff,Tvaraff[1]);
4144: scanf("%d", i);*/
4145: for (i=-5; i<=nlstate+ndeath; i++)
4146: for (jk=-5; jk<=nlstate+ndeath; jk++)
1.231 brouard 4147: for(m=iagemin; m <= iagemax+3; m++)
4148: freq[i][jk][m]=0;
4149:
1.226 brouard 4150: for (i=1; i<=nlstate; i++) {
4151: for(m=iagemin; m <= iagemax+3; m++)
1.231 brouard 4152: prop[i][m]=0;
1.226 brouard 4153: posprop[i]=0;
4154: pospropt[i]=0;
4155: }
1.227 brouard 4156: /* for (z1=1; z1<= nqfveff; z1++) { */
4157: /* meanq[z1]+=0.; */
4158: /* for(m=1;m<=lastpass;m++){ */
4159: /* meanqt[m][z1]=0.; */
4160: /* } */
4161: /* } */
1.231 brouard 4162:
1.226 brouard 4163: dateintsum=0;
4164: k2cpt=0;
1.227 brouard 4165: /* For that combination of covariate j1, we count and print the frequencies in one pass */
1.226 brouard 4166: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
4167: bool=1;
1.227 brouard 4168: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
1.234 brouard 4169: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
1.227 brouard 4170: /* for (z1=1; z1<= nqfveff; z1++) { */
4171: /* meanq[z1]+=coqvar[Tvar[z1]][iind]; /\* Computes mean of quantitative with selected filter *\/ */
4172: /* } */
1.234 brouard 4173: for (z1=1; z1<=cptcoveff; z1++) {
4174: /* if(Tvaraff[z1] ==-20){ */
4175: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
4176: /* }else if(Tvaraff[z1] ==-10){ */
4177: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
4178: /* }else */
4179: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]){
4180: /* Tests if this individual iind responded to j1 (V4=1 V3=0) */
4181: bool=0;
4182: /* 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",
4183: bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),
4184: j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
4185: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
4186: } /* Onlyf fixed */
4187: } /* end z1 */
4188: } /* cptcovn > 0 */
1.227 brouard 4189: } /* end any */
4190: if (bool==1){ /* We selected an individual iind satisfying combination j1 or all fixed */
1.234 brouard 4191: /* for(m=firstpass; m<=lastpass; m++){ */
4192: for(mi=1; mi<wav[iind];mi++){ /* For that wave */
4193: m=mw[mi][iind];
4194: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
4195: for (z1=1; z1<=cptcoveff; z1++) {
4196: if( Fixed[Tmodelind[z1]]==1){
4197: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
4198: if (cotvar[m][iv][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality */
4199: bool=0;
4200: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
4201: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
4202: bool=0;
4203: }
4204: }
4205: }
4206: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
4207: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
4208: if(bool==1){
4209: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
4210: and mw[mi+1][iind]. dh depends on stepm. */
4211: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
4212: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
4213: if(m >=firstpass && m <=lastpass){
4214: k2=anint[m][iind]+(mint[m][iind]/12.);
4215: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
4216: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
4217: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
4218: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
4219: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
4220: if (m<lastpass) {
4221: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
4222: /* 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]); */
4223: if(s[m][iind]==-1)
4224: 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.));
4225: freq[s[m][iind]][s[m+1][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
4226: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
4227: 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 */
4228: }
4229: } /* end if between passes */
4230: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99)) {
4231: dateintsum=dateintsum+k2;
4232: k2cpt++;
4233: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
4234: }
4235: } /* end bool 2 */
4236: } /* end m */
1.226 brouard 4237: } /* end bool */
4238: } /* end iind = 1 to imx */
4239: /* prop[s][age] is feeded for any initial and valid live state as well as
4240: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
1.231 brouard 4241:
4242:
1.226 brouard 4243: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
4244: pstamp(ficresp);
1.227 brouard 4245: /* if (ncoveff>0) { */
4246: if (cptcoveff>0) {
1.226 brouard 4247: fprintf(ficresp, "\n#********** Variable ");
4248: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
4249: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
1.227 brouard 4250: for (z1=1; z1<=cptcoveff; z1++){
1.234 brouard 4251: fprintf(ficresp, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4252: fprintf(ficresphtm, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4253: fprintf(ficresphtmfr, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.226 brouard 4254: }
4255: fprintf(ficresp, "**********\n#");
4256: fprintf(ficresphtm, "**********</h3>\n");
4257: fprintf(ficresphtmfr, "**********</h3>\n");
4258: fprintf(ficlog, "\n#********** Variable ");
1.227 brouard 4259: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficlog, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.226 brouard 4260: fprintf(ficlog, "**********\n");
4261: }
4262: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
4263: for(i=1; i<=nlstate;i++) {
4264: fprintf(ficresp, " Age Prev(%d) N(%d) N",i,i);
4265: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
4266: }
4267: fprintf(ficresp, "\n");
4268: fprintf(ficresphtm, "\n");
1.231 brouard 4269:
1.226 brouard 4270: /* Header of frequency table by age */
4271: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
4272: fprintf(ficresphtmfr,"<th>Age</th> ");
4273: for(jk=-1; jk <=nlstate+ndeath; jk++){
4274: for(m=-1; m <=nlstate+ndeath; m++){
1.234 brouard 4275: if(jk!=0 && m!=0)
4276: fprintf(ficresphtmfr,"<th>%d%d</th> ",jk,m);
1.226 brouard 4277: }
4278: }
4279: fprintf(ficresphtmfr, "\n");
1.231 brouard 4280:
1.226 brouard 4281: /* For each age */
4282: for(iage=iagemin; iage <= iagemax+3; iage++){
4283: fprintf(ficresphtm,"<tr>");
4284: if(iage==iagemax+1){
1.231 brouard 4285: fprintf(ficlog,"1");
4286: fprintf(ficresphtmfr,"<tr><th>0</th> ");
1.226 brouard 4287: }else if(iage==iagemax+2){
1.231 brouard 4288: fprintf(ficlog,"0");
4289: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
1.226 brouard 4290: }else if(iage==iagemax+3){
1.231 brouard 4291: fprintf(ficlog,"Total");
4292: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
1.226 brouard 4293: }else{
1.231 brouard 4294: if(first==1){
4295: first=0;
4296: printf("See log file for details...\n");
4297: }
4298: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
4299: fprintf(ficlog,"Age %d", iage);
1.226 brouard 4300: }
4301: for(jk=1; jk <=nlstate ; jk++){
1.231 brouard 4302: for(m=-1, pp[jk]=0; m <=nlstate+ndeath ; m++)
4303: pp[jk] += freq[jk][m][iage];
1.226 brouard 4304: }
4305: for(jk=1; jk <=nlstate ; jk++){
1.231 brouard 4306: for(m=-1, pos=0; m <=0 ; m++)
4307: pos += freq[jk][m][iage];
4308: if(pp[jk]>=1.e-10){
4309: if(first==1){
4310: printf(" %d.=%.0f loss[%d]=%.1f%%",jk,pp[jk],jk,100*pos/pp[jk]);
4311: }
4312: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",jk,pp[jk],jk,100*pos/pp[jk]);
4313: }else{
4314: if(first==1)
4315: printf(" %d.=%.0f loss[%d]=NaNQ%%",jk,pp[jk],jk);
4316: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",jk,pp[jk],jk);
4317: }
1.226 brouard 4318: }
1.231 brouard 4319:
1.226 brouard 4320: for(jk=1; jk <=nlstate ; jk++){
1.231 brouard 4321: /* posprop[jk]=0; */
4322: for(m=0, pp[jk]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
4323: pp[jk] += freq[jk][m][iage];
1.226 brouard 4324: } /* pp[jk] is the total number of transitions starting from state jk and any ending status until this age */
1.231 brouard 4325:
1.226 brouard 4326: for(jk=1,pos=0, pospropta=0.; jk <=nlstate ; jk++){
1.231 brouard 4327: pos += pp[jk]; /* pos is the total number of transitions until this age */
4328: posprop[jk] += prop[jk][iage]; /* prop is the number of transitions from a live state
4329: from jk at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
4330: pospropta += prop[jk][iage]; /* prop is the number of transitions from a live state
4331: from jk at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
1.226 brouard 4332: }
4333: for(jk=1; jk <=nlstate ; jk++){
1.231 brouard 4334: if(pos>=1.e-5){
4335: if(first==1)
4336: printf(" %d.=%.0f prev[%d]=%.1f%%",jk,pp[jk],jk,100*pp[jk]/pos);
4337: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",jk,pp[jk],jk,100*pp[jk]/pos);
4338: }else{
4339: if(first==1)
4340: printf(" %d.=%.0f prev[%d]=NaNQ%%",jk,pp[jk],jk);
4341: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",jk,pp[jk],jk);
4342: }
4343: if( iage <= iagemax){
4344: if(pos>=1.e-5){
4345: fprintf(ficresp," %d %.5f %.0f %.0f",iage,prop[jk][iage]/pospropta, prop[jk][iage],pospropta);
4346: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[jk][iage]/pospropta, prop[jk][iage],pospropta);
4347: /*probs[iage][jk][j1]= pp[jk]/pos;*/
4348: /*printf("\niage=%d jk=%d j1=%d %.5f %.0f %.0f %f",iage,jk,j1,pp[jk]/pos, pp[jk],pos,probs[iage][jk][j1]);*/
4349: }
4350: else{
4351: fprintf(ficresp," %d NaNq %.0f %.0f",iage,prop[jk][iage],pospropta);
4352: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[jk][iage],pospropta);
4353: }
4354: }
4355: pospropt[jk] +=posprop[jk];
1.226 brouard 4356: } /* end loop jk */
4357: /* pospropt=0.; */
4358: for(jk=-1; jk <=nlstate+ndeath; jk++){
1.231 brouard 4359: for(m=-1; m <=nlstate+ndeath; m++){
4360: if(freq[jk][m][iage] !=0 ) { /* minimizing output */
4361: if(first==1){
4362: printf(" %d%d=%.0f",jk,m,freq[jk][m][iage]);
4363: }
4364: fprintf(ficlog," %d%d=%.0f",jk,m,freq[jk][m][iage]);
4365: }
4366: if(jk!=0 && m!=0)
4367: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[jk][m][iage]);
4368: }
1.226 brouard 4369: } /* end loop jk */
4370: posproptt=0.;
4371: for(jk=1; jk <=nlstate; jk++){
1.231 brouard 4372: posproptt += pospropt[jk];
1.226 brouard 4373: }
4374: fprintf(ficresphtmfr,"</tr>\n ");
4375: if(iage <= iagemax){
1.231 brouard 4376: fprintf(ficresp,"\n");
4377: fprintf(ficresphtm,"</tr>\n");
1.226 brouard 4378: }
4379: if(first==1)
1.231 brouard 4380: printf("Others in log...\n");
1.226 brouard 4381: fprintf(ficlog,"\n");
4382: } /* end loop age iage */
4383: fprintf(ficresphtm,"<tr><th>Tot</th>");
4384: for(jk=1; jk <=nlstate ; jk++){
4385: if(posproptt < 1.e-5){
1.231 brouard 4386: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[jk],posproptt);
1.226 brouard 4387: }else{
1.231 brouard 4388: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[jk]/posproptt,pospropt[jk],posproptt);
1.226 brouard 4389: }
4390: }
4391: fprintf(ficresphtm,"</tr>\n");
4392: fprintf(ficresphtm,"</table>\n");
4393: fprintf(ficresphtmfr,"</table>\n");
4394: if(posproptt < 1.e-5){
4395: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
4396: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
4397: fprintf(ficres,"\n This combination (%d) is not valid and no result will be produced\n\n",j1);
4398: invalidvarcomb[j1]=1;
4399: }else{
4400: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced.</p>",j1);
4401: invalidvarcomb[j1]=0;
4402: }
4403: fprintf(ficresphtmfr,"</table>\n");
4404: } /* end selected combination of covariate j1 */
4405: dateintmean=dateintsum/k2cpt;
1.231 brouard 4406:
1.226 brouard 4407: fclose(ficresp);
4408: fclose(ficresphtm);
4409: fclose(ficresphtmfr);
4410: free_vector(meanq,1,nqfveff);
4411: free_matrix(meanqt,1,lastpass,1,nqtveff);
4412: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+3+AGEMARGE);
4413: free_vector(pospropt,1,nlstate);
4414: free_vector(posprop,1,nlstate);
4415: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+3+AGEMARGE);
4416: free_vector(pp,1,nlstate);
4417: /* End of freqsummary */
4418: }
1.126 brouard 4419:
4420: /************ Prevalence ********************/
1.227 brouard 4421: 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)
4422: {
4423: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
4424: in each health status at the date of interview (if between dateprev1 and dateprev2).
4425: We still use firstpass and lastpass as another selection.
4426: */
1.126 brouard 4427:
1.227 brouard 4428: int i, m, jk, j1, bool, z1,j, iv;
4429: int mi; /* Effective wave */
4430: int iage;
4431: double agebegin, ageend;
4432:
4433: double **prop;
4434: double posprop;
4435: double y2; /* in fractional years */
4436: int iagemin, iagemax;
4437: int first; /** to stop verbosity which is redirected to log file */
4438:
4439: iagemin= (int) agemin;
4440: iagemax= (int) agemax;
4441: /*pp=vector(1,nlstate);*/
4442: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+3+AGEMARGE);
4443: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
4444: j1=0;
1.222 brouard 4445:
1.227 brouard 4446: /*j=cptcoveff;*/
4447: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 4448:
1.227 brouard 4449: first=1;
4450: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of covariate */
4451: for (i=1; i<=nlstate; i++)
4452: for(iage=iagemin-AGEMARGE; iage <= iagemax+3+AGEMARGE; iage++)
4453: prop[i][iage]=0.0;
4454: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
4455: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
4456: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
4457:
4458: for (i=1; i<=imx; i++) { /* Each individual */
4459: bool=1;
4460: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
4461: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
4462: m=mw[mi][i];
4463: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
4464: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
4465: for (z1=1; z1<=cptcoveff; z1++){
4466: if( Fixed[Tmodelind[z1]]==1){
4467: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
4468: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality */
4469: bool=0;
4470: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
4471: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
4472: bool=0;
4473: }
4474: }
4475: if(bool==1){ /* Otherwise we skip that wave/person */
4476: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
4477: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
4478: if(m >=firstpass && m <=lastpass){
4479: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
4480: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
4481: if(agev[m][i]==0) agev[m][i]=iagemax+1;
4482: if(agev[m][i]==1) agev[m][i]=iagemax+2;
4483: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+3+AGEMARGE){
4484: 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);
4485: exit(1);
4486: }
4487: if (s[m][i]>0 && s[m][i]<=nlstate) {
4488: /*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]]);*/
4489: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
4490: prop[s[m][i]][iagemax+3] += weight[i];
4491: } /* end valid statuses */
4492: } /* end selection of dates */
4493: } /* end selection of waves */
4494: } /* end bool */
4495: } /* end wave */
4496: } /* end individual */
4497: for(i=iagemin; i <= iagemax+3; i++){
4498: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
4499: posprop += prop[jk][i];
4500: }
4501:
4502: for(jk=1; jk <=nlstate ; jk++){
4503: if( i <= iagemax){
4504: if(posprop>=1.e-5){
4505: probs[i][jk][j1]= prop[jk][i]/posprop;
4506: } else{
4507: if(first==1){
4508: first=0;
4509: printf("Warning Observed prevalence probs[%d][%d][%d]=%lf because of lack of cases\nSee others in log file...\n",jk,i,j1,probs[i][jk][j1]);
4510: }
4511: }
4512: }
4513: }/* end jk */
4514: }/* end i */
1.222 brouard 4515: /*} *//* end i1 */
1.227 brouard 4516: } /* end j1 */
1.222 brouard 4517:
1.227 brouard 4518: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
4519: /*free_vector(pp,1,nlstate);*/
4520: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+3+AGEMARGE);
4521: } /* End of prevalence */
1.126 brouard 4522:
4523: /************* Waves Concatenation ***************/
4524:
4525: 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)
4526: {
4527: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
4528: Death is a valid wave (if date is known).
4529: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
4530: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
4531: and mw[mi+1][i]. dh depends on stepm.
1.227 brouard 4532: */
1.126 brouard 4533:
1.224 brouard 4534: int i=0, mi=0, m=0, mli=0;
1.126 brouard 4535: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
4536: double sum=0., jmean=0.;*/
1.224 brouard 4537: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 4538: int j, k=0,jk, ju, jl;
4539: double sum=0.;
4540: first=0;
1.214 brouard 4541: firstwo=0;
1.217 brouard 4542: firsthree=0;
1.218 brouard 4543: firstfour=0;
1.164 brouard 4544: jmin=100000;
1.126 brouard 4545: jmax=-1;
4546: jmean=0.;
1.224 brouard 4547:
4548: /* Treating live states */
1.214 brouard 4549: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 4550: mi=0; /* First valid wave */
1.227 brouard 4551: mli=0; /* Last valid wave */
1.126 brouard 4552: m=firstpass;
1.214 brouard 4553: while(s[m][i] <= nlstate){ /* a live state */
1.227 brouard 4554: 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 */
4555: mli=m-1;/* mw[++mi][i]=m-1; */
4556: }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 */
4557: mw[++mi][i]=m;
4558: mli=m;
1.224 brouard 4559: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
4560: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 4561: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 4562: }
1.227 brouard 4563: else{ /* m >= lastpass, eventual special issue with warning */
1.224 brouard 4564: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 4565: break;
1.224 brouard 4566: #else
1.227 brouard 4567: if(s[m][i]==-1 && (int) andc[i] == 9999 && (int)anint[m][i] != 9999){
4568: if(firsthree == 0){
4569: 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 pi. .\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);
4570: firsthree=1;
4571: }
4572: 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 pi. .\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);
4573: mw[++mi][i]=m;
4574: mli=m;
4575: }
4576: if(s[m][i]==-2){ /* Vital status is really unknown */
4577: nbwarn++;
4578: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified? */
4579: 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);
4580: 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);
4581: }
4582: break;
4583: }
4584: break;
1.224 brouard 4585: #endif
1.227 brouard 4586: }/* End m >= lastpass */
1.126 brouard 4587: }/* end while */
1.224 brouard 4588:
1.227 brouard 4589: /* 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 4590: /* After last pass */
1.224 brouard 4591: /* Treating death states */
1.214 brouard 4592: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 4593: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
4594: /* } */
1.126 brouard 4595: mi++; /* Death is another wave */
4596: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 4597: /* Only death is a correct wave */
1.126 brouard 4598: mw[mi][i]=m;
1.224 brouard 4599: }
4600: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.227 brouard 4601: else if ((int) andc[i] != 9999) { /* Status is negative. A death occured after lastpass, we can't take it into account because of potential bias */
1.216 brouard 4602: /* m++; */
4603: /* mi++; */
4604: /* s[m][i]=nlstate+1; /\* We are setting the status to the last of non live state *\/ */
4605: /* mw[mi][i]=m; */
1.218 brouard 4606: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.227 brouard 4607: if((andc[i]+moisdc[i]/12.) <=(anint[m][i]+mint[m][i]/12.)){ /* death occured before last wave and status should have been death instead of -1 */
4608: nbwarn++;
4609: if(firstfiv==0){
4610: printf("Warning! Death for individual %ld line=%d occurred at %d/%d before last wave %d interviewed at %d/%d and should have been coded as death instead of '%d'. This case (%d)/wave (%d) is contributing to likelihood.\nOthers in log file only\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], s[m][i], i,m );
4611: firstfiv=1;
4612: }else{
4613: fprintf(ficlog,"Warning! Death for individual %ld line=%d occurred at %d/%d before last wave %d interviewed at %d/%d and should have been coded as death instead of '%d'. This case (%d)/wave (%d) is contributing to likelihood.\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], s[m][i], i,m );
4614: }
4615: }else{ /* Death occured afer last wave potential bias */
4616: nberr++;
4617: if(firstwo==0){
4618: printf("Error! Death for individual %ld line=%d occurred at %d/%d after last wave %d interviewed at %d/%d. Potential bias if other individuals are still alive at this date but ignored. This case (%d)/wave (%d) is skipped, no contribution to likelihood.\nOthers in log file only\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], i,m );
4619: firstwo=1;
4620: }
4621: fprintf(ficlog,"Error! Death for individual %ld line=%d occurred at %d/%d after last wave %d interviewed at %d/%d. Potential bias if other individuals are still alive at this date but ignored. This case (%d)/wave (%d) is skipped, no contribution to likelihood.\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], i,m );
4622: }
1.218 brouard 4623: }else{ /* end date of interview is known */
1.227 brouard 4624: /* death is known but not confirmed by death status at any wave */
4625: if(firstfour==0){
4626: printf("Error! Death for individual %ld line=%d occurred %d/%d but not confirmed by any death status for any wave, including last wave %d at unknown date %d/%d. Potential bias if other individuals are still alive at this date but ignored. This case (%d)/wave (%d) is skipped, no contribution to likelihood.\nOthers in log file only\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], i,m );
4627: firstfour=1;
4628: }
4629: fprintf(ficlog,"Error! Death for individual %ld line=%d occurred %d/%d but not confirmed by any death status for any wave, including last wave %d at unknown date %d/%d. Potential bias if other individuals are still alive at this date but ignored. This case (%d)/wave (%d) is skipped, no contribution to likelihood.\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], i,m );
1.214 brouard 4630: }
1.224 brouard 4631: } /* end if date of death is known */
4632: #endif
4633: wav[i]=mi; /* mi should be the last effective wave (or mli) */
4634: /* wav[i]=mw[mi][i]; */
1.126 brouard 4635: if(mi==0){
4636: nbwarn++;
4637: if(first==0){
1.227 brouard 4638: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
4639: first=1;
1.126 brouard 4640: }
4641: if(first==1){
1.227 brouard 4642: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 4643: }
4644: } /* end mi==0 */
4645: } /* End individuals */
1.214 brouard 4646: /* wav and mw are no more changed */
1.223 brouard 4647:
1.214 brouard 4648:
1.126 brouard 4649: for(i=1; i<=imx; i++){
4650: for(mi=1; mi<wav[i];mi++){
4651: if (stepm <=0)
1.227 brouard 4652: dh[mi][i]=1;
1.126 brouard 4653: else{
1.227 brouard 4654: if (s[mw[mi+1][i]][i] > nlstate) { /* A death */
4655: if (agedc[i] < 2*AGESUP) {
4656: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
4657: if(j==0) j=1; /* Survives at least one month after exam */
4658: else if(j<0){
4659: nberr++;
4660: 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]);
4661: j=1; /* Temporary Dangerous patch */
4662: 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);
4663: 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]);
4664: 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);
4665: }
4666: k=k+1;
4667: if (j >= jmax){
4668: jmax=j;
4669: ijmax=i;
4670: }
4671: if (j <= jmin){
4672: jmin=j;
4673: ijmin=i;
4674: }
4675: sum=sum+j;
4676: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
4677: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
4678: }
4679: }
4680: else{
4681: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 4682: /* 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 4683:
1.227 brouard 4684: k=k+1;
4685: if (j >= jmax) {
4686: jmax=j;
4687: ijmax=i;
4688: }
4689: else if (j <= jmin){
4690: jmin=j;
4691: ijmin=i;
4692: }
4693: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
4694: /*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]);*/
4695: if(j<0){
4696: nberr++;
4697: 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]);
4698: 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]);
4699: }
4700: sum=sum+j;
4701: }
4702: jk= j/stepm;
4703: jl= j -jk*stepm;
4704: ju= j -(jk+1)*stepm;
4705: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
4706: if(jl==0){
4707: dh[mi][i]=jk;
4708: bh[mi][i]=0;
4709: }else{ /* We want a negative bias in order to only have interpolation ie
4710: * to avoid the price of an extra matrix product in likelihood */
4711: dh[mi][i]=jk+1;
4712: bh[mi][i]=ju;
4713: }
4714: }else{
4715: if(jl <= -ju){
4716: dh[mi][i]=jk;
4717: bh[mi][i]=jl; /* bias is positive if real duration
4718: * is higher than the multiple of stepm and negative otherwise.
4719: */
4720: }
4721: else{
4722: dh[mi][i]=jk+1;
4723: bh[mi][i]=ju;
4724: }
4725: if(dh[mi][i]==0){
4726: dh[mi][i]=1; /* At least one step */
4727: bh[mi][i]=ju; /* At least one step */
4728: /* 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);*/
4729: }
4730: } /* end if mle */
1.126 brouard 4731: }
4732: } /* end wave */
4733: }
4734: jmean=sum/k;
4735: 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 4736: 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 4737: }
1.126 brouard 4738:
4739: /*********** Tricode ****************************/
1.220 brouard 4740: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.126 brouard 4741: {
1.144 brouard 4742: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
4743: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
1.169 brouard 4744: * Boring subroutine which should only output nbcode[Tvar[j]][k]
1.224 brouard 4745: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
4746: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
1.144 brouard 4747: */
1.130 brouard 4748:
1.145 brouard 4749: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
1.136 brouard 4750: int modmaxcovj=0; /* Modality max of covariates j */
1.145 brouard 4751: int cptcode=0; /* Modality max of covariates j */
4752: int modmincovj=0; /* Modality min of covariates j */
4753:
4754:
1.220 brouard 4755: /* cptcoveff=0; */
1.224 brouard 4756: /* *cptcov=0; */
1.126 brouard 4757:
1.144 brouard 4758: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.126 brouard 4759:
1.224 brouard 4760: /* Loop on covariates without age and products and no quantitative variable */
4761: /* for (j=1; j<=(cptcovs); j++) { /\* From model V1 + V2*age+ V3 + V3*V4 keeps V1 + V3 = 2 only *\/ */
1.227 brouard 4762: for (k=1; k<=cptcovt; k++) { /* From model V1 + V2*age + V3 + V3*V4 keeps V1 + V3 = 2 only */
4763: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
4764: if(Dummy[k]==0 && Typevar[k] !=1){ /* Dummy covariate and not age product */
4765: switch(Fixed[k]) {
4766: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
1.231 brouard 4767: 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*/
4768: ij=(int)(covar[Tvar[k]][i]);
4769: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
4770: * If product of Vn*Vm, still boolean *:
4771: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
4772: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
4773: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
4774: modality of the nth covariate of individual i. */
4775: if (ij > modmaxcovj)
4776: modmaxcovj=ij;
4777: else if (ij < modmincovj)
4778: modmincovj=ij;
4779: if ((ij < -1) && (ij > NCOVMAX)){
4780: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
4781: exit(1);
4782: }else
4783: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
4784: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
4785: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
4786: /* getting the maximum value of the modality of the covariate
4787: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
4788: female ies 1, then modmaxcovj=1.
4789: */
4790: } /* end for loop on individuals i */
4791: printf(" Minimal and maximal values of %d th covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
4792: fprintf(ficlog," Minimal and maximal values of %d th covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
4793: cptcode=modmaxcovj;
4794: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
4795: /*for (i=0; i<=cptcode; i++) {*/
4796: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
4797: printf("Frequencies of covariates %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
4798: fprintf(ficlog, "Frequencies of covariates %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
4799: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
4800: if( j != -1){
4801: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
4802: covariate for which somebody answered excluding
4803: undefined. Usually 2: 0 and 1. */
4804: }
4805: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
4806: covariate for which somebody answered including
4807: undefined. Usually 3: -1, 0 and 1. */
4808: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
4809: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
4810: } /* Ndum[-1] number of undefined modalities */
4811:
4812: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
4813: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
4814: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
4815: /* modmincovj=3; modmaxcovj = 7; */
4816: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
4817: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
4818: /* defining two dummy variables: variables V1_1 and V1_2.*/
4819: /* nbcode[Tvar[j]][ij]=k; */
4820: /* nbcode[Tvar[j]][1]=0; */
4821: /* nbcode[Tvar[j]][2]=1; */
4822: /* nbcode[Tvar[j]][3]=2; */
4823: /* To be continued (not working yet). */
4824: ij=0; /* ij is similar to i but can jump over null modalities */
4825: 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*/
4826: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
4827: break;
4828: }
4829: ij++;
4830: 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*/
4831: cptcode = ij; /* New max modality for covar j */
4832: } /* end of loop on modality i=-1 to 1 or more */
4833: break;
1.227 brouard 4834: case 1: /* Testing on varying covariate, could be simple and
4835: * should look at waves or product of fixed *
4836: * varying. No time to test -1, assuming 0 and 1 only */
1.231 brouard 4837: ij=0;
4838: for(i=0; i<=1;i++){
4839: nbcode[Tvar[k]][++ij]=i;
4840: }
4841: break;
1.227 brouard 4842: default:
1.231 brouard 4843: break;
1.227 brouard 4844: } /* end switch */
4845: } /* end dummy test */
1.225 brouard 4846:
1.192 brouard 4847: /* for (k=0; k<= cptcode; k++) { /\* k=-1 ? k=0 to 1 *\//\* Could be 1 to 4 *\//\* cptcode=modmaxcovj *\/ */
4848: /* /\*recode from 0 *\/ */
4849: /* k is a modality. If we have model=V1+V1*sex */
4850: /* then: nbcode[1][1]=0 ; nbcode[1][2]=1; nbcode[2][1]=0 ; nbcode[2][2]=1; */
4851: /* But if some modality were not used, it is recoded from 0 to a newer modmaxcovj=cptcode *\/ */
4852: /* } */
4853: /* /\* cptcode = ij; *\/ /\* New max modality for covar j *\/ */
4854: /* if (ij > ncodemax[j]) { */
4855: /* printf( " Error ij=%d > ncodemax[%d]=%d\n", ij, j, ncodemax[j]); */
4856: /* fprintf(ficlog, " Error ij=%d > ncodemax[%d]=%d\n", ij, j, ncodemax[j]); */
4857: /* break; */
4858: /* } */
4859: /* } /\* end of loop on modality k *\/ */
1.137 brouard 4860: } /* end of loop on model-covariate j. nbcode[Tvarj][1]=0 and nbcode[Tvarj][2]=1 sets the value of covariate j*/
4861:
1.225 brouard 4862: for (k=-1; k< maxncov; k++) Ndum[k]=0;
1.227 brouard 4863: /* Look at fixed dummy (single or product) covariates to check empty modalities */
1.187 brouard 4864: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
1.225 brouard 4865: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
1.227 brouard 4866: 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 */
4867: 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 */
4868: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
1.225 brouard 4869: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
4870:
4871: ij=0;
1.227 brouard 4872: /* for (i=0; i<= maxncov-1; i++) { /\* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) *\/ */
4873: for (k=1; k<= cptcovt; k++) { /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
1.225 brouard 4874: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
1.227 brouard 4875: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
4876: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy and non empty in the model */
4877: /* If product not in single variable we don't print results */
1.225 brouard 4878: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
1.230 brouard 4879: ++ij;/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, */
4880: 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*/
4881: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
1.231 brouard 4882: 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 */
1.227 brouard 4883: if(Fixed[k]!=0)
4884: anyvaryingduminmodel=1;
1.231 brouard 4885: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
4886: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
4887: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
4888: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
4889: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
4890: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
1.227 brouard 4891: }
1.225 brouard 4892: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
4893: /* ij--; */
4894: /* cptcoveff=ij; /\*Number of total covariates*\/ */
4895: *cptcov=ij; /*Number of total real effective covariates: effective
1.231 brouard 4896: * because they can be excluded from the model and real
4897: * if in the model but excluded because missing values, but how to get k from ij?*/
1.227 brouard 4898: for(j=ij+1; j<= cptcovt; j++){
4899: Tvaraff[j]=0;
4900: Tmodelind[j]=0;
4901: }
1.228 brouard 4902: for(j=ntveff+1; j<= cptcovt; j++){
4903: TmodelInvind[j]=0;
4904: }
1.227 brouard 4905: /* To be sorted */
4906: ;
1.126 brouard 4907: }
4908:
1.145 brouard 4909:
1.126 brouard 4910: /*********** Health Expectancies ****************/
4911:
1.235 brouard 4912: 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 4913:
4914: {
4915: /* Health expectancies, no variances */
1.164 brouard 4916: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 4917: int nhstepma, nstepma; /* Decreasing with age */
4918: double age, agelim, hf;
4919: double ***p3mat;
4920: double eip;
4921:
1.238 ! brouard 4922: /* pstamp(ficreseij); */
1.126 brouard 4923: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
4924: fprintf(ficreseij,"# Age");
4925: for(i=1; i<=nlstate;i++){
4926: for(j=1; j<=nlstate;j++){
4927: fprintf(ficreseij," e%1d%1d ",i,j);
4928: }
4929: fprintf(ficreseij," e%1d. ",i);
4930: }
4931: fprintf(ficreseij,"\n");
4932:
4933:
4934: if(estepm < stepm){
4935: printf ("Problem %d lower than %d\n",estepm, stepm);
4936: }
4937: else hstepm=estepm;
4938: /* We compute the life expectancy from trapezoids spaced every estepm months
4939: * This is mainly to measure the difference between two models: for example
4940: * if stepm=24 months pijx are given only every 2 years and by summing them
4941: * we are calculating an estimate of the Life Expectancy assuming a linear
4942: * progression in between and thus overestimating or underestimating according
4943: * to the curvature of the survival function. If, for the same date, we
4944: * estimate the model with stepm=1 month, we can keep estepm to 24 months
4945: * to compare the new estimate of Life expectancy with the same linear
4946: * hypothesis. A more precise result, taking into account a more precise
4947: * curvature will be obtained if estepm is as small as stepm. */
4948:
4949: /* For example we decided to compute the life expectancy with the smallest unit */
4950: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
4951: nhstepm is the number of hstepm from age to agelim
4952: nstepm is the number of stepm from age to agelin.
4953: Look at hpijx to understand the reason of that which relies in memory size
4954: and note for a fixed period like estepm months */
4955: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
4956: survival function given by stepm (the optimization length). Unfortunately it
4957: means that if the survival funtion is printed only each two years of age and if
4958: you sum them up and add 1 year (area under the trapezoids) you won't get the same
4959: results. So we changed our mind and took the option of the best precision.
