1: /* $Id: imach.c,v 1.65 2002/12/11 16:58:19 lievre Exp $
2: Interpolated Markov Chain
3:
4: Short summary of the programme:
5:
6: This program computes Healthy Life Expectancies from
7: cross-longitudinal data. Cross-longitudinal data consist in: -1- a
8: first survey ("cross") where individuals from different ages are
9: interviewed on their health status or degree of disability (in the
10: case of a health survey which is our main interest) -2- at least a
11: second wave of interviews ("longitudinal") which measure each change
12: (if any) in individual health status. Health expectancies are
13: computed from the time spent in each health state according to a
14: model. More health states you consider, more time is necessary to reach the
15: Maximum Likelihood of the parameters involved in the model. The
16: simplest model is the multinomial logistic model where pij is the
17: probability to be observed in state j at the second wave
18: conditional to be observed in state i at the first wave. Therefore
19: the model is: log(pij/pii)= aij + bij*age+ cij*sex + etc , where
20: 'age' is age and 'sex' is a covariate. If you want to have a more
21: complex model than "constant and age", you should modify the program
22: where the markup *Covariates have to be included here again* invites
23: you to do it. More covariates you add, slower the
24: convergence.
25:
26: The advantage of this computer programme, compared to a simple
27: multinomial logistic model, is clear when the delay between waves is not
28: identical for each individual. Also, if a individual missed an
29: intermediate interview, the information is lost, but taken into
30: account using an interpolation or extrapolation.
31:
32: hPijx is the probability to be observed in state i at age x+h
33: conditional to the observed state i at age x. The delay 'h' can be
34: split into an exact number (nh*stepm) of unobserved intermediate
35: states. This elementary transition (by month or quarter trimester,
36: semester or year) is model as a multinomial logistic. The hPx
37: matrix is simply the matrix product of nh*stepm elementary matrices
38: and the contribution of each individual to the likelihood is simply
39: hPijx.
40:
41: Also this programme outputs the covariance matrix of the parameters but also
42: of the life expectancies. It also computes the stable prevalence.
43:
44: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
45: Institut national d'études démographiques, Paris.
46: This software have been partly granted by Euro-REVES, a concerted action
47: from the European Union.
48: It is copyrighted identically to a GNU software product, ie programme and
49: software can be distributed freely for non commercial use. Latest version
50: can be accessed at http://euroreves.ined.fr/imach .
51: **********************************************************************/
52:
53: #include <math.h>
54: #include <stdio.h>
55: #include <stdlib.h>
56: #include <unistd.h>
57:
58: #define MAXLINE 256
59: #define GNUPLOTPROGRAM "gnuplot"
60: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
61: #define FILENAMELENGTH 80
62: /*#define DEBUG*/
63: #define windows
64: #define GLOCK_ERROR_NOPATH -1 /* empty path */
65: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
66:
67: #define MAXPARM 30 /* Maximum number of parameters for the optimization */
68: #define NPARMAX 64 /* (nlstate+ndeath-1)*nlstate*ncovmodel */
69:
70: #define NINTERVMAX 8
71: #define NLSTATEMAX 8 /* Maximum number of live states (for func) */
72: #define NDEATHMAX 8 /* Maximum number of dead states (for func) */
73: #define NCOVMAX 8 /* Maximum number of covariates */
74: #define MAXN 20000
75: #define YEARM 12. /* Number of months per year */
76: #define AGESUP 130
77: #define AGEBASE 40
78: #ifdef windows
79: #define DIRSEPARATOR '\\'
80: #define ODIRSEPARATOR '/'
81: #else
82: #define DIRSEPARATOR '/'
83: #define ODIRSEPARATOR '\\'
84: #endif
85:
86: char version[80]="Imach version 0.9, November 2002, INED-EUROREVES ";
87: int erreur; /* Error number */
88: int nvar;
89: int cptcovn=0, cptcovage=0, cptcoveff=0,cptcov;
90: int npar=NPARMAX;
91: int nlstate=2; /* Number of live states */
92: int ndeath=1; /* Number of dead states */
93: int ncovmodel, ncovcol; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
94: int popbased=0;
95:
96: int *wav; /* Number of waves for this individuual 0 is possible */
97: int maxwav; /* Maxim number of waves */
98: int jmin, jmax; /* min, max spacing between 2 waves */
99: int mle, weightopt;
100: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
101: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
102: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
103: * wave mi and wave mi+1 is not an exact multiple of stepm. */
104: double jmean; /* Mean space between 2 waves */
105: double **oldm, **newm, **savm; /* Working pointers to matrices */
106: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
107: FILE *fic,*ficpar, *ficparo,*ficres, *ficrespl, *ficrespij, *ficrest,*ficresf,*ficrespop;
108: FILE *ficlog;
109: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
110: FILE *ficresprobmorprev;
111: FILE *fichtm; /* Html File */
112: FILE *ficreseij;
113: char filerese[FILENAMELENGTH];
114: FILE *ficresvij;
115: char fileresv[FILENAMELENGTH];
116: FILE *ficresvpl;
117: char fileresvpl[FILENAMELENGTH];
118: char title[MAXLINE];