4960: */
4961: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
4962:
4963: agelim=AGESUP;
4964: /* If stepm=6 months */
4965: /* Computed by stepm unit matrices, product of hstepm matrices, stored
4966: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
4967:
4968: /* nhstepm age range expressed in number of stepm */
4969: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
4970: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
4971: /* if (stepm >= YEARM) hstepm=1;*/
4972: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
4973: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
4974:
4975: for (age=bage; age<=fage; age ++){
4976: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
4977: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
4978: /* if (stepm >= YEARM) hstepm=1;*/
4979: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
4980:
4981: /* If stepm=6 months */
4982: /* Computed by stepm unit matrices, product of hstepma matrices, stored
4983: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
4984:
1.235 brouard 4985: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 4986:
4987: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
4988:
4989: printf("%d|",(int)age);fflush(stdout);
4990: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
4991:
4992: /* Computing expectancies */
4993: for(i=1; i<=nlstate;i++)
4994: for(j=1; j<=nlstate;j++)
4995: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
4996: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
4997:
4998: /* 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]);*/
4999:
5000: }
5001:
5002: fprintf(ficreseij,"%3.0f",age );
5003: for(i=1; i<=nlstate;i++){
5004: eip=0;
5005: for(j=1; j<=nlstate;j++){
5006: eip +=eij[i][j][(int)age];
5007: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
5008: }
5009: fprintf(ficreseij,"%9.4f", eip );
5010: }
5011: fprintf(ficreseij,"\n");
5012:
5013: }
5014: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5015: printf("\n");
5016: fprintf(ficlog,"\n");
5017:
5018: }
5019:
1.235 brouard 5020: 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 5021:
5022: {
5023: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 5024: to initial status i, ei. .
1.126 brouard 5025: */
5026: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
5027: int nhstepma, nstepma; /* Decreasing with age */
5028: double age, agelim, hf;
5029: double ***p3matp, ***p3matm, ***varhe;
5030: double **dnewm,**doldm;
5031: double *xp, *xm;
5032: double **gp, **gm;
5033: double ***gradg, ***trgradg;
5034: int theta;
5035:
5036: double eip, vip;
5037:
5038: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
5039: xp=vector(1,npar);
5040: xm=vector(1,npar);
5041: dnewm=matrix(1,nlstate*nlstate,1,npar);
5042: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
5043:
5044: pstamp(ficresstdeij);
5045: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
5046: fprintf(ficresstdeij,"# Age");
5047: for(i=1; i<=nlstate;i++){
5048: for(j=1; j<=nlstate;j++)
5049: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
5050: fprintf(ficresstdeij," e%1d. ",i);
5051: }
5052: fprintf(ficresstdeij,"\n");
5053:
5054: pstamp(ficrescveij);
5055: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
5056: fprintf(ficrescveij,"# Age");
5057: for(i=1; i<=nlstate;i++)
5058: for(j=1; j<=nlstate;j++){
5059: cptj= (j-1)*nlstate+i;
5060: for(i2=1; i2<=nlstate;i2++)
5061: for(j2=1; j2<=nlstate;j2++){
5062: cptj2= (j2-1)*nlstate+i2;
5063: if(cptj2 <= cptj)
5064: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
5065: }
5066: }
5067: fprintf(ficrescveij,"\n");
5068:
5069: if(estepm < stepm){
5070: printf ("Problem %d lower than %d\n",estepm, stepm);
5071: }
5072: else hstepm=estepm;
5073: /* We compute the life expectancy from trapezoids spaced every estepm months
5074: * This is mainly to measure the difference between two models: for example
5075: * if stepm=24 months pijx are given only every 2 years and by summing them
5076: * we are calculating an estimate of the Life Expectancy assuming a linear
5077: * progression in between and thus overestimating or underestimating according
5078: * to the curvature of the survival function. If, for the same date, we
5079: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5080: * to compare the new estimate of Life expectancy with the same linear
5081: * hypothesis. A more precise result, taking into account a more precise
5082: * curvature will be obtained if estepm is as small as stepm. */
5083:
5084: /* For example we decided to compute the life expectancy with the smallest unit */
5085: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5086: nhstepm is the number of hstepm from age to agelim
5087: nstepm is the number of stepm from age to agelin.
5088: Look at hpijx to understand the reason of that which relies in memory size
5089: and note for a fixed period like estepm months */
5090: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5091: survival function given by stepm (the optimization length). Unfortunately it
5092: means that if the survival funtion is printed only each two years of age and if
5093: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5094: results. So we changed our mind and took the option of the best precision.
5095: */
5096: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5097:
5098: /* If stepm=6 months */
5099: /* nhstepm age range expressed in number of stepm */
5100: agelim=AGESUP;
5101: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
5102: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5103: /* if (stepm >= YEARM) hstepm=1;*/
5104: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5105:
5106: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5107: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5108: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
5109: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
5110: gp=matrix(0,nhstepm,1,nlstate*nlstate);
5111: gm=matrix(0,nhstepm,1,nlstate*nlstate);
5112:
5113: for (age=bage; age<=fage; age ++){
5114: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5115: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5116: /* if (stepm >= YEARM) hstepm=1;*/
5117: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 5118:
1.126 brouard 5119: /* If stepm=6 months */
5120: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5121: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5122:
5123: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 5124:
1.126 brouard 5125: /* Computing Variances of health expectancies */
5126: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
5127: decrease memory allocation */
5128: for(theta=1; theta <=npar; theta++){
5129: for(i=1; i<=npar; i++){
1.222 brouard 5130: xp[i] = x[i] + (i==theta ?delti[theta]:0);
5131: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 5132: }
1.235 brouard 5133: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
5134: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 5135:
1.126 brouard 5136: for(j=1; j<= nlstate; j++){
1.222 brouard 5137: for(i=1; i<=nlstate; i++){
5138: for(h=0; h<=nhstepm-1; h++){
5139: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
5140: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
5141: }
5142: }
1.126 brouard 5143: }
1.218 brouard 5144:
1.126 brouard 5145: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 5146: for(h=0; h<=nhstepm-1; h++){
5147: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
5148: }
1.126 brouard 5149: }/* End theta */
5150:
5151:
5152: for(h=0; h<=nhstepm-1; h++)
5153: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 5154: for(theta=1; theta <=npar; theta++)
5155: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 5156:
1.218 brouard 5157:
1.222 brouard 5158: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 5159: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 5160: varhe[ij][ji][(int)age] =0.;
1.218 brouard 5161:
1.222 brouard 5162: printf("%d|",(int)age);fflush(stdout);
5163: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5164: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 5165: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 5166: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
5167: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
5168: for(ij=1;ij<=nlstate*nlstate;ij++)
5169: for(ji=1;ji<=nlstate*nlstate;ji++)
5170: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 5171: }
5172: }
1.218 brouard 5173:
1.126 brouard 5174: /* Computing expectancies */
1.235 brouard 5175: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 5176: for(i=1; i<=nlstate;i++)
5177: for(j=1; j<=nlstate;j++)
1.222 brouard 5178: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5179: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 5180:
1.222 brouard 5181: /* 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 5182:
1.222 brouard 5183: }
1.218 brouard 5184:
1.126 brouard 5185: fprintf(ficresstdeij,"%3.0f",age );
5186: for(i=1; i<=nlstate;i++){
5187: eip=0.;
5188: vip=0.;
5189: for(j=1; j<=nlstate;j++){
1.222 brouard 5190: eip += eij[i][j][(int)age];
5191: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
5192: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
5193: 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 5194: }
5195: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
5196: }
5197: fprintf(ficresstdeij,"\n");
1.218 brouard 5198:
1.126 brouard 5199: fprintf(ficrescveij,"%3.0f",age );
5200: for(i=1; i<=nlstate;i++)
5201: for(j=1; j<=nlstate;j++){
1.222 brouard 5202: cptj= (j-1)*nlstate+i;
5203: for(i2=1; i2<=nlstate;i2++)
5204: for(j2=1; j2<=nlstate;j2++){
5205: cptj2= (j2-1)*nlstate+i2;
5206: if(cptj2 <= cptj)
5207: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
5208: }
1.126 brouard 5209: }
5210: fprintf(ficrescveij,"\n");
1.218 brouard 5211:
1.126 brouard 5212: }
5213: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
5214: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
5215: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
5216: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
5217: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5218: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5219: printf("\n");
5220: fprintf(ficlog,"\n");
1.218 brouard 5221:
1.126 brouard 5222: free_vector(xm,1,npar);
5223: free_vector(xp,1,npar);
5224: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
5225: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
5226: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
5227: }
1.218 brouard 5228:
1.126 brouard 5229: /************ Variance ******************/
1.235 brouard 5230: 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 5231: {
5232: /* Variance of health expectancies */
5233: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);*/
5234: /* double **newm;*/
5235: /* int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)*/
5236:
5237: /* int movingaverage(); */
5238: double **dnewm,**doldm;
5239: double **dnewmp,**doldmp;
5240: int i, j, nhstepm, hstepm, h, nstepm ;
5241: int k;
5242: double *xp;
5243: double **gp, **gm; /* for var eij */
5244: double ***gradg, ***trgradg; /*for var eij */
5245: double **gradgp, **trgradgp; /* for var p point j */
5246: double *gpp, *gmp; /* for var p point j */
5247: double **varppt; /* for var p point j nlstate to nlstate+ndeath */
5248: double ***p3mat;
5249: double age,agelim, hf;
5250: /* double ***mobaverage; */
5251: int theta;
5252: char digit[4];
5253: char digitp[25];
5254:
5255: char fileresprobmorprev[FILENAMELENGTH];
5256:
5257: if(popbased==1){
5258: if(mobilav!=0)
5259: strcpy(digitp,"-POPULBASED-MOBILAV_");
5260: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
5261: }
5262: else
5263: strcpy(digitp,"-STABLBASED_");
1.126 brouard 5264:
1.218 brouard 5265: /* if (mobilav!=0) { */
5266: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
5267: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
5268: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
5269: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
5270: /* } */
5271: /* } */
5272:
5273: strcpy(fileresprobmorprev,"PRMORPREV-");
5274: sprintf(digit,"%-d",ij);
5275: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
5276: strcat(fileresprobmorprev,digit); /* Tvar to be done */
5277: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
5278: strcat(fileresprobmorprev,fileresu);
5279: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
5280: printf("Problem with resultfile: %s\n", fileresprobmorprev);
5281: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
5282: }
5283: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
5284: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
5285: pstamp(ficresprobmorprev);
5286: 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 5287: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
! 5288: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
! 5289: fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
! 5290: }
! 5291: for(j=1;j<=cptcoveff;j++)
! 5292: fprintf(ficresprobmorprev,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,j)]);
! 5293: fprintf(ficresprobmorprev,"\n");
! 5294:
1.218 brouard 5295: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
5296: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
5297: fprintf(ficresprobmorprev," p.%-d SE",j);
5298: for(i=1; i<=nlstate;i++)
5299: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
5300: }
5301: fprintf(ficresprobmorprev,"\n");
5302:
5303: fprintf(ficgp,"\n# Routine varevsij");
5304: fprintf(ficgp,"\nunset title \n");
5305: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
5306: 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");
5307: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
5308: /* } */
5309: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
5310: pstamp(ficresvij);
5311: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
5312: if(popbased==1)
5313: 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);
5314: else
5315: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
5316: fprintf(ficresvij,"# Age");
5317: for(i=1; i<=nlstate;i++)
5318: for(j=1; j<=nlstate;j++)
5319: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
5320: fprintf(ficresvij,"\n");
5321:
5322: xp=vector(1,npar);
5323: dnewm=matrix(1,nlstate,1,npar);
5324: doldm=matrix(1,nlstate,1,nlstate);
5325: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
5326: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
5327:
5328: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
5329: gpp=vector(nlstate+1,nlstate+ndeath);
5330: gmp=vector(nlstate+1,nlstate+ndeath);
5331: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 5332:
1.218 brouard 5333: if(estepm < stepm){
5334: printf ("Problem %d lower than %d\n",estepm, stepm);
5335: }
5336: else hstepm=estepm;
5337: /* For example we decided to compute the life expectancy with the smallest unit */
5338: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5339: nhstepm is the number of hstepm from age to agelim
5340: nstepm is the number of stepm from age to agelim.
5341: Look at function hpijx to understand why because of memory size limitations,
5342: we decided (b) to get a life expectancy respecting the most precise curvature of the
5343: survival function given by stepm (the optimization length). Unfortunately it
5344: means that if the survival funtion is printed every two years of age and if
5345: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5346: results. So we changed our mind and took the option of the best precision.
5347: */
5348: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5349: agelim = AGESUP;
5350: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
5351: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
5352: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5353: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5354: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
5355: gp=matrix(0,nhstepm,1,nlstate);
5356: gm=matrix(0,nhstepm,1,nlstate);
5357:
5358:
5359: for(theta=1; theta <=npar; theta++){
5360: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
5361: xp[i] = x[i] + (i==theta ?delti[theta]:0);
5362: }
5363:
1.235 brouard 5364: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nresult);
1.218 brouard 5365:
5366: if (popbased==1) {
5367: if(mobilav ==0){
5368: for(i=1; i<=nlstate;i++)
5369: prlim[i][i]=probs[(int)age][i][ij];
5370: }else{ /* mobilav */
5371: for(i=1; i<=nlstate;i++)
5372: prlim[i][i]=mobaverage[(int)age][i][ij];
5373: }
5374: }
5375:
1.235 brouard 5376: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres); /* Returns p3mat[i][j][h] for h=1 to nhstepm */
1.218 brouard 5377: for(j=1; j<= nlstate; j++){
5378: for(h=0; h<=nhstepm; h++){
5379: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
5380: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
5381: }
5382: }
5383: /* Next for computing probability of death (h=1 means
5384: computed over hstepm matrices product = hstepm*stepm months)
5385: as a weighted average of prlim.
5386: */
5387: for(j=nlstate+1;j<=nlstate+ndeath;j++){
5388: for(i=1,gpp[j]=0.; i<= nlstate; i++)
5389: gpp[j] += prlim[i][i]*p3mat[i][j][1];
5390: }
5391: /* end probability of death */
5392:
5393: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
5394: xp[i] = x[i] - (i==theta ?delti[theta]:0);
5395:
1.235 brouard 5396: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nresult);
1.218 brouard 5397:
5398: if (popbased==1) {
5399: if(mobilav ==0){
5400: for(i=1; i<=nlstate;i++)
5401: prlim[i][i]=probs[(int)age][i][ij];
5402: }else{ /* mobilav */
5403: for(i=1; i<=nlstate;i++)
5404: prlim[i][i]=mobaverage[(int)age][i][ij];
5405: }
5406: }
5407:
1.235 brouard 5408: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 5409:
5410: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
5411: for(h=0; h<=nhstepm; h++){
5412: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
5413: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
5414: }
5415: }
5416: /* This for computing probability of death (h=1 means
5417: computed over hstepm matrices product = hstepm*stepm months)
5418: as a weighted average of prlim.
5419: */
5420: for(j=nlstate+1;j<=nlstate+ndeath;j++){
5421: for(i=1,gmp[j]=0.; i<= nlstate; i++)
5422: gmp[j] += prlim[i][i]*p3mat[i][j][1];
5423: }
5424: /* end probability of death */
5425:
5426: for(j=1; j<= nlstate; j++) /* vareij */
5427: for(h=0; h<=nhstepm; h++){
5428: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
5429: }
5430:
5431: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu */
5432: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
5433: }
5434:
5435: } /* End theta */
5436:
5437: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
5438:
5439: for(h=0; h<=nhstepm; h++) /* veij */
5440: for(j=1; j<=nlstate;j++)
5441: for(theta=1; theta <=npar; theta++)
5442: trgradg[h][j][theta]=gradg[h][theta][j];
5443:
5444: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
5445: for(theta=1; theta <=npar; theta++)
5446: trgradgp[j][theta]=gradgp[theta][j];
5447:
5448:
5449: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
5450: for(i=1;i<=nlstate;i++)
5451: for(j=1;j<=nlstate;j++)
5452: vareij[i][j][(int)age] =0.;
5453:
5454: for(h=0;h<=nhstepm;h++){
5455: for(k=0;k<=nhstepm;k++){
5456: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
5457: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
5458: for(i=1;i<=nlstate;i++)
5459: for(j=1;j<=nlstate;j++)
5460: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
5461: }
5462: }
5463:
5464: /* pptj */
5465: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
5466: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
5467: for(j=nlstate+1;j<=nlstate+ndeath;j++)
5468: for(i=nlstate+1;i<=nlstate+ndeath;i++)
5469: varppt[j][i]=doldmp[j][i];
5470: /* end ppptj */
5471: /* x centered again */
5472:
1.235 brouard 5473: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nresult);
1.218 brouard 5474:
5475: if (popbased==1) {
5476: if(mobilav ==0){
5477: for(i=1; i<=nlstate;i++)
5478: prlim[i][i]=probs[(int)age][i][ij];
5479: }else{ /* mobilav */
5480: for(i=1; i<=nlstate;i++)
5481: prlim[i][i]=mobaverage[(int)age][i][ij];
5482: }
5483: }
5484:
5485: /* This for computing probability of death (h=1 means
5486: computed over hstepm (estepm) matrices product = hstepm*stepm months)
5487: as a weighted average of prlim.
5488: */
1.235 brouard 5489: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 5490: for(j=nlstate+1;j<=nlstate+ndeath;j++){
5491: for(i=1,gmp[j]=0.;i<= nlstate; i++)
5492: gmp[j] += prlim[i][i]*p3mat[i][j][1];
5493: }
5494: /* end probability of death */
5495:
5496: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
5497: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
5498: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
5499: for(i=1; i<=nlstate;i++){
5500: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
5501: }
5502: }
5503: fprintf(ficresprobmorprev,"\n");
5504:
5505: fprintf(ficresvij,"%.0f ",age );
5506: for(i=1; i<=nlstate;i++)
5507: for(j=1; j<=nlstate;j++){
5508: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
5509: }
5510: fprintf(ficresvij,"\n");
5511: free_matrix(gp,0,nhstepm,1,nlstate);
5512: free_matrix(gm,0,nhstepm,1,nlstate);
5513: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
5514: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
5515: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5516: } /* End age */
5517: free_vector(gpp,nlstate+1,nlstate+ndeath);
5518: free_vector(gmp,nlstate+1,nlstate+ndeath);
5519: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
5520: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
5521: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
5522: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
5523: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
5524: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
5525: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
5526: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
5527: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
5528: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
5529: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
5530: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
5531: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
5532: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
5533: 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);
5534: /* 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 5535: */
1.218 brouard 5536: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
5537: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 5538:
1.218 brouard 5539: free_vector(xp,1,npar);
5540: free_matrix(doldm,1,nlstate,1,nlstate);
5541: free_matrix(dnewm,1,nlstate,1,npar);
5542: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
5543: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
5544: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
5545: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
5546: fclose(ficresprobmorprev);
5547: fflush(ficgp);
5548: fflush(fichtm);
5549: } /* end varevsij */
1.126 brouard 5550:
5551: /************ Variance of prevlim ******************/
1.235 brouard 5552: void varprevlim(char fileres[], 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 5553: {
1.205 brouard 5554: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 5555: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 5556:
1.126 brouard 5557: double **dnewm,**doldm;
5558: int i, j, nhstepm, hstepm;
5559: double *xp;
5560: double *gp, *gm;
5561: double **gradg, **trgradg;
1.208 brouard 5562: double **mgm, **mgp;
1.126 brouard 5563: double age,agelim;
5564: int theta;
5565:
5566: pstamp(ficresvpl);
5567: fprintf(ficresvpl,"# Standard deviation of period (stable) prevalences \n");
5568: fprintf(ficresvpl,"# Age");
5569: for(i=1; i<=nlstate;i++)
5570: fprintf(ficresvpl," %1d-%1d",i,i);
5571: fprintf(ficresvpl,"\n");
5572:
5573: xp=vector(1,npar);
5574: dnewm=matrix(1,nlstate,1,npar);
5575: doldm=matrix(1,nlstate,1,nlstate);
5576:
5577: hstepm=1*YEARM; /* Every year of age */
5578: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
5579: agelim = AGESUP;
5580: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
5581: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
5582: if (stepm >= YEARM) hstepm=1;
5583: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
5584: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 5585: mgp=matrix(1,npar,1,nlstate);
5586: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 5587: gp=vector(1,nlstate);
5588: gm=vector(1,nlstate);
5589:
5590: for(theta=1; theta <=npar; theta++){
5591: for(i=1; i<=npar; i++){ /* Computes gradient */
5592: xp[i] = x[i] + (i==theta ?delti[theta]:0);
5593: }
1.209 brouard 5594: if((int)age==79 ||(int)age== 80 ||(int)age== 81 )
1.235 brouard 5595: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.209 brouard 5596: else
1.235 brouard 5597: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 5598: for(i=1;i<=nlstate;i++){
1.126 brouard 5599: gp[i] = prlim[i][i];
1.208 brouard 5600: mgp[theta][i] = prlim[i][i];
5601: }
1.126 brouard 5602: for(i=1; i<=npar; i++) /* Computes gradient */
5603: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.209 brouard 5604: if((int)age==79 ||(int)age== 80 ||(int)age== 81 )
1.235 brouard 5605: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.209 brouard 5606: else
1.235 brouard 5607: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 5608: for(i=1;i<=nlstate;i++){
1.126 brouard 5609: gm[i] = prlim[i][i];
1.208 brouard 5610: mgm[theta][i] = prlim[i][i];
5611: }
1.126 brouard 5612: for(i=1;i<=nlstate;i++)
5613: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 5614: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 5615: } /* End theta */
5616:
5617: trgradg =matrix(1,nlstate,1,npar);
5618:
5619: for(j=1; j<=nlstate;j++)
5620: for(theta=1; theta <=npar; theta++)
5621: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 5622: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
5623: /* printf("\nmgm mgp %d ",(int)age); */
5624: /* for(j=1; j<=nlstate;j++){ */
5625: /* printf(" %d ",j); */
5626: /* for(theta=1; theta <=npar; theta++) */
5627: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
5628: /* printf("\n "); */
5629: /* } */
5630: /* } */
5631: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
5632: /* printf("\n gradg %d ",(int)age); */
5633: /* for(j=1; j<=nlstate;j++){ */
5634: /* printf("%d ",j); */
5635: /* for(theta=1; theta <=npar; theta++) */
5636: /* printf("%d %lf ",theta,gradg[theta][j]); */
5637: /* printf("\n "); */
5638: /* } */
5639: /* } */
1.126 brouard 5640:
5641: for(i=1;i<=nlstate;i++)
5642: varpl[i][(int)age] =0.;
1.209 brouard 5643: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.205 brouard 5644: matprod2(dnewm,trgradg,1,nlstate,1,npar,1,npar,matcov);
5645: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg);
5646: }else{
1.126 brouard 5647: matprod2(dnewm,trgradg,1,nlstate,1,npar,1,npar,matcov);
5648: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 5649: }
1.126 brouard 5650: for(i=1;i<=nlstate;i++)
5651: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
5652:
5653: fprintf(ficresvpl,"%.0f ",age );
5654: for(i=1; i<=nlstate;i++)
5655: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
5656: fprintf(ficresvpl,"\n");
5657: free_vector(gp,1,nlstate);
5658: free_vector(gm,1,nlstate);
1.208 brouard 5659: free_matrix(mgm,1,npar,1,nlstate);
5660: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 5661: free_matrix(gradg,1,npar,1,nlstate);
5662: free_matrix(trgradg,1,nlstate,1,npar);
5663: } /* End age */
5664:
5665: free_vector(xp,1,npar);
5666: free_matrix(doldm,1,nlstate,1,npar);
5667: free_matrix(dnewm,1,nlstate,1,nlstate);
5668:
5669: }
5670:
5671: /************ Variance of one-step probabilities ******************/
5672: 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 5673: {
5674: int i, j=0, k1, l1, tj;
5675: int k2, l2, j1, z1;
5676: int k=0, l;
5677: int first=1, first1, first2;
5678: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
5679: double **dnewm,**doldm;
5680: double *xp;
5681: double *gp, *gm;
5682: double **gradg, **trgradg;
5683: double **mu;
5684: double age, cov[NCOVMAX+1];
5685: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
5686: int theta;
5687: char fileresprob[FILENAMELENGTH];
5688: char fileresprobcov[FILENAMELENGTH];
5689: char fileresprobcor[FILENAMELENGTH];
5690: double ***varpij;
5691:
5692: strcpy(fileresprob,"PROB_");
5693: strcat(fileresprob,fileres);
5694: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
5695: printf("Problem with resultfile: %s\n", fileresprob);
5696: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
5697: }
5698: strcpy(fileresprobcov,"PROBCOV_");
5699: strcat(fileresprobcov,fileresu);
5700: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
5701: printf("Problem with resultfile: %s\n", fileresprobcov);
5702: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
5703: }
5704: strcpy(fileresprobcor,"PROBCOR_");
5705: strcat(fileresprobcor,fileresu);
5706: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
5707: printf("Problem with resultfile: %s\n", fileresprobcor);
5708: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
5709: }
5710: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
5711: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
5712: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
5713: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
5714: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
5715: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
5716: pstamp(ficresprob);
5717: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
5718: fprintf(ficresprob,"# Age");
5719: pstamp(ficresprobcov);
5720: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
5721: fprintf(ficresprobcov,"# Age");
5722: pstamp(ficresprobcor);
5723: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
5724: fprintf(ficresprobcor,"# Age");
1.126 brouard 5725:
5726:
1.222 brouard 5727: for(i=1; i<=nlstate;i++)
5728: for(j=1; j<=(nlstate+ndeath);j++){
5729: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
5730: fprintf(ficresprobcov," p%1d-%1d ",i,j);
5731: fprintf(ficresprobcor," p%1d-%1d ",i,j);
5732: }
5733: /* fprintf(ficresprob,"\n");
5734: fprintf(ficresprobcov,"\n");
5735: fprintf(ficresprobcor,"\n");
5736: */
5737: xp=vector(1,npar);
5738: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
5739: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
5740: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
5741: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
5742: first=1;
5743: fprintf(ficgp,"\n# Routine varprob");
5744: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
5745: fprintf(fichtm,"\n");
5746:
5747: 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.</li>\n",optionfilehtmcov);
5748: 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);
5749: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 5750: and drawn. It helps understanding how is the covariance between two incidences.\
5751: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 5752: 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 5753: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
5754: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
5755: standard deviations wide on each axis. <br>\
5756: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
5757: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
5758: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
5759:
1.222 brouard 5760: cov[1]=1;
5761: /* tj=cptcoveff; */
1.225 brouard 5762: tj = (int) pow(2,cptcoveff);
1.222 brouard 5763: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
5764: j1=0;
1.224 brouard 5765: for(j1=1; j1<=tj;j1++){ /* For each valid combination of covariates or only once*/
1.222 brouard 5766: if (cptcovn>0) {
5767: fprintf(ficresprob, "\n#********** Variable ");
1.225 brouard 5768: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 5769: fprintf(ficresprob, "**********\n#\n");
5770: fprintf(ficresprobcov, "\n#********** Variable ");
1.225 brouard 5771: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcov, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 5772: fprintf(ficresprobcov, "**********\n#\n");
1.220 brouard 5773:
1.222 brouard 5774: fprintf(ficgp, "\n#********** Variable ");
1.225 brouard 5775: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficgp, " V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 5776: fprintf(ficgp, "**********\n#\n");
1.220 brouard 5777:
5778:
1.222 brouard 5779: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
1.225 brouard 5780: for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtm, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 5781: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 5782:
1.222 brouard 5783: fprintf(ficresprobcor, "\n#********** Variable ");
1.225 brouard 5784: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcor, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 5785: fprintf(ficresprobcor, "**********\n#");
5786: if(invalidvarcomb[j1]){
5787: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
5788: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
5789: continue;
5790: }
5791: }
5792: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
5793: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
5794: gp=vector(1,(nlstate)*(nlstate+ndeath));
5795: gm=vector(1,(nlstate)*(nlstate+ndeath));
5796: for (age=bage; age<=fage; age ++){
5797: cov[2]=age;
5798: if(nagesqr==1)
5799: cov[3]= age*age;
5800: for (k=1; k<=cptcovn;k++) {
5801: cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)];
5802: /*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*//* j1 1 2 3 4
5803: * 1 1 1 1 1
5804: * 2 2 1 1 1
5805: * 3 1 2 1 1
5806: */
5807: /* nbcode[1][1]=0 nbcode[1][2]=1;*/
5808: }
5809: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; */
5810: for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
5811: for (k=1; k<=cptcovprod;k++)
5812: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.220 brouard 5813:
5814:
1.222 brouard 5815: for(theta=1; theta <=npar; theta++){
5816: for(i=1; i<=npar; i++)
5817: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 5818:
1.222 brouard 5819: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 5820:
1.222 brouard 5821: k=0;
5822: for(i=1; i<= (nlstate); i++){
5823: for(j=1; j<=(nlstate+ndeath);j++){
5824: k=k+1;
5825: gp[k]=pmmij[i][j];
5826: }
5827: }
1.220 brouard 5828:
1.222 brouard 5829: for(i=1; i<=npar; i++)
5830: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 5831:
1.222 brouard 5832: pmij(pmmij,cov,ncovmodel,xp,nlstate);
5833: k=0;
5834: for(i=1; i<=(nlstate); i++){
5835: for(j=1; j<=(nlstate+ndeath);j++){
5836: k=k+1;
5837: gm[k]=pmmij[i][j];
5838: }
5839: }
1.220 brouard 5840:
1.222 brouard 5841: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
5842: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
5843: }
1.126 brouard 5844:
1.222 brouard 5845: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
5846: for(theta=1; theta <=npar; theta++)
5847: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 5848:
1.222 brouard 5849: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
5850: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 5851:
1.222 brouard 5852: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 5853:
1.222 brouard 5854: k=0;
5855: for(i=1; i<=(nlstate); i++){
5856: for(j=1; j<=(nlstate+ndeath);j++){
5857: k=k+1;
5858: mu[k][(int) age]=pmmij[i][j];
5859: }
5860: }
5861: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
5862: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
5863: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 5864:
1.222 brouard 5865: /*printf("\n%d ",(int)age);
5866: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
5867: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
5868: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
5869: }*/
1.220 brouard 5870:
1.222 brouard 5871: fprintf(ficresprob,"\n%d ",(int)age);
5872: fprintf(ficresprobcov,"\n%d ",(int)age);
5873: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 5874:
1.222 brouard 5875: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
5876: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
5877: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
5878: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
5879: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
5880: }
5881: i=0;
5882: for (k=1; k<=(nlstate);k++){
5883: for (l=1; l<=(nlstate+ndeath);l++){
5884: i++;
5885: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
5886: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
5887: for (j=1; j<=i;j++){
5888: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
5889: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
5890: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
5891: }
5892: }
5893: }/* end of loop for state */
5894: } /* end of loop for age */
5895: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
5896: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
5897: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
5898: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
5899:
5900: /* Confidence intervalle of pij */
5901: /*
5902: fprintf(ficgp,"\nunset parametric;unset label");
5903: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
5904: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
5905: 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);
5906: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
5907: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
5908: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
5909: */
5910:
5911: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
5912: first1=1;first2=2;
5913: for (k2=1; k2<=(nlstate);k2++){
5914: for (l2=1; l2<=(nlstate+ndeath);l2++){
5915: if(l2==k2) continue;
5916: j=(k2-1)*(nlstate+ndeath)+l2;
5917: for (k1=1; k1<=(nlstate);k1++){
5918: for (l1=1; l1<=(nlstate+ndeath);l1++){
5919: if(l1==k1) continue;
5920: i=(k1-1)*(nlstate+ndeath)+l1;
5921: if(i<=j) continue;
5922: for (age=bage; age<=fage; age ++){
5923: if ((int)age %5==0){
5924: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
5925: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
5926: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
5927: mu1=mu[i][(int) age]/stepm*YEARM ;
5928: mu2=mu[j][(int) age]/stepm*YEARM;
5929: c12=cv12/sqrt(v1*v2);
5930: /* Computing eigen value of matrix of covariance */
5931: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
5932: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
5933: if ((lc2 <0) || (lc1 <0) ){
5934: if(first2==1){
5935: first1=0;
5936: 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);
5937: }
5938: 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);
5939: /* lc1=fabs(lc1); */ /* If we want to have them positive */
5940: /* lc2=fabs(lc2); */
5941: }
1.220 brouard 5942:
1.222 brouard 5943: /* Eigen vectors */
5944: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
5945: /*v21=sqrt(1.-v11*v11); *//* error */
5946: v21=(lc1-v1)/cv12*v11;
5947: v12=-v21;
5948: v22=v11;
5949: tnalp=v21/v11;
5950: if(first1==1){
5951: first1=0;
5952: 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);
5953: }
5954: 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);
5955: /*printf(fignu*/
5956: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
5957: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
5958: if(first==1){
5959: first=0;
5960: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
5961: fprintf(ficgp,"\nset parametric;unset label");
5962: 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);
5963: fprintf(ficgp,"\nset ter svg size 640, 480");
5964: fprintf(fichtmcov,"\n<br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 5965: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 5966: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 5967: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
5968: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
5969: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
5970: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
5971: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
5972: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
5973: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
5974: 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", \
5975: mu1,std,v11,sqrt(lc1),v12,sqrt(lc2), \
5976: mu2,std,v21,sqrt(lc1),v22,sqrt(lc2));
5977: }else{
5978: first=0;
5979: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
5980: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
5981: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
5982: 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", \
5983: mu1,std,v11,sqrt(lc1),v12,sqrt(lc2), \
5984: mu2,std,v21,sqrt(lc1),v22,sqrt(lc2));
5985: }/* if first */
5986: } /* age mod 5 */
5987: } /* end loop age */
5988: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
5989: first=1;
5990: } /*l12 */
5991: } /* k12 */
5992: } /*l1 */
5993: }/* k1 */
5994: } /* loop on combination of covariates j1 */
5995: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
5996: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
5997: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
5998: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
5999: free_vector(xp,1,npar);
6000: fclose(ficresprob);
6001: fclose(ficresprobcov);
6002: fclose(ficresprobcor);
6003: fflush(ficgp);
6004: fflush(fichtmcov);
6005: }
1.126 brouard 6006:
6007:
6008: /******************* Printing html file ***********/
1.201 brouard 6009: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 6010: int lastpass, int stepm, int weightopt, char model[],\
6011: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.217 brouard 6012: int popforecast, int prevfcast, int backcast, int estepm , \
1.213 brouard 6013: double jprev1, double mprev1,double anprev1, double dateprev1, \
6014: double jprev2, double mprev2,double anprev2, double dateprev2){
1.237 brouard 6015: int jj1, k1, i1, cpt, k4, nres;
1.126 brouard 6016:
6017: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
6018: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
6019: </ul>");
1.237 brouard 6020: fprintf(fichtm,"<ul><li> model=1+age+%s\n \
6021: </ul>", model);
1.214 brouard 6022: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
6023: 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",
6024: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
6025: fprintf(fichtm,"<li> - Observed prevalence in each state (during the period defined between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf): <a href=\"%s\">%s</a> (html file) ",
1.213 brouard 6026: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
6027: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 6028: fprintf(fichtm,"\
6029: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 6030: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 6031: fprintf(fichtm,"\
1.217 brouard 6032: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
6033: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
6034: fprintf(fichtm,"\
1.126 brouard 6035: - Period (stable) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 6036: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 6037: fprintf(fichtm,"\
1.217 brouard 6038: - Period (stable) back prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
6039: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
6040: fprintf(fichtm,"\
1.211 brouard 6041: - (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 6042: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 6043: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 6044: if(prevfcast==1){
6045: fprintf(fichtm,"\
6046: - Prevalence projections by age and states: \
1.201 brouard 6047: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 6048: }
1.126 brouard 6049:
1.222 brouard 6050: fprintf(fichtm," \n<ul><li><b>Graphs</b></li><p>");
1.126 brouard 6051:
1.225 brouard 6052: m=pow(2,cptcoveff);
1.222 brouard 6053: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 6054:
1.222 brouard 6055: jj1=0;
1.237 brouard 6056:
6057: for(nres=1; nres <= nresult; nres++) /* For each resultline */
1.222 brouard 6058: for(k1=1; k1<=m;k1++){
1.237 brouard 6059: if(TKresult[nres]!= k1)
6060: continue;
1.220 brouard 6061:
1.222 brouard 6062: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
6063: jj1++;
6064: if (cptcovn > 0) {
6065: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 6066: for (cpt=1; cpt<=cptcoveff;cpt++){
1.237 brouard 6067: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6068: printf(" V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);fflush(stdout);
6069: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
6070: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 6071: }
1.237 brouard 6072: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6073: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6074: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);fflush(stdout);
6075: }
6076:
1.230 brouard 6077: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.222 brouard 6078: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
6079: if(invalidvarcomb[k1]){
6080: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
6081: printf("\nCombination (%d) ignored because no cases \n",k1);
6082: continue;
6083: }
6084: }
6085: /* aij, bij */
6086: fprintf(fichtm,"<br>- Logit model (yours is: 1+age+%s), for example: logit(pij)=log(pij/pii)= aij+ bij age + V1 age + etc. as a function of age: <a href=\"%s_%d-1.svg\">%s_%d-1.svg</a><br> \
1.211 brouard 6087: <img src=\"%s_%d-1.svg\">",model,subdirf2(optionfilefiname,"PE_"),jj1,subdirf2(optionfilefiname,"PE_"),jj1,subdirf2(optionfilefiname,"PE_"),jj1);
1.222 brouard 6088: /* Pij */
6089: 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.svg\">%s_%d-2.svg</a><br> \
1.201 brouard 6090: <img src=\"%s_%d-2.svg\">",stepm,subdirf2(optionfilefiname,"PE_"),jj1,subdirf2(optionfilefiname,"PE_"),jj1,subdirf2(optionfilefiname,"PE_"),jj1);
1.222 brouard 6091: /* Quasi-incidences */
6092: 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 6093: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 6094: incidence (rates) are the limit when h tends to zero of the ratio of the probability <sub>h</sub>P<sub>ij</sub> \
6095: divided by h: <sub>h</sub>P<sub>ij</sub>/h : <a href=\"%s_%d-3.svg\">%s_%d-3.svg</a><br> \
1.201 brouard 6096: <img src=\"%s_%d-3.svg\">",stepm,subdirf2(optionfilefiname,"PE_"),jj1,subdirf2(optionfilefiname,"PE_"),jj1,subdirf2(optionfilefiname,"PE_"),jj1);
1.222 brouard 6097: /* Survival functions (period) in state j */
6098: for(cpt=1; cpt<=nlstate;cpt++){
6099: fprintf(fichtm,"<br>\n- Survival functions in state %d. Or probability to survive in state %d being in state (1 to %d) at different ages. <a href=\"%s%d_%d.svg\">%s%d_%d.svg</a><br> \
1.201 brouard 6100: <img src=\"%s_%d-%d.svg\">", cpt, cpt, nlstate, subdirf2(optionfilefiname,"LIJ_"),cpt,jj1,subdirf2(optionfilefiname,"LIJ_"),cpt,jj1,subdirf2(optionfilefiname,"LIJ_"),cpt,jj1);
1.222 brouard 6101: }
6102: /* State specific survival functions (period) */
6103: for(cpt=1; cpt<=nlstate;cpt++){
6104: fprintf(fichtm,"<br>\n- Survival functions from state %d in each live state and total.\
1.220 brouard 6105: Or probability to survive in various states (1 to %d) being in state %d at different ages. \
1.201 brouard 6106: <a href=\"%s%d_%d.svg\">%s%d_%d.svg</a><br> <img src=\"%s_%d-%d.svg\">", cpt, nlstate, cpt, subdirf2(optionfilefiname,"LIJT_"),cpt,jj1,subdirf2(optionfilefiname,"LIJT_"),cpt,jj1,subdirf2(optionfilefiname,"LIJT_"),cpt,jj1);
1.222 brouard 6107: }
6108: /* Period (stable) prevalence in each health state */
6109: for(cpt=1; cpt<=nlstate;cpt++){
6110: fprintf(fichtm,"<br>\n- Convergence to period (stable) prevalence in state %d. Or probability to be in state %d being in state (1 to %d) at different ages. <a href=\"%s_%d-%d.svg\">%s_%d-%d.svg</a><br> \
1.201 brouard 6111: <img src=\"%s_%d-%d.svg\">", cpt, cpt, nlstate, subdirf2(optionfilefiname,"P_"),cpt,jj1,subdirf2(optionfilefiname,"P_"),cpt,jj1,subdirf2(optionfilefiname,"P_"),cpt,jj1);
1.222 brouard 6112: }
6113: if(backcast==1){
6114: /* Period (stable) back prevalence in each health state */
6115: for(cpt=1; cpt<=nlstate;cpt++){
6116: fprintf(fichtm,"<br>\n- Convergence to period (stable) back prevalence in state %d. Or probability to be in state %d being in state (1 to %d) at different ages. <a href=\"%s_%d-%d.svg\">%s_%d-%d.svg</a><br> \
1.217 brouard 6117: <img src=\"%s_%d-%d.svg\">", cpt, cpt, nlstate, subdirf2(optionfilefiname,"PB_"),cpt,jj1,subdirf2(optionfilefiname,"PB_"),cpt,jj1,subdirf2(optionfilefiname,"PB_"),cpt,jj1);
1.222 brouard 6118: }
1.217 brouard 6119: }
1.222 brouard 6120: if(prevfcast==1){
6121: /* Projection of prevalence up to period (stable) prevalence in each health state */
6122: for(cpt=1; cpt<=nlstate;cpt++){
6123: fprintf(fichtm,"<br>\n- Projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f) up to period (stable) prevalence in state %d. Or probability to be in state %d being in state (1 to %d) at different ages. <a href=\"%s%d_%d.svg\">%s%d_%d.svg</a><br> \
1.213 brouard 6124: <img src=\"%s_%d-%d.svg\">", dateprev1, dateprev2, cpt, cpt, nlstate, subdirf2(optionfilefiname,"PROJ_"),cpt,jj1,subdirf2(optionfilefiname,"PROJ_"),cpt,jj1,subdirf2(optionfilefiname,"PROJ_"),cpt,jj1);
1.222 brouard 6125: }
6126: }
1.220 brouard 6127:
1.222 brouard 6128: for(cpt=1; cpt<=nlstate;cpt++) {
6129: 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.svg\">%s_%d%d.svg</a> <br> \
1.201 brouard 6130: <img src=\"%s_%d%d.svg\">",cpt,nlstate,subdirf2(optionfilefiname,"EXP_"),cpt,jj1,subdirf2(optionfilefiname,"EXP_"),cpt,jj1,subdirf2(optionfilefiname,"EXP_"),cpt,jj1);
1.222 brouard 6131: }
6132: /* } /\* end i1 *\/ */
6133: }/* End k1 */
6134: fprintf(fichtm,"</ul>");
1.126 brouard 6135:
1.222 brouard 6136: fprintf(fichtm,"\
1.126 brouard 6137: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 6138: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 6139: - 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 6140: But because parameters are usually highly correlated (a higher incidence of disability \
6141: and a higher incidence of recovery can give very close observed transition) it might \
6142: be very useful to look not only at linear confidence intervals estimated from the \
6143: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
6144: (parameters) of the logistic regression, it might be more meaningful to visualize the \
6145: covariance matrix of the one-step probabilities. \
6146: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 6147:
1.222 brouard 6148: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
6149: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
6150: fprintf(fichtm,"\
1.126 brouard 6151: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 6152: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 6153:
1.222 brouard 6154: fprintf(fichtm,"\
1.126 brouard 6155: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 6156: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
6157: fprintf(fichtm,"\
1.126 brouard 6158: - 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): \
6159: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 6160: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 6161: fprintf(fichtm,"\
1.126 brouard 6162: - (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): \
6163: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 6164: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 6165: fprintf(fichtm,"\
1.128 brouard 6166: - Variances and covariances of health expectancies by age. Status (i) based health expectancies (in state j), e<sup>ij</sup> are weighted by the 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 6167: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
6168: fprintf(fichtm,"\
1.128 brouard 6169: - 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 6170: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
6171: fprintf(fichtm,"\
1.126 brouard 6172: - Standard deviation of period (stable) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 6173: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 6174:
6175: /* if(popforecast==1) fprintf(fichtm,"\n */
6176: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
6177: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
6178: /* <br>",fileres,fileres,fileres,fileres); */
6179: /* else */
6180: /* fprintf(fichtm,"\n No population forecast: popforecast = %d (instead of 1) or stepm = %d (instead of 1) or model=%s (instead of .)<br><br></li>\n",popforecast, stepm, model); */
1.222 brouard 6181: fflush(fichtm);
6182: fprintf(fichtm," <ul><li><b>Graphs</b></li><p>");
1.126 brouard 6183:
1.225 brouard 6184: m=pow(2,cptcoveff);
1.222 brouard 6185: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 6186:
1.222 brouard 6187: jj1=0;
1.237 brouard 6188:
6189: for(nres=1; nres <= nresult; nres++) /* For each resultline */
1.222 brouard 6190: for(k1=1; k1<=m;k1++){
1.237 brouard 6191: if(TKresult[nres]!= k1)
6192: continue;
1.222 brouard 6193: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
6194: jj1++;
1.126 brouard 6195: if (cptcovn > 0) {
6196: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 6197: for (cpt=1; cpt<=cptcoveff;cpt++) /**< cptcoveff number of variables */
1.237 brouard 6198: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);
6199: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
6200: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6201: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6202: }
6203:
1.126 brouard 6204: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 6205:
1.222 brouard 6206: if(invalidvarcomb[k1]){
6207: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
6208: continue;
6209: }
1.126 brouard 6210: }
6211: for(cpt=1; cpt<=nlstate;cpt++) {
1.218 brouard 6212: fprintf(fichtm,"\n<br>- Observed (cross-sectional) and period (incidence based) \
6213: prevalence (with 95%% confidence interval) in state (%d): <a href=\"%s_%d-%d.svg\"> %s_%d-%d.svg</a>\n <br>\
1.205 brouard 6214: <img src=\"%s_%d-%d.svg\">",cpt,subdirf2(optionfilefiname,"V_"),cpt,jj1,subdirf2(optionfilefiname,"V_"),cpt,jj1,subdirf2(optionfilefiname,"V_"),cpt,jj1);
1.126 brouard 6215: }
6216: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.128 brouard 6217: health expectancies in states (1) and (2). If popbased=1 the smooth (due to the model) \
6218: true period expectancies (those weighted with period prevalences are also\
6219: drawn in addition to the population based expectancies computed using\
1.218 brouard 6220: observed and cahotic prevalences: <a href=\"%s_%d.svg\">%s_%d.svg</a>\n<br>\
1.205 brouard 6221: <img src=\"%s_%d.svg\">",subdirf2(optionfilefiname,"E_"),jj1,subdirf2(optionfilefiname,"E_"),jj1,subdirf2(optionfilefiname,"E_"),jj1);
1.222 brouard 6222: /* } /\* end i1 *\/ */
6223: }/* End k1 */
6224: fprintf(fichtm,"</ul>");
6225: fflush(fichtm);
1.126 brouard 6226: }
6227:
6228: /******************* Gnuplot file **************/
1.223 brouard 6229: void printinggnuplot(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , int prevfcast, int backcast, char pathc[], double p[]){
1.126 brouard 6230:
6231: char dirfileres[132],optfileres[132];
1.223 brouard 6232: char gplotcondition[132];
1.237 brouard 6233: 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 6234: int lv=0, vlv=0, kl=0;
1.130 brouard 6235: int ng=0;
1.201 brouard 6236: int vpopbased;
1.223 brouard 6237: int ioffset; /* variable offset for columns */
1.235 brouard 6238: int nres=0; /* Index of resultline */
1.219 brouard 6239:
1.126 brouard 6240: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
6241: /* printf("Problem with file %s",optionfilegnuplot); */
6242: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
6243: /* } */
6244:
6245: /*#ifdef windows */
6246: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 6247: /*#endif */
1.225 brouard 6248: m=pow(2,cptcoveff);
1.126 brouard 6249:
1.202 brouard 6250: /* Contribution to likelihood */
6251: /* Plot the probability implied in the likelihood */
1.223 brouard 6252: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
6253: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
6254: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
6255: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 6256: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 6257: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
6258: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 6259: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
6260: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
6261: 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));
6262: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
6263: 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));
6264: for (i=1; i<= nlstate ; i ++) {
6265: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
6266: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
6267: 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);
6268: for (j=2; j<= nlstate+ndeath ; j ++) {
6269: 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);
6270: }
6271: fprintf(ficgp,";\nset out; unset ylabel;\n");
6272: }
6273: /* 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 */
6274: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
6275: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
6276: fprintf(ficgp,"\nset out;unset log\n");
6277: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 6278:
1.126 brouard 6279: strcpy(dirfileres,optionfilefiname);
6280: strcpy(optfileres,"vpl");
1.223 brouard 6281: /* 1eme*/
1.238 ! brouard 6282: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
! 6283: for (k1=1; k1<= m ; k1 ++){ /* For each valid combination of covariate */
1.236 brouard 6284: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.238 ! brouard 6285: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
! 6286: if(TKresult[nres]!= k1)
! 6287: continue;
! 6288: /* We are interested in selected combination by the resultline */
! 6289: printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
! 6290: fprintf(ficgp,"\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
! 6291: for (k=1; k<=cptcoveff; k++){ /* For each covariate k get corresponding value lv for combination k1 */
! 6292: lv= decodtabm(k1,k,cptcoveff); /* Should be the value of the covariate corresponding to k1 combination */
! 6293: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
! 6294: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
! 6295: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
! 6296: vlv= nbcode[Tvaraff[k]][lv]; /* vlv is the value of the covariate lv, 0 or 1 */
! 6297: /* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv */
! 6298: printf(" V%d=%d ",Tvaraff[k],vlv);
! 6299: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
! 6300: }
! 6301: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
! 6302: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
! 6303: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
! 6304: }
! 6305: printf("\n#\n");
! 6306: fprintf(ficgp,"\n#\n");
! 6307: if(invalidvarcomb[k1]){
! 6308: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
! 6309: continue;
! 6310: }
1.235 brouard 6311:
1.238 ! brouard 6312: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1);
! 6313: fprintf(ficgp,"\n#set out \"V_%s_%d-%d.svg\" \n",optionfilefiname,cpt,k1);
! 6314: fprintf(ficgp,"set xlabel \"Age\" \n\
1.235 brouard 6315: set ylabel \"Probability\" \n \
6316: set ter svg size 640, 480\n \
1.201 brouard 6317: plot [%.f:%.f] \"%s\" every :::%d::%d u 1:2 \"%%lf",ageminpar,fage,subdirf2(fileresu,"VPL_"),k1-1,k1-1);
1.235 brouard 6318:
1.238 ! brouard 6319: for (i=1; i<= nlstate ; i ++) {
! 6320: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
! 6321: else fprintf(ficgp," %%*lf (%%*lf)");
! 6322: }
! 6323: fprintf(ficgp,"\" t\"Period (stable) prevalence\" w l lt 0,\"%s\" every :::%d::%d u 1:($2+1.96*$3) \"%%lf",subdirf2(fileresu,"VPL_"),k1-1,k1-1);
! 6324: for (i=1; i<= nlstate ; i ++) {
! 6325: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
! 6326: else fprintf(ficgp," %%*lf (%%*lf)");
! 6327: }
! 6328: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2-1.96*$3) \"%%lf",subdirf2(fileresu,"VPL_"),k1-1,k1-1);
! 6329: for (i=1; i<= nlstate ; i ++) {
! 6330: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
! 6331: else fprintf(ficgp," %%*lf (%%*lf)");
! 6332: }
! 6333: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1));
! 6334: if(backcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
! 6335: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
! 6336: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1 */
! 6337: if(cptcoveff ==0){
! 6338: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line ", 2+(cpt-1), cpt );
! 6339: }else{
! 6340: kl=0;
! 6341: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
! 6342: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
! 6343: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
! 6344: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
! 6345: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
! 6346: vlv= nbcode[Tvaraff[k]][lv];
1.223 brouard 6347: kl++;
1.238 ! brouard 6348: /* 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 *\/ */
! 6349: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
! 6350: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
! 6351: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
! 6352: if(k==cptcoveff){
! 6353: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
! 6354: 4+(cpt-1), cpt ); /* 4 or 6 ?*/
! 6355: }else{
! 6356: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
! 6357: kl++;
! 6358: }
! 6359: } /* end covariate */
! 6360: } /* end if no covariate */
! 6361: } /* end if backcast */
! 6362: fprintf(ficgp,"\nset out \n");
! 6363: } /* nres */
1.201 brouard 6364: } /* k1 */
6365: } /* cpt */
1.235 brouard 6366:
6367:
1.126 brouard 6368: /*2 eme*/
1.238 ! brouard 6369: for (k1=1; k1<= m ; k1 ++){
! 6370: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
! 6371: if(TKresult[nres]!= k1)
! 6372: continue;
! 6373: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
! 6374: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.225 brouard 6375: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
1.223 brouard 6376: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
6377: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
6378: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
6379: vlv= nbcode[Tvaraff[k]][lv];
6380: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 6381: }
1.237 brouard 6382: /* for(k=1; k <= ncovds; k++){ */
1.236 brouard 6383: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 ! brouard 6384: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.236 brouard 6385: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 ! brouard 6386: }
1.211 brouard 6387: fprintf(ficgp,"\n#\n");
1.223 brouard 6388: if(invalidvarcomb[k1]){
6389: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
6390: continue;
6391: }
1.219 brouard 6392:
1.238 ! brouard 6393: fprintf(ficgp,"\nset out \"%s_%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1);
! 6394: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
! 6395: if(vpopbased==0)
! 6396: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
! 6397: else
! 6398: fprintf(ficgp,"\nreplot ");
! 6399: for (i=1; i<= nlstate+1 ; i ++) {
! 6400: k=2*i;
! 6401: fprintf(ficgp,"\"%s\" every :::%d::%d u 1:($2==%d && $4!=0 ?$4 : 1/0) \"%%lf %%lf %%lf",subdirf2(fileresu,"T_"),k1-1,k1-1, vpopbased);
! 6402: for (j=1; j<= nlstate+1 ; j ++) {
! 6403: if (j==i) fprintf(ficgp," %%lf (%%lf)");
! 6404: else fprintf(ficgp," %%*lf (%%*lf)");
! 6405: }
! 6406: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
! 6407: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
! 6408: fprintf(ficgp,"\"%s\" every :::%d::%d u 1:($2==%d && $4!=0 ? $4-$5*2 : 1/0) \"%%lf %%lf %%lf",subdirf2(fileresu,"T_"),k1-1,k1-1,vpopbased);
! 6409: for (j=1; j<= nlstate+1 ; j ++) {
! 6410: if (j==i) fprintf(ficgp," %%lf (%%lf)");
! 6411: else fprintf(ficgp," %%*lf (%%*lf)");
! 6412: }
! 6413: fprintf(ficgp,"\" t\"\" w l lt 0,");
! 6414: fprintf(ficgp,"\"%s\" every :::%d::%d u 1:($2==%d && $4!=0 ? $4+$5*2 : 1/0) \"%%lf %%lf %%lf",subdirf2(fileresu,"T_"),k1-1,k1-1,vpopbased);
! 6415: for (j=1; j<= nlstate+1 ; j ++) {
! 6416: if (j==i) fprintf(ficgp," %%lf (%%lf)");
! 6417: else fprintf(ficgp," %%*lf (%%*lf)");
! 6418: }
! 6419: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
! 6420: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
! 6421: } /* state */
! 6422: } /* vpopbased */
! 6423: fprintf(ficgp,"\nset out;set out \"%s_%d.svg\"; replot; set out; \n",subdirf2(optionfilefiname,"E_"),k1); /* Buggy gnuplot */
! 6424: } /* end nres */
! 6425: } /* k1 end 2 eme*/
! 6426:
! 6427:
! 6428: /*3eme*/
! 6429: for (k1=1; k1<= m ; k1 ++){
! 6430: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
! 6431: if(TKresult[nres]!= k)
! 6432: continue;
! 6433:
! 6434: for (cpt=1; cpt<= nlstate ; cpt ++) {
! 6435: fprintf(ficgp,"\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
! 6436: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
! 6437: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
! 6438: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
! 6439: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
! 6440: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
! 6441: vlv= nbcode[Tvaraff[k]][lv];
! 6442: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
! 6443: }
! 6444: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
! 6445: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
! 6446: }
! 6447: fprintf(ficgp,"\n#\n");
! 6448: if(invalidvarcomb[k1]){
! 6449: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
! 6450: continue;
! 6451: }
! 6452:
! 6453: /* k=2+nlstate*(2*cpt-2); */
! 6454: k=2+(nlstate+1)*(cpt-1);
! 6455: fprintf(ficgp,"\nset out \"%s_%d%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1);
! 6456: fprintf(ficgp,"set ter svg size 640, 480\n\
1.201 brouard 6457: plot [%.f:%.f] \"%s\" every :::%d::%d u 1:%d t \"e%d1\" w l",ageminpar,fage,subdirf2(fileresu,"E_"),k1-1,k1-1,k,cpt);
1.238 ! brouard 6458: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
! 6459: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
! 6460: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
! 6461: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
! 6462: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
! 6463: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 6464:
1.238 ! brouard 6465: */
! 6466: for (i=1; i< nlstate ; i ++) {
! 6467: fprintf(ficgp," ,\"%s\" every :::%d::%d u 1:%d t \"e%d%d\" w l",subdirf2(fileresu,"E_"),k1-1,k1-1,k+i,cpt,i+1);
! 6468: /* 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 6469:
1.238 ! brouard 6470: }
! 6471: fprintf(ficgp," ,\"%s\" every :::%d::%d u 1:%d t \"e%d.\" w l",subdirf2(fileresu,"E_"),k1-1,k1-1,k+nlstate,cpt);
! 6472: }
! 6473: } /* end nres */
! 6474: } /* end kl 3eme */
1.126 brouard 6475:
1.223 brouard 6476: /* 4eme */
1.201 brouard 6477: /* Survival functions (period) from state i in state j by initial state i */
1.238 ! brouard 6478: for (k1=1; k1<=m; k1++){ /* For each covariate and each value */
! 6479: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
! 6480: if(TKresult[nres]!= k1)
1.223 brouard 6481: continue;
1.238 ! brouard 6482: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
! 6483: fprintf(ficgp,"\n#\n#\n# Survival functions in state j : 'LIJ_' files, cov=%d state=%d",k1, cpt);
! 6484: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
! 6485: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
! 6486: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
! 6487: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
! 6488: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
! 6489: vlv= nbcode[Tvaraff[k]][lv];
! 6490: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
! 6491: }
! 6492: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
! 6493: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
! 6494: }
! 6495: fprintf(ficgp,"\n#\n");
! 6496: if(invalidvarcomb[k1]){
! 6497: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
! 6498: continue;
1.223 brouard 6499: }
1.238 ! brouard 6500:
! 6501: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1);
! 6502: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
! 6503: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
! 6504: k=3;
! 6505: for (i=1; i<= nlstate ; i ++){
! 6506: if(i==1){
! 6507: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
! 6508: }else{
! 6509: fprintf(ficgp,", '' ");
! 6510: }
! 6511: l=(nlstate+ndeath)*(i-1)+1;
! 6512: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
! 6513: for (j=2; j<= nlstate+ndeath ; j ++)
! 6514: fprintf(ficgp,"+$%d",k+l+j-1);
! 6515: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
! 6516: } /* nlstate */
! 6517: fprintf(ficgp,"\nset out\n");
! 6518: } /* end cpt state*/
! 6519: } /* end nres */
! 6520: } /* end covariate k1 */
! 6521:
1.220 brouard 6522: /* 5eme */
1.201 brouard 6523: /* Survival functions (period) from state i in state j by final state j */
1.238 ! brouard 6524: for (k1=1; k1<= m ; k1++){ /* For each covariate combination if any */
! 6525: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
! 6526: if(TKresult[nres]!= k1)
1.227 brouard 6527: continue;
1.238 ! brouard 6528: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
! 6529: 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);
! 6530: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
! 6531: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
! 6532: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
! 6533: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
! 6534: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
! 6535: vlv= nbcode[Tvaraff[k]][lv];
! 6536: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
! 6537: }
! 6538: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
! 6539: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
! 6540: }
! 6541: fprintf(ficgp,"\n#\n");
! 6542: if(invalidvarcomb[k1]){
! 6543: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
! 6544: continue;
! 6545: }
1.227 brouard 6546:
1.238 ! brouard 6547: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1);
! 6548: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
! 6549: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
! 6550: k=3;
! 6551: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
! 6552: if(j==1)
! 6553: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
! 6554: else
! 6555: fprintf(ficgp,", '' ");
! 6556: l=(nlstate+ndeath)*(cpt-1) +j;
! 6557: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
! 6558: /* for (i=2; i<= nlstate+ndeath ; i ++) */
! 6559: /* fprintf(ficgp,"+$%d",k+l+i-1); */
! 6560: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
! 6561: } /* nlstate */
! 6562: fprintf(ficgp,", '' ");
! 6563: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
! 6564: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
! 6565: l=(nlstate+ndeath)*(cpt-1) +j;
! 6566: if(j < nlstate)
! 6567: fprintf(ficgp,"$%d +",k+l);
! 6568: else
! 6569: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
! 6570: }
! 6571: fprintf(ficgp,"\nset out\n");
! 6572: } /* end cpt state*/
! 6573: } /* end covariate */
! 6574: } /* end nres */
1.227 brouard 6575:
1.220 brouard 6576: /* 6eme */
1.202 brouard 6577: /* CV preval stable (period) for each covariate */
1.237 brouard 6578: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
6579: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
6580: if(TKresult[nres]!= k1)
6581: continue;
1.153 brouard 6582: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.227 brouard 6583:
1.211 brouard 6584: fprintf(ficgp,"\n#\n#\n#CV preval stable (period): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.225 brouard 6585: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.227 brouard 6586: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
6587: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
6588: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
6589: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
6590: vlv= nbcode[Tvaraff[k]][lv];
6591: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 6592: }
1.237 brouard 6593: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6594: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6595: }
1.211 brouard 6596: fprintf(ficgp,"\n#\n");
1.223 brouard 6597: if(invalidvarcomb[k1]){
1.227 brouard 6598: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
6599: continue;
1.223 brouard 6600: }
1.227 brouard 6601:
1.201 brouard 6602: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1);
1.126 brouard 6603: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 ! brouard 6604: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 6605: k=3; /* Offset */
1.153 brouard 6606: for (i=1; i<= nlstate ; i ++){
1.227 brouard 6607: if(i==1)
6608: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
6609: else
6610: fprintf(ficgp,", '' ");
6611: l=(nlstate+ndeath)*(i-1)+1;
6612: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
6613: for (j=2; j<= nlstate ; j ++)
6614: fprintf(ficgp,"+$%d",k+l+j-1);
6615: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 6616: } /* nlstate */
1.201 brouard 6617: fprintf(ficgp,"\nset out\n");
1.153 brouard 6618: } /* end cpt state*/
6619: } /* end covariate */
1.227 brouard 6620:
6621:
1.220 brouard 6622: /* 7eme */
1.218 brouard 6623: if(backcast == 1){
1.217 brouard 6624: /* CV back preval stable (period) for each covariate */
1.237 brouard 6625: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
6626: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
6627: if(TKresult[nres]!= k1)
6628: continue;
1.218 brouard 6629: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.227 brouard 6630: fprintf(ficgp,"\n#\n#\n#CV Back preval stable (period): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
6631: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
6632: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
6633: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
6634: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
1.223 brouard 6635: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.227 brouard 6636: vlv= nbcode[Tvaraff[k]][lv];
6637: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
6638: }
1.237 brouard 6639: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6640: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6641: }
1.227 brouard 6642: fprintf(ficgp,"\n#\n");
6643: if(invalidvarcomb[k1]){
6644: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
6645: continue;
6646: }
6647:
6648: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1);
6649: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 ! brouard 6650: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 6651: k=3; /* Offset */
6652: for (i=1; i<= nlstate ; i ++){
6653: if(i==1)
6654: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
6655: else
6656: fprintf(ficgp,", '' ");
6657: /* l=(nlstate+ndeath)*(i-1)+1; */
6658: l=(nlstate+ndeath)*(cpt-1)+1;
6659: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
6660: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l+(cpt-1)+i-1); /\* a vérifier *\/ */
6661: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+(cpt-1)+i-1); /* a vérifier */
6662: /* for (j=2; j<= nlstate ; j ++) */
6663: /* fprintf(ficgp,"+$%d",k+l+j-1); */
6664: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
6665: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",i,cpt);
6666: } /* nlstate */
6667: fprintf(ficgp,"\nset out\n");
1.218 brouard 6668: } /* end cpt state*/
6669: } /* end covariate */
6670: } /* End if backcast */
6671:
1.223 brouard 6672: /* 8eme */
1.218 brouard 6673: if(prevfcast==1){
6674: /* Projection from cross-sectional to stable (period) for each covariate */
6675:
1.237 brouard 6676: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
6677: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
6678: if(TKresult[nres]!= k1)
6679: continue;
1.211 brouard 6680: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.227 brouard 6681: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to stable (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
6682: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
6683: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
6684: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
6685: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
6686: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
6687: vlv= nbcode[Tvaraff[k]][lv];
6688: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
6689: }
1.237 brouard 6690: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6691: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6692: }
1.227 brouard 6693: fprintf(ficgp,"\n#\n");
6694: if(invalidvarcomb[k1]){
6695: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
6696: continue;
6697: }
6698:
6699: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
6700: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1);
6701: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 ! brouard 6702: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 6703: for (i=1; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
6704: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
6705: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
6706: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
6707: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
6708: if(i==1){
6709: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
6710: }else{
6711: fprintf(ficgp,",\\\n '' ");
6712: }
6713: if(cptcoveff ==0){ /* No covariate */
6714: ioffset=2; /* Age is in 2 */
6715: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
6716: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
6717: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
6718: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
6719: fprintf(ficgp," u %d:(", ioffset);
6720: if(i==nlstate+1)
6721: fprintf(ficgp," $%d/(1.-$%d)) t 'pw.%d' with line ", \
6722: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
6723: else
6724: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
6725: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
6726: }else{ /* more than 2 covariates */
6727: if(cptcoveff ==1){
6728: ioffset=4; /* Age is in 4 */
6729: }else{
6730: ioffset=6; /* Age is in 6 */
6731: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
6732: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
6733: }
6734: fprintf(ficgp," u %d:(",ioffset);
6735: kl=0;
6736: strcpy(gplotcondition,"(");
6737: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
6738: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
6739: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
6740: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
6741: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
6742: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
6743: kl++;
6744: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
6745: kl++;
6746: if(k <cptcoveff && cptcoveff>1)
6747: sprintf(gplotcondition+strlen(gplotcondition)," && ");
6748: }
6749: strcpy(gplotcondition+strlen(gplotcondition),")");
6750: /* 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 *\/ */
6751: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
6752: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
6753: /* '' 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*/
6754: if(i==nlstate+1){
6755: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p.%d' with line ", gplotcondition, \
6756: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
6757: }else{
6758: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
6759: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
6760: }
6761: } /* end if covariate */
6762: } /* nlstate */
6763: fprintf(ficgp,"\nset out\n");
1.223 brouard 6764: } /* end cpt state*/
6765: } /* end covariate */
6766: } /* End if prevfcast */
1.227 brouard 6767:
6768:
1.238 ! brouard 6769: /* 9eme writing MLE parameters */
! 6770: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 6771: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 6772: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 6773: for(k=1; k <=(nlstate+ndeath); k++){
6774: if (k != i) {
1.227 brouard 6775: fprintf(ficgp,"# current state %d\n",k);
6776: for(j=1; j <=ncovmodel; j++){
6777: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
6778: jk++;
6779: }
6780: fprintf(ficgp,"\n");
1.126 brouard 6781: }
6782: }
1.223 brouard 6783: }
1.187 brouard 6784: fprintf(ficgp,"##############\n#\n");
1.227 brouard 6785:
1.145 brouard 6786: /*goto avoid;*/
1.238 ! brouard 6787: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
! 6788: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 6789: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
6790: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
6791: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
6792: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
6793: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
6794: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
6795: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
6796: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
6797: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
6798: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
6799: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
6800: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
6801: fprintf(ficgp,"#\n");
1.223 brouard 6802: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 ! brouard 6803: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.237 brouard 6804: fprintf(ficgp,"#model=%s \n",model);
1.238 ! brouard 6805: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.237 brouard 6806: fprintf(ficgp,"# jk=1 to 2^%d=%d\n",cptcoveff,m);/* to be checked */
6807: for(jk=1; jk <=m; jk++) /* For each combination of covariate */
6808: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
6809: if(TKresult[nres]!= jk)
6810: continue;
6811: fprintf(ficgp,"# Combination of dummy jk=%d and ",jk);
6812: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6813: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6814: }
6815: fprintf(ficgp,"\n#\n");
1.223 brouard 6816: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),jk,ng);
6817: fprintf(ficgp,"\nset ter svg size 640, 480 ");
6818: if (ng==1){
6819: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
6820: fprintf(ficgp,"\nunset log y");
6821: }else if (ng==2){
6822: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
6823: fprintf(ficgp,"\nset log y");
6824: }else if (ng==3){
6825: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
6826: fprintf(ficgp,"\nset log y");
6827: }else
6828: fprintf(ficgp,"\nunset title ");
6829: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
6830: i=1;
6831: for(k2=1; k2<=nlstate; k2++) {
6832: k3=i;
6833: for(k=1; k<=(nlstate+ndeath); k++) {
6834: if (k != k2){
6835: switch( ng) {
6836: case 1:
6837: if(nagesqr==0)
6838: fprintf(ficgp," p%d+p%d*x",i,i+1);
6839: else /* nagesqr =1 */
6840: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
6841: break;
6842: case 2: /* ng=2 */
6843: if(nagesqr==0)
6844: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
6845: else /* nagesqr =1 */
6846: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
6847: break;
6848: case 3:
6849: if(nagesqr==0)
6850: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
6851: else /* nagesqr =1 */
6852: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
6853: break;
6854: }
6855: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 6856: ijp=1; /* product no age */
6857: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
6858: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 6859: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.237 brouard 6860: if(j==Tage[ij]) { /* Product by age */
6861: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
1.238 ! brouard 6862: if(DummyV[j]==0){
1.237 brouard 6863: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
6864: }else{ /* quantitative */
6865: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
6866: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(jk,Tvar[j-2])]); */
6867: }
6868: ij++;
6869: }
6870: }else if(j==Tprod[ijp]) { /* */
6871: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
6872: if(ijp <=cptcovprod) { /* Product */
1.238 ! brouard 6873: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
! 6874: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
1.237 brouard 6875: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(jk,j)],nbcode[Tvard[ijp][2]][codtabm(jk,j)]); */
6876: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
6877: }else{ /* Vn is dummy and Vm is quanti */
6878: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(jk,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
6879: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
6880: }
6881: }else{ /* Vn*Vm Vn is quanti */
1.238 ! brouard 6882: if(DummyV[Tvard[ijp][2]]==0){
1.237 brouard 6883: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
6884: }else{ /* Both quanti */
6885: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
6886: }
6887: }
1.238 ! brouard 6888: ijp++;
1.237 brouard 6889: }
6890: } else{ /* simple covariate */
6891: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(jk,j)]); /\* Valgrind bug nbcode *\/ */
6892: if(Dummy[j]==0){
6893: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
6894: }else{ /* quantitative */
6895: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.223 brouard 6896: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(jk,Tvar[j-2])]); */
6897: }
1.237 brouard 6898: } /* end simple */
6899: } /* end j */
1.223 brouard 6900: }else{
6901: i=i-ncovmodel;
6902: if(ng !=1 ) /* For logit formula of log p11 is more difficult to get */
6903: fprintf(ficgp," (1.");
6904: }
1.227 brouard 6905:
1.223 brouard 6906: if(ng != 1){
6907: fprintf(ficgp,")/(1");
1.227 brouard 6908:
1.223 brouard 6909: for(k1=1; k1 <=nlstate; k1++){
6910: if(nagesqr==0)
6911: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(k1-1)*ncovmodel,k3+(k1-1)*ncovmodel+1);
6912: else /* nagesqr =1 */
6913: fprintf(ficgp,"+exp(p%d+p%d*x+p%d*x*x",k3+(k1-1)*ncovmodel,k3+(k1-1)*ncovmodel+1,k3+(k1-1)*ncovmodel+1+nagesqr);
1.217 brouard 6914:
1.223 brouard 6915: ij=1;
6916: for(j=3; j <=ncovmodel-nagesqr; j++){
1.237 brouard 6917: if((j-2)==Tage[ij]) { /* Bug valgrind */
6918: if(ij <=cptcovage) { /* Bug valgrind */
1.223 brouard 6919: fprintf(ficgp,"+p%d*%d*x",k3+(k1-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(jk,j-2)]);
6920: /* fprintf(ficgp,"+p%d*%d*x",k3+(k1-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(jk,Tvar[j-2])]); */
6921: ij++;
6922: }
6923: }
6924: else
1.225 brouard 6925: fprintf(ficgp,"+p%d*%d",k3+(k1-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(jk,j-2)]);/* Valgrind bug nbcode */
1.223 brouard 6926: }
6927: fprintf(ficgp,")");
6928: }
6929: fprintf(ficgp,")");
6930: if(ng ==2)
6931: fprintf(ficgp," t \"p%d%d\" ", k2,k);
6932: else /* ng= 3 */
6933: fprintf(ficgp," t \"i%d%d\" ", k2,k);
6934: }else{ /* end ng <> 1 */
6935: if( k !=k2) /* logit p11 is hard to draw */
6936: fprintf(ficgp," t \"logit(p%d%d)\" ", k2,k);
6937: }
6938: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
6939: fprintf(ficgp,",");
6940: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
6941: fprintf(ficgp,",");
6942: i=i+ncovmodel;
6943: } /* end k */
6944: } /* end k2 */
6945: fprintf(ficgp,"\n set out\n");
6946: } /* end jk */
6947: } /* end ng */
6948: /* avoid: */
6949: fflush(ficgp);
1.126 brouard 6950: } /* end gnuplot */
6951:
6952:
6953: /*************** Moving average **************/
1.219 brouard 6954: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 6955: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 6956:
1.222 brouard 6957: int i, cpt, cptcod;
6958: int modcovmax =1;
6959: int mobilavrange, mob;
6960: int iage=0;
6961:
6962: double sum=0.;
6963: double age;
6964: double *sumnewp, *sumnewm;
6965: double *agemingood, *agemaxgood; /* Currently identical for all covariates */
6966:
6967:
1.225 brouard 6968: /* modcovmax=2*cptcoveff;/\* Max number of modalities. We suppose */
1.222 brouard 6969: /* a covariate has 2 modalities, should be equal to ncovcombmax *\/ */
6970:
6971: sumnewp = vector(1,ncovcombmax);
6972: sumnewm = vector(1,ncovcombmax);
6973: agemingood = vector(1,ncovcombmax);
6974: agemaxgood = vector(1,ncovcombmax);
6975:
6976: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
6977: sumnewm[cptcod]=0.;
6978: sumnewp[cptcod]=0.;
6979: agemingood[cptcod]=0;
6980: agemaxgood[cptcod]=0;
6981: }
6982: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
6983:
6984: if(mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
6985: if(mobilav==1) mobilavrange=5; /* default */
6986: else mobilavrange=mobilav;
6987: for (age=bage; age<=fage; age++)
6988: for (i=1; i<=nlstate;i++)
6989: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
6990: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
6991: /* We keep the original values on the extreme ages bage, fage and for
6992: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
6993: we use a 5 terms etc. until the borders are no more concerned.