119: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH];
120: char optionfilext[10], optionfilefiname[FILENAMELENGTH], plotcmd[FILENAMELENGTH];
121:
122: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
123: char filelog[FILENAMELENGTH]; /* Log file */
124: char filerest[FILENAMELENGTH];
125: char fileregp[FILENAMELENGTH];
126: char popfile[FILENAMELENGTH];
127:
128: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH];
129:
130: #define NR_END 1
131: #define FREE_ARG char*
132: #define FTOL 1.0e-10
133:
134: #define NRANSI
135: #define ITMAX 200
136:
137: #define TOL 2.0e-4
138:
139: #define CGOLD 0.3819660
140: #define ZEPS 1.0e-10
141: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
142:
143: #define GOLD 1.618034
144: #define GLIMIT 100.0
145: #define TINY 1.0e-20
146:
147: static double maxarg1,maxarg2;
148: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
149: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
150:
151: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
152: #define rint(a) floor(a+0.5)
153:
154: static double sqrarg;
155: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
156: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
157:
158: int imx;
159: int stepm;
160: /* Stepm, step in month: minimum step interpolation*/
161:
162: int estepm;
163: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
164:
165: int m,nb;
166: int *num, firstpass=0, lastpass=4,*cod, *ncodemax, *Tage;
167: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
168: double **pmmij, ***probs;
169: double dateintmean=0;
170:
171: double *weight;
172: int **s; /* Status */
173: double *agedc, **covar, idx;
174: int **nbcode, *Tcode, *Tvar, **codtab, **Tvard, *Tprod, cptcovprod, *Tvaraff;
175:
176: double ftol=FTOL; /* Tolerance for computing Max Likelihood */
177: double ftolhess; /* Tolerance for computing hessian */
178:
179: /**************** split *************************/
180: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
181: {
182: char *ss; /* pointer */
183: int l1, l2; /* length counters */
184:
185: l1 = strlen(path ); /* length of path */
186: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
187: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
188: if ( ss == NULL ) { /* no directory, so use current */
189: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
190: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
191: #if defined(__bsd__) /* get current working directory */
192: extern char *getwd( );
193:
194: if ( getwd( dirc ) == NULL ) {
195: #else
196: extern char *getcwd( );
197:
198: if ( getcwd( dirc, FILENAME_MAX ) == NULL ) {
199: #endif
200: return( GLOCK_ERROR_GETCWD );
201: }
202: strcpy( name, path ); /* we've got it */
203: } else { /* strip direcotry from path */
204: ss++; /* after this, the filename */
205: l2 = strlen( ss ); /* length of filename */
206: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
207: strcpy( name, ss ); /* save file name */
208: strncpy( dirc, path, l1 - l2 ); /* now the directory */
209: dirc[l1-l2] = 0; /* add zero */
210: }
211: l1 = strlen( dirc ); /* length of directory */
212: #ifdef windows
213: if ( dirc[l1-1] != '\\' ) { dirc[l1] = '\\'; dirc[l1+1] = 0; }
214: #else
215: if ( dirc[l1-1] != '/' ) { dirc[l1] = '/'; dirc[l1+1] = 0; }
216: #endif
217: ss = strrchr( name, '.' ); /* find last / */
218: ss++;
219: strcpy(ext,ss); /* save extension */
220: l1= strlen( name);
221: l2= strlen(ss)+1;
222: strncpy( finame, name, l1-l2);
223: finame[l1-l2]= 0;
224: return( 0 ); /* we're done */
225: }
226:
227:
228: /******************************************/
229:
230: void replace(char *s, char*t)
231: {
232: int i;
233: int lg=20;
234: i=0;
235: lg=strlen(t);
236: for(i=0; i<= lg; i++) {
237: (s[i] = t[i]);
238: if (t[i]== '\\') s[i]='/';
239: }
240: }
241:
242: int nbocc(char *s, char occ)
243: {
244: int i,j=0;
245: int lg=20;
246: i=0;
247: lg=strlen(s);
248: for(i=0; i<= lg; i++) {
249: if (s[i] == occ ) j++;
250: }
251: return j;
252: }
253:
254: void cutv(char *u,char *v, char*t, char occ)
255: {
256: /* cuts string t into u and v where u is ended by char occ excluding it
257: and v is after occ excluding it too : ex cutv(u,v,"abcdef2ghi2j",2)
258: gives u="abcedf" and v="ghi2j" */
259: int i,lg,j,p=0;
260: i=0;
261: for(j=0; j<=strlen(t)-1; j++) {
262: if((t[j]!= occ) && (t[j+1]== occ)) p=j+1;
263: }
264:
265: lg=strlen(t);
266: for(j=0; j<p; j++) {
267: (u[j] = t[j]);
268: }
269: u[p]='\0';
270:
271: for(j=0; j<= lg; j++) {
272: if (j>=(p+1))(v[j-p-1] = t[j]);
273: }
274: }
275:
276: /********************** nrerror ********************/
277:
278: void nrerror(char error_text[])
279: {
280: fprintf(stderr,"ERREUR ...\n");
281: fprintf(stderr,"%s\n",error_text);
282: exit(EXIT_FAILURE);
283: }
284: /*********************** vector *******************/
285: double *vector(int nl, int nh)
286: {
287: double *v;
288: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
289: if (!v) nrerror("allocation failure in vector");
290: return v-nl+NR_END;
291: }
292:
293: /************************ free vector ******************/
294: void free_vector(double*v, int nl, int nh)
295: {
296: free((FREE_ARG)(v+nl-NR_END));
297: }
298:
299: /************************ivector *******************************/
300: int *ivector(long nl,long nh)
301: {
302: int *v;
303: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