6994: */
6995: for (mob=3;mob <=mobilavrange;mob=mob+2){
6996: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
6997: for (i=1; i<=nlstate;i++){
6998: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
6999: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
7000: for (cpt=1;cpt<=(mob-1)/2;cpt++){
7001: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
7002: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
7003: }
7004: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
7005: }
7006: }
7007: }/* end age */
7008: }/* end mob */
7009: }else
7010: return -1;
7011: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
7012: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
7013: if(invalidvarcomb[cptcod]){
7014: printf("\nCombination (%d) ignored because no cases \n",cptcod);
7015: continue;
7016: }
1.219 brouard 7017:
1.222 brouard 7018: agemingood[cptcod]=fage-(mob-1)/2;
7019: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, finding the youngest wrong */
7020: sumnewm[cptcod]=0.;
7021: for (i=1; i<=nlstate;i++){
7022: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
7023: }
7024: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
7025: agemingood[cptcod]=age;
7026: }else{ /* bad */
7027: for (i=1; i<=nlstate;i++){
7028: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
7029: } /* i */
7030: } /* end bad */
7031: }/* age */
7032: sum=0.;
7033: for (i=1; i<=nlstate;i++){
7034: sum+=mobaverage[(int)agemingood[cptcod]][i][cptcod];
7035: }
7036: if(fabs(sum - 1.) > 1.e-3) { /* bad */
7037: printf("For this combination of covariate cptcod=%d, we can't get a smoothed prevalence which sums to one at any descending age!\n",cptcod);
7038: /* for (i=1; i<=nlstate;i++){ */
7039: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
7040: /* } /\* i *\/ */
7041: } /* end bad */
7042: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
7043: /* From youngest, finding the oldest wrong */
7044: agemaxgood[cptcod]=bage+(mob-1)/2;
7045: for (age=bage+(mob-1)/2; age<=fage; age++){
7046: sumnewm[cptcod]=0.;
7047: for (i=1; i<=nlstate;i++){
7048: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
7049: }
7050: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
7051: agemaxgood[cptcod]=age;
7052: }else{ /* bad */
7053: for (i=1; i<=nlstate;i++){
7054: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
7055: } /* i */
7056: } /* end bad */
7057: }/* age */
7058: sum=0.;
7059: for (i=1; i<=nlstate;i++){
7060: sum+=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
7061: }
7062: if(fabs(sum - 1.) > 1.e-3) { /* bad */
7063: printf("For this combination of covariate cptcod=%d, we can't get a smoothed prevalence which sums to one at any ascending age!\n",cptcod);
7064: /* for (i=1; i<=nlstate;i++){ */
7065: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
7066: /* } /\* i *\/ */
7067: } /* end bad */
7068:
7069: for (age=bage; age<=fage; age++){
1.235 brouard 7070: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 7071: sumnewp[cptcod]=0.;
7072: sumnewm[cptcod]=0.;
7073: for (i=1; i<=nlstate;i++){
7074: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
7075: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
7076: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
7077: }
7078: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
7079: }
7080: /* printf("\n"); */
7081: /* } */
7082: /* brutal averaging */
7083: for (i=1; i<=nlstate;i++){
7084: for (age=1; age<=bage; age++){
7085: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
7086: /* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); */
7087: }
7088: for (age=fage; age<=AGESUP; age++){
7089: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
7090: /* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); */
7091: }
7092: } /* end i status */
7093: for (i=nlstate+1; i<=nlstate+ndeath;i++){
7094: for (age=1; age<=AGESUP; age++){
7095: /*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*/
7096: mobaverage[(int)age][i][cptcod]=0.;
7097: }
7098: }
7099: }/* end cptcod */
7100: free_vector(sumnewm,1, ncovcombmax);
7101: free_vector(sumnewp,1, ncovcombmax);
7102: free_vector(agemaxgood,1, ncovcombmax);
7103: free_vector(agemingood,1, ncovcombmax);
7104: return 0;
7105: }/* End movingaverage */
1.218 brouard 7106:
1.126 brouard 7107:
7108: /************** Forecasting ******************/
1.235 brouard 7109: void prevforecast(char fileres[], double anproj1, double mproj1, double jproj1, double ageminpar, double agemax, double dateprev1, double dateprev2, int mobilav, double bage, double fage, int firstpass, int lastpass, double anproj2, double p[], int cptcoveff){
1.126 brouard 7110: /* proj1, year, month, day of starting projection
7111: agemin, agemax range of age
7112: dateprev1 dateprev2 range of dates during which prevalence is computed
7113: anproj2 year of en of projection (same day and month as proj1).
7114: */
1.235 brouard 7115: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 7116: double agec; /* generic age */
7117: double agelim, ppij, yp,yp1,yp2,jprojmean,mprojmean,anprojmean;
7118: double *popeffectif,*popcount;
7119: double ***p3mat;
1.218 brouard 7120: /* double ***mobaverage; */
1.126 brouard 7121: char fileresf[FILENAMELENGTH];
7122:
7123: agelim=AGESUP;
1.211 brouard 7124: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
7125: in each health status at the date of interview (if between dateprev1 and dateprev2).
7126: We still use firstpass and lastpass as another selection.
7127: */
1.214 brouard 7128: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
7129: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 7130:
1.201 brouard 7131: strcpy(fileresf,"F_");
7132: strcat(fileresf,fileresu);
1.126 brouard 7133: if((ficresf=fopen(fileresf,"w"))==NULL) {
7134: printf("Problem with forecast resultfile: %s\n", fileresf);
7135: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
7136: }
1.235 brouard 7137: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
7138: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 7139:
1.225 brouard 7140: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 7141:
7142:
7143: stepsize=(int) (stepm+YEARM-1)/YEARM;
7144: if (stepm<=12) stepsize=1;
7145: if(estepm < stepm){
7146: printf ("Problem %d lower than %d\n",estepm, stepm);
7147: }
7148: else hstepm=estepm;
7149:
7150: hstepm=hstepm/stepm;
7151: yp1=modf(dateintmean,&yp);/* extracts integral of datemean in yp and
7152: fractional in yp1 */
7153: anprojmean=yp;
7154: yp2=modf((yp1*12),&yp);
7155: mprojmean=yp;
7156: yp1=modf((yp2*30.5),&yp);
7157: jprojmean=yp;
7158: if(jprojmean==0) jprojmean=1;
7159: if(mprojmean==0) jprojmean=1;
7160:
1.227 brouard 7161: i1=pow(2,cptcoveff);
1.126 brouard 7162: if (cptcovn < 1){i1=1;}
7163:
7164: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
7165:
7166: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 7167:
1.126 brouard 7168: /* if (h==(int)(YEARM*yearp)){ */
1.235 brouard 7169: for(nres=1; nres <= nresult; nres++) /* For each resultline */
7170: for(k=1; k<=i1;k++){
7171: if(TKresult[nres]!= k)
7172: continue;
1.227 brouard 7173: if(invalidvarcomb[k]){
7174: printf("\nCombination (%d) projection ignored because no cases \n",k);
7175: continue;
7176: }
7177: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
7178: for(j=1;j<=cptcoveff;j++) {
7179: fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
7180: }
1.235 brouard 7181: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 ! brouard 7182: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.235 brouard 7183: }
1.227 brouard 7184: fprintf(ficresf," yearproj age");
7185: for(j=1; j<=nlstate+ndeath;j++){
7186: for(i=1; i<=nlstate;i++)
7187: fprintf(ficresf," p%d%d",i,j);
7188: fprintf(ficresf," wp.%d",j);
7189: }
7190: for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) {
7191: fprintf(ficresf,"\n");
7192: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jproj1,mproj1,anproj1+yearp);
7193: for (agec=fage; agec>=(ageminpar-1); agec--){
7194: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
7195: nhstepm = nhstepm/hstepm;
7196: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
7197: oldm=oldms;savm=savms;
1.235 brouard 7198: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.227 brouard 7199:
7200: for (h=0; h<=nhstepm; h++){
7201: if (h*hstepm/YEARM*stepm ==yearp) {
7202: fprintf(ficresf,"\n");
7203: for(j=1;j<=cptcoveff;j++)
7204: fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
7205: fprintf(ficresf,"%.f %.f ",anproj1+yearp,agec+h*hstepm/YEARM*stepm);
7206: }
7207: for(j=1; j<=nlstate+ndeath;j++) {
7208: ppij=0.;
7209: for(i=1; i<=nlstate;i++) {
7210: if (mobilav==1)
7211: ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][i][k];
7212: else {
7213: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
7214: }
7215: if (h*hstepm/YEARM*stepm== yearp) {
7216: fprintf(ficresf," %.3f", p3mat[i][j][h]);
7217: }
7218: } /* end i */
7219: if (h*hstepm/YEARM*stepm==yearp) {
7220: fprintf(ficresf," %.3f", ppij);
7221: }
7222: }/* end j */
7223: } /* end h */
7224: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
7225: } /* end agec */
7226: } /* end yearp */
7227: } /* end k */
1.219 brouard 7228:
1.126 brouard 7229: fclose(ficresf);
1.215 brouard 7230: printf("End of Computing forecasting \n");
7231: fprintf(ficlog,"End of Computing forecasting\n");
7232:
1.126 brouard 7233: }
7234:
1.218 brouard 7235: /* /\************** Back Forecasting ******************\/ */
1.225 brouard 7236: /* void prevbackforecast(char fileres[], 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){ */
1.218 brouard 7237: /* /\* back1, year, month, day of starting backection */
7238: /* agemin, agemax range of age */
7239: /* dateprev1 dateprev2 range of dates during which prevalence is computed */
7240: /* anback2 year of en of backection (same day and month as back1). */
7241: /* *\/ */
7242: /* int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1; */
7243: /* double agec; /\* generic age *\/ */
7244: /* double agelim, ppij, yp,yp1,yp2,jprojmean,mprojmean,anprojmean; */
7245: /* double *popeffectif,*popcount; */
7246: /* double ***p3mat; */
7247: /* /\* double ***mobaverage; *\/ */
7248: /* char fileresfb[FILENAMELENGTH]; */
7249:
7250: /* agelim=AGESUP; */
7251: /* /\* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people */
7252: /* in each health status at the date of interview (if between dateprev1 and dateprev2). */
7253: /* We still use firstpass and lastpass as another selection. */
7254: /* *\/ */
7255: /* /\* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ *\/ */
7256: /* /\* firstpass, lastpass, stepm, weightopt, model); *\/ */
7257: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
7258:
7259: /* strcpy(fileresfb,"FB_"); */
7260: /* strcat(fileresfb,fileresu); */
7261: /* if((ficresfb=fopen(fileresfb,"w"))==NULL) { */
7262: /* printf("Problem with back forecast resultfile: %s\n", fileresfb); */
7263: /* fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb); */
7264: /* } */
7265: /* printf("Computing back forecasting: result on file '%s', please wait... \n", fileresfb); */
7266: /* fprintf(ficlog,"Computing back forecasting: result on file '%s', please wait... \n", fileresfb); */
7267:
1.225 brouard 7268: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.218 brouard 7269:
7270: /* /\* if (mobilav!=0) { *\/ */
7271: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
7272: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
7273: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
7274: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
7275: /* /\* } *\/ */
7276: /* /\* } *\/ */
7277:
7278: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
7279: /* if (stepm<=12) stepsize=1; */
7280: /* if(estepm < stepm){ */
7281: /* printf ("Problem %d lower than %d\n",estepm, stepm); */
7282: /* } */
7283: /* else hstepm=estepm; */
7284:
7285: /* hstepm=hstepm/stepm; */
7286: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
7287: /* fractional in yp1 *\/ */
7288: /* anprojmean=yp; */
7289: /* yp2=modf((yp1*12),&yp); */
7290: /* mprojmean=yp; */
7291: /* yp1=modf((yp2*30.5),&yp); */
7292: /* jprojmean=yp; */
7293: /* if(jprojmean==0) jprojmean=1; */
7294: /* if(mprojmean==0) jprojmean=1; */
7295:
1.225 brouard 7296: /* i1=cptcoveff; */
1.218 brouard 7297: /* if (cptcovn < 1){i1=1;} */
1.217 brouard 7298:
1.218 brouard 7299: /* fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2); */
1.217 brouard 7300:
1.218 brouard 7301: /* fprintf(ficresfb,"#****** Routine prevbackforecast **\n"); */
7302:
7303: /* /\* if (h==(int)(YEARM*yearp)){ *\/ */
7304: /* for(cptcov=1, k=0;cptcov<=i1;cptcov++){ */
1.225 brouard 7305: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
1.218 brouard 7306: /* k=k+1; */
7307: /* fprintf(ficresfb,"\n#****** hbijx=probability over h years, hp.jx is weighted by observed prev \n#"); */
1.225 brouard 7308: /* for(j=1;j<=cptcoveff;j++) { */
1.218 brouard 7309: /* fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
7310: /* } */
7311: /* fprintf(ficresfb," yearbproj age"); */
7312: /* for(j=1; j<=nlstate+ndeath;j++){ */
7313: /* for(i=1; i<=nlstate;i++) */
7314: /* fprintf(ficresfb," p%d%d",i,j); */
7315: /* fprintf(ficresfb," p.%d",j); */
7316: /* } */
7317: /* for (yearp=0; yearp>=(anback2-anback1);yearp -=stepsize) { */
7318: /* /\* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { *\/ */
7319: /* fprintf(ficresfb,"\n"); */
7320: /* fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
7321: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
7322: /* nhstepm=(int) rint((agelim-agec)*YEARM/stepm); */
7323: /* nhstepm = nhstepm/hstepm; */
7324: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
7325: /* oldm=oldms;savm=savms; */
7326: /* hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm,oldm,savm, dnewm, doldm, dsavm, k); */
7327: /* for (h=0; h<=nhstepm; h++){ */
7328: /* if (h*hstepm/YEARM*stepm ==yearp) { */
7329: /* fprintf(ficresfb,"\n"); */
1.225 brouard 7330: /* for(j=1;j<=cptcoveff;j++) */
1.218 brouard 7331: /* fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
7332: /* fprintf(ficresfb,"%.f %.f ",anback1+yearp,agec+h*hstepm/YEARM*stepm); */
7333: /* } */
7334: /* for(j=1; j<=nlstate+ndeath;j++) { */
7335: /* ppij=0.; */
7336: /* for(i=1; i<=nlstate;i++) { */
7337: /* if (mobilav==1) */
7338: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][i][cptcod]; */
7339: /* else { */
7340: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][cptcod]; */
7341: /* } */
7342: /* if (h*hstepm/YEARM*stepm== yearp) { */
7343: /* fprintf(ficresfb," %.3f", p3mat[i][j][h]); */
7344: /* } */
7345: /* } /\* end i *\/ */
7346: /* if (h*hstepm/YEARM*stepm==yearp) { */
7347: /* fprintf(ficresfb," %.3f", ppij); */
7348: /* } */
7349: /* }/\* end j *\/ */
7350: /* } /\* end h *\/ */
7351: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
7352: /* } /\* end agec *\/ */
7353: /* } /\* end yearp *\/ */
7354: /* } /\* end cptcod *\/ */
7355: /* } /\* end cptcov *\/ */
7356:
7357: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
7358:
7359: /* fclose(ficresfb); */
7360: /* printf("End of Computing Back forecasting \n"); */
7361: /* fprintf(ficlog,"End of Computing Back forecasting\n"); */
1.217 brouard 7362:
1.218 brouard 7363: /* } */
1.217 brouard 7364:
1.126 brouard 7365: /************** Forecasting *****not tested NB*************/
1.227 brouard 7366: /* 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 7367:
1.227 brouard 7368: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
7369: /* int *popage; */
7370: /* double calagedatem, agelim, kk1, kk2; */
7371: /* double *popeffectif,*popcount; */
7372: /* double ***p3mat,***tabpop,***tabpopprev; */
7373: /* /\* double ***mobaverage; *\/ */
7374: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 7375:
1.227 brouard 7376: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
7377: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
7378: /* agelim=AGESUP; */
7379: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 7380:
1.227 brouard 7381: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 7382:
7383:
1.227 brouard 7384: /* strcpy(filerespop,"POP_"); */
7385: /* strcat(filerespop,fileresu); */
7386: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
7387: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
7388: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
7389: /* } */
7390: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
7391: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 7392:
1.227 brouard 7393: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 7394:
1.227 brouard 7395: /* /\* if (mobilav!=0) { *\/ */
7396: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
7397: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
7398: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
7399: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
7400: /* /\* } *\/ */
7401: /* /\* } *\/ */
1.126 brouard 7402:
1.227 brouard 7403: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
7404: /* if (stepm<=12) stepsize=1; */
1.126 brouard 7405:
1.227 brouard 7406: /* agelim=AGESUP; */
1.126 brouard 7407:
1.227 brouard 7408: /* hstepm=1; */
7409: /* hstepm=hstepm/stepm; */
1.218 brouard 7410:
1.227 brouard 7411: /* if (popforecast==1) { */
7412: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
7413: /* printf("Problem with population file : %s\n",popfile);exit(0); */
7414: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
7415: /* } */
7416: /* popage=ivector(0,AGESUP); */
7417: /* popeffectif=vector(0,AGESUP); */
7418: /* popcount=vector(0,AGESUP); */
1.126 brouard 7419:
1.227 brouard 7420: /* i=1; */
7421: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 7422:
1.227 brouard 7423: /* imx=i; */
7424: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
7425: /* } */
1.218 brouard 7426:
1.227 brouard 7427: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
7428: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
7429: /* k=k+1; */
7430: /* fprintf(ficrespop,"\n#******"); */
7431: /* for(j=1;j<=cptcoveff;j++) { */
7432: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
7433: /* } */
7434: /* fprintf(ficrespop,"******\n"); */
7435: /* fprintf(ficrespop,"# Age"); */
7436: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
7437: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 7438:
1.227 brouard 7439: /* for (cpt=0; cpt<=0;cpt++) { */
7440: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 7441:
1.227 brouard 7442: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
7443: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
7444: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 7445:
1.227 brouard 7446: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
7447: /* oldm=oldms;savm=savms; */
7448: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 7449:
1.227 brouard 7450: /* for (h=0; h<=nhstepm; h++){ */
7451: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
7452: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
7453: /* } */
7454: /* for(j=1; j<=nlstate+ndeath;j++) { */
7455: /* kk1=0.;kk2=0; */
7456: /* for(i=1; i<=nlstate;i++) { */
7457: /* if (mobilav==1) */
7458: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
7459: /* else { */
7460: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
7461: /* } */
7462: /* } */
7463: /* if (h==(int)(calagedatem+12*cpt)){ */
7464: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
7465: /* /\*fprintf(ficrespop," %.3f", kk1); */
7466: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
7467: /* } */
7468: /* } */
7469: /* for(i=1; i<=nlstate;i++){ */
7470: /* kk1=0.; */
7471: /* for(j=1; j<=nlstate;j++){ */
7472: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
7473: /* } */
7474: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
7475: /* } */
1.218 brouard 7476:
1.227 brouard 7477: /* if (h==(int)(calagedatem+12*cpt)) */
7478: /* for(j=1; j<=nlstate;j++) */
7479: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
7480: /* } */
7481: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
7482: /* } */
7483: /* } */
1.218 brouard 7484:
1.227 brouard 7485: /* /\******\/ */
1.218 brouard 7486:
1.227 brouard 7487: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
7488: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
7489: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
7490: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
7491: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 7492:
1.227 brouard 7493: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
7494: /* oldm=oldms;savm=savms; */
7495: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
7496: /* for (h=0; h<=nhstepm; h++){ */
7497: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
7498: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
7499: /* } */
7500: /* for(j=1; j<=nlstate+ndeath;j++) { */
7501: /* kk1=0.;kk2=0; */
7502: /* for(i=1; i<=nlstate;i++) { */
7503: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
7504: /* } */
7505: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
7506: /* } */
7507: /* } */
7508: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
7509: /* } */
7510: /* } */
7511: /* } */
7512: /* } */
1.218 brouard 7513:
1.227 brouard 7514: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 7515:
1.227 brouard 7516: /* if (popforecast==1) { */
7517: /* free_ivector(popage,0,AGESUP); */
7518: /* free_vector(popeffectif,0,AGESUP); */
7519: /* free_vector(popcount,0,AGESUP); */
7520: /* } */
7521: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
7522: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
7523: /* fclose(ficrespop); */
7524: /* } /\* End of popforecast *\/ */
1.218 brouard 7525:
1.126 brouard 7526: int fileappend(FILE *fichier, char *optionfich)
7527: {
7528: if((fichier=fopen(optionfich,"a"))==NULL) {
7529: printf("Problem with file: %s\n", optionfich);
7530: fprintf(ficlog,"Problem with file: %s\n", optionfich);
7531: return (0);
7532: }
7533: fflush(fichier);
7534: return (1);
7535: }
7536:
7537:
7538: /**************** function prwizard **********************/
7539: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
7540: {
7541:
7542: /* Wizard to print covariance matrix template */
7543:
1.164 brouard 7544: char ca[32], cb[32];
7545: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 7546: int numlinepar;
7547:
7548: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
7549: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
7550: for(i=1; i <=nlstate; i++){
7551: jj=0;
7552: for(j=1; j <=nlstate+ndeath; j++){
7553: if(j==i) continue;
7554: jj++;
7555: /*ca[0]= k+'a'-1;ca[1]='\0';*/
7556: printf("%1d%1d",i,j);
7557: fprintf(ficparo,"%1d%1d",i,j);
7558: for(k=1; k<=ncovmodel;k++){
7559: /* printf(" %lf",param[i][j][k]); */
7560: /* fprintf(ficparo," %lf",param[i][j][k]); */
7561: printf(" 0.");
7562: fprintf(ficparo," 0.");
7563: }
7564: printf("\n");
7565: fprintf(ficparo,"\n");
7566: }
7567: }
7568: printf("# Scales (for hessian or gradient estimation)\n");
7569: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
7570: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
7571: for(i=1; i <=nlstate; i++){
7572: jj=0;
7573: for(j=1; j <=nlstate+ndeath; j++){
7574: if(j==i) continue;
7575: jj++;
7576: fprintf(ficparo,"%1d%1d",i,j);
7577: printf("%1d%1d",i,j);
7578: fflush(stdout);
7579: for(k=1; k<=ncovmodel;k++){
7580: /* printf(" %le",delti3[i][j][k]); */
7581: /* fprintf(ficparo," %le",delti3[i][j][k]); */
7582: printf(" 0.");
7583: fprintf(ficparo," 0.");
7584: }
7585: numlinepar++;
7586: printf("\n");
7587: fprintf(ficparo,"\n");
7588: }
7589: }
7590: printf("# Covariance matrix\n");
7591: /* # 121 Var(a12)\n\ */
7592: /* # 122 Cov(b12,a12) Var(b12)\n\ */
7593: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
7594: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
7595: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
7596: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
7597: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
7598: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
7599: fflush(stdout);
7600: fprintf(ficparo,"# Covariance matrix\n");
7601: /* # 121 Var(a12)\n\ */
7602: /* # 122 Cov(b12,a12) Var(b12)\n\ */
7603: /* # ...\n\ */
7604: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
7605:
7606: for(itimes=1;itimes<=2;itimes++){
7607: jj=0;
7608: for(i=1; i <=nlstate; i++){
7609: for(j=1; j <=nlstate+ndeath; j++){
7610: if(j==i) continue;
7611: for(k=1; k<=ncovmodel;k++){
7612: jj++;
7613: ca[0]= k+'a'-1;ca[1]='\0';
7614: if(itimes==1){
7615: printf("#%1d%1d%d",i,j,k);
7616: fprintf(ficparo,"#%1d%1d%d",i,j,k);
7617: }else{
7618: printf("%1d%1d%d",i,j,k);
7619: fprintf(ficparo,"%1d%1d%d",i,j,k);
7620: /* printf(" %.5le",matcov[i][j]); */
7621: }
7622: ll=0;
7623: for(li=1;li <=nlstate; li++){
7624: for(lj=1;lj <=nlstate+ndeath; lj++){
7625: if(lj==li) continue;
7626: for(lk=1;lk<=ncovmodel;lk++){
7627: ll++;
7628: if(ll<=jj){
7629: cb[0]= lk +'a'-1;cb[1]='\0';
7630: if(ll<jj){
7631: if(itimes==1){
7632: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
7633: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
7634: }else{
7635: printf(" 0.");
7636: fprintf(ficparo," 0.");
7637: }
7638: }else{
7639: if(itimes==1){
7640: printf(" Var(%s%1d%1d)",ca,i,j);
7641: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
7642: }else{
7643: printf(" 0.");
7644: fprintf(ficparo," 0.");
7645: }
7646: }
7647: }
7648: } /* end lk */
7649: } /* end lj */
7650: } /* end li */
7651: printf("\n");
7652: fprintf(ficparo,"\n");
7653: numlinepar++;
7654: } /* end k*/
7655: } /*end j */
7656: } /* end i */
7657: } /* end itimes */
7658:
7659: } /* end of prwizard */
7660: /******************* Gompertz Likelihood ******************************/
7661: double gompertz(double x[])
7662: {
7663: double A,B,L=0.0,sump=0.,num=0.;
7664: int i,n=0; /* n is the size of the sample */
7665:
1.220 brouard 7666: for (i=1;i<=imx ; i++) {
1.126 brouard 7667: sump=sump+weight[i];
7668: /* sump=sump+1;*/
7669: num=num+1;
7670: }
7671:
7672:
7673: /* for (i=0; i<=imx; i++)
7674: 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]);*/
7675:
7676: for (i=1;i<=imx ; i++)
7677: {
7678: if (cens[i] == 1 && wav[i]>1)
7679: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
7680:
7681: if (cens[i] == 0 && wav[i]>1)
7682: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
7683: +log(x[1]/YEARM)+x[2]*(agedc[i]-agegomp)+log(YEARM);
7684:
7685: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
7686: if (wav[i] > 1 ) { /* ??? */
7687: L=L+A*weight[i];
7688: /* 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]);*/
7689: }
7690: }
7691:
7692: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
7693:
7694: return -2*L*num/sump;
7695: }
7696:
1.136 brouard 7697: #ifdef GSL
7698: /******************* Gompertz_f Likelihood ******************************/
7699: double gompertz_f(const gsl_vector *v, void *params)
7700: {
7701: double A,B,LL=0.0,sump=0.,num=0.;
7702: double *x= (double *) v->data;
7703: int i,n=0; /* n is the size of the sample */
7704:
7705: for (i=0;i<=imx-1 ; i++) {
7706: sump=sump+weight[i];
7707: /* sump=sump+1;*/
7708: num=num+1;
7709: }
7710:
7711:
7712: /* for (i=0; i<=imx; i++)
7713: 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]);*/
7714: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
7715: for (i=1;i<=imx ; i++)
7716: {
7717: if (cens[i] == 1 && wav[i]>1)
7718: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
7719:
7720: if (cens[i] == 0 && wav[i]>1)
7721: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
7722: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
7723:
7724: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
7725: if (wav[i] > 1 ) { /* ??? */
7726: LL=LL+A*weight[i];
7727: /* 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]);*/
7728: }
7729: }
7730:
7731: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
7732: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
7733:
7734: return -2*LL*num/sump;
7735: }
7736: #endif
7737:
1.126 brouard 7738: /******************* Printing html file ***********/
1.201 brouard 7739: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 7740: int lastpass, int stepm, int weightopt, char model[],\
7741: int imx, double p[],double **matcov,double agemortsup){
7742: int i,k;
7743:
7744: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
7745: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
7746: for (i=1;i<=2;i++)
7747: 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 7748: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 7749: fprintf(fichtm,"</ul>");
7750:
7751: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
7752:
7753: 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>");
7754:
7755: for (k=agegomp;k<(agemortsup-2);k++)
7756: 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]);
7757:
7758:
7759: fflush(fichtm);
7760: }
7761:
7762: /******************* Gnuplot file **************/
1.201 brouard 7763: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 7764:
7765: char dirfileres[132],optfileres[132];
1.164 brouard 7766:
1.126 brouard 7767: int ng;
7768:
7769:
7770: /*#ifdef windows */
7771: fprintf(ficgp,"cd \"%s\" \n",pathc);
7772: /*#endif */
7773:
7774:
7775: strcpy(dirfileres,optionfilefiname);
7776: strcpy(optfileres,"vpl");
1.199 brouard 7777: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 7778: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 7779: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 7780: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 7781: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
7782:
7783: }
7784:
1.136 brouard 7785: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
7786: {
1.126 brouard 7787:
1.136 brouard 7788: /*-------- data file ----------*/
7789: FILE *fic;
7790: char dummy[]=" ";
1.223 brouard 7791: int i=0, j=0, n=0, iv=0;
7792: int lstra;
1.136 brouard 7793: int linei, month, year,iout;
7794: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 7795: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 7796: char *stratrunc;
1.223 brouard 7797:
1.126 brouard 7798:
7799:
1.136 brouard 7800: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 7801: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
7802: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 7803: }
1.126 brouard 7804:
1.136 brouard 7805: i=1;
7806: linei=0;
7807: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
7808: linei=linei+1;
7809: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
7810: if(line[j] == '\t')
7811: line[j] = ' ';
7812: }
7813: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
7814: ;
7815: };
7816: line[j+1]=0; /* Trims blanks at end of line */
7817: if(line[0]=='#'){
7818: fprintf(ficlog,"Comment line\n%s\n",line);
7819: printf("Comment line\n%s\n",line);
7820: continue;
7821: }
7822: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 7823: strcpy(line, linetmp);
1.223 brouard 7824:
7825: /* Loops on waves */
7826: for (j=maxwav;j>=1;j--){
7827: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 ! brouard 7828: cutv(stra, strb, line, ' ');
! 7829: if(strb[0]=='.') { /* Missing value */
! 7830: lval=-1;
! 7831: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
! 7832: cotvar[j][ntv+iv][i]=-1; /* For performance reasons */
! 7833: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
! 7834: 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);
! 7835: 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);
! 7836: return 1;
! 7837: }
! 7838: }else{
! 7839: errno=0;
! 7840: /* what_kind_of_number(strb); */
! 7841: dval=strtod(strb,&endptr);
! 7842: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
! 7843: /* if(strb != endptr && *endptr == '\0') */
! 7844: /* dval=dlval; */
! 7845: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
! 7846: if( strb[0]=='\0' || (*endptr != '\0')){
! 7847: 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);
! 7848: 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);
! 7849: return 1;
! 7850: }
! 7851: cotqvar[j][iv][i]=dval;
! 7852: cotvar[j][ntv+iv][i]=dval;
! 7853: }
! 7854: strcpy(line,stra);
1.223 brouard 7855: }/* end loop ntqv */
1.225 brouard 7856:
1.223 brouard 7857: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 ! brouard 7858: cutv(stra, strb, line, ' ');
! 7859: if(strb[0]=='.') { /* Missing value */
! 7860: lval=-1;
! 7861: }else{
! 7862: errno=0;
! 7863: lval=strtol(strb,&endptr,10);
! 7864: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
! 7865: if( strb[0]=='\0' || (*endptr != '\0')){
! 7866: 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);
! 7867: 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);
! 7868: return 1;
! 7869: }
! 7870: }
! 7871: if(lval <-1 || lval >1){
! 7872: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.223 brouard 7873: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
7874: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 ! brouard 7875: For example, for multinomial values like 1, 2 and 3,\n \
! 7876: build V1=0 V2=0 for the reference value (1),\n \
! 7877: V1=1 V2=0 for (2) \n \
1.223 brouard 7878: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 ! brouard 7879: output of IMaCh is often meaningless.\n \
1.223 brouard 7880: Exiting.\n",lval,linei, i,line,j);
1.238 ! brouard 7881: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.223 brouard 7882: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
7883: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 ! brouard 7884: For example, for multinomial values like 1, 2 and 3,\n \
! 7885: build V1=0 V2=0 for the reference value (1),\n \
! 7886: V1=1 V2=0 for (2) \n \
1.223 brouard 7887: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 ! brouard 7888: output of IMaCh is often meaningless.\n \
1.223 brouard 7889: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.238 ! brouard 7890: return 1;
! 7891: }
! 7892: cotvar[j][iv][i]=(double)(lval);
! 7893: strcpy(line,stra);
1.223 brouard 7894: }/* end loop ntv */
1.225 brouard 7895:
1.223 brouard 7896: /* Statuses at wave */
1.137 brouard 7897: cutv(stra, strb, line, ' ');
1.223 brouard 7898: if(strb[0]=='.') { /* Missing value */
1.238 ! brouard 7899: lval=-1;
1.136 brouard 7900: }else{
1.238 ! brouard 7901: errno=0;
! 7902: lval=strtol(strb,&endptr,10);
! 7903: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
! 7904: if( strb[0]=='\0' || (*endptr != '\0')){
! 7905: 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);
! 7906: 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);
! 7907: return 1;
! 7908: }
1.136 brouard 7909: }
1.225 brouard 7910:
1.136 brouard 7911: s[j][i]=lval;
1.225 brouard 7912:
1.223 brouard 7913: /* Date of Interview */
1.136 brouard 7914: strcpy(line,stra);
7915: cutv(stra, strb,line,' ');
1.169 brouard 7916: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 7917: }
1.169 brouard 7918: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 7919: month=99;
7920: year=9999;
1.136 brouard 7921: }else{
1.225 brouard 7922: 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);
7923: 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);
7924: return 1;
1.136 brouard 7925: }
7926: anint[j][i]= (double) year;
7927: mint[j][i]= (double)month;
7928: strcpy(line,stra);
1.223 brouard 7929: } /* End loop on waves */
1.225 brouard 7930:
1.223 brouard 7931: /* Date of death */
1.136 brouard 7932: cutv(stra, strb,line,' ');
1.169 brouard 7933: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 7934: }
1.169 brouard 7935: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 7936: month=99;
7937: year=9999;
7938: }else{
1.141 brouard 7939: 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 7940: 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);
7941: return 1;
1.136 brouard 7942: }
7943: andc[i]=(double) year;