304: if (!v) nrerror("allocation failure in ivector");
305: return v-nl+NR_END;
306: }
307:
308: /******************free ivector **************************/
309: void free_ivector(int *v, long nl, long nh)
310: {
311: free((FREE_ARG)(v+nl-NR_END));
312: }
313:
314: /******************* imatrix *******************************/
315: int **imatrix(long nrl, long nrh, long ncl, long nch)
316: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
317: {
318: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
319: int **m;
320:
321: /* allocate pointers to rows */
322: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
323: if (!m) nrerror("allocation failure 1 in matrix()");
324: m += NR_END;
325: m -= nrl;
326:
327:
328: /* allocate rows and set pointers to them */
329: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
330: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
331: m[nrl] += NR_END;
332: m[nrl] -= ncl;
333:
334: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
335:
336: /* return pointer to array of pointers to rows */
337: return m;
338: }
339:
340: /****************** free_imatrix *************************/
341: void free_imatrix(m,nrl,nrh,ncl,nch)
342: int **m;
343: long nch,ncl,nrh,nrl;
344: /* free an int matrix allocated by imatrix() */
345: {
346: free((FREE_ARG) (m[nrl]+ncl-NR_END));
347: free((FREE_ARG) (m+nrl-NR_END));
348: }
349:
350: /******************* matrix *******************************/
351: double **matrix(long nrl, long nrh, long ncl, long nch)
352: {
353: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
354: double **m;
355:
356: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
357: if (!m) nrerror("allocation failure 1 in matrix()");
358: m += NR_END;
359: m -= nrl;
360:
361: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
362: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
363: m[nrl] += NR_END;
364: m[nrl] -= ncl;
365:
366: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
367: return m;
368: }
369:
370: /*************************free matrix ************************/
371: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
372: {
373: free((FREE_ARG)(m[nrl]+ncl-NR_END));
374: free((FREE_ARG)(m+nrl-NR_END));
375: }
376:
377: /******************* ma3x *******************************/
378: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
379: {
380: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
381: double ***m;
382:
383: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
384: if (!m) nrerror("allocation failure 1 in matrix()");
385: m += NR_END;
386: m -= nrl;
387:
388: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
389: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
390: m[nrl] += NR_END;
391: m[nrl] -= ncl;
392:
393: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
394:
395: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
396: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
397: m[nrl][ncl] += NR_END;
398: m[nrl][ncl] -= nll;
399: for (j=ncl+1; j<=nch; j++)
400: m[nrl][j]=m[nrl][j-1]+nlay;
401:
402: for (i=nrl+1; i<=nrh; i++) {
403: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
404: for (j=ncl+1; j<=nch; j++)
405: m[i][j]=m[i][j-1]+nlay;
406: }
407: return m;
408: }
409:
410: /*************************free ma3x ************************/
411: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
412: {
413: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
414: free((FREE_ARG)(m[nrl]+ncl-NR_END));
415: free((FREE_ARG)(m+nrl-NR_END));
416: }
417:
418: /***************** f1dim *************************/
419: extern int ncom;
420: extern double *pcom,*xicom;
421: extern double (*nrfunc)(double []);
422:
423: double f1dim(double x)
424: {
425: int j;
426: double f;
427: double *xt;
428:
429: xt=vector(1,ncom);
430: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
431: f=(*nrfunc)(xt);
432: free_vector(xt,1,ncom);
433: return f;
434: }
435:
436: /*****************brent *************************/
437: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
438: {
439: int iter;
440: double a,b,d,etemp;
441: double fu,fv,fw,fx;
442: double ftemp;
443: double p,q,r,tol1,tol2,u,v,w,x,xm;
444: double e=0.0;
445:
446: a=(ax < cx ? ax : cx);
447: b=(ax > cx ? ax : cx);
448: x=w=v=bx;
449: fw=fv=fx=(*f)(x);
450: for (iter=1;iter<=ITMAX;iter++) {
451: xm=0.5*(a+b);
452: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
453: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
454: printf(".");fflush(stdout);
455: fprintf(ficlog,".");fflush(ficlog);
456: #ifdef DEBUG
457: 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);
458: 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);
459: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
460: #endif
461: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
462: *xmin=x;
463: return fx;
464: }
465: ftemp=fu;
466: if (fabs(e) > tol1) {
467: r=(x-w)*(fx-fv);
468: q=(x-v)*(fx-fw);
469: p=(x-v)*q-(x-w)*r;
470: q=2.0*(q-r);
471: if (q > 0.0) p = -p;
472: q=fabs(q);
473: etemp=e;
474: e=d;
475: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
476: d=CGOLD*(e=(x >= xm ? a-x : b-x));
477: else {
478: d=p/q;
479: u=x+d;
480: if (u-a < tol2 || b-u < tol2)
481: d=SIGN(tol1,xm-x);
482: }
483: } else {
484: d=CGOLD*(e=(x >= xm ? a-x : b-x));
485: }
486: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
487: fu=(*f)(u);
488: if (fu <= fx) {
489: if (u >= x) a=x; else b=x;
490: SHFT(v,w,x,u)