7944: moisdc[i]=(double) month;
7945: strcpy(line,stra);
7946:
1.223 brouard 7947: /* Date of birth */
1.136 brouard 7948: cutv(stra, strb,line,' ');
1.169 brouard 7949: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 7950: }
1.169 brouard 7951: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 7952: month=99;
7953: year=9999;
7954: }else{
1.141 brouard 7955: 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);
7956: 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 7957: return 1;
1.136 brouard 7958: }
7959: if (year==9999) {
1.141 brouard 7960: 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);
7961: 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 7962: return 1;
7963:
1.136 brouard 7964: }
7965: annais[i]=(double)(year);
7966: moisnais[i]=(double)(month);
7967: strcpy(line,stra);
1.225 brouard 7968:
1.223 brouard 7969: /* Sample weight */
1.136 brouard 7970: cutv(stra, strb,line,' ');
7971: errno=0;
7972: dval=strtod(strb,&endptr);
7973: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 7974: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
7975: 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 7976: fflush(ficlog);
7977: return 1;
7978: }
7979: weight[i]=dval;
7980: strcpy(line,stra);
1.225 brouard 7981:
1.223 brouard 7982: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
7983: cutv(stra, strb, line, ' ');
7984: if(strb[0]=='.') { /* Missing value */
1.225 brouard 7985: lval=-1;
1.223 brouard 7986: }else{
1.225 brouard 7987: errno=0;
7988: /* what_kind_of_number(strb); */
7989: dval=strtod(strb,&endptr);
7990: /* if(strb != endptr && *endptr == '\0') */
7991: /* dval=dlval; */
7992: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
7993: if( strb[0]=='\0' || (*endptr != '\0')){
7994: 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);
7995: 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);
7996: return 1;
7997: }
7998: coqvar[iv][i]=dval;
1.226 brouard 7999: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 8000: }
8001: strcpy(line,stra);
8002: }/* end loop nqv */
1.136 brouard 8003:
1.223 brouard 8004: /* Covariate values */
1.136 brouard 8005: for (j=ncovcol;j>=1;j--){
8006: cutv(stra, strb,line,' ');
1.223 brouard 8007: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 8008: lval=-1;
1.136 brouard 8009: }else{
1.225 brouard 8010: errno=0;
8011: lval=strtol(strb,&endptr,10);
8012: if( strb[0]=='\0' || (*endptr != '\0')){
8013: 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);
8014: 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);
8015: return 1;
8016: }
1.136 brouard 8017: }
8018: if(lval <-1 || lval >1){
1.225 brouard 8019: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 8020: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
8021: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 8022: For example, for multinomial values like 1, 2 and 3,\n \
8023: build V1=0 V2=0 for the reference value (1),\n \
8024: V1=1 V2=0 for (2) \n \
1.136 brouard 8025: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 8026: output of IMaCh is often meaningless.\n \
1.136 brouard 8027: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 8028: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 8029: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
8030: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 8031: For example, for multinomial values like 1, 2 and 3,\n \
8032: build V1=0 V2=0 for the reference value (1),\n \
8033: V1=1 V2=0 for (2) \n \
1.136 brouard 8034: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 8035: output of IMaCh is often meaningless.\n \
1.136 brouard 8036: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 8037: return 1;
1.136 brouard 8038: }
8039: covar[j][i]=(double)(lval);
8040: strcpy(line,stra);
8041: }
8042: lstra=strlen(stra);
1.225 brouard 8043:
1.136 brouard 8044: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
8045: stratrunc = &(stra[lstra-9]);
8046: num[i]=atol(stratrunc);
8047: }
8048: else
8049: num[i]=atol(stra);
8050: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
8051: 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;}*/
8052:
8053: i=i+1;
8054: } /* End loop reading data */
1.225 brouard 8055:
1.136 brouard 8056: *imax=i-1; /* Number of individuals */
8057: fclose(fic);
1.225 brouard 8058:
1.136 brouard 8059: return (0);
1.164 brouard 8060: /* endread: */
1.225 brouard 8061: printf("Exiting readdata: ");
8062: fclose(fic);
8063: return (1);
1.223 brouard 8064: }
1.126 brouard 8065:
1.234 brouard 8066: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 8067: char *p1 = *stri, *p2 = *stri;
1.235 brouard 8068: while (*p2 == ' ')
1.234 brouard 8069: p2++;
8070: /* while ((*p1++ = *p2++) !=0) */
8071: /* ; */
8072: /* do */
8073: /* while (*p2 == ' ') */
8074: /* p2++; */
8075: /* while (*p1++ == *p2++); */
8076: *stri=p2;
1.145 brouard 8077: }
8078:
1.235 brouard 8079: int decoderesult ( char resultline[], int nres)
1.230 brouard 8080: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
8081: {
1.235 brouard 8082: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 8083: char resultsav[MAXLINE];
1.234 brouard 8084: int resultmodel[MAXLINE];
8085: int modelresult[MAXLINE];
1.230 brouard 8086: char stra[80], strb[80], strc[80], strd[80],stre[80];
8087:
1.234 brouard 8088: removefirstspace(&resultline);
1.233 brouard 8089: printf("decoderesult:%s\n",resultline);
1.230 brouard 8090:
8091: if (strstr(resultline,"v") !=0){
8092: printf("Error. 'v' must be in upper case 'V' result: %s ",resultline);
8093: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultline);fflush(ficlog);
8094: return 1;
8095: }
8096: trimbb(resultsav, resultline);
8097: if (strlen(resultsav) >1){
8098: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' */
8099: }
1.234 brouard 8100: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
8101: printf("ERROR: the number of variable in the resultline, %d, differs from the number of variable used in the model line, %d.\n",j, cptcovs);
8102: fprintf(ficlog,"ERROR: the number of variable in the resultline, %d, differs from the number of variable used in the model line, %d.\n",j, cptcovs);
8103: }
8104: for(k=1; k<=j;k++){ /* Loop on any covariate of the result line */
8105: if(nbocc(resultsav,'=') >1){
8106: cutl(stra,strb,resultsav,' '); /* keeps in strb after the first ' '
8107: resultsav= V4=1 V5=25.1 V3=0 strb=V3=0 stra= V4=1 V5=25.1 */
8108: cutl(strc,strd,strb,'='); /* strb:V4=1 strc=1 strd=V4 */
8109: }else
8110: cutl(strc,strd,resultsav,'=');
1.230 brouard 8111: Tvalsel[k]=atof(strc); /* 1 */
1.234 brouard 8112:
1.230 brouard 8113: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
8114: Tvarsel[k]=atoi(strc);
8115: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
8116: /* cptcovsel++; */
8117: if (nbocc(stra,'=') >0)
8118: strcpy(resultsav,stra); /* and analyzes it */
8119: }
1.235 brouard 8120: /* Checking for missing or useless values in comparison of current model needs */
1.236 brouard 8121: for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
8122: if(Typevar[k1]==0){ /* Single covariate in model */
1.234 brouard 8123: match=0;
1.236 brouard 8124: for(k2=1; k2 <=j;k2++){/* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.237 brouard 8125: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar[1]=5 == Tvarsel[2]=5 */
1.236 brouard 8126: modelresult[k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.234 brouard 8127: match=1;
8128: break;
8129: }
8130: }
8131: if(match == 0){
8132: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
8133: }
8134: }
8135: }
1.235 brouard 8136: /* Checking for missing or useless values in comparison of current model needs */
8137: for(k2=1; k2 <=j;k2++){ /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 8138: match=0;
1.235 brouard 8139: for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
8140: if(Typevar[k1]==0){ /* Single */
1.237 brouard 8141: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 */
1.235 brouard 8142: resultmodel[k1]=k2; /* resultmodel[2]=1 resultmodel[1]=2 resultmodel[3]=3 resultmodel[6]=4 resultmodel[9]=5 */
1.234 brouard 8143: ++match;
8144: }
8145: }
8146: }
8147: if(match == 0){
8148: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
8149: }else if(match > 1){
8150: printf("Error in result line: %d doubled; result: %s, model=%s\n",k2, resultline, model);
8151: }
8152: }
1.235 brouard 8153:
1.234 brouard 8154: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 8155: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
8156: /* result line V4=1 V5=25.1 V3=0 V2=8 V1=1 */
8157: /* should give a combination of dummy V4=1, V3=0, V1=1 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 5 + (1offset) = 6*/
8158: /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
8159: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
8160: /* 1 0 0 0 */
8161: /* 2 1 0 0 */
8162: /* 3 0 1 0 */
8163: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 */
8164: /* 5 0 0 1 */
8165: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 */
8166: /* 7 0 1 1 */
8167: /* 8 1 1 1 */
1.237 brouard 8168: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
8169: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
8170: /* V5*age V5 known which value for nres? */
8171: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.235 brouard 8172: for(k1=1, k=0, k4=0, k4q=0; k1 <=cptcovt;k1++){ /* model line */
8173: if( Dummy[k1]==0 && Typevar[k1]==0 ){ /* Single dummy */
1.237 brouard 8174: k3= resultmodel[k1]; /* resultmodel[2(V4)] = 1=k3 */
1.235 brouard 8175: k2=(int)Tvarsel[k3]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
8176: k+=Tvalsel[k3]*pow(2,k4); /* Tvalsel[1]=1 */
1.237 brouard 8177: Tresult[nres][k4+1]=Tvalsel[k3];/* Tresult[nres][1]=1(V4=1) Tresult[nres][2]=0(V3=0) */
8178: Tvresult[nres][k4+1]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
8179: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.235 brouard 8180: printf("Decoderesult Dummy k=%d, V(k2=V%d)= Tvalsel[%d]=%d, 2**(%d)\n",k, k2, k3, (int)Tvalsel[k3], k4);
8181: k4++;;
8182: } else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Single quantitative */
8183: k3q= resultmodel[k1]; /* resultmodel[2] = 1=k3 */
8184: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
1.237 brouard 8185: Tqresult[nres][k4q+1]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
8186: Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
8187: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.235 brouard 8188: printf("Decoderesult Quantitative nres=%d, V(k2q=V%d)= Tvalsel[%d]=%d, Tvarsel[%d]=%f\n",nres, k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]);
8189: k4q++;;
8190: }
8191: }
1.234 brouard 8192:
1.235 brouard 8193: TKresult[nres]=++k; /* Combination for the nresult and the model */
1.230 brouard 8194: return (0);
8195: }
1.235 brouard 8196:
1.230 brouard 8197: int decodemodel( char model[], int lastobs)
8198: /**< This routine decodes the model and returns:
1.224 brouard 8199: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
8200: * - nagesqr = 1 if age*age in the model, otherwise 0.
8201: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
8202: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
8203: * - cptcovage number of covariates with age*products =2
8204: * - cptcovs number of simple covariates
8205: * - 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
8206: * which is a new column after the 9 (ncovcol) variables.
8207: * - if k is a product Vn*Vm covar[k][i] is filled with correct values for each individual
8208: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
8209: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
8210: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
8211: */
1.136 brouard 8212: {
1.238 ! brouard 8213: int i, j, k, ks, v;
1.227 brouard 8214: int j1, k1, k2, k3, k4;
1.136 brouard 8215: char modelsav[80];
1.145 brouard 8216: char stra[80], strb[80], strc[80], strd[80],stre[80];
1.187 brouard 8217: char *strpt;
1.136 brouard 8218:
1.145 brouard 8219: /*removespace(model);*/
1.136 brouard 8220: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.145 brouard 8221: j=0, j1=0, k1=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 8222: if (strstr(model,"AGE") !=0){
1.192 brouard 8223: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
8224: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 8225: return 1;
8226: }
1.141 brouard 8227: if (strstr(model,"v") !=0){
8228: printf("Error. 'v' must be in upper case 'V' model=%s ",model);
8229: fprintf(ficlog,"Error. 'v' must be in upper case model=%s ",model);fflush(ficlog);
8230: return 1;
8231: }
1.187 brouard 8232: strcpy(modelsav,model);
8233: if ((strpt=strstr(model,"age*age")) !=0){
8234: printf(" strpt=%s, model=%s\n",strpt, model);
8235: if(strpt != model){
1.234 brouard 8236: printf("Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 8237: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 8238: corresponding column of parameters.\n",model);
1.234 brouard 8239: fprintf(ficlog,"Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 8240: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 8241: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 8242: return 1;
1.225 brouard 8243: }
1.187 brouard 8244: nagesqr=1;
8245: if (strstr(model,"+age*age") !=0)
1.234 brouard 8246: substrchaine(modelsav, model, "+age*age");
1.187 brouard 8247: else if (strstr(model,"age*age+") !=0)
1.234 brouard 8248: substrchaine(modelsav, model, "age*age+");
1.187 brouard 8249: else
1.234 brouard 8250: substrchaine(modelsav, model, "age*age");
1.187 brouard 8251: }else
8252: nagesqr=0;
8253: if (strlen(modelsav) >1){
8254: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
8255: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.224 brouard 8256: cptcovs=j+1-j1; /**< Number of simple covariates V1+V1*age+V3 +V3*V4+age*age=> V1 + V3 =5-3=2 */
1.187 brouard 8257: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 8258: * cst, age and age*age
8259: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
8260: /* including age products which are counted in cptcovage.
8261: * but the covariates which are products must be treated
8262: * separately: ncovn=4- 2=2 (V1+V3). */
1.187 brouard 8263: cptcovprod=j1; /**< Number of products V1*V2 +v3*age = 2 */
8264: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.225 brouard 8265:
8266:
1.187 brouard 8267: /* Design
8268: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
8269: * < ncovcol=8 >
8270: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
8271: * k= 1 2 3 4 5 6 7 8
8272: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
8273: * covar[k,i], value of kth covariate if not including age for individual i:
1.224 brouard 8274: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
8275: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 8276: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
8277: * Tage[++cptcovage]=k
8278: * if products, new covar are created after ncovcol with k1
8279: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
8280: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
8281: * 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
8282: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
8283: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
8284: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
8285: * < ncovcol=8 >
8286: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
8287: * k= 1 2 3 4 5 6 7 8 9 10 11 12
8288: * Tvar[k]= 2 1 3 3 10 11 8 8 5 6 7 8
8289: * p Tvar[1]@12={2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
8290: * p Tprod[1]@2={ 6, 5}
8291: *p Tvard[1][1]@4= {7, 8, 5, 6}
8292: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
8293: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
8294: *How to reorganize?
8295: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
8296: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
8297: * {2, 1, 4, 8, 5, 6, 3, 7}
8298: * Struct []
8299: */
1.225 brouard 8300:
1.187 brouard 8301: /* This loop fills the array Tvar from the string 'model'.*/
8302: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
8303: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
8304: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
8305: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
8306: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
8307: /* k=1 Tvar[1]=2 (from V2) */
8308: /* k=5 Tvar[5] */
8309: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 8310: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 8311: /* } */
1.198 brouard 8312: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 8313: /*
8314: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 8315: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
8316: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
8317: }
1.187 brouard 8318: cptcovage=0;
8319: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model */
1.234 brouard 8320: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+'
1.225 brouard 8321: modelsav==V2+V1+V4+V3*age strb=V3*age stra=V2+V1+V4 */
1.234 brouard 8322: if (nbocc(modelsav,'+')==0) strcpy(strb,modelsav); /* and analyzes it */
8323: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
8324: /*scanf("%d",i);*/
8325: if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V4+V3*age strb=V3*age */
8326: cutl(strc,strd,strb,'*'); /**< strd*strc Vm*Vn: strb=V3*age(input) strc=age strd=V3 ; V3*V2 strc=V2, strd=V3 */
8327: if (strcmp(strc,"age")==0) { /**< Model includes age: Vn*age */
8328: /* covar is not filled and then is empty */
8329: cptcovprod--;
8330: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
8331: Tvar[k]=atoi(stre); /* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1 */
8332: Typevar[k]=1; /* 1 for age product */
8333: cptcovage++; /* Sums the number of covariates which include age as a product */
8334: Tage[cptcovage]=k; /* Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */
8335: /*printf("stre=%s ", stre);*/
8336: } else if (strcmp(strd,"age")==0) { /* or age*Vn */
8337: cptcovprod--;
8338: cutl(stre,strb,strc,'V');
8339: Tvar[k]=atoi(stre);
8340: Typevar[k]=1; /* 1 for age product */
8341: cptcovage++;
8342: Tage[cptcovage]=k;
8343: } else { /* Age is not in the model product V2+V1+V1*V4+V3*age+V3*V2 strb=V3*V2*/
8344: /* loops on k1=1 (V3*V2) and k1=2 V4*V3 */
8345: cptcovn++;
8346: cptcovprodnoage++;k1++;
8347: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
8348: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* For model-covariate k tells which data-covariate to use but
8349: because this model-covariate is a construction we invent a new column
8350: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
8351: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2
8352: Tvar[3=V1*V4]=4+1 Tvar[5=V3*V2]=4 + 2= 6, etc */
8353: Typevar[k]=2; /* 2 for double fixed dummy covariates */
8354: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
8355: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 */
8356: Tposprod[k]=k1; /* Tpsprod[3]=1, Tposprod[2]=5 */
8357: Tvard[k1][1] =atoi(strc); /* m 1 for V1*/
8358: Tvard[k1][2] =atoi(stre); /* n 4 for V4*/
8359: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
8360: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
8361: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
1.225 brouard 8362: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
1.234 brouard 8363: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
8364: for (i=1; i<=lastobs;i++){
8365: /* Computes the new covariate which is a product of
8366: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
8367: covar[ncovcol+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
8368: }
8369: } /* End age is not in the model */
8370: } /* End if model includes a product */
8371: else { /* no more sum */
8372: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
8373: /* scanf("%d",i);*/
8374: cutl(strd,strc,strb,'V');
8375: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
8376: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
8377: Tvar[k]=atoi(strd);
8378: Typevar[k]=0; /* 0 for simple covariates */
8379: }
8380: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 8381: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 8382: scanf("%d",i);*/
1.187 brouard 8383: } /* end of loop + on total covariates */
8384: } /* end if strlen(modelsave == 0) age*age might exist */
8385: } /* end if strlen(model == 0) */
1.136 brouard 8386:
8387: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
8388: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 8389:
1.136 brouard 8390: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 8391: printf("cptcovprod=%d ", cptcovprod);
8392: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
8393: scanf("%d ",i);*/
8394:
8395:
1.230 brouard 8396: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
8397: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 8398: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
8399: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
8400: k = 1 2 3 4 5 6 7 8 9
8401: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
8402: Typevar[k]= 0 0 0 2 1 0 2 1 1
1.227 brouard 8403: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
8404: Dummy[k] 1 0 0 0 3 1 1 2 3
8405: Tmodelind[combination of covar]=k;
1.225 brouard 8406: */
8407: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 8408: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 8409: /* 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 8410: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.227 brouard 8411: printf("Model=%s\n\
8412: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
8413: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
8414: 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);
8415: fprintf(ficlog,"Model=%s\n\
8416: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
8417: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
8418: 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);
8419:
1.238 ! brouard 8420: for(v=1; v <=ncovcol;v++){
! 8421: DummyV[v]=0;
! 8422: FixedV[v]=0;
! 8423: }
! 8424: for(v=ncovcol+1; v <=ncovcol+nqv;v++){
! 8425: DummyV[v]=1;
! 8426: FixedV[v]=0;
! 8427: }
! 8428: for(v=ncovcol+nqv+1; v <=ncovcol+nqv+ntv;v++){
! 8429: DummyV[v]=0;
! 8430: FixedV[v]=1;
! 8431: }
! 8432: for(v=ncovcol+nqv+ntv+1; v <=ncovcol+nqv+ntv+nqtv;v++){
! 8433: DummyV[v]=1;
! 8434: FixedV[v]=1;
! 8435: }
! 8436: for(v=1; v <=ncovcol+nqv+ntv+nqtv;v++){
! 8437: printf("Decodemodel: V%d, Dummy(V%d)=%d, FixedV(V%d)=%d\n",v,v,DummyV[v],v,FixedV[v]);
! 8438: fprintf(ficlog,"Decodemodel: V%d, Dummy(V%d)=%d, FixedV(V%d)=%d\n",v,v,DummyV[v],v,FixedV[v]);
! 8439: }
1.234 brouard 8440: 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 */
8441: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 8442: Fixed[k]= 0;
8443: Dummy[k]= 0;
1.225 brouard 8444: ncoveff++;
1.232 brouard 8445: ncovf++;
1.234 brouard 8446: nsd++;
8447: modell[k].maintype= FTYPE;
8448: TvarsD[nsd]=Tvar[k];
8449: TvarsDind[nsd]=k;
8450: TvarF[ncovf]=Tvar[k];
8451: TvarFind[ncovf]=k;
8452: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
8453: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
8454: }else if( Tvar[k] <=ncovcol && Typevar[k]==2){ /* Product of fixed dummy (<=ncovcol) covariates */
8455: Fixed[k]= 0;
8456: Dummy[k]= 0;
8457: ncoveff++;
8458: ncovf++;
8459: modell[k].maintype= FTYPE;
8460: TvarF[ncovf]=Tvar[k];
8461: TvarFind[ncovf]=k;
1.230 brouard 8462: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.231 brouard 8463: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
8464: }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 8465: Fixed[k]= 0;
8466: Dummy[k]= 1;
1.230 brouard 8467: nqfveff++;
1.234 brouard 8468: modell[k].maintype= FTYPE;
8469: modell[k].subtype= FQ;
8470: nsq++;
8471: TvarsQ[nsq]=Tvar[k];
8472: TvarsQind[nsq]=k;
1.232 brouard 8473: ncovf++;
1.234 brouard 8474: TvarF[ncovf]=Tvar[k];
8475: TvarFind[ncovf]=k;
1.231 brouard 8476: 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 8477: 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 */
1.234 brouard 8478: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying variables */
1.227 brouard 8479: Fixed[k]= 1;
8480: Dummy[k]= 0;
1.225 brouard 8481: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 8482: modell[k].maintype= VTYPE;
8483: modell[k].subtype= VD;
8484: nsd++;
8485: TvarsD[nsd]=Tvar[k];
8486: TvarsDind[nsd]=k;
8487: ncovv++; /* Only simple time varying variables */
8488: TvarV[ncovv]=Tvar[k];
8489: TvarVind[ncovv]=k;
1.231 brouard 8490: 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 */
8491: 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 8492: 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);
8493: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 8494: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.234 brouard 8495: Fixed[k]= 1;
8496: Dummy[k]= 1;
8497: nqtveff++;
8498: modell[k].maintype= VTYPE;
8499: modell[k].subtype= VQ;
8500: ncovv++; /* Only simple time varying variables */
8501: nsq++;
8502: TvarsQ[nsq]=Tvar[k];
8503: TvarsQind[nsq]=k;
8504: TvarV[ncovv]=Tvar[k];
8505: TvarVind[ncovv]=k;
1.231 brouard 8506: 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 */
8507: 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 8508: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
8509: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
8510: 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 8511: printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv);
1.227 brouard 8512: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 8513: ncova++;
8514: TvarA[ncova]=Tvar[k];
8515: TvarAind[ncova]=k;
1.231 brouard 8516: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.234 brouard 8517: Fixed[k]= 2;
8518: Dummy[k]= 2;
8519: modell[k].maintype= ATYPE;
8520: modell[k].subtype= APFD;
8521: /* ncoveff++; */
1.227 brouard 8522: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.234 brouard 8523: Fixed[k]= 2;
8524: Dummy[k]= 3;
8525: modell[k].maintype= ATYPE;
8526: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
8527: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 8528: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.234 brouard 8529: Fixed[k]= 3;
8530: Dummy[k]= 2;
8531: modell[k].maintype= ATYPE;
8532: modell[k].subtype= APVD; /* Product age * varying dummy */
8533: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 8534: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.234 brouard 8535: Fixed[k]= 3;
8536: Dummy[k]= 3;
8537: modell[k].maintype= ATYPE;
8538: modell[k].subtype= APVQ; /* Product age * varying quantitative */
8539: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 8540: }
8541: }else if (Typevar[k] == 2) { /* product without age */
8542: k1=Tposprod[k];
8543: if(Tvard[k1][1] <=ncovcol){
1.234 brouard 8544: if(Tvard[k1][2] <=ncovcol){
8545: Fixed[k]= 1;
8546: Dummy[k]= 0;
8547: modell[k].maintype= FTYPE;
8548: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
8549: ncovf++; /* Fixed variables without age */
8550: TvarF[ncovf]=Tvar[k];
8551: TvarFind[ncovf]=k;
8552: }else if(Tvard[k1][2] <=ncovcol+nqv){
8553: Fixed[k]= 0; /* or 2 ?*/
8554: Dummy[k]= 1;
8555: modell[k].maintype= FTYPE;
8556: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
8557: ncovf++; /* Varying variables without age */
8558: TvarF[ncovf]=Tvar[k];
8559: TvarFind[ncovf]=k;
8560: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
8561: Fixed[k]= 1;
8562: Dummy[k]= 0;
8563: modell[k].maintype= VTYPE;
8564: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
8565: ncovv++; /* Varying variables without age */
8566: TvarV[ncovv]=Tvar[k];
8567: TvarVind[ncovv]=k;
8568: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
8569: Fixed[k]= 1;
8570: Dummy[k]= 1;
8571: modell[k].maintype= VTYPE;
8572: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
8573: ncovv++; /* Varying variables without age */
8574: TvarV[ncovv]=Tvar[k];
8575: TvarVind[ncovv]=k;
8576: }
1.227 brouard 8577: }else if(Tvard[k1][1] <=ncovcol+nqv){
1.234 brouard 8578: if(Tvard[k1][2] <=ncovcol){
8579: Fixed[k]= 0; /* or 2 ?*/
8580: Dummy[k]= 1;
8581: modell[k].maintype= FTYPE;
8582: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
8583: ncovf++; /* Fixed variables without age */
8584: TvarF[ncovf]=Tvar[k];
8585: TvarFind[ncovf]=k;
8586: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
8587: Fixed[k]= 1;
8588: Dummy[k]= 1;
8589: modell[k].maintype= VTYPE;
8590: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
8591: ncovv++; /* Varying variables without age */
8592: TvarV[ncovv]=Tvar[k];
8593: TvarVind[ncovv]=k;
8594: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
8595: Fixed[k]= 1;
8596: Dummy[k]= 1;
8597: modell[k].maintype= VTYPE;
8598: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
8599: ncovv++; /* Varying variables without age */
8600: TvarV[ncovv]=Tvar[k];
8601: TvarVind[ncovv]=k;
8602: ncovv++; /* Varying variables without age */
8603: TvarV[ncovv]=Tvar[k];
8604: TvarVind[ncovv]=k;
8605: }
1.227 brouard 8606: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){
1.234 brouard 8607: if(Tvard[k1][2] <=ncovcol){
8608: Fixed[k]= 1;
8609: Dummy[k]= 1;
8610: modell[k].maintype= VTYPE;
8611: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
8612: ncovv++; /* Varying variables without age */
8613: TvarV[ncovv]=Tvar[k];
8614: TvarVind[ncovv]=k;
8615: }else if(Tvard[k1][2] <=ncovcol+nqv){
8616: Fixed[k]= 1;
8617: Dummy[k]= 1;
8618: modell[k].maintype= VTYPE;
8619: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
8620: ncovv++; /* Varying variables without age */
8621: TvarV[ncovv]=Tvar[k];
8622: TvarVind[ncovv]=k;
8623: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
8624: Fixed[k]= 1;
8625: Dummy[k]= 0;
8626: modell[k].maintype= VTYPE;
8627: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
8628: ncovv++; /* Varying variables without age */
8629: TvarV[ncovv]=Tvar[k];
8630: TvarVind[ncovv]=k;
8631: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
8632: Fixed[k]= 1;
8633: Dummy[k]= 1;
8634: modell[k].maintype= VTYPE;
8635: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
8636: ncovv++; /* Varying variables without age */
8637: TvarV[ncovv]=Tvar[k];
8638: TvarVind[ncovv]=k;
8639: }
1.227 brouard 8640: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){
1.234 brouard 8641: if(Tvard[k1][2] <=ncovcol){
8642: Fixed[k]= 1;
8643: Dummy[k]= 1;
8644: modell[k].maintype= VTYPE;
8645: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
8646: ncovv++; /* Varying variables without age */
8647: TvarV[ncovv]=Tvar[k];
8648: TvarVind[ncovv]=k;
8649: }else if(Tvard[k1][2] <=ncovcol+nqv){
8650: Fixed[k]= 1;
8651: Dummy[k]= 1;
8652: modell[k].maintype= VTYPE;
8653: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
8654: ncovv++; /* Varying variables without age */
8655: TvarV[ncovv]=Tvar[k];
8656: TvarVind[ncovv]=k;
8657: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
8658: Fixed[k]= 1;
8659: Dummy[k]= 1;
8660: modell[k].maintype= VTYPE;
8661: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
8662: ncovv++; /* Varying variables without age */
8663: TvarV[ncovv]=Tvar[k];
8664: TvarVind[ncovv]=k;
8665: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
8666: Fixed[k]= 1;
8667: Dummy[k]= 1;
8668: modell[k].maintype= VTYPE;
8669: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
8670: ncovv++; /* Varying variables without age */
8671: TvarV[ncovv]=Tvar[k];
8672: TvarVind[ncovv]=k;
8673: }
1.227 brouard 8674: }else{
1.234 brouard 8675: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
8676: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
1.226 brouard 8677: } /* end k1 */
1.225 brouard 8678: }else{
1.226 brouard 8679: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
8680: 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 8681: }
1.227 brouard 8682: 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 8683: printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype);
1.227 brouard 8684: 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]);
8685: }
8686: /* Searching for doublons in the model */
8687: for(k1=1; k1<= cptcovt;k1++){
8688: for(k2=1; k2 <k1;k2++){
8689: if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){
1.234 brouard 8690: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
8691: if(Tvar[k1]==Tvar[k2]){
8692: printf("Error duplication in the model=%s at positions (+) %d and %d, Tvar[%d]=V%d, Tvar[%d]=V%d, Typevar=%d, Fixed=%d, Dummy=%d\n", model, k1,k2, k1, Tvar[k1], k2, Tvar[k2],Typevar[k1],Fixed[Tvar[k1]],Dummy[Tvar[k1]]);
8693: fprintf(ficlog,"Error duplication in the model=%s at positions (+) %d and %d, Tvar[%d]=V%d, Tvar[%d]=V%d, Typevar=%d, Fixed=%d, Dummy=%d\n", model, k1,k2, k1, Tvar[k1], k2, Tvar[k2],Typevar[k1],Fixed[Tvar[k1]],Dummy[Tvar[k1]]); fflush(ficlog);
8694: return(1);
8695: }
8696: }else if (Typevar[k1] ==2){
8697: k3=Tposprod[k1];
8698: k4=Tposprod[k2];
8699: 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])) ){
8700: printf("Error duplication in the model=%s at positions (+) %d and %d, V%d*V%d, Typevar=%d, Fixed=%d, Dummy=%d\n",model, k1,k2, Tvard[k3][1], Tvard[k3][2],Typevar[k1],Fixed[Tvar[k1]],Dummy[Tvar[k1]]);
8701: fprintf(ficlog,"Error duplication in the model=%s at positions (+) %d and %d, V%d*V%d, Typevar=%d, Fixed=%d, Dummy=%d\n",model, k1,k2, Tvard[k3][1], Tvard[k3][2],Typevar[k1],Fixed[Tvar[k1]],Dummy[Tvar[k1]]); fflush(ficlog);
8702: return(1);
8703: }
8704: }
1.227 brouard 8705: }
8706: }
1.225 brouard 8707: }
8708: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
8709: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 8710: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
8711: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.137 brouard 8712: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 8713: /*endread:*/
1.225 brouard 8714: printf("Exiting decodemodel: ");
8715: return (1);
1.136 brouard 8716: }
8717:
1.169 brouard 8718: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.136 brouard 8719: {
8720: int i, m;
1.218 brouard 8721: int firstone=0;
8722:
1.136 brouard 8723: for (i=1; i<=imx; i++) {
8724: for(m=2; (m<= maxwav); m++) {
8725: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
8726: anint[m][i]=9999;
1.216 brouard 8727: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
8728: s[m][i]=-1;
1.136 brouard 8729: }
8730: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.169 brouard 8731: *nberr = *nberr + 1;
1.218 brouard 8732: if(firstone == 0){
8733: firstone=1;
8734: printf("Error! Date of death (month %2d and year %4d) of individual %ld on line %d was unknown, you must set an arbitrary year of death or he/she is skipped and results can be biased (%d) because status is a death state %d at wave %d. Wave dropped.\nOther similar cases in log file\n",(int)moisdc[i],(int)andc[i],num[i],i, *nberr,s[m][i],m);
8735: }
8736: fprintf(ficlog,"Error! Date of death (month %2d and year %4d) of individual %ld on line %d was unknown, you must set an arbitrary year of death or he/she is skipped and results can be biased (%d) because status is a death state %d at wave %d. Wave dropped.\n",(int)moisdc[i],(int)andc[i],num[i],i, *nberr,s[m][i],m);
1.136 brouard 8737: s[m][i]=-1;
8738: }
8739: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 8740: (*nberr)++;
1.136 brouard 8741: printf("Error! Month of death of individual %ld on line %d was unknown %2d, you should set it otherwise the information on the death is skipped and results are biased.\n",num[i],i,(int)moisdc[i]);
8742: fprintf(ficlog,"Error! Month of death of individual %ld on line %d was unknown %f, you should set it otherwise the information on the death is skipped and results are biased.\n",num[i],i,moisdc[i]);
8743: s[m][i]=-1; /* We prefer to skip it (and to skip it in version 0.8a1 too */