491: SHFT(fv,fw,fx,fu)
492: } else {
493: if (u < x) a=u; else b=u;
494: if (fu <= fw || w == x) {
495: v=w;
496: w=u;
497: fv=fw;
498: fw=fu;
499: } else if (fu <= fv || v == x || v == w) {
500: v=u;
501: fv=fu;
502: }
503: }
504: }
505: nrerror("Too many iterations in brent");
506: *xmin=x;
507: return fx;
508: }
509:
510: /****************** mnbrak ***********************/
511:
512: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
513: double (*func)(double))
514: {
515: double ulim,u,r,q, dum;
516: double fu;
517:
518: *fa=(*func)(*ax);
519: *fb=(*func)(*bx);
520: if (*fb > *fa) {
521: SHFT(dum,*ax,*bx,dum)
522: SHFT(dum,*fb,*fa,dum)
523: }
524: *cx=(*bx)+GOLD*(*bx-*ax);
525: *fc=(*func)(*cx);
526: while (*fb > *fc) {
527: r=(*bx-*ax)*(*fb-*fc);
528: q=(*bx-*cx)*(*fb-*fa);
529: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
530: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r));
531: ulim=(*bx)+GLIMIT*(*cx-*bx);
532: if ((*bx-u)*(u-*cx) > 0.0) {
533: fu=(*func)(u);
534: } else if ((*cx-u)*(u-ulim) > 0.0) {
535: fu=(*func)(u);
536: if (fu < *fc) {
537: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
538: SHFT(*fb,*fc,fu,(*func)(u))
539: }
540: } else if ((u-ulim)*(ulim-*cx) >= 0.0) {
541: u=ulim;
542: fu=(*func)(u);
543: } else {
544: u=(*cx)+GOLD*(*cx-*bx);
545: fu=(*func)(u);
546: }
547: SHFT(*ax,*bx,*cx,u)
548: SHFT(*fa,*fb,*fc,fu)
549: }
550: }
551:
552: /*************** linmin ************************/
553:
554: int ncom;
555: double *pcom,*xicom;
556: double (*nrfunc)(double []);
557:
558: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
559: {
560: double brent(double ax, double bx, double cx,
561: double (*f)(double), double tol, double *xmin);
562: double f1dim(double x);
563: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
564: double *fc, double (*func)(double));
565: int j;
566: double xx,xmin,bx,ax;
567: double fx,fb,fa;
568:
569: ncom=n;
570: pcom=vector(1,n);
571: xicom=vector(1,n);
572: nrfunc=func;
573: for (j=1;j<=n;j++) {
574: pcom[j]=p[j];
575: xicom[j]=xi[j];
576: }
577: ax=0.0;
578: xx=1.0;
579: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim);
580: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin);
581: #ifdef DEBUG
582: printf("retour brent fret=%.12e xmin=%.12e\n",*fret,xmin);
583: fprintf(ficlog,"retour brent fret=%.12e xmin=%.12e\n",*fret,xmin);
584: #endif
585: for (j=1;j<=n;j++) {
586: xi[j] *= xmin;
587: p[j] += xi[j];
588: }
589: free_vector(xicom,1,n);
590: free_vector(pcom,1,n);
591: }
592:
593: /*************** powell ************************/
594: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
595: double (*func)(double []))
596: {
597: void linmin(double p[], double xi[], int n, double *fret,
598: double (*func)(double []));
599: int i,ibig,j;
600: double del,t,*pt,*ptt,*xit;
601: double fp,fptt;
602: double *xits;
603: pt=vector(1,n);
604: ptt=vector(1,n);
605: xit=vector(1,n);
606: xits=vector(1,n);
607: *fret=(*func)(p);
608: for (j=1;j<=n;j++) pt[j]=p[j];
609: for (*iter=1;;++(*iter)) {
610: fp=(*fret);
611: ibig=0;
612: del=0.0;
613: printf("\nPowell iter=%d -2*LL=%.12f",*iter,*fret);
614: fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f",*iter,*fret);
615: for (i=1;i<=n;i++)
616: printf(" %d %.12f",i, p[i]);
617: fprintf(ficlog," %d %.12f",i, p[i]);
618: printf("\n");
619: fprintf(ficlog,"\n");
620: for (i=1;i<=n;i++) {
621: for (j=1;j<=n;j++) xit[j]=xi[j][i];
622: fptt=(*fret);
623: #ifdef DEBUG
624: printf("fret=%lf \n",*fret);
625: fprintf(ficlog,"fret=%lf \n",*fret);
626: #endif
627: printf("%d",i);fflush(stdout);
628: fprintf(ficlog,"%d",i);fflush(ficlog);
629: linmin(p,xit,n,fret,func);
630: if (fabs(fptt-(*fret)) > del) {
631: del=fabs(fptt-(*fret));
632: ibig=i;
633: }
634: #ifdef DEBUG
635: printf("%d %.12e",i,(*fret));
636: fprintf(ficlog,"%d %.12e",i,(*fret));
637: for (j=1;j<=n;j++) {
638: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
639: printf(" x(%d)=%.12e",j,xit[j]);
640: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
641: }
642: for(j=1;j<=n;j++) {
643: printf(" p=%.12e",p[j]);
644: fprintf(ficlog," p=%.12e",p[j]);
645: }
646: printf("\n");
647: fprintf(ficlog,"\n");
648: #endif
649: }
650: if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) {
651: #ifdef DEBUG
652: int k[2],l;
653: k[0]=1;
654: k[1]=-1;
655: printf("Max: %.12e",(*func)(p));
656: fprintf(ficlog,"Max: %.12e",(*func)(p));
657: for (j=1;j<=n;j++) {
658: printf(" %.12e",p[j]);
659: fprintf(ficlog," %.12e",p[j]);
660: }
661: printf("\n");
662: fprintf(ficlog,"\n");
663: for(l=0;l<=1;l++) {
664: for (j=1;j<=n;j++) {
665: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
666: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
667: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
668: }
669: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
670: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
671: }
672: #endif
673:
674:
675: free_vector(xit,1,n);
676: free_vector(xits,1,n);
677: free_vector(ptt,1,n);
678: free_vector(pt,1,n);
679: return;
680: }
681: if (*iter == ITMAX) nrerror("powell exceeding maximum iterations.");
682: for (j=1;j<=n;j++) {
683: ptt[j]=2.0*p[j]-pt[j];
684: xit[j]=p[j]-pt[j];
685: pt[j]=p[j];
686: }
687: fptt=(*func)(ptt);
688: if (fptt < fp) {
689: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt);
690: if (t < 0.0) {
691: linmin(p,xit,n,fret,func);
692: for (j=1;j<=n;j++) {
693: xi[j][ibig]=xi[j][n];
694: xi[j][n]=xit[j];
695: }
696: #ifdef DEBUG
697: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
698: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
699: for(j=1;j<=n;j++){
700: printf(" %.12e",xit[j]);
701: fprintf(ficlog," %.12e",xit[j]);
702: }
703: printf("\n");
704: fprintf(ficlog,"\n");
705: #endif
706: }
707: }
708: }
709: }
710:
711: /**** Prevalence limit (stable prevalence) ****************/
712:
713: double **prevalim(double **prlim, int nlstate, double x[], double age, double **oldm, double **savm, double ftolpl, int ij)
714: {
715: /* Computes the prevalence limit in each live state at age x by left multiplying the unit
716: matrix by transitions matrix until convergence is reached */
717:
718: int i, ii,j,k;
719: double min, max, maxmin, maxmax,sumnew=0.;
720: double **matprod2();
721: double **out, cov[NCOVMAX], **pmij();
722: double **newm;
723: double agefin, delaymax=50 ; /* Max number of years to converge */
724:
725: for (ii=1;ii<=nlstate+ndeath;ii++)
726: for (j=1;j<=nlstate+ndeath;j++){
727: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
728: }
729:
730: cov[1]=1.;
731:
732: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
733: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
734: newm=savm;
735: /* Covariates have to be included here again */
736: cov[2]=agefin;
737:
738: for (k=1; k<=cptcovn;k++) {
739: cov[2+k]=nbcode[Tvar[k]][codtab[ij][Tvar[k]]];
740: /* printf("ij=%d k=%d Tvar[k]=%d nbcode=%d cov=%lf codtab[ij][Tvar[k]]=%d \n",ij,k, Tvar[k],nbcode[Tvar[k]][codtab[ij][Tvar[k]]],cov[2+k], codtab[ij][Tvar[k]]);*/
741: }
742: for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2];
743: for (k=1; k<=cptcovprod;k++)
744: cov[2+Tprod[k]]=nbcode[Tvard[k][1]][codtab[ij][Tvard[k][1]]]*nbcode[Tvard[k][2]][codtab[ij][Tvard[k][2]]];
745:
746: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
747: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
748: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
749: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);
750:
751: savm=oldm;
752: oldm=newm;
753: maxmax=0.;
754: for(j=1;j<=nlstate;j++){
755: min=1.;
756: max=0.;
757: for(i=1; i<=nlstate; i++) {
758: sumnew=0;
759: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
760: prlim[i][j]= newm[i][j]/(1-sumnew);
761: max=FMAX(max,prlim[i][j]);
762: min=FMIN(min,prlim[i][j]);
763: }
764: maxmin=max-min;
765: maxmax=FMAX(maxmax,maxmin);
766: }
767: if(maxmax < ftolpl){
768: return prlim;
769: }
770: }
771: }
772:
773: /*************** transition probabilities ***************/
774:
775: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
776: {
777: double s1, s2;
778: /*double t34;*/
779: int i,j,j1, nc, ii, jj;
780:
781: for(i=1; i<= nlstate; i++){
782: for(j=1; j<i;j++){
783: for (nc=1, s2=0.;nc <=ncovmodel; nc++){
784: /*s2 += param[i][j][nc]*cov[nc];*/
785: s2 += x[(i-1)*nlstate*ncovmodel+(j-1)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];
786: /*printf("Int j<i s1=%.17e, s2=%.17e\n",s1,s2);*/
787: }
788: ps[i][j]=s2;
789: /*printf("s1=%.17e, s2=%.17e\n",s1,s2);*/
790: }
791: for(j=i+1; j<=nlstate+ndeath;j++){
792: for (nc=1, s2=0.;nc <=ncovmodel; nc++){
793: s2 += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];
794: /*printf("Int j>i s1=%.17e, s2=%.17e %lx %lx\n",s1,s2,s1,s2);*/
795: }
796: ps[i][j]=s2;
797: }
798: }
799: /*ps[3][2]=1;*/
800:
801: for(i=1; i<= nlstate; i++){
802: s1=0;
803: for(j=1; j<i; j++)
804: s1+=exp(ps[i][j]);
805: for(j=i+1; j<=nlstate+ndeath; j++)
806: s1+=exp(ps[i][j]);
807: ps[i][i]=1./(s1+1.);
808: for(j=1; j<i; j++)
809: ps[i][j]= exp(ps[i][j])*ps[i][i];
810: for(j=i+1; j<=nlstate+ndeath; j++)
811: ps[i][j]= exp(ps[i][j])*ps[i][i];
812: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
813: } /* end i */
814:
815: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
816: for(jj=1; jj<= nlstate+ndeath; jj++){
817: ps[ii][jj]=0;
818: ps[ii][ii]=1;
819: }
820: }
821:
822:
823: /* for(ii=1; ii<= nlstate+ndeath; ii++){
824: for(jj=1; jj<= nlstate+ndeath; jj++){
825: printf("%lf ",ps[ii][jj]);
826: }
827: printf("\n ");
828: }
829: printf("\n ");printf("%lf ",cov[2]);*/
830: /*
831: for(i=1; i<= npar; i++) printf("%f ",x[i]);
832: goto end;*/
833: return ps;
834: }
835:
836: /**************** Product of 2 matrices ******************/
837:
838: double **matprod2(double **out, double **in,long nrl, long nrh, long ncl, long nch, long ncolol, long ncoloh, double **b)
839: {
840: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
841: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
842: /* in, b, out are matrice of pointers which should have been initialized
843: before: only the contents of out is modified. The function returns
844: a pointer to pointers identical to out */
845: long i, j, k;
846: for(i=nrl; i<= nrh; i++)
847: for(k=ncolol; k<=ncoloh; k++)
848: for(j=ncl,out[i][k]=0.; j<=nch; j++)
849: out[i][k] +=in[i][j]*b[j][k];
850:
851: return out;
852: }
853:
854:
855: /************* Higher Matrix Product ***************/
856:
857: double ***hpxij(double ***po, int nhstepm, double age, int hstepm, double *x, int nlstate, int stepm, double **oldm, double **savm, int ij )
858: {
859: /* Computes the transition matrix starting at age 'age' over 'nhstepm*hstepm*stepm' month
860: duration (i.e. until
861: age (in years) age+nhstepm*stepm/12) by multiplying nhstepm*hstepm matrices.