8744: }
8745: }
8746: }
8747:
8748: for (i=1; i<=imx; i++) {
8749: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
8750: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 8751: 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 8752: if (s[m][i] >= nlstate+1) {
1.169 brouard 8753: if(agedc[i]>0){
8754: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 8755: agev[m][i]=agedc[i];
1.214 brouard 8756: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 8757: }else {
1.136 brouard 8758: if ((int)andc[i]!=9999){
8759: nbwarn++;
8760: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
8761: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
8762: agev[m][i]=-1;
8763: }
8764: }
1.169 brouard 8765: } /* agedc > 0 */
1.214 brouard 8766: } /* end if */
1.136 brouard 8767: else if(s[m][i] !=9){ /* Standard case, age in fractional
8768: years but with the precision of a month */
8769: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
8770: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
8771: agev[m][i]=1;
8772: else if(agev[m][i] < *agemin){
8773: *agemin=agev[m][i];
8774: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
8775: }
8776: else if(agev[m][i] >*agemax){
8777: *agemax=agev[m][i];
1.156 brouard 8778: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 8779: }
8780: /*agev[m][i]=anint[m][i]-annais[i];*/
8781: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 8782: } /* en if 9*/
1.136 brouard 8783: else { /* =9 */
1.214 brouard 8784: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 8785: agev[m][i]=1;
8786: s[m][i]=-1;
8787: }
8788: }
1.214 brouard 8789: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 8790: agev[m][i]=1;
1.214 brouard 8791: else{
8792: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
8793: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
8794: agev[m][i]=0;
8795: }
8796: } /* End for lastpass */
8797: }
1.136 brouard 8798:
8799: for (i=1; i<=imx; i++) {
8800: for(m=firstpass; (m<=lastpass); m++){
8801: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 8802: (*nberr)++;
1.136 brouard 8803: 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);
8804: 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);
8805: return 1;
8806: }
8807: }
8808: }
8809:
8810: /*for (i=1; i<=imx; i++){
8811: for (m=firstpass; (m<lastpass); m++){
8812: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
8813: }
8814:
8815: }*/
8816:
8817:
1.139 brouard 8818: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
8819: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 8820:
8821: return (0);
1.164 brouard 8822: /* endread:*/
1.136 brouard 8823: printf("Exiting calandcheckages: ");
8824: return (1);
8825: }
8826:
1.172 brouard 8827: #if defined(_MSC_VER)
8828: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
8829: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
8830: //#include "stdafx.h"
8831: //#include <stdio.h>
8832: //#include <tchar.h>
8833: //#include <windows.h>
8834: //#include <iostream>
8835: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
8836:
8837: LPFN_ISWOW64PROCESS fnIsWow64Process;
8838:
8839: BOOL IsWow64()
8840: {
8841: BOOL bIsWow64 = FALSE;
8842:
8843: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
8844: // (HANDLE, PBOOL);
8845:
8846: //LPFN_ISWOW64PROCESS fnIsWow64Process;
8847:
8848: HMODULE module = GetModuleHandle(_T("kernel32"));
8849: const char funcName[] = "IsWow64Process";
8850: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
8851: GetProcAddress(module, funcName);
8852:
8853: if (NULL != fnIsWow64Process)
8854: {
8855: if (!fnIsWow64Process(GetCurrentProcess(),
8856: &bIsWow64))
8857: //throw std::exception("Unknown error");
8858: printf("Unknown error\n");
8859: }
8860: return bIsWow64 != FALSE;
8861: }
8862: #endif
1.177 brouard 8863:
1.191 brouard 8864: void syscompilerinfo(int logged)
1.167 brouard 8865: {
8866: /* #include "syscompilerinfo.h"*/
1.185 brouard 8867: /* command line Intel compiler 32bit windows, XP compatible:*/
8868: /* /GS /W3 /Gy
8869: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
8870: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
8871: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 8872: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
8873: */
8874: /* 64 bits */
1.185 brouard 8875: /*
8876: /GS /W3 /Gy
8877: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
8878: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
8879: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
8880: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
8881: /* Optimization are useless and O3 is slower than O2 */
8882: /*
8883: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
8884: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
8885: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
8886: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
8887: */
1.186 brouard 8888: /* Link is */ /* /OUT:"visual studio
1.185 brouard 8889: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
8890: /PDB:"visual studio
8891: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
8892: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
8893: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
8894: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
8895: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
8896: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
8897: uiAccess='false'"
8898: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
8899: /NOLOGO /TLBID:1
8900: */
1.177 brouard 8901: #if defined __INTEL_COMPILER
1.178 brouard 8902: #if defined(__GNUC__)
8903: struct utsname sysInfo; /* For Intel on Linux and OS/X */
8904: #endif
1.177 brouard 8905: #elif defined(__GNUC__)
1.179 brouard 8906: #ifndef __APPLE__
1.174 brouard 8907: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 8908: #endif
1.177 brouard 8909: struct utsname sysInfo;
1.178 brouard 8910: int cross = CROSS;
8911: if (cross){
8912: printf("Cross-");
1.191 brouard 8913: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 8914: }
1.174 brouard 8915: #endif
8916:
1.171 brouard 8917: #include <stdint.h>
1.178 brouard 8918:
1.191 brouard 8919: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 8920: #if defined(__clang__)
1.191 brouard 8921: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 8922: #endif
8923: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 8924: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 8925: #endif
8926: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 8927: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 8928: #endif
8929: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 8930: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 8931: #endif
8932: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 8933: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 8934: #endif
8935: #if defined(_MSC_VER)
1.191 brouard 8936: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 8937: #endif
8938: #if defined(__PGI)
1.191 brouard 8939: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 8940: #endif
8941: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 8942: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 8943: #endif
1.191 brouard 8944: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 8945:
1.167 brouard 8946: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
8947: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
8948: // Windows (x64 and x86)
1.191 brouard 8949: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 8950: #elif __unix__ // all unices, not all compilers
8951: // Unix
1.191 brouard 8952: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 8953: #elif __linux__
8954: // linux
1.191 brouard 8955: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 8956: #elif __APPLE__
1.174 brouard 8957: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 8958: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 8959: #endif
8960:
8961: /* __MINGW32__ */
8962: /* __CYGWIN__ */
8963: /* __MINGW64__ */
8964: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
8965: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
8966: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
8967: /* _WIN64 // Defined for applications for Win64. */
8968: /* _M_X64 // Defined for compilations that target x64 processors. */
8969: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 8970:
1.167 brouard 8971: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 8972: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 8973: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 8974: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 8975: #else
1.191 brouard 8976: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 8977: #endif
8978:
1.169 brouard 8979: #if defined(__GNUC__)
8980: # if defined(__GNUC_PATCHLEVEL__)
8981: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
8982: + __GNUC_MINOR__ * 100 \
8983: + __GNUC_PATCHLEVEL__)
8984: # else
8985: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
8986: + __GNUC_MINOR__ * 100)
8987: # endif
1.174 brouard 8988: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 8989: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 8990:
8991: if (uname(&sysInfo) != -1) {
8992: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 8993: 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 8994: }
8995: else
8996: perror("uname() error");
1.179 brouard 8997: //#ifndef __INTEL_COMPILER
8998: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 8999: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 9000: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 9001: #endif
1.169 brouard 9002: #endif
1.172 brouard 9003:
9004: // void main()
9005: // {
1.169 brouard 9006: #if defined(_MSC_VER)
1.174 brouard 9007: if (IsWow64()){
1.191 brouard 9008: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
9009: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 9010: }
9011: else{
1.191 brouard 9012: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
9013: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 9014: }
1.172 brouard 9015: // printf("\nPress Enter to continue...");
9016: // getchar();
9017: // }
9018:
1.169 brouard 9019: #endif
9020:
1.167 brouard 9021:
1.219 brouard 9022: }
1.136 brouard 9023:
1.219 brouard 9024: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.180 brouard 9025: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.235 brouard 9026: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 9027: /* double ftolpl = 1.e-10; */
1.180 brouard 9028: double age, agebase, agelim;
1.203 brouard 9029: double tot;
1.180 brouard 9030:
1.202 brouard 9031: strcpy(filerespl,"PL_");
9032: strcat(filerespl,fileresu);
9033: if((ficrespl=fopen(filerespl,"w"))==NULL) {
9034: printf("Problem with period (stable) prevalence resultfile: %s\n", filerespl);return 1;
9035: fprintf(ficlog,"Problem with period (stable) prevalence resultfile: %s\n", filerespl);return 1;
9036: }
1.227 brouard 9037: printf("\nComputing period (stable) prevalence: result on file '%s' \n", filerespl);
9038: fprintf(ficlog,"\nComputing period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 9039: pstamp(ficrespl);
1.203 brouard 9040: fprintf(ficrespl,"# Period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 9041: fprintf(ficrespl,"#Age ");
9042: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
9043: fprintf(ficrespl,"\n");
1.180 brouard 9044:
1.219 brouard 9045: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 9046:
1.219 brouard 9047: agebase=ageminpar;
9048: agelim=agemaxpar;
1.180 brouard 9049:
1.227 brouard 9050: /* i1=pow(2,ncoveff); */
1.234 brouard 9051: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 9052: if (cptcovn < 1){i1=1;}
1.180 brouard 9053:
1.238 ! brouard 9054: for(k=1; k<=i1;k++){ /* For each combination k of dummy covariates in the model */
! 9055: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
! 9056: if(TKresult[nres]!= k)
! 9057: continue;
1.235 brouard 9058:
1.238 ! brouard 9059: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
! 9060: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
! 9061: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
! 9062: /* k=k+1; */
! 9063: /* to clean */
! 9064: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
! 9065: fprintf(ficrespl,"#******");
! 9066: printf("#******");
! 9067: fprintf(ficlog,"#******");
! 9068: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
! 9069: fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); /* Here problem for varying dummy*/
! 9070: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
! 9071: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
! 9072: }
! 9073: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
! 9074: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
! 9075: fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
! 9076: fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
! 9077: }
! 9078: fprintf(ficrespl,"******\n");
! 9079: printf("******\n");
! 9080: fprintf(ficlog,"******\n");
! 9081: if(invalidvarcomb[k]){
! 9082: printf("\nCombination (%d) ignored because no case \n",k);
! 9083: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
! 9084: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
! 9085: continue;
! 9086: }
1.219 brouard 9087:
1.238 ! brouard 9088: fprintf(ficrespl,"#Age ");
! 9089: for(j=1;j<=cptcoveff;j++) {
! 9090: fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
! 9091: }
! 9092: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
! 9093: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 9094:
1.238 ! brouard 9095: for (age=agebase; age<=agelim; age++){
! 9096: /* for (age=agebase; age<=agebase; age++){ */
! 9097: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres);
! 9098: fprintf(ficrespl,"%.0f ",age );
! 9099: for(j=1;j<=cptcoveff;j++)
! 9100: fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
! 9101: tot=0.;
! 9102: for(i=1; i<=nlstate;i++){
! 9103: tot += prlim[i][i];
! 9104: fprintf(ficrespl," %.5f", prlim[i][i]);
! 9105: }
! 9106: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
! 9107: } /* Age */
! 9108: /* was end of cptcod */
! 9109: } /* cptcov */
! 9110: } /* nres */
1.219 brouard 9111: return 0;
1.180 brouard 9112: }
9113:
1.218 brouard 9114: 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){
9115: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
9116:
9117: /* Computes the back prevalence limit for any combination of covariate values
9118: * at any age between ageminpar and agemaxpar
9119: */
1.235 brouard 9120: int i, j, k, i1, nres=0 ;
1.217 brouard 9121: /* double ftolpl = 1.e-10; */
9122: double age, agebase, agelim;
9123: double tot;
1.218 brouard 9124: /* double ***mobaverage; */
9125: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 9126:
9127: strcpy(fileresplb,"PLB_");
9128: strcat(fileresplb,fileresu);
9129: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
9130: printf("Problem with period (stable) back prevalence resultfile: %s\n", fileresplb);return 1;
9131: fprintf(ficlog,"Problem with period (stable) back prevalence resultfile: %s\n", fileresplb);return 1;
9132: }
9133: printf("Computing period (stable) back prevalence: result on file '%s' \n", fileresplb);
9134: fprintf(ficlog,"Computing period (stable) back prevalence: result on file '%s' \n", fileresplb);
9135: pstamp(ficresplb);
9136: fprintf(ficresplb,"# Period (stable) back prevalence. Precision given by ftolpl=%g \n", ftolpl);
9137: fprintf(ficresplb,"#Age ");
9138: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
9139: fprintf(ficresplb,"\n");
9140:
1.218 brouard 9141:
9142: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
9143:
9144: agebase=ageminpar;
9145: agelim=agemaxpar;
9146:
9147:
1.227 brouard 9148: i1=pow(2,cptcoveff);
1.218 brouard 9149: if (cptcovn < 1){i1=1;}
1.227 brouard 9150:
1.238 ! brouard 9151: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
! 9152: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
! 9153: if(TKresult[nres]!= k)
! 9154: continue;
! 9155: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
! 9156: fprintf(ficresplb,"#******");
! 9157: printf("#******");
! 9158: fprintf(ficlog,"#******");
! 9159: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
! 9160: fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
! 9161: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
! 9162: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
! 9163: }
! 9164: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
! 9165: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
! 9166: fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
! 9167: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
! 9168: }
! 9169: fprintf(ficresplb,"******\n");
! 9170: printf("******\n");
! 9171: fprintf(ficlog,"******\n");
! 9172: if(invalidvarcomb[k]){
! 9173: printf("\nCombination (%d) ignored because no cases \n",k);
! 9174: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
! 9175: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
! 9176: continue;
! 9177: }
1.218 brouard 9178:
1.238 ! brouard 9179: fprintf(ficresplb,"#Age ");
! 9180: for(j=1;j<=cptcoveff;j++) {
! 9181: fprintf(ficresplb,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
! 9182: }
! 9183: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
! 9184: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 9185:
9186:
1.238 ! brouard 9187: for (age=agebase; age<=agelim; age++){
! 9188: /* for (age=agebase; age<=agebase; age++){ */
! 9189: if(mobilavproj > 0){
! 9190: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
! 9191: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
! 9192: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k);
! 9193: }else if (mobilavproj == 0){
! 9194: 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);
! 9195: 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);
! 9196: exit(1);
! 9197: }else{
! 9198: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
! 9199: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k);
! 9200: }
! 9201: fprintf(ficresplb,"%.0f ",age );
! 9202: for(j=1;j<=cptcoveff;j++)
! 9203: fprintf(ficresplb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
! 9204: tot=0.;
! 9205: for(i=1; i<=nlstate;i++){
! 9206: tot += bprlim[i][i];
! 9207: fprintf(ficresplb," %.5f", bprlim[i][i]);
! 9208: }
! 9209: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
! 9210: } /* Age */
! 9211: /* was end of cptcod */
! 9212: } /* end of any combination */
! 9213: } /* end of nres */
1.218 brouard 9214: /* hBijx(p, bage, fage); */
9215: /* fclose(ficrespijb); */
9216:
9217: return 0;
1.217 brouard 9218: }
1.218 brouard 9219:
1.180 brouard 9220: int hPijx(double *p, int bage, int fage){
9221: /*------------- h Pij x at various ages ------------*/
9222:
9223: int stepsize;
9224: int agelim;
9225: int hstepm;
9226: int nhstepm;
1.235 brouard 9227: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 9228:
9229: double agedeb;
9230: double ***p3mat;
9231:
1.201 brouard 9232: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
1.180 brouard 9233: if((ficrespij=fopen(filerespij,"w"))==NULL) {
9234: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
9235: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
9236: }
9237: printf("Computing pij: result on file '%s' \n", filerespij);
9238: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
9239:
9240: stepsize=(int) (stepm+YEARM-1)/YEARM;
9241: /*if (stepm<=24) stepsize=2;*/
9242:
9243: agelim=AGESUP;
9244: hstepm=stepsize*YEARM; /* Every year of age */
9245: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
1.218 brouard 9246:
1.180 brouard 9247: /* hstepm=1; aff par mois*/
9248: pstamp(ficrespij);
9249: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
1.227 brouard 9250: i1= pow(2,cptcoveff);
1.218 brouard 9251: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
9252: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
9253: /* k=k+1; */
1.235 brouard 9254: for(nres=1; nres <= nresult; nres++) /* For each resultline */
9255: for(k=1; k<=i1;k++){
9256: if(TKresult[nres]!= k)
9257: continue;
1.183 brouard 9258: fprintf(ficrespij,"\n#****** ");
1.227 brouard 9259: for(j=1;j<=cptcoveff;j++)
1.198 brouard 9260: fprintf(ficrespij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 9261: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
9262: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
9263: fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
9264: }
1.183 brouard 9265: fprintf(ficrespij,"******\n");
9266:
9267: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
9268: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
9269: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
9270:
9271: /* nhstepm=nhstepm*YEARM; aff par mois*/
1.180 brouard 9272:
1.183 brouard 9273: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9274: oldm=oldms;savm=savms;
1.235 brouard 9275: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.183 brouard 9276: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
9277: for(i=1; i<=nlstate;i++)
9278: for(j=1; j<=nlstate+ndeath;j++)
9279: fprintf(ficrespij," %1d-%1d",i,j);
9280: fprintf(ficrespij,"\n");
9281: for (h=0; h<=nhstepm; h++){
9282: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
9283: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.180 brouard 9284: for(i=1; i<=nlstate;i++)
9285: for(j=1; j<=nlstate+ndeath;j++)
1.183 brouard 9286: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.180 brouard 9287: fprintf(ficrespij,"\n");
9288: }
1.183 brouard 9289: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9290: fprintf(ficrespij,"\n");
9291: }
1.180 brouard 9292: /*}*/
9293: }
1.218 brouard 9294: return 0;
1.180 brouard 9295: }
1.218 brouard 9296:
9297: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 9298: /*------------- h Bij x at various ages ------------*/
9299:
9300: int stepsize;
1.218 brouard 9301: /* int agelim; */
9302: int ageminl;
1.217 brouard 9303: int hstepm;
9304: int nhstepm;
1.238 ! brouard 9305: int h, i, i1, j, k, nres;
1.218 brouard 9306:
1.217 brouard 9307: double agedeb;
9308: double ***p3mat;
1.218 brouard 9309:
9310: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
9311: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
9312: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
9313: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
9314: }
9315: printf("Computing pij back: result on file '%s' \n", filerespijb);
9316: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
9317:
9318: stepsize=(int) (stepm+YEARM-1)/YEARM;
9319: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 9320:
1.218 brouard 9321: /* agelim=AGESUP; */
9322: ageminl=30;
9323: hstepm=stepsize*YEARM; /* Every year of age */
9324: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
9325:
9326: /* hstepm=1; aff par mois*/
9327: pstamp(ficrespijb);
9328: fprintf(ficrespijb,"#****** h Pij x Back Probability to be in state i at age x-h being in j at x ");
1.227 brouard 9329: i1= pow(2,cptcoveff);
1.218 brouard 9330: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
9331: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
9332: /* k=k+1; */
1.238 ! brouard 9333: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
! 9334: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
! 9335: if(TKresult[nres]!= k)
! 9336: continue;
! 9337: fprintf(ficrespijb,"\n#****** ");
! 9338: for(j=1;j<=cptcoveff;j++)
! 9339: fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
! 9340: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
! 9341: fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
! 9342: }
! 9343: fprintf(ficrespijb,"******\n");
! 9344: if(invalidvarcomb[k]){
! 9345: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
! 9346: continue;
! 9347: }
! 9348:
! 9349: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
! 9350: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
! 9351: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
! 9352: nhstepm=(int) rint((agedeb-ageminl)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
! 9353: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 */
! 9354:
! 9355: /* nhstepm=nhstepm*YEARM; aff par mois*/
! 9356:
! 9357: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
! 9358: /* oldm=oldms;savm=savms; */
! 9359: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
! 9360: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k);
! 9361: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
! 9362: fprintf(ficrespijb,"# Cov Agex agex-h hpijx with i,j=");
1.217 brouard 9363: for(i=1; i<=nlstate;i++)
9364: for(j=1; j<=nlstate+ndeath;j++)
1.238 ! brouard 9365: fprintf(ficrespijb," %1d-%1d",i,j);
1.217 brouard 9366: fprintf(ficrespijb,"\n");
1.238 ! brouard 9367: for (h=0; h<=nhstepm; h++){
! 9368: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
! 9369: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
! 9370: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
! 9371: for(i=1; i<=nlstate;i++)
! 9372: for(j=1; j<=nlstate+ndeath;j++)
! 9373: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);
! 9374: fprintf(ficrespijb,"\n");
! 9375: }
! 9376: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
! 9377: fprintf(ficrespijb,"\n");
! 9378: } /* end age deb */
! 9379: } /* end combination */
! 9380: } /* end nres */
1.218 brouard 9381: return 0;
9382: } /* hBijx */
1.217 brouard 9383:
1.180 brouard 9384:
1.136 brouard 9385: /***********************************************/
9386: /**************** Main Program *****************/
9387: /***********************************************/
9388:
9389: int main(int argc, char *argv[])
9390: {
9391: #ifdef GSL
9392: const gsl_multimin_fminimizer_type *T;
9393: size_t iteri = 0, it;
9394: int rval = GSL_CONTINUE;
9395: int status = GSL_SUCCESS;
9396: double ssval;
9397: #endif
9398: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.164 brouard 9399: int i,j, k, n=MAXN,iter=0,m,size=100, cptcod;
1.209 brouard 9400: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 9401: int jj, ll, li, lj, lk;
1.136 brouard 9402: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 9403: int num_filled;
1.136 brouard 9404: int itimes;
9405: int NDIM=2;
9406: int vpopbased=0;
1.235 brouard 9407: int nres=0;
1.136 brouard 9408:
1.164 brouard 9409: char ca[32], cb[32];
1.136 brouard 9410: /* FILE *fichtm; *//* Html File */
9411: /* FILE *ficgp;*/ /*Gnuplot File */
9412: struct stat info;
1.191 brouard 9413: double agedeb=0.;
1.194 brouard 9414:
9415: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 9416: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 9417:
1.165 brouard 9418: double fret;
1.191 brouard 9419: double dum=0.; /* Dummy variable */
1.136 brouard 9420: double ***p3mat;
1.218 brouard 9421: /* double ***mobaverage; */
1.164 brouard 9422:
9423: char line[MAXLINE];
1.197 brouard 9424: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
9425:
1.234 brouard 9426: char modeltemp[MAXLINE];
1.230 brouard 9427: char resultline[MAXLINE];
9428:
1.136 brouard 9429: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 9430: char *tok, *val; /* pathtot */
1.136 brouard 9431: int firstobs=1, lastobs=10;
1.195 brouard 9432: int c, h , cpt, c2;
1.191 brouard 9433: int jl=0;
9434: int i1, j1, jk, stepsize=0;
1.194 brouard 9435: int count=0;
9436:
1.164 brouard 9437: int *tab;
1.136 brouard 9438: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.217 brouard 9439: int backcast=0;
1.136 brouard 9440: int mobilav=0,popforecast=0;
1.191 brouard 9441: int hstepm=0, nhstepm=0;
1.136 brouard 9442: int agemortsup;
9443: float sumlpop=0.;
9444: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
9445: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
9446:
1.191 brouard 9447: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 9448: double ftolpl=FTOL;
9449: double **prlim;
1.217 brouard 9450: double **bprlim;
1.136 brouard 9451: double ***param; /* Matrix of parameters */
9452: double *p;
9453: double **matcov; /* Matrix of covariance */
1.203 brouard 9454: double **hess; /* Hessian matrix */
1.136 brouard 9455: double ***delti3; /* Scale */
9456: double *delti; /* Scale */
9457: double ***eij, ***vareij;
9458: double **varpl; /* Variances of prevalence limits by age */
9459: double *epj, vepp;
1.164 brouard 9460:
1.136 brouard 9461: double dateprev1, dateprev2,jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000;
1.217 brouard 9462: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000;
9463:
1.136 brouard 9464: double **ximort;
1.145 brouard 9465: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 9466: int *dcwave;
9467:
1.164 brouard 9468: char z[1]="c";
1.136 brouard 9469:
9470: /*char *strt;*/
9471: char strtend[80];
1.126 brouard 9472:
1.164 brouard 9473:
1.126 brouard 9474: /* setlocale (LC_ALL, ""); */
9475: /* bindtextdomain (PACKAGE, LOCALEDIR); */
9476: /* textdomain (PACKAGE); */
9477: /* setlocale (LC_CTYPE, ""); */
9478: /* setlocale (LC_MESSAGES, ""); */
9479:
9480: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 9481: rstart_time = time(NULL);
9482: /* (void) gettimeofday(&start_time,&tzp);*/
9483: start_time = *localtime(&rstart_time);
1.126 brouard 9484: curr_time=start_time;
1.157 brouard 9485: /*tml = *localtime(&start_time.tm_sec);*/
9486: /* strcpy(strstart,asctime(&tml)); */
9487: strcpy(strstart,asctime(&start_time));
1.126 brouard 9488:
9489: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 9490: /* tp.tm_sec = tp.tm_sec +86400; */
9491: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 9492: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
9493: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
9494: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 9495: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 9496: /* strt=asctime(&tmg); */
9497: /* printf("Time(after) =%s",strstart); */
9498: /* (void) time (&time_value);
9499: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
9500: * tm = *localtime(&time_value);
9501: * strstart=asctime(&tm);
9502: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
9503: */
9504:
9505: nberr=0; /* Number of errors and warnings */
9506: nbwarn=0;
1.184 brouard 9507: #ifdef WIN32
9508: _getcwd(pathcd, size);
9509: #else
1.126 brouard 9510: getcwd(pathcd, size);
1.184 brouard 9511: #endif
1.191 brouard 9512: syscompilerinfo(0);
1.196 brouard 9513: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 9514: if(argc <=1){
9515: printf("\nEnter the parameter file name: ");
1.205 brouard 9516: if(!fgets(pathr,FILENAMELENGTH,stdin)){
9517: printf("ERROR Empty parameter file name\n");
9518: goto end;
9519: }
1.126 brouard 9520: i=strlen(pathr);
9521: if(pathr[i-1]=='\n')
9522: pathr[i-1]='\0';
1.156 brouard 9523: i=strlen(pathr);
1.205 brouard 9524: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 9525: pathr[i-1]='\0';
1.205 brouard 9526: }
9527: i=strlen(pathr);
9528: if( i==0 ){
9529: printf("ERROR Empty parameter file name\n");
9530: goto end;
9531: }
9532: for (tok = pathr; tok != NULL; ){
1.126 brouard 9533: printf("Pathr |%s|\n",pathr);
9534: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
9535: printf("val= |%s| pathr=%s\n",val,pathr);
9536: strcpy (pathtot, val);
9537: if(pathr[0] == '\0') break; /* Dirty */
9538: }
9539: }
9540: else{
9541: strcpy(pathtot,argv[1]);
9542: }
9543: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
9544: /*cygwin_split_path(pathtot,path,optionfile);
9545: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
9546: /* cutv(path,optionfile,pathtot,'\\');*/
9547:
9548: /* Split argv[0], imach program to get pathimach */
9549: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
9550: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
9551: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
9552: /* strcpy(pathimach,argv[0]); */
9553: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
9554: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
9555: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 9556: #ifdef WIN32
9557: _chdir(path); /* Can be a relative path */
9558: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
9559: #else
1.126 brouard 9560: chdir(path); /* Can be a relative path */
1.184 brouard 9561: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
9562: #endif
9563: printf("Current directory %s!\n",pathcd);
1.126 brouard 9564: strcpy(command,"mkdir ");
9565: strcat(command,optionfilefiname);
9566: if((outcmd=system(command)) != 0){
1.169 brouard 9567: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 9568: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
9569: /* fclose(ficlog); */
9570: /* exit(1); */
9571: }
9572: /* if((imk=mkdir(optionfilefiname))<0){ */
9573: /* perror("mkdir"); */
9574: /* } */
9575:
9576: /*-------- arguments in the command line --------*/
9577:
1.186 brouard 9578: /* Main Log file */
1.126 brouard 9579: strcat(filelog, optionfilefiname);
9580: strcat(filelog,".log"); /* */
9581: if((ficlog=fopen(filelog,"w"))==NULL) {
9582: printf("Problem with logfile %s\n",filelog);
9583: goto end;
9584: }
9585: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 9586: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 9587: fprintf(ficlog,"\nEnter the parameter file name: \n");
9588: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
9589: path=%s \n\
9590: optionfile=%s\n\
9591: optionfilext=%s\n\
1.156 brouard 9592: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 9593:
1.197 brouard 9594: syscompilerinfo(1);
1.167 brouard 9595:
1.126 brouard 9596: printf("Local time (at start):%s",strstart);
9597: fprintf(ficlog,"Local time (at start): %s",strstart);
9598: fflush(ficlog);
9599: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 9600: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 9601:
9602: /* */
9603: strcpy(fileres,"r");
9604: strcat(fileres, optionfilefiname);
1.201 brouard 9605: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 9606: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 9607: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 9608:
1.186 brouard 9609: /* Main ---------arguments file --------*/
1.126 brouard 9610:
9611: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 9612: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
9613: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 9614: fflush(ficlog);
1.149 brouard 9615: /* goto end; */
9616: exit(70);
1.126 brouard 9617: }
9618:
9619:
9620:
9621: strcpy(filereso,"o");
1.201 brouard 9622: strcat(filereso,fileresu);
1.126 brouard 9623: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
9624: printf("Problem with Output resultfile: %s\n", filereso);
9625: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
9626: fflush(ficlog);
9627: goto end;
9628: }
9629:
9630: /* Reads comments: lines beginning with '#' */
9631: numlinepar=0;
1.197 brouard 9632:
9633: /* First parameter line */
9634: while(fgets(line, MAXLINE, ficpar)) {
9635: /* If line starts with a # it is a comment */
9636: if (line[0] == '#') {
9637: numlinepar++;
9638: fputs(line,stdout);
9639: fputs(line,ficparo);
9640: fputs(line,ficlog);
9641: continue;
9642: }else
9643: break;
9644: }
9645: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
9646: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
9647: if (num_filled != 5) {
9648: printf("Should be 5 parameters\n");
9649: }
1.126 brouard 9650: numlinepar++;
1.197 brouard 9651: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
9652: }
9653: /* Second parameter line */
9654: while(fgets(line, MAXLINE, ficpar)) {
9655: /* If line starts with a # it is a comment */
9656: if (line[0] == '#') {
9657: numlinepar++;
9658: fputs(line,stdout);
9659: fputs(line,ficparo);
9660: fputs(line,ficlog);
9661: continue;
9662: }else
9663: break;
9664: }
1.223 brouard 9665: 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", \