862: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
863: (typically every 2 years instead of every month which is too big).
864: Model is determined by parameters x and covariates have to be
865: included manually here.
866:
867: */
868:
869: int i, j, d, h, k;
870: double **out, cov[NCOVMAX];
871: double **newm;
872:
873: /* Hstepm could be zero and should return the unit matrix */
874: for (i=1;i<=nlstate+ndeath;i++)
875: for (j=1;j<=nlstate+ndeath;j++){
876: oldm[i][j]=(i==j ? 1.0 : 0.0);
877: po[i][j][0]=(i==j ? 1.0 : 0.0);
878: }
879: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
880: for(h=1; h <=nhstepm; h++){
881: for(d=1; d <=hstepm; d++){
882: newm=savm;
883: /* Covariates have to be included here again */
884: cov[1]=1.;
885: cov[2]=age+((h-1)*hstepm + (d-1))*stepm/YEARM;
886: for (k=1; k<=cptcovn;k++) cov[2+k]=nbcode[Tvar[k]][codtab[ij][Tvar[k]]];
887: for (k=1; k<=cptcovage;k++)
888: cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2];
889: for (k=1; k<=cptcovprod;k++)
890: cov[2+Tprod[k]]=nbcode[Tvard[k][1]][codtab[ij][Tvard[k][1]]]*nbcode[Tvard[k][2]][codtab[ij][Tvard[k][2]]];
891:
892:
893: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
894: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
895: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
896: pmij(pmmij,cov,ncovmodel,x,nlstate));
897: savm=oldm;
898: oldm=newm;
899: }
900: for(i=1; i<=nlstate+ndeath; i++)
901: for(j=1;j<=nlstate+ndeath;j++) {
902: po[i][j][h]=newm[i][j];
903: /*printf("i=%d j=%d h=%d po[i][j][h]=%f ",i,j,h,po[i][j][h]);
904: */
905: }
906: } /* end h */
907: return po;
908: }
909:
910:
911: /*************** log-likelihood *************/
912: double func( double *x)
913: {
914: int i, ii, j, k, mi, d, kk;
915: double l, ll[NLSTATEMAX], cov[NCOVMAX];
916: double **out;
917: double sw; /* Sum of weights */
918: double lli; /* Individual log likelihood */
919: int s1, s2;
920: double bbh;
921: long ipmx;
922: /*extern weight */
923: /* We are differentiating ll according to initial status */
924: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
925: /*for(i=1;i<imx;i++)
926: printf(" %d\n",s[4][i]);
927: */
928: cov[1]=1.;
929:
930: for(k=1; k<=nlstate; k++) ll[k]=0.;
931:
932: if(mle==1){
933: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
934: for (k=1; k<=cptcovn;k++) cov[2+k]=covar[Tvar[k]][i];
935: for(mi=1; mi<= wav[i]-1; mi++){
936: for (ii=1;ii<=nlstate+ndeath;ii++)
937: for (j=1;j<=nlstate+ndeath;j++){
938: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
939: savm[ii][j]=(ii==j ? 1.0 : 0.0);
940: }
941: for(d=0; d<dh[mi][i]; d++){
942: newm=savm;
943: cov[2]=agev[mw[mi][i]][i]+d*stepm/YEARM;
944: for (kk=1; kk<=cptcovage;kk++) {
945: cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
946: }
947: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
948: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
949: savm=oldm;
950: oldm=newm;
951: } /* end mult */
952:
953: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
954: /* But now since version 0.9 we anticipate for bias and large stepm.
955: * If stepm is larger than one month (smallest stepm) and if the exact delay
956: * (in months) between two waves is not a multiple of stepm, we rounded to
957: * the nearest (and in case of equal distance, to the lowest) interval but now
958: * we keep into memory the bias bh[mi][i] and also the previous matrix product
959: * (i.e to dh[mi][i]-1) saved in 'savm'. The we inter(extra)polate the
960: * probability in order to take into account the bias as a fraction of the way
961: * from savm to out if bh is neagtive or even beyond if bh is positive. bh varies
962: * -stepm/2 to stepm/2 .
963: * For stepm=1 the results are the same as for previous versions of Imach.
964: * For stepm > 1 the results are less biased than in previous versions.
965: */
966: s1=s[mw[mi][i]][i];
967: s2=s[mw[mi+1][i]][i];
968: bbh=(double)bh[mi][i]/(double)stepm;
969: /* bias is positive if real duration
970: * is higher than the multiple of stepm and negative otherwise.
971: */
972: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
973: 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 */
974: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
975: /*if(lli ==000.0)*/
976: /*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); */
977: ipmx +=1;
978: sw += weight[i];
979: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
980: } /* end of wave */
981: } /* end of individual */
982: } else if(mle==2){
983: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
984: for (k=1; k<=cptcovn;k++) cov[2+k]=covar[Tvar[k]][i];
985: for(mi=1; mi<= wav[i]-1; mi++){
986: for (ii=1;ii<=nlstate+ndeath;ii++)
987: for (j=1;j<=nlstate+ndeath;j++){
988: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
989: savm[ii][j]=(ii==j ? 1.0 : 0.0);
990: }
991: for(d=0; d<=dh[mi][i]; d++){
992: newm=savm;
993: cov[2]=agev[mw[mi][i]][i]+d*stepm/YEARM;
994: for (kk=1; kk<=cptcovage;kk++) {
995: cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
996: }
997: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
998: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
999: savm=oldm;
1000: oldm=newm;
1001: } /* end mult */
1002:
1003: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
1004: /* But now since version 0.9 we anticipate for bias and large stepm.
1005: * If stepm is larger than one month (smallest stepm) and if the exact delay
1006: * (in months) between two waves is not a multiple of stepm, we rounded to
1007: * the nearest (and in case of equal distance, to the lowest) interval but now
1008: * we keep into memory the bias bh[mi][i] and also the previous matrix product
1009: * (i.e to dh[mi][i]-1) saved in 'savm'. The we inter(extra)polate the
1010: * probability in order to take into account the bias as a fraction of the way
1011: * from savm to out if bh is neagtive or even beyond if bh is positive. bh varies
1012: * -stepm/2 to stepm/2 .
1013: * For stepm=1 the results are the same as for previous versions of Imach.
1014: * For stepm > 1 the results are less biased than in previous versions.
1015: */
1016: s1=s[mw[mi][i]][i];
1017: s2=s[mw[mi+1][i]][i];
1018: bbh=(double)bh[mi][i]/(double)stepm;
1019: /* bias is positive if real duration
1020: * is higher than the multiple of stepm and negative otherwise.
1021: */
1022: 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 */
1023: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
1024: /*lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.-+bh)*out[s1][s2])); */ /* exponential interpolation */
1025: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
1026: /*if(lli ==000.0)*/
1027: /*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); */
1028: ipmx +=1;
1029: sw += weight[i];
1030: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1031: } /* end of wave */
1032: } /* end of individual */
1033: } else if(mle==3){ /* exponential inter-extrapolation */
1034: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1035: for (k=1; k<=cptcovn;k++) cov[2+k]=covar[Tvar[k]][i];
1036: for(mi=1; mi<= wav[i]-1; mi++){
1037: for (ii=1;ii<=nlstate+ndeath;ii++)
1038: for (j=1;j<=nlstate+ndeath;j++){
1039: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
1040: savm[ii][j]=(ii==j ? 1.0 : 0.0);
1041: }
1042: for(d=0; d<dh[mi][i]; d++){
1043: newm=savm;
1044: cov[2]=agev[mw[mi][i]][i]+d*stepm/YEARM;
1045: for (kk=1; kk<=cptcovage;kk++) {
1046: cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
1047: }
1048: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
1049: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
1050: savm=oldm;
1051: oldm=newm;
1052: } /* end mult */
1053:
1054: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
1055: /* But now since version 0.9 we anticipate for bias and large stepm.
1056: * If stepm is larger than one month (smallest stepm) and if the exact delay
1057: * (in months) between two waves is not a multiple of stepm, we rounded to
1058: * the nearest (and in case of equal distance, to the lowest) interval but now
1059: * we keep into memory the bias bh[mi][i] and also the previous matrix product
1060: * (i.e to dh[mi][i]-1) saved in 'savm'. The we inter(extra)polate the
1061: * probability in order to take into account the bias as a fraction of the way
1062: * from savm to out if bh is neagtive or even beyond if bh is positive. bh varies
1063: * -stepm/2 to stepm/2 .
1064: * For stepm=1 the results are the same as for previous versions of Imach.
1065: * For stepm > 1 the results are less biased than in previous versions.
1066: */
1067: s1=s[mw[mi][i]][i];
1068: s2=s[mw[mi+1][i]][i];
1069: bbh=(double)bh[mi][i]/(double)stepm;
1070: /* bias is positive if real duration
1071: * is higher than the multiple of stepm and negative otherwise.
1072: */
1073: /* 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 */
1074: 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 */
1075: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
1076: /*if(lli ==000.0)*/
1077: /*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); */
1078: ipmx +=1;
1079: sw += weight[i];
1080: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1081: } /* end of wave */
1082: } /* end of individual */
1083: }else{ /* ml=4 no inter-extrapolation */
1084: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1085: for (k=1; k<=cptcovn;k++) cov[2+k]=covar[Tvar[k]][i];
1086: for(mi=1; mi<= wav[i]-1; mi++){
1087: for (ii=1;ii<=nlstate+ndeath;ii++)
1088: for (j=1;j<=nlstate+ndeath;j++){
1089: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
1090: savm[ii][j]=(ii==j ? 1.0 : 0.0);
1091: }
1092: for(d=0; d<dh[mi][i]; d++){
1093: newm=savm;
1094: cov[2]=agev[mw[mi][i]][i]+d*stepm/YEARM;
1095: for (kk=1; kk<=cptcovage;kk++) {
1096: cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
1097: }
1098:
1099: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
1100: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
1101: savm=oldm;
1102: oldm=newm;
1103: } /* end mult */
1104:
1105: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
1106: ipmx +=1;
1107: sw += weight[i];
1108: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1109: } /* end of wave */
1110: } /* end of individual */
1111: } /* End of if */
1112: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
1113: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
1114: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
1115: return -l;
1116: }
1117:
1118:
1119: /*********** Maximum Likelihood Estimation ***************/
1120:
1121: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