9666: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
9667: if (num_filled != 11) {
9668: 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 9669: printf("but line=%s\n",line);
1.197 brouard 9670: }
1.223 brouard 9671: 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);
1.126 brouard 9672: }
1.203 brouard 9673: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 9674: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 9675: /* Third parameter line */
9676: while(fgets(line, MAXLINE, ficpar)) {
9677: /* If line starts with a # it is a comment */
9678: if (line[0] == '#') {
9679: numlinepar++;
9680: fputs(line,stdout);
9681: fputs(line,ficparo);
9682: fputs(line,ficlog);
9683: continue;
9684: }else
9685: break;
9686: }
1.201 brouard 9687: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){
9688: if (num_filled == 0)
9689: model[0]='\0';
9690: else if (num_filled != 1){
1.197 brouard 9691: printf("ERROR %d: Model should be at minimum 'model=1+age.' %s\n",num_filled, line);
9692: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age.' %s\n",num_filled, line);
9693: model[0]='\0';
9694: goto end;
9695: }
9696: else{
9697: if (model[0]=='+'){
9698: for(i=1; i<=strlen(model);i++)
9699: modeltemp[i-1]=model[i];
1.201 brouard 9700: strcpy(model,modeltemp);
1.197 brouard 9701: }
9702: }
1.199 brouard 9703: /* printf(" model=1+age%s modeltemp= %s, model=%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 9704: printf("model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 9705: }
9706: /* 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); */
9707: /* numlinepar=numlinepar+3; /\* In general *\/ */
9708: /* 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); */
1.223 brouard 9709: 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);
9710: 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 9711: fflush(ficlog);
1.190 brouard 9712: /* if(model[0]=='#'|| model[0]== '\0'){ */
9713: if(model[0]=='#'){
1.187 brouard 9714: printf("Error in 'model' line: model should start with 'model=1+age+' and end with '.' \n \
9715: 'model=1+age+.' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age.' or \n \
9716: 'model=1+age+V1+V2.' or 'model=1+age+V1+V2+V1*V2.' etc. \n"); \
9717: if(mle != -1){
9718: printf("Fix the model line and run imach with mle=-1 to get a correct template of the parameter file.\n");
9719: exit(1);
9720: }
9721: }
1.126 brouard 9722: while((c=getc(ficpar))=='#' && c!= EOF){
9723: ungetc(c,ficpar);
9724: fgets(line, MAXLINE, ficpar);
9725: numlinepar++;
1.195 brouard 9726: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
9727: z[0]=line[1];
9728: }
9729: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 9730: fputs(line, stdout);
9731: //puts(line);
1.126 brouard 9732: fputs(line,ficparo);
9733: fputs(line,ficlog);
9734: }
9735: ungetc(c,ficpar);
9736:
9737:
1.145 brouard 9738: covar=matrix(0,NCOVMAX,1,n); /**< used in readdata */
1.225 brouard 9739: coqvar=matrix(1,nqv,1,n); /**< Fixed quantitative covariate */
1.233 brouard 9740: cotvar=ma3x(1,maxwav,1,ntv+nqtv,1,n); /**< Time varying covariate (dummy and quantitative)*/
1.225 brouard 9741: cotqvar=ma3x(1,maxwav,1,nqtv,1,n); /**< Time varying quantitative covariate */
1.136 brouard 9742: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
9743: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
9744: v1+v2*age+v2*v3 makes cptcovn = 3
9745: */
9746: if (strlen(model)>1)
1.187 brouard 9747: 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 9748: else
1.187 brouard 9749: ncovmodel=2; /* Constant and age */
1.133 brouard 9750: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
9751: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 9752: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
9753: 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);
9754: 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);
9755: fflush(stdout);
9756: fclose (ficlog);
9757: goto end;
9758: }
1.126 brouard 9759: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
9760: delti=delti3[1][1];
9761: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
9762: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
9763: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 9764: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
9765: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 9766: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
9767: fclose (ficparo);
9768: fclose (ficlog);
9769: goto end;
9770: exit(0);
1.220 brouard 9771: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 9772: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 9773: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
9774: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 9775: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
9776: matcov=matrix(1,npar,1,npar);
1.203 brouard 9777: hess=matrix(1,npar,1,npar);
1.220 brouard 9778: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 9779: /* Read guessed parameters */
1.126 brouard 9780: /* Reads comments: lines beginning with '#' */
9781: while((c=getc(ficpar))=='#' && c!= EOF){
9782: ungetc(c,ficpar);
9783: fgets(line, MAXLINE, ficpar);
9784: numlinepar++;
1.141 brouard 9785: fputs(line,stdout);
1.126 brouard 9786: fputs(line,ficparo);
9787: fputs(line,ficlog);
9788: }
9789: ungetc(c,ficpar);
9790:
9791: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
9792: for(i=1; i <=nlstate; i++){
1.234 brouard 9793: j=0;
1.126 brouard 9794: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 9795: if(jj==i) continue;
9796: j++;
9797: fscanf(ficpar,"%1d%1d",&i1,&j1);
9798: if ((i1 != i) || (j1 != jj)){
9799: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 9800: It might be a problem of design; if ncovcol and the model are correct\n \
9801: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 9802: exit(1);
9803: }
9804: fprintf(ficparo,"%1d%1d",i1,j1);
9805: if(mle==1)
9806: printf("%1d%1d",i,jj);
9807: fprintf(ficlog,"%1d%1d",i,jj);
9808: for(k=1; k<=ncovmodel;k++){
9809: fscanf(ficpar," %lf",¶m[i][j][k]);
9810: if(mle==1){
9811: printf(" %lf",param[i][j][k]);
9812: fprintf(ficlog," %lf",param[i][j][k]);
9813: }
9814: else
9815: fprintf(ficlog," %lf",param[i][j][k]);
9816: fprintf(ficparo," %lf",param[i][j][k]);
9817: }
9818: fscanf(ficpar,"\n");
9819: numlinepar++;
9820: if(mle==1)
9821: printf("\n");
9822: fprintf(ficlog,"\n");
9823: fprintf(ficparo,"\n");
1.126 brouard 9824: }
9825: }
9826: fflush(ficlog);
1.234 brouard 9827:
1.145 brouard 9828: /* Reads scales values */
1.126 brouard 9829: p=param[1][1];
9830:
9831: /* Reads comments: lines beginning with '#' */
9832: while((c=getc(ficpar))=='#' && c!= EOF){
9833: ungetc(c,ficpar);
9834: fgets(line, MAXLINE, ficpar);
9835: numlinepar++;
1.141 brouard 9836: fputs(line,stdout);
1.126 brouard 9837: fputs(line,ficparo);
9838: fputs(line,ficlog);
9839: }
9840: ungetc(c,ficpar);
9841:
9842: for(i=1; i <=nlstate; i++){
9843: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 9844: fscanf(ficpar,"%1d%1d",&i1,&j1);
9845: if ( (i1-i) * (j1-j) != 0){
9846: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
9847: exit(1);
9848: }
9849: printf("%1d%1d",i,j);
9850: fprintf(ficparo,"%1d%1d",i1,j1);
9851: fprintf(ficlog,"%1d%1d",i1,j1);
9852: for(k=1; k<=ncovmodel;k++){
9853: fscanf(ficpar,"%le",&delti3[i][j][k]);
9854: printf(" %le",delti3[i][j][k]);
9855: fprintf(ficparo," %le",delti3[i][j][k]);
9856: fprintf(ficlog," %le",delti3[i][j][k]);
9857: }
9858: fscanf(ficpar,"\n");
9859: numlinepar++;
9860: printf("\n");
9861: fprintf(ficparo,"\n");
9862: fprintf(ficlog,"\n");
1.126 brouard 9863: }
9864: }
9865: fflush(ficlog);
1.234 brouard 9866:
1.145 brouard 9867: /* Reads covariance matrix */
1.126 brouard 9868: delti=delti3[1][1];
1.220 brouard 9869:
9870:
1.126 brouard 9871: /* 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 9872:
1.126 brouard 9873: /* Reads comments: lines beginning with '#' */
9874: while((c=getc(ficpar))=='#' && c!= EOF){
9875: ungetc(c,ficpar);
9876: fgets(line, MAXLINE, ficpar);
9877: numlinepar++;
1.141 brouard 9878: fputs(line,stdout);
1.126 brouard 9879: fputs(line,ficparo);
9880: fputs(line,ficlog);
9881: }
9882: ungetc(c,ficpar);
1.220 brouard 9883:
1.126 brouard 9884: matcov=matrix(1,npar,1,npar);
1.203 brouard 9885: hess=matrix(1,npar,1,npar);
1.131 brouard 9886: for(i=1; i <=npar; i++)
9887: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 9888:
1.194 brouard 9889: /* Scans npar lines */
1.126 brouard 9890: for(i=1; i <=npar; i++){
1.226 brouard 9891: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 9892: if(count != 3){
1.226 brouard 9893: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 9894: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
9895: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 9896: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 9897: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
9898: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 9899: exit(1);
1.220 brouard 9900: }else{
1.226 brouard 9901: if(mle==1)
9902: printf("%1d%1d%d",i1,j1,jk);
9903: }
9904: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
9905: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 9906: for(j=1; j <=i; j++){
1.226 brouard 9907: fscanf(ficpar," %le",&matcov[i][j]);
9908: if(mle==1){
9909: printf(" %.5le",matcov[i][j]);
9910: }
9911: fprintf(ficlog," %.5le",matcov[i][j]);
9912: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 9913: }
9914: fscanf(ficpar,"\n");
9915: numlinepar++;
9916: if(mle==1)
1.220 brouard 9917: printf("\n");
1.126 brouard 9918: fprintf(ficlog,"\n");
9919: fprintf(ficparo,"\n");
9920: }
1.194 brouard 9921: /* End of read covariance matrix npar lines */
1.126 brouard 9922: for(i=1; i <=npar; i++)
9923: for(j=i+1;j<=npar;j++)
1.226 brouard 9924: matcov[i][j]=matcov[j][i];
1.126 brouard 9925:
9926: if(mle==1)
9927: printf("\n");
9928: fprintf(ficlog,"\n");
9929:
9930: fflush(ficlog);
9931:
9932: /*-------- Rewriting parameter file ----------*/
9933: strcpy(rfileres,"r"); /* "Rparameterfile */
9934: strcat(rfileres,optionfilefiname); /* Parameter file first name*/
9935: strcat(rfileres,"."); /* */
9936: strcat(rfileres,optionfilext); /* Other files have txt extension */
9937: if((ficres =fopen(rfileres,"w"))==NULL) {
1.201 brouard 9938: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
9939: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
1.126 brouard 9940: }
9941: fprintf(ficres,"#%s\n",version);
9942: } /* End of mle != -3 */
1.218 brouard 9943:
1.186 brouard 9944: /* Main data
9945: */
1.126 brouard 9946: n= lastobs;
9947: num=lvector(1,n);
9948: moisnais=vector(1,n);
9949: annais=vector(1,n);
9950: moisdc=vector(1,n);
9951: andc=vector(1,n);
1.220 brouard 9952: weight=vector(1,n);
1.126 brouard 9953: agedc=vector(1,n);
9954: cod=ivector(1,n);
1.220 brouard 9955: for(i=1;i<=n;i++){
1.234 brouard 9956: num[i]=0;
9957: moisnais[i]=0;
9958: annais[i]=0;
9959: moisdc[i]=0;
9960: andc[i]=0;
9961: agedc[i]=0;
9962: cod[i]=0;
9963: weight[i]=1.0; /* Equal weights, 1 by default */
9964: }
1.126 brouard 9965: mint=matrix(1,maxwav,1,n);
9966: anint=matrix(1,maxwav,1,n);
1.131 brouard 9967: s=imatrix(1,maxwav+1,1,n); /* s[i][j] health state for wave i and individual j */
1.126 brouard 9968: tab=ivector(1,NCOVMAX);
1.144 brouard 9969: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 9970: 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 9971:
1.136 brouard 9972: /* Reads data from file datafile */
9973: if (readdata(datafile, firstobs, lastobs, &imx)==1)
9974: goto end;
9975:
9976: /* Calculation of the number of parameters from char model */
1.234 brouard 9977: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 9978: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
9979: k=3 V4 Tvar[k=3]= 4 (from V4)
9980: k=2 V1 Tvar[k=2]= 1 (from V1)
9981: k=1 Tvar[1]=2 (from V2)
1.234 brouard 9982: */
9983:
9984: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
9985: TvarsDind=ivector(1,NCOVMAX); /* */
9986: TvarsD=ivector(1,NCOVMAX); /* */
9987: TvarsQind=ivector(1,NCOVMAX); /* */
9988: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 9989: TvarF=ivector(1,NCOVMAX); /* */
9990: TvarFind=ivector(1,NCOVMAX); /* */
9991: TvarV=ivector(1,NCOVMAX); /* */
9992: TvarVind=ivector(1,NCOVMAX); /* */
9993: TvarA=ivector(1,NCOVMAX); /* */
9994: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 9995: TvarFD=ivector(1,NCOVMAX); /* */
9996: TvarFDind=ivector(1,NCOVMAX); /* */
9997: TvarFQ=ivector(1,NCOVMAX); /* */
9998: TvarFQind=ivector(1,NCOVMAX); /* */
9999: TvarVD=ivector(1,NCOVMAX); /* */
10000: TvarVDind=ivector(1,NCOVMAX); /* */
10001: TvarVQ=ivector(1,NCOVMAX); /* */
10002: TvarVQind=ivector(1,NCOVMAX); /* */
10003:
1.230 brouard 10004: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 10005: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 10006: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
10007: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
10008: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.238 ! brouard 10009: DummyV=ivector(1,NCOVMAX); /* 1 to 3 */
! 10010: FixedV=ivector(1,NCOVMAX); /* 1 to 3 */
1.137 brouard 10011: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
10012: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
10013: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
10014: */
10015: /* For model-covariate k tells which data-covariate to use but
10016: because this model-covariate is a construction we invent a new column
10017: ncovcol + k1
10018: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
10019: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 10020: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
10021: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 10022: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
10023: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 10024: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 10025: */
1.145 brouard 10026: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
10027: 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 10028: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
10029: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.145 brouard 10030: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 10031: 4 covariates (3 plus signs)
10032: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
10033: */
1.230 brouard 10034: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 10035: * individual dummy, fixed or varying:
10036: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
10037: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 10038: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
10039: * V1 df, V2 qf, V3 & V4 dv, V5 qv
10040: * Tmodelind[1]@9={9,0,3,2,}*/
10041: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
10042: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 10043: * individual quantitative, fixed or varying:
10044: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
10045: * 3, 1, 0, 0, 0, 0, 0, 0},
10046: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.186 brouard 10047: /* Main decodemodel */
10048:
1.187 brouard 10049:
1.223 brouard 10050: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 10051: goto end;
10052:
1.137 brouard 10053: if((double)(lastobs-imx)/(double)imx > 1.10){
10054: nbwarn++;
10055: 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);
10056: 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);
10057: }
1.136 brouard 10058: /* if(mle==1){*/
1.137 brouard 10059: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
10060: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 10061: }
10062:
10063: /*-calculation of age at interview from date of interview and age at death -*/
10064: agev=matrix(1,maxwav,1,imx);
10065:
10066: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
10067: goto end;
10068:
1.126 brouard 10069:
1.136 brouard 10070: agegomp=(int)agemin;
10071: free_vector(moisnais,1,n);
10072: free_vector(annais,1,n);
1.126 brouard 10073: /* free_matrix(mint,1,maxwav,1,n);
10074: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 10075: /* free_vector(moisdc,1,n); */
10076: /* free_vector(andc,1,n); */
1.145 brouard 10077: /* */
10078:
1.126 brouard 10079: wav=ivector(1,imx);
1.214 brouard 10080: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
10081: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
10082: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
10083: 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.*/
10084: bh=imatrix(1,lastpass-firstpass+2,1,imx);
10085: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 10086:
10087: /* Concatenates waves */
1.214 brouard 10088: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
10089: Death is a valid wave (if date is known).
10090: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
10091: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
10092: and mw[mi+1][i]. dh depends on stepm.
10093: */
10094:
1.126 brouard 10095: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.145 brouard 10096: /* */
10097:
1.215 brouard 10098: free_vector(moisdc,1,n);
10099: free_vector(andc,1,n);
10100:
1.126 brouard 10101: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
10102: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
10103: ncodemax[1]=1;
1.145 brouard 10104: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 10105: cptcoveff=0;
1.220 brouard 10106: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
10107: tricode(&cptcoveff,Tvar,nbcode,imx, Ndum); /**< Fills nbcode[Tvar[j]][l]; */
1.227 brouard 10108: }
10109:
10110: ncovcombmax=pow(2,cptcoveff);
10111: invalidvarcomb=ivector(1, ncovcombmax);
10112: for(i=1;i<ncovcombmax;i++)
10113: invalidvarcomb[i]=0;
10114:
1.211 brouard 10115: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 10116: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 10117: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 10118:
1.200 brouard 10119: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 10120: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 10121: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 10122: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
10123: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
10124: * (currently 0 or 1) in the data.
10125: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
10126: * corresponding modality (h,j).
10127: */
10128:
1.145 brouard 10129: h=0;
10130: /*if (cptcovn > 0) */
1.126 brouard 10131: m=pow(2,cptcoveff);
10132:
1.144 brouard 10133: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 10134: * For k=4 covariates, h goes from 1 to m=2**k
10135: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
10136: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.186 brouard 10137: * h\k 1 2 3 4
1.143 brouard 10138: *______________________________
10139: * 1 i=1 1 i=1 1 i=1 1 i=1 1
10140: * 2 2 1 1 1
10141: * 3 i=2 1 2 1 1
10142: * 4 2 2 1 1
10143: * 5 i=3 1 i=2 1 2 1
10144: * 6 2 1 2 1
10145: * 7 i=4 1 2 2 1
10146: * 8 2 2 2 1
1.197 brouard 10147: * 9 i=5 1 i=3 1 i=2 1 2
10148: * 10 2 1 1 2
10149: * 11 i=6 1 2 1 2
10150: * 12 2 2 1 2
10151: * 13 i=7 1 i=4 1 2 2
10152: * 14 2 1 2 2
10153: * 15 i=8 1 2 2 2
10154: * 16 2 2 2 2
1.143 brouard 10155: */
1.212 brouard 10156: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 10157: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
10158: * and the value of each covariate?
10159: * V1=1, V2=1, V3=2, V4=1 ?
10160: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
10161: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
10162: * In order to get the real value in the data, we use nbcode
10163: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
10164: * We are keeping this crazy system in order to be able (in the future?)
10165: * to have more than 2 values (0 or 1) for a covariate.
10166: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
10167: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
10168: * bbbbbbbb
10169: * 76543210
10170: * h-1 00000101 (6-1=5)
1.219 brouard 10171: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 10172: * &
10173: * 1 00000001 (1)
1.219 brouard 10174: * 00000000 = 1 & ((h-1) >> (k-1))
10175: * +1= 00000001 =1
1.211 brouard 10176: *
10177: * h=14, k=3 => h'=h-1=13, k'=k-1=2
10178: * h' 1101 =2^3+2^2+0x2^1+2^0
10179: * >>k' 11
10180: * & 00000001
10181: * = 00000001
10182: * +1 = 00000010=2 = codtabm(14,3)
10183: * Reverse h=6 and m=16?
10184: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
10185: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
10186: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
10187: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
10188: * V3=decodtabm(14,3,2**4)=2
10189: * h'=13 1101 =2^3+2^2+0x2^1+2^0
10190: *(h-1) >> (j-1) 0011 =13 >> 2
10191: * &1 000000001
10192: * = 000000001
10193: * +1= 000000010 =2
10194: * 2211
10195: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
10196: * V3=2
1.220 brouard 10197: * codtabm and decodtabm are identical
1.211 brouard 10198: */
10199:
1.145 brouard 10200:
10201: free_ivector(Ndum,-1,NCOVMAX);
10202:
10203:
1.126 brouard 10204:
1.186 brouard 10205: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 10206: strcpy(optionfilegnuplot,optionfilefiname);
10207: if(mle==-3)
1.201 brouard 10208: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 10209: strcat(optionfilegnuplot,".gp");
10210:
10211: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
10212: printf("Problem with file %s",optionfilegnuplot);
10213: }
10214: else{
1.204 brouard 10215: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 10216: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 10217: //fprintf(ficgp,"set missing 'NaNq'\n");
10218: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 10219: }
10220: /* fclose(ficgp);*/
1.186 brouard 10221:
10222:
10223: /* Initialisation of --------- index.htm --------*/
1.126 brouard 10224:
10225: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
10226: if(mle==-3)
1.201 brouard 10227: strcat(optionfilehtm,"-MORT_");
1.126 brouard 10228: strcat(optionfilehtm,".htm");
10229: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 10230: printf("Problem with %s \n",optionfilehtm);
10231: exit(0);
1.126 brouard 10232: }
10233:
10234: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
10235: strcat(optionfilehtmcov,"-cov.htm");
10236: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
10237: printf("Problem with %s \n",optionfilehtmcov), exit(0);
10238: }
10239: else{
10240: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
10241: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 10242: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 10243: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
10244: }
10245:
1.213 brouard 10246: fprintf(fichtm,"<html><head>\n<head>\n<meta charset=\"utf-8\"/><meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n<title>IMaCh %s</title></head>\n <body><font size=\"7\"><a href=http:/euroreves.ined.fr/imach>IMaCh for Interpolated Markov Chain</a> </font><br>\n<font size=\"3\">Sponsored by Copyright (C) 2002-2015 <a href=http://www.ined.fr>INED</a>-EUROREVES-Institut de longévité-2013-2016-Japan Society for the Promotion of Sciences 日本学術振興会 (<a href=https://www.jsps.go.jp/english/e-grants/>Grant-in-Aid for Scientific Research 25293121</a>) - <a href=https://software.intel.com/en-us>Intel Software 2015-2018</a></font><br> \
1.204 brouard 10247: <hr size=\"2\" color=\"#EC5E5E\"> \n\
10248: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 10249: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 10250: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n\
1.126 brouard 10251: \n\
10252: <hr size=\"2\" color=\"#EC5E5E\">\
10253: <ul><li><h4>Parameter files</h4>\n\
10254: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
10255: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
10256: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
10257: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
10258: - Date and time at start: %s</ul>\n",\
10259: optionfilehtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model,\
10260: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
10261: fileres,fileres,\
10262: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
10263: fflush(fichtm);
10264:
10265: strcpy(pathr,path);
10266: strcat(pathr,optionfilefiname);
1.184 brouard 10267: #ifdef WIN32
10268: _chdir(optionfilefiname); /* Move to directory named optionfile */
10269: #else
1.126 brouard 10270: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 10271: #endif
10272:
1.126 brouard 10273:
1.220 brouard 10274: /* Calculates basic frequencies. Computes observed prevalence at single age
10275: and for any valid combination of covariates
1.126 brouard 10276: and prints on file fileres'p'. */
1.227 brouard 10277: freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
10278: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 10279:
10280: fprintf(fichtm,"\n");
10281: fprintf(fichtm,"<br>Total number of observations=%d <br>\n\
10282: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
10283: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
10284: imx,agemin,agemax,jmin,jmax,jmean);
10285: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.220 brouard 10286: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
10287: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
10288: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
10289: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 10290:
1.126 brouard 10291: /* For Powell, parameters are in a vector p[] starting at p[1]
10292: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
10293: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
10294:
10295: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 10296: /* For mortality only */
1.126 brouard 10297: if (mle==-3){
1.136 brouard 10298: ximort=matrix(1,NDIM,1,NDIM);
1.220 brouard 10299: for(i=1;i<=NDIM;i++)
10300: for(j=1;j<=NDIM;j++)
10301: ximort[i][j]=0.;
1.186 brouard 10302: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.126 brouard 10303: cens=ivector(1,n);
10304: ageexmed=vector(1,n);
10305: agecens=vector(1,n);
10306: dcwave=ivector(1,n);
1.223 brouard 10307:
1.126 brouard 10308: for (i=1; i<=imx; i++){
10309: dcwave[i]=-1;
10310: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 10311: if (s[m][i]>nlstate) {
10312: dcwave[i]=m;
10313: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
10314: break;
10315: }
1.126 brouard 10316: }
1.226 brouard 10317:
1.126 brouard 10318: for (i=1; i<=imx; i++) {
10319: if (wav[i]>0){
1.226 brouard 10320: ageexmed[i]=agev[mw[1][i]][i];
10321: j=wav[i];
10322: agecens[i]=1.;
10323:
10324: if (ageexmed[i]> 1 && wav[i] > 0){
10325: agecens[i]=agev[mw[j][i]][i];
10326: cens[i]= 1;
10327: }else if (ageexmed[i]< 1)
10328: cens[i]= -1;
10329: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
10330: cens[i]=0 ;
1.126 brouard 10331: }
10332: else cens[i]=-1;
10333: }
10334:
10335: for (i=1;i<=NDIM;i++) {
10336: for (j=1;j<=NDIM;j++)
1.226 brouard 10337: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 10338: }
10339:
1.145 brouard 10340: /*p[1]=0.0268; p[NDIM]=0.083;*/
1.126 brouard 10341: /*printf("%lf %lf", p[1], p[2]);*/
10342:
10343:
1.136 brouard 10344: #ifdef GSL
10345: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 10346: #else
1.126 brouard 10347: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 10348: #endif
1.201 brouard 10349: strcpy(filerespow,"POW-MORT_");
10350: strcat(filerespow,fileresu);
1.126 brouard 10351: if((ficrespow=fopen(filerespow,"w"))==NULL) {
10352: printf("Problem with resultfile: %s\n", filerespow);
10353: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
10354: }
1.136 brouard 10355: #ifdef GSL
10356: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 10357: #else
1.126 brouard 10358: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 10359: #endif
1.126 brouard 10360: /* for (i=1;i<=nlstate;i++)
10361: for(j=1;j<=nlstate+ndeath;j++)
10362: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
10363: */
10364: fprintf(ficrespow,"\n");
1.136 brouard 10365: #ifdef GSL
10366: /* gsl starts here */
10367: T = gsl_multimin_fminimizer_nmsimplex;
10368: gsl_multimin_fminimizer *sfm = NULL;
10369: gsl_vector *ss, *x;
10370: gsl_multimin_function minex_func;
10371:
10372: /* Initial vertex size vector */
10373: ss = gsl_vector_alloc (NDIM);
10374:
10375: if (ss == NULL){
10376: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
10377: }
10378: /* Set all step sizes to 1 */
10379: gsl_vector_set_all (ss, 0.001);
10380:
10381: /* Starting point */
1.126 brouard 10382:
1.136 brouard 10383: x = gsl_vector_alloc (NDIM);
10384:
10385: if (x == NULL){
10386: gsl_vector_free(ss);
10387: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
10388: }
10389:
10390: /* Initialize method and iterate */
10391: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 10392: /* gsl_vector_set(x, 0, 0.0268); */
10393: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 10394: gsl_vector_set(x, 0, p[1]);
10395: gsl_vector_set(x, 1, p[2]);
10396:
10397: minex_func.f = &gompertz_f;
10398: minex_func.n = NDIM;
10399: minex_func.params = (void *)&p; /* ??? */
10400:
10401: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
10402: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
10403:
10404: printf("Iterations beginning .....\n\n");
10405: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
10406:
10407: iteri=0;
10408: while (rval == GSL_CONTINUE){
10409: iteri++;
10410: status = gsl_multimin_fminimizer_iterate(sfm);
10411:
10412: if (status) printf("error: %s\n", gsl_strerror (status));
10413: fflush(0);
10414:
10415: if (status)
10416: break;
10417:
10418: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
10419: ssval = gsl_multimin_fminimizer_size (sfm);
10420:
10421: if (rval == GSL_SUCCESS)
10422: printf ("converged to a local maximum at\n");
10423:
10424: printf("%5d ", iteri);
10425: for (it = 0; it < NDIM; it++){
10426: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
10427: }
10428: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
10429: }
10430:
10431: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
10432:
10433: gsl_vector_free(x); /* initial values */
10434: gsl_vector_free(ss); /* inital step size */
10435: for (it=0; it<NDIM; it++){
10436: p[it+1]=gsl_vector_get(sfm->x,it);
10437: fprintf(ficrespow," %.12lf", p[it]);
10438: }
10439: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
10440: #endif
10441: #ifdef POWELL
10442: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
10443: #endif
1.126 brouard 10444: fclose(ficrespow);
10445:
1.203 brouard 10446: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 10447:
10448: for(i=1; i <=NDIM; i++)
10449: for(j=i+1;j<=NDIM;j++)
1.220 brouard 10450: matcov[i][j]=matcov[j][i];
1.126 brouard 10451:
10452: printf("\nCovariance matrix\n ");
1.203 brouard 10453: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 10454: for(i=1; i <=NDIM; i++) {
10455: for(j=1;j<=NDIM;j++){
1.220 brouard 10456: printf("%f ",matcov[i][j]);
10457: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 10458: }
1.203 brouard 10459: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 10460: }
10461:
10462: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 10463: for (i=1;i<=NDIM;i++) {
1.126 brouard 10464: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 10465: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
10466: }
1.126 brouard 10467: lsurv=vector(1,AGESUP);
10468: lpop=vector(1,AGESUP);
10469: tpop=vector(1,AGESUP);
10470: lsurv[agegomp]=100000;
10471:
10472: for (k=agegomp;k<=AGESUP;k++) {
10473: agemortsup=k;
10474: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
10475: }
10476:
10477: for (k=agegomp;k<agemortsup;k++)
10478: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
10479:
10480: for (k=agegomp;k<agemortsup;k++){
10481: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
10482: sumlpop=sumlpop+lpop[k];
10483: }
10484:
10485: tpop[agegomp]=sumlpop;
10486: for (k=agegomp;k<(agemortsup-3);k++){
10487: /* tpop[k+1]=2;*/
10488: tpop[k+1]=tpop[k]-lpop[k];
10489: }
10490:
10491:
10492: printf("\nAge lx qx dx Lx Tx e(x)\n");
10493: for (k=agegomp;k<(agemortsup-2);k++)
10494: 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]);
10495:
10496:
10497: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 10498: ageminpar=50;
10499: agemaxpar=100;
1.194 brouard 10500: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
10501: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
10502: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
10503: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
10504: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
10505: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
10506: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 10507: }else{
10508: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
10509: 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 10510: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 10511: }
1.201 brouard 10512: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 10513: stepm, weightopt,\
10514: model,imx,p,matcov,agemortsup);
10515:
10516: free_vector(lsurv,1,AGESUP);
10517: free_vector(lpop,1,AGESUP);
10518: free_vector(tpop,1,AGESUP);
1.220 brouard 10519: free_matrix(ximort,1,NDIM,1,NDIM);
1.136 brouard 10520: free_ivector(cens,1,n);
10521: free_vector(agecens,1,n);
10522: free_ivector(dcwave,1,n);
1.220 brouard 10523: #ifdef GSL
1.136 brouard 10524: #endif
1.186 brouard 10525: } /* Endof if mle==-3 mortality only */
1.205 brouard 10526: /* Standard */
10527: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
10528: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
10529: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 10530: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 10531: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
10532: for (k=1; k<=npar;k++)
10533: printf(" %d %8.5f",k,p[k]);
10534: printf("\n");
1.205 brouard 10535: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
10536: /* mlikeli uses func not funcone */
10537: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
10538: }
10539: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
10540: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
10541: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
10542: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
10543: }
10544: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 10545: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
10546: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
10547: for (k=1; k<=npar;k++)
10548: printf(" %d %8.5f",k,p[k]);
10549: printf("\n");
10550:
10551: /*--------- results files --------------*/
1.224 brouard 10552: 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 10553:
10554:
10555: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
10556: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
10557: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
10558: for(i=1,jk=1; i <=nlstate; i++){
10559: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 10560: if (k != i) {
10561: printf("%d%d ",i,k);
10562: fprintf(ficlog,"%d%d ",i,k);
10563: fprintf(ficres,"%1d%1d ",i,k);
10564: for(j=1; j <=ncovmodel; j++){
10565: printf("%12.7f ",p[jk]);
10566: fprintf(ficlog,"%12.7f ",p[jk]);
10567: fprintf(ficres,"%12.7f ",p[jk]);
10568: jk++;
10569: }
10570: printf("\n");
10571: fprintf(ficlog,"\n");
10572: fprintf(ficres,"\n");
10573: }
1.126 brouard 10574: }
10575: }
1.203 brouard 10576: if(mle != 0){
10577: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 10578: ftolhess=ftol; /* Usually correct */
1.203 brouard 10579: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