1122: {
1123: int i,j, iter;
1124: double **xi,*delti;
1125: double fret;
1126: xi=matrix(1,npar,1,npar);
1127: for (i=1;i<=npar;i++)
1128: for (j=1;j<=npar;j++)
1129: xi[i][j]=(i==j ? 1.0 : 0.0);
1130: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1131: powell(p,xi,npar,ftol,&iter,&fret,func);
1132:
1133: printf("\n#Number of iterations = %d, -2 Log likelihood = %.12f\n",iter,func(p));
1134: fprintf(ficlog,"\n#Number of iterations = %d, -2 Log likelihood = %.12f \n",iter,func(p));
1135: fprintf(ficres,"#Number of iterations = %d, -2 Log likelihood = %.12f \n",iter,func(p));
1136:
1137: }
1138:
1139: /**** Computes Hessian and covariance matrix ***/
1140: void hesscov(double **matcov, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1141: {
1142: double **a,**y,*x,pd;
1143: double **hess;
1144: int i, j,jk;
1145: int *indx;
1146:
1147: double hessii(double p[], double delta, int theta, double delti[]);
1148: double hessij(double p[], double delti[], int i, int j);
1149: void lubksb(double **a, int npar, int *indx, double b[]) ;
1150: void ludcmp(double **a, int npar, int *indx, double *d) ;
1151:
1152: hess=matrix(1,npar,1,npar);
1153:
1154: printf("\nCalculation of the hessian matrix. Wait...\n");
1155: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
1156: for (i=1;i<=npar;i++){
1157: printf("%d",i);fflush(stdout);
1158: fprintf(ficlog,"%d",i);fflush(ficlog);
1159: hess[i][i]=hessii(p,ftolhess,i,delti);
1160: /*printf(" %f ",p[i]);*/
1161: /*printf(" %lf ",hess[i][i]);*/
1162: }
1163:
1164: for (i=1;i<=npar;i++) {
1165: for (j=1;j<=npar;j++) {
1166: if (j>i) {
1167: printf(".%d%d",i,j);fflush(stdout);
1168: fprintf(ficlog,".%d%d",i,j);fflush(ficlog);
1169: hess[i][j]=hessij(p,delti,i,j);
1170: hess[j][i]=hess[i][j];
1171: /*printf(" %lf ",hess[i][j]);*/
1172: }
1173: }
1174: }
1175: printf("\n");
1176: fprintf(ficlog,"\n");
1177:
1178: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
1179: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
1180:
1181: a=matrix(1,npar,1,npar);
1182: y=matrix(1,npar,1,npar);
1183: x=vector(1,npar);
1184: indx=ivector(1,npar);
1185: for (i=1;i<=npar;i++)
1186: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
1187: ludcmp(a,npar,indx,&pd);
1188:
1189: for (j=1;j<=npar;j++) {
1190: for (i=1;i<=npar;i++) x[i]=0;
1191: x[j]=1;
1192: lubksb(a,npar,indx,x);
1193: for (i=1;i<=npar;i++){
1194: matcov[i][j]=x[i];
1195: }
1196: }
1197:
1198: printf("\n#Hessian matrix#\n");
1199: fprintf(ficlog,"\n#Hessian matrix#\n");
1200: for (i=1;i<=npar;i++) {
1201: for (j=1;j<=npar;j++) {
1202: printf("%.3e ",hess[i][j]);
1203: fprintf(ficlog,"%.3e ",hess[i][j]);
1204: }
1205: printf("\n");
1206: fprintf(ficlog,"\n");
1207: }
1208:
1209: /* Recompute Inverse */
1210: for (i=1;i<=npar;i++)
1211: for (j=1;j<=npar;j++) a[i][j]=matcov[i][j];
1212: ludcmp(a,npar,indx,&pd);
1213:
1214: /* printf("\n#Hessian matrix recomputed#\n");
1215:
1216: for (j=1;j<=npar;j++) {
1217: for (i=1;i<=npar;i++) x[i]=0;
1218: x[j]=1;
1219: lubksb(a,npar,indx,x);
1220: for (i=1;i<=npar;i++){
1221: y[i][j]=x[i];
1222: printf("%.3e ",y[i][j]);
1223: fprintf(ficlog,"%.3e ",y[i][j]);
1224: }
1225: printf("\n");
1226: fprintf(ficlog,"\n");
1227: }
1228: */
1229:
1230: free_matrix(a,1,npar,1,npar);
1231: free_matrix(y,1,npar,1,npar);
1232: free_vector(x,1,npar);
1233: free_ivector(indx,1,npar);
1234: free_matrix(hess,1,npar,1,npar);
1235:
1236:
1237: }
1238:
1239: /*************** hessian matrix ****************/
1240: double hessii( double x[], double delta, int theta, double delti[])
1241: {
1242: int i;
1243: int l=1, lmax=20;
1244: double k1,k2;
1245: double p2[NPARMAX+1];
1246: double res;
1247: double delt, delts, nkhi=10.,nkhif=1., khi=1.e-4;
1248: double fx;
1249: int k=0,kmax=10;
1250: double l1;
1251:
1252: fx=func(x);
1253: for (i=1;i<=npar;i++) p2[i]=x[i];
1254: for(l=0 ; l <=lmax; l++){
1255: l1=pow(10,l);
1256: delts=delt;
1257: for(k=1 ; k <kmax; k=k+1){
1258: delt = delta*(l1*k);
1259: p2[theta]=x[theta] +delt;
1260: k1=func(p2)-fx;
1261: p2[theta]=x[theta]-delt;
1262: k2=func(p2)-fx;
1263: /*res= (k1-2.0*fx+k2)/delt/delt; */
1264: res= (k1+k2)/delt/delt/2.; /* Divided by because L and not 2*L */
1265:
1266: #ifdef DEBUG
1267: 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);
1268: 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);
1269: #endif
1270: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
1271: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
1272: k=kmax;
1273: }
1274: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1275: k=kmax; l=lmax*10.;
1276: }
1277: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
1278: delts=delt;
1279: }
1280: }
1281: }
1282: delti[theta]=delts;
1283: return res;
1284:
1285: }
1286:
1287: double hessij( double x[], double delti[], int thetai,int thetaj)
1288: {
1289: int i;
1290: int l=1, l1, lmax=20;
1291: double k1,k2,k3,k4,res,fx;
1292: double p2[NPARMAX+1];
1293: int k;
1294:
1295: fx=func(x);
1296: for (k=1; k<=2; k++) {
1297: for (i=1;i<=npar;i++) p2[i]=x[i];
1298: p2[thetai]=x[thetai]+delti[thetai]/k;
1299: p2[thetaj]=x[thetaj]+delti[thetaj]/k;
1300: k1=func(p2)-fx;
1301:
1302: p2[thetai]=x[thetai]+delti[thetai]/k;
1303: p2[thetaj