10580: 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");
10581: 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");
10582: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 10583: for(k=1; k <=(nlstate+ndeath); k++){
10584: if (k != i) {
10585: printf("%d%d ",i,k);
10586: fprintf(ficlog,"%d%d ",i,k);
10587: for(j=1; j <=ncovmodel; j++){
10588: printf("%12.7f W=%8.3f CI=[%12.7f ; %12.7f] ",p[jk], p[jk]/sqrt(matcov[jk][jk]), p[jk]-1.96*sqrt(matcov[jk][jk]),p[jk]+1.96*sqrt(matcov[jk][jk]));
10589: fprintf(ficlog,"%12.7f W=%8.3f CI=[%12.7f ; %12.7f] ",p[jk], p[jk]/sqrt(matcov[jk][jk]), p[jk]-1.96*sqrt(matcov[jk][jk]),p[jk]+1.96*sqrt(matcov[jk][jk]));
10590: jk++;
10591: }
10592: printf("\n");
10593: fprintf(ficlog,"\n");
10594: }
10595: }
1.193 brouard 10596: }
1.203 brouard 10597: } /* end of hesscov and Wald tests */
1.225 brouard 10598:
1.203 brouard 10599: /* */
1.126 brouard 10600: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
10601: printf("# Scales (for hessian or gradient estimation)\n");
10602: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
10603: for(i=1,jk=1; i <=nlstate; i++){
10604: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 10605: if (j!=i) {
10606: fprintf(ficres,"%1d%1d",i,j);
10607: printf("%1d%1d",i,j);
10608: fprintf(ficlog,"%1d%1d",i,j);
10609: for(k=1; k<=ncovmodel;k++){
10610: printf(" %.5e",delti[jk]);
10611: fprintf(ficlog," %.5e",delti[jk]);
10612: fprintf(ficres," %.5e",delti[jk]);
10613: jk++;
10614: }
10615: printf("\n");
10616: fprintf(ficlog,"\n");
10617: fprintf(ficres,"\n");
10618: }
1.126 brouard 10619: }
10620: }
10621:
10622: 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 10623: if(mle >= 1) /* To big for the screen */
1.126 brouard 10624: 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");
10625: 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");
10626: /* # 121 Var(a12)\n\ */
10627: /* # 122 Cov(b12,a12) Var(b12)\n\ */
10628: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
10629: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
10630: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
10631: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
10632: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
10633: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
10634:
10635:
10636: /* Just to have a covariance matrix which will be more understandable
10637: even is we still don't want to manage dictionary of variables
10638: */
10639: for(itimes=1;itimes<=2;itimes++){
10640: jj=0;
10641: for(i=1; i <=nlstate; i++){
1.225 brouard 10642: for(j=1; j <=nlstate+ndeath; j++){
10643: if(j==i) continue;
10644: for(k=1; k<=ncovmodel;k++){
10645: jj++;
10646: ca[0]= k+'a'-1;ca[1]='\0';
10647: if(itimes==1){
10648: if(mle>=1)
10649: printf("#%1d%1d%d",i,j,k);
10650: fprintf(ficlog,"#%1d%1d%d",i,j,k);
10651: fprintf(ficres,"#%1d%1d%d",i,j,k);
10652: }else{
10653: if(mle>=1)
10654: printf("%1d%1d%d",i,j,k);
10655: fprintf(ficlog,"%1d%1d%d",i,j,k);
10656: fprintf(ficres,"%1d%1d%d",i,j,k);
10657: }
10658: ll=0;
10659: for(li=1;li <=nlstate; li++){
10660: for(lj=1;lj <=nlstate+ndeath; lj++){
10661: if(lj==li) continue;
10662: for(lk=1;lk<=ncovmodel;lk++){
10663: ll++;
10664: if(ll<=jj){
10665: cb[0]= lk +'a'-1;cb[1]='\0';
10666: if(ll<jj){
10667: if(itimes==1){
10668: if(mle>=1)
10669: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
10670: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
10671: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
10672: }else{
10673: if(mle>=1)
10674: printf(" %.5e",matcov[jj][ll]);
10675: fprintf(ficlog," %.5e",matcov[jj][ll]);
10676: fprintf(ficres," %.5e",matcov[jj][ll]);
10677: }
10678: }else{
10679: if(itimes==1){
10680: if(mle>=1)
10681: printf(" Var(%s%1d%1d)",ca,i,j);
10682: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
10683: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
10684: }else{
10685: if(mle>=1)
10686: printf(" %.7e",matcov[jj][ll]);
10687: fprintf(ficlog," %.7e",matcov[jj][ll]);
10688: fprintf(ficres," %.7e",matcov[jj][ll]);
10689: }
10690: }
10691: }
10692: } /* end lk */
10693: } /* end lj */
10694: } /* end li */
10695: if(mle>=1)
10696: printf("\n");
10697: fprintf(ficlog,"\n");
10698: fprintf(ficres,"\n");
10699: numlinepar++;
10700: } /* end k*/
10701: } /*end j */
1.126 brouard 10702: } /* end i */
10703: } /* end itimes */
10704:
10705: fflush(ficlog);
10706: fflush(ficres);
1.225 brouard 10707: while(fgets(line, MAXLINE, ficpar)) {
10708: /* If line starts with a # it is a comment */
10709: if (line[0] == '#') {
10710: numlinepar++;
10711: fputs(line,stdout);
10712: fputs(line,ficparo);
10713: fputs(line,ficlog);
10714: continue;
10715: }else
10716: break;
10717: }
10718:
1.209 brouard 10719: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
10720: /* ungetc(c,ficpar); */
10721: /* fgets(line, MAXLINE, ficpar); */
10722: /* fputs(line,stdout); */
10723: /* fputs(line,ficparo); */
10724: /* } */
10725: /* ungetc(c,ficpar); */
1.126 brouard 10726:
10727: estepm=0;
1.209 brouard 10728: 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 10729:
10730: if (num_filled != 6) {
10731: 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);
10732: 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);
10733: goto end;
10734: }
10735: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
10736: }
10737: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
10738: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
10739:
1.209 brouard 10740: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 10741: if (estepm==0 || estepm < stepm) estepm=stepm;
10742: if (fage <= 2) {
10743: bage = ageminpar;
10744: fage = agemaxpar;
10745: }
10746:
10747: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 10748: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
10749: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 10750:
1.186 brouard 10751: /* Other stuffs, more or less useful */
1.126 brouard 10752: while((c=getc(ficpar))=='#' && c!= EOF){
10753: ungetc(c,ficpar);
10754: fgets(line, MAXLINE, ficpar);
1.141 brouard 10755: fputs(line,stdout);
1.126 brouard 10756: fputs(line,ficparo);
10757: }
10758: ungetc(c,ficpar);
10759:
10760: fscanf(ficpar,"begin-prev-date=%lf/%lf/%lf end-prev-date=%lf/%lf/%lf mov_average=%d\n",&jprev1, &mprev1,&anprev1,&jprev2, &mprev2,&anprev2,&mobilav);
10761: 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);
10762: 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);
10763: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
10764: 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);
10765:
10766: while((c=getc(ficpar))=='#' && c!= EOF){
10767: ungetc(c,ficpar);
10768: fgets(line, MAXLINE, ficpar);
1.141 brouard 10769: fputs(line,stdout);
1.126 brouard 10770: fputs(line,ficparo);
10771: }
10772: ungetc(c,ficpar);
10773:
10774:
10775: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
10776: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
10777:
10778: fscanf(ficpar,"pop_based=%d\n",&popbased);
1.193 brouard 10779: fprintf(ficlog,"pop_based=%d\n",popbased);
1.126 brouard 10780: fprintf(ficparo,"pop_based=%d\n",popbased);
10781: fprintf(ficres,"pop_based=%d\n",popbased);
10782:
10783: while((c=getc(ficpar))=='#' && c!= EOF){
10784: ungetc(c,ficpar);
10785: fgets(line, MAXLINE, ficpar);
1.141 brouard 10786: fputs(line,stdout);
1.238 ! brouard 10787: fputs(line,ficres);
1.126 brouard 10788: fputs(line,ficparo);
10789: }
10790: ungetc(c,ficpar);
10791:
10792: fscanf(ficpar,"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);
10793: 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);
10794: 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);
10795: 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);
10796: 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);
10797: /* day and month of proj2 are not used but only year anproj2.*/
10798:
1.217 brouard 10799: while((c=getc(ficpar))=='#' && c!= EOF){
10800: ungetc(c,ficpar);
10801: fgets(line, MAXLINE, ficpar);
10802: fputs(line,stdout);
10803: fputs(line,ficparo);
1.238 ! brouard 10804: fputs(line,ficres);
1.217 brouard 10805: }
10806: ungetc(c,ficpar);
10807:
10808: fscanf(ficpar,"backcast=%d starting-back-date=%lf/%lf/%lf final-back-date=%lf/%lf/%lf mobil_average=%d\n",&backcast,&jback1,&mback1,&anback1,&jback2,&mback2,&anback2,&mobilavproj);
1.223 brouard 10809: fprintf(ficparo,"backcast=%d starting-back-date=%.lf/%.lf/%.lf final-back-date=%.lf/%.lf/%.lf mobil_average=%d\n",backcast,jback1,mback1,anback1,jback2,mback2,anback2,mobilavproj);
10810: fprintf(ficlog,"backcast=%d starting-back-date=%.lf/%.lf/%.lf final-back-date=%.lf/%.lf/%.lf mobil_average=%d\n",backcast,jback1,mback1,anback1,jback2,mback2,anback2,mobilavproj);
10811: fprintf(ficres,"backcast=%d starting-back-date=%.lf/%.lf/%.lf final-back-date=%.lf/%.lf/%.lf mobil_average=%d\n",backcast,jback1,mback1,anback1,jback2,mback2,anback2,mobilavproj);
1.217 brouard 10812: /* day and month of proj2 are not used but only year anproj2.*/
1.126 brouard 10813:
1.230 brouard 10814: /* Results */
1.235 brouard 10815: nresult=0;
1.230 brouard 10816: while(fgets(line, MAXLINE, ficpar)) {
10817: /* If line starts with a # it is a comment */
10818: if (line[0] == '#') {
10819: numlinepar++;
10820: fputs(line,stdout);
10821: fputs(line,ficparo);
10822: fputs(line,ficlog);
1.238 ! brouard 10823: fputs(line,ficres);
1.230 brouard 10824: continue;
10825: }else
10826: break;
10827: }
10828: while((num_filled=sscanf(line,"result:%[^\n]\n",resultline)) !=EOF){
10829: if (num_filled == 0)
10830: resultline[0]='\0';
10831: else if (num_filled != 1){
10832: printf("ERROR %d: result line should be at minimum 'result=' %s\n",num_filled, line);
10833: }
1.235 brouard 10834: nresult++; /* Sum of resultlines */
10835: printf("Result %d: result=%s\n",nresult, resultline);
10836: if(nresult > MAXRESULTLINES){
10837: printf("ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\n",MAXRESULTLINES,nresult);
10838: fprintf(ficlog,"ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\n",MAXRESULTLINES,nresult);
10839: goto end;
10840: }
10841: decoderesult(resultline, nresult); /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
1.238 ! brouard 10842: fprintf(ficparo,"result: %s\n",resultline);
! 10843: fprintf(ficres,"result: %s\n",resultline);
! 10844: fprintf(ficlog,"result: %s\n",resultline);
1.230 brouard 10845: while(fgets(line, MAXLINE, ficpar)) {
10846: /* If line starts with a # it is a comment */
10847: if (line[0] == '#') {
10848: numlinepar++;
10849: fputs(line,stdout);
10850: fputs(line,ficparo);
1.238 ! brouard 10851: fputs(line,ficres);
1.230 brouard 10852: fputs(line,ficlog);
10853: continue;
10854: }else
10855: break;
10856: }
10857: if (feof(ficpar))
10858: break;
10859: else{ /* Processess output results for this combination of covariate values */
10860: }
10861: }
10862:
10863:
1.126 brouard 10864:
1.230 brouard 10865: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 10866: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 10867:
10868: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 10869: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 10870: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 10871: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
10872: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 10873: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 10874: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
10875: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 10876: }else{
1.218 brouard 10877: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p);
1.220 brouard 10878: }
10879: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.225 brouard 10880: model,imx,jmin,jmax,jmean,rfileres,popforecast,prevfcast,backcast, estepm, \
10881: jprev1,mprev1,anprev1,dateprev1,jprev2,mprev2,anprev2,dateprev2);
1.220 brouard 10882:
1.225 brouard 10883: /*------------ free_vector -------------*/
10884: /* chdir(path); */
1.220 brouard 10885:
1.215 brouard 10886: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
10887: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
10888: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
10889: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.126 brouard 10890: free_lvector(num,1,n);
10891: free_vector(agedc,1,n);
10892: /*free_matrix(covar,0,NCOVMAX,1,n);*/
10893: /*free_matrix(covar,1,NCOVMAX,1,n);*/
10894: fclose(ficparo);
10895: fclose(ficres);
1.220 brouard 10896:
10897:
1.186 brouard 10898: /* Other results (useful)*/
1.220 brouard 10899:
10900:
1.126 brouard 10901: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 10902: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
10903: prlim=matrix(1,nlstate,1,nlstate);
1.209 brouard 10904: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 10905: fclose(ficrespl);
10906:
10907: /*------------- h Pij x at various ages ------------*/
1.180 brouard 10908: /*#include "hpijx.h"*/
10909: hPijx(p, bage, fage);
1.145 brouard 10910: fclose(ficrespij);
1.227 brouard 10911:
1.220 brouard 10912: /* ncovcombmax= pow(2,cptcoveff); */
1.219 brouard 10913: /*-------------- Variance of one-step probabilities---*/
1.145 brouard 10914: k=1;
1.126 brouard 10915: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 10916:
1.219 brouard 10917: /* Prevalence for each covariates in probs[age][status][cov] */
1.218 brouard 10918: probs= ma3x(1,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.126 brouard 10919: for(i=1;i<=AGESUP;i++)
1.219 brouard 10920: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 10921: for(k=1;k<=ncovcombmax;k++)
10922: probs[i][j][k]=0.;
1.219 brouard 10923: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
10924: if (mobilav!=0 ||mobilavproj !=0 ) {
10925: mobaverages= ma3x(1, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.227 brouard 10926: for(i=1;i<=AGESUP;i++)
10927: for(j=1;j<=nlstate;j++)
10928: for(k=1;k<=ncovcombmax;k++)
10929: mobaverages[i][j][k]=0.;
1.219 brouard 10930: mobaverage=mobaverages;
10931: if (mobilav!=0) {
1.235 brouard 10932: printf("Movingaveraging observed prevalence\n");
1.227 brouard 10933: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
10934: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
10935: printf(" Error in movingaverage mobilav=%d\n",mobilav);
10936: }
1.219 brouard 10937: }
10938: /* /\* Prevalence for each covariates in probs[age][status][cov] *\/ */
10939: /* prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
10940: else if (mobilavproj !=0) {
1.235 brouard 10941: printf("Movingaveraging projected observed prevalence\n");
1.227 brouard 10942: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
10943: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
10944: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
10945: }
1.219 brouard 10946: }
10947: }/* end if moving average */
1.227 brouard 10948:
1.126 brouard 10949: /*---------- Forecasting ------------------*/
10950: /*if((stepm == 1) && (strcmp(model,".")==0)){*/
10951: if(prevfcast==1){
10952: /* if(stepm ==1){*/
1.225 brouard 10953: prevforecast(fileresu, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);
1.126 brouard 10954: }
1.217 brouard 10955: if(backcast==1){
1.219 brouard 10956: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
10957: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
10958: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
10959:
10960: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
10961:
10962: bprlim=matrix(1,nlstate,1,nlstate);
10963: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
10964: fclose(ficresplb);
10965:
1.222 brouard 10966: hBijx(p, bage, fage, mobaverage);
10967: fclose(ficrespijb);
1.219 brouard 10968: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
10969:
10970: /* prevbackforecast(fileresu, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, mobilavproj,
1.225 brouard 10971: bage, fage, firstpass, lastpass, anback2, p, cptcoveff); */
1.219 brouard 10972: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
10973: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
10974: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
10975: }
1.217 brouard 10976:
1.186 brouard 10977:
10978: /* ------ Other prevalence ratios------------ */
1.126 brouard 10979:
1.215 brouard 10980: free_ivector(wav,1,imx);
10981: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
10982: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
10983: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 10984:
10985:
1.127 brouard 10986: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 10987:
1.201 brouard 10988: strcpy(filerese,"E_");
10989: strcat(filerese,fileresu);
1.126 brouard 10990: if((ficreseij=fopen(filerese,"w"))==NULL) {
10991: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
10992: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
10993: }
1.208 brouard 10994: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
10995: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 ! brouard 10996:
! 10997: pstamp(ficreseij);
1.219 brouard 10998:
1.235 brouard 10999: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
11000: if (cptcovn < 1){i1=1;}
11001:
11002: for(nres=1; nres <= nresult; nres++) /* For each resultline */
11003: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
11004: if(TKresult[nres]!= k)
11005: continue;
1.219 brouard 11006: fprintf(ficreseij,"\n#****** ");
1.235 brouard 11007: printf("\n#****** ");
1.225 brouard 11008: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 11009: fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 11010: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
11011: }
11012: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
11013: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
11014: fprintf(ficreseij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
1.219 brouard 11015: }
11016: fprintf(ficreseij,"******\n");
1.235 brouard 11017: printf("******\n");
1.219 brouard 11018:
11019: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
11020: oldm=oldms;savm=savms;
1.235 brouard 11021: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 11022:
1.219 brouard 11023: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 11024: }
11025: fclose(ficreseij);
1.208 brouard 11026: printf("done evsij\n");fflush(stdout);
11027: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.218 brouard 11028:
1.227 brouard 11029: /*---------- State-specific expectancies and variances ------------*/
1.218 brouard 11030:
11031:
1.201 brouard 11032: strcpy(filerest,"T_");
11033: strcat(filerest,fileresu);
1.127 brouard 11034: if((ficrest=fopen(filerest,"w"))==NULL) {
11035: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
11036: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
11037: }
1.208 brouard 11038: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
11039: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.218 brouard 11040:
1.126 brouard 11041:
1.201 brouard 11042: strcpy(fileresstde,"STDE_");
11043: strcat(fileresstde,fileresu);
1.126 brouard 11044: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 11045: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
11046: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 11047: }
1.227 brouard 11048: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
11049: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 11050:
1.201 brouard 11051: strcpy(filerescve,"CVE_");
11052: strcat(filerescve,fileresu);
1.126 brouard 11053: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 11054: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
11055: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 11056: }
1.227 brouard 11057: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
11058: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 11059:
1.201 brouard 11060: strcpy(fileresv,"V_");
11061: strcat(fileresv,fileresu);
1.126 brouard 11062: if((ficresvij=fopen(fileresv,"w"))==NULL) {
11063: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
11064: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
11065: }
1.227 brouard 11066: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
11067: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 11068:
1.145 brouard 11069: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
11070: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
11071:
1.235 brouard 11072: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
11073: if (cptcovn < 1){i1=1;}
11074:
11075: for(nres=1; nres <= nresult; nres++) /* For each resultline */
11076: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
11077: if(TKresult[nres]!= k)
11078: continue;
11079: printf("\n#****** Selected:");
11080: fprintf(ficrest,"\n#****** Selected:");
11081: fprintf(ficlog,"\n#****** Selected:");
1.227 brouard 11082: for(j=1;j<=cptcoveff;j++){
11083: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
11084: fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
11085: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
11086: }
1.235 brouard 11087: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
11088: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
11089: fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
11090: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
11091: }
1.208 brouard 11092: fprintf(ficrest,"******\n");
1.227 brouard 11093: fprintf(ficlog,"******\n");
11094: printf("******\n");
1.208 brouard 11095:
11096: fprintf(ficresstdeij,"\n#****** ");
11097: fprintf(ficrescveij,"\n#****** ");
1.225 brouard 11098: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 11099: fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
11100: fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.208 brouard 11101: }
1.235 brouard 11102: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
11103: fprintf(ficresstdeij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
11104: fprintf(ficrescveij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
11105: }
1.208 brouard 11106: fprintf(ficresstdeij,"******\n");
11107: fprintf(ficrescveij,"******\n");
11108:
11109: fprintf(ficresvij,"\n#****** ");
1.238 ! brouard 11110: /* pstamp(ficresvij); */
1.225 brouard 11111: for(j=1;j<=cptcoveff;j++)
1.227 brouard 11112: fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 11113: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
11114: fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
11115: }
1.208 brouard 11116: fprintf(ficresvij,"******\n");
11117:
11118: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
11119: oldm=oldms;savm=savms;
1.235 brouard 11120: printf(" cvevsij ");
11121: fprintf(ficlog, " cvevsij ");
11122: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 11123: printf(" end cvevsij \n ");
11124: fprintf(ficlog, " end cvevsij \n ");
11125:
11126: /*
11127: */
11128: /* goto endfree; */
11129:
11130: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
11131: pstamp(ficrest);
11132:
11133:
11134: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 11135: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
11136: cptcod= 0; /* To be deleted */
11137: printf("varevsij vpopbased=%d \n",vpopbased);
11138: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 11139: 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 11140: 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 ");
11141: if(vpopbased==1)
11142: 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);
11143: else
11144: fprintf(ficrest,"the age specific period (stable) prevalences in each health state \n");
11145: fprintf(ficrest,"# Age popbased mobilav e.. (std) ");
11146: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
11147: fprintf(ficrest,"\n");
11148: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
11149: epj=vector(1,nlstate+1);
11150: printf("Computing age specific period (stable) prevalences in each health state \n");
11151: fprintf(ficlog,"Computing age specific period (stable) prevalences in each health state \n");
11152: for(age=bage; age <=fage ;age++){
1.235 brouard 11153: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 11154: if (vpopbased==1) {
11155: if(mobilav ==0){
11156: for(i=1; i<=nlstate;i++)
11157: prlim[i][i]=probs[(int)age][i][k];
11158: }else{ /* mobilav */
11159: for(i=1; i<=nlstate;i++)
11160: prlim[i][i]=mobaverage[(int)age][i][k];
11161: }
11162: }
1.219 brouard 11163:
1.227 brouard 11164: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
11165: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
11166: /* printf(" age %4.0f ",age); */
11167: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
11168: for(i=1, epj[j]=0.;i <=nlstate;i++) {
11169: epj[j] += prlim[i][i]*eij[i][j][(int)age];
11170: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
11171: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
11172: }
11173: epj[nlstate+1] +=epj[j];
11174: }
11175: /* printf(" age %4.0f \n",age); */
1.219 brouard 11176:
1.227 brouard 11177: for(i=1, vepp=0.;i <=nlstate;i++)
11178: for(j=1;j <=nlstate;j++)
11179: vepp += vareij[i][j][(int)age];
11180: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
11181: for(j=1;j <=nlstate;j++){
11182: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
11183: }
11184: fprintf(ficrest,"\n");
11185: }
1.208 brouard 11186: } /* End vpopbased */
11187: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
11188: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
11189: free_vector(epj,1,nlstate+1);
1.235 brouard 11190: printf("done selection\n");fflush(stdout);
11191: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 11192:
1.145 brouard 11193: /*}*/
1.235 brouard 11194: } /* End k selection */
1.227 brouard 11195:
11196: printf("done State-specific expectancies\n");fflush(stdout);
11197: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
11198:
1.126 brouard 11199: /*------- Variance of period (stable) prevalence------*/
1.227 brouard 11200:
1.201 brouard 11201: strcpy(fileresvpl,"VPL_");
11202: strcat(fileresvpl,fileresu);
1.126 brouard 11203: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
11204: printf("Problem with variance of period (stable) prevalence resultfile: %s\n", fileresvpl);
11205: exit(0);
11206: }
1.208 brouard 11207: printf("Computing Variance-covariance of period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
11208: fprintf(ficlog, "Computing Variance-covariance of period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
1.227 brouard 11209:
1.145 brouard 11210: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
11211: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
1.227 brouard 11212:
1.235 brouard 11213: i1=pow(2,cptcoveff);
11214: if (cptcovn < 1){i1=1;}
11215:
11216: for(nres=1; nres <= nresult; nres++) /* For each resultline */
11217: for(k=1; k<=i1;k++){
11218: if(TKresult[nres]!= k)
11219: continue;
1.227 brouard 11220: fprintf(ficresvpl,"\n#****** ");
11221: printf("\n#****** ");
11222: fprintf(ficlog,"\n#****** ");
11223: for(j=1;j<=cptcoveff;j++) {
11224: fprintf(ficresvpl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
11225: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
11226: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
11227: }
1.235 brouard 11228: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
11229: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
11230: fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
11231: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
11232: }
1.227 brouard 11233: fprintf(ficresvpl,"******\n");
11234: printf("******\n");
11235: fprintf(ficlog,"******\n");
11236:
11237: varpl=matrix(1,nlstate,(int) bage, (int) fage);
11238: oldm=oldms;savm=savms;
1.235 brouard 11239: varprevlim(fileres, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, &ncvyear, k, strstart, nres);
1.227 brouard 11240: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
1.145 brouard 11241: /*}*/
1.126 brouard 11242: }
1.227 brouard 11243:
1.126 brouard 11244: fclose(ficresvpl);
1.208 brouard 11245: printf("done variance-covariance of period prevalence\n");fflush(stdout);
11246: fprintf(ficlog,"done variance-covariance of period prevalence\n");fflush(ficlog);
1.227 brouard 11247:
11248: free_vector(weight,1,n);
11249: free_imatrix(Tvard,1,NCOVMAX,1,2);
11250: free_imatrix(s,1,maxwav+1,1,n);
11251: free_matrix(anint,1,maxwav,1,n);
11252: free_matrix(mint,1,maxwav,1,n);
11253: free_ivector(cod,1,n);
11254: free_ivector(tab,1,NCOVMAX);
11255: fclose(ficresstdeij);
11256: fclose(ficrescveij);
11257: fclose(ficresvij);
11258: fclose(ficrest);
11259: fclose(ficpar);
11260:
11261:
1.126 brouard 11262: /*---------- End : free ----------------*/
1.219 brouard 11263: if (mobilav!=0 ||mobilavproj !=0)
11264: free_ma3x(mobaverages,1, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
1.218 brouard 11265: free_ma3x(probs,1,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 11266: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
11267: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 11268: } /* mle==-3 arrives here for freeing */
1.227 brouard 11269: /* endfree:*/
11270: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
11271: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
11272: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
11273: free_ma3x(cotqvar,1,maxwav,1,nqtv,1,n);
1.233 brouard 11274: free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,1,n);
1.227 brouard 11275: free_matrix(coqvar,1,maxwav,1,n);
11276: free_matrix(covar,0,NCOVMAX,1,n);
11277: free_matrix(matcov,1,npar,1,npar);
11278: free_matrix(hess,1,npar,1,npar);
11279: /*free_vector(delti,1,npar);*/
11280: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
11281: free_matrix(agev,1,maxwav,1,imx);
11282: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
11283:
11284: free_ivector(ncodemax,1,NCOVMAX);
11285: free_ivector(ncodemaxwundef,1,NCOVMAX);
11286: free_ivector(Dummy,-1,NCOVMAX);
11287: free_ivector(Fixed,-1,NCOVMAX);
1.238 ! brouard 11288: free_ivector(DummyV,1,NCOVMAX);
! 11289: free_ivector(FixedV,1,NCOVMAX);
1.227 brouard 11290: free_ivector(Typevar,-1,NCOVMAX);
11291: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 11292: free_ivector(TvarsQ,1,NCOVMAX);
11293: free_ivector(TvarsQind,1,NCOVMAX);
11294: free_ivector(TvarsD,1,NCOVMAX);
11295: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 11296: free_ivector(TvarFD,1,NCOVMAX);
11297: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 11298: free_ivector(TvarF,1,NCOVMAX);
11299: free_ivector(TvarFind,1,NCOVMAX);
11300: free_ivector(TvarV,1,NCOVMAX);
11301: free_ivector(TvarVind,1,NCOVMAX);
11302: free_ivector(TvarA,1,NCOVMAX);
11303: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 11304: free_ivector(TvarFQ,1,NCOVMAX);
11305: free_ivector(TvarFQind,1,NCOVMAX);
11306: free_ivector(TvarVD,1,NCOVMAX);
11307: free_ivector(TvarVDind,1,NCOVMAX);
11308: free_ivector(TvarVQ,1,NCOVMAX);
11309: free_ivector(TvarVQind,1,NCOVMAX);
1.230 brouard 11310: free_ivector(Tvarsel,1,NCOVMAX);
11311: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 11312: free_ivector(Tposprod,1,NCOVMAX);
11313: free_ivector(Tprod,1,NCOVMAX);
11314: free_ivector(Tvaraff,1,NCOVMAX);
11315: free_ivector(invalidvarcomb,1,ncovcombmax);
11316: free_ivector(Tage,1,NCOVMAX);
11317: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 11318: free_ivector(TmodelInvind,1,NCOVMAX);
11319: free_ivector(TmodelInvQind,1,NCOVMAX);
1.227 brouard 11320:
11321: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
11322: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 11323: fflush(fichtm);
11324: fflush(ficgp);
11325:
1.227 brouard 11326:
1.126 brouard 11327: if((nberr >0) || (nbwarn>0)){
1.216 brouard 11328: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
11329: 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 11330: }else{
11331: printf("End of Imach\n");
11332: fprintf(ficlog,"End of Imach\n");
11333: }
11334: printf("See log file on %s\n",filelog);
11335: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 11336: /*(void) gettimeofday(&end_time,&tzp);*/
11337: rend_time = time(NULL);
11338: end_time = *localtime(&rend_time);
11339: /* tml = *localtime(&end_time.tm_sec); */
11340: strcpy(strtend,asctime(&end_time));
1.126 brouard 11341: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
11342: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 11343: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 11344:
1.157 brouard 11345: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
11346: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
11347: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 11348: /* printf("Total time was %d uSec.\n", total_usecs);*/
11349: /* if(fileappend(fichtm,optionfilehtm)){ */
11350: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
11351: fclose(fichtm);
11352: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
11353: fclose(fichtmcov);
11354: fclose(ficgp);
11355: fclose(ficlog);
11356: /*------ End -----------*/
1.227 brouard 11357:
11358:
11359: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 11360: #ifdef WIN32
1.227 brouard 11361: if (_chdir(pathcd) != 0)
11362: printf("Can't move to directory %s!\n",path);
11363: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 11364: #else
1.227 brouard 11365: if(chdir(pathcd) != 0)
11366: printf("Can't move to directory %s!\n", path);
11367: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 11368: #endif
1.126 brouard 11369: printf("Current directory %s!\n",pathcd);
11370: /*strcat(plotcmd,CHARSEPARATOR);*/
11371: sprintf(plotcmd,"gnuplot");
1.157 brouard 11372: #ifdef _WIN32
1.126 brouard 11373: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
11374: #endif
11375: if(!stat(plotcmd,&info)){
1.158 brouard 11376: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 11377: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 11378: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 11379: }else
11380: strcpy(pplotcmd,plotcmd);
1.157 brouard 11381: #ifdef __unix
1.126 brouard 11382: strcpy(plotcmd,GNUPLOTPROGRAM);
11383: if(!stat(plotcmd,&info)){
1.158 brouard 11384: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 11385: }else
11386: strcpy(pplotcmd,plotcmd);
11387: #endif
11388: }else
11389: strcpy(pplotcmd,plotcmd);
11390:
11391: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 11392: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.227 brouard 11393:
1.126 brouard 11394: if((outcmd=system(plotcmd)) != 0){
1.158 brouard 11395: printf("gnuplot command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 11396: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 11397: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.150 brouard 11398: if((outcmd=system(plotcmd)) != 0)
1.153 brouard 11399: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.126 brouard 11400: }
1.158 brouard 11401: printf(" Successful, please wait...");
1.126 brouard 11402: while (z[0] != 'q') {
11403: /* chdir(path); */
1.154 brouard 11404: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 11405: scanf("%s",z);
11406: /* if (z[0] == 'c') system("./imach"); */
11407: if (z[0] == 'e') {
1.158 brouard 11408: #ifdef __APPLE__
1.152 brouard 11409: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 11410: #elif __linux
11411: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 11412: #else
1.152 brouard 11413: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 11414: #endif
11415: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
11416: system(pplotcmd);
1.126 brouard 11417: }
11418: else if (z[0] == 'g') system(plotcmd);
11419: else if (z[0] == 'q') exit(0);
11420: }
1.227 brouard 11421: end:
1.126 brouard 11422: while (z[0] != 'q') {
1.195 brouard 11423: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 11424: scanf("%s",z);
11425: }
11426: }
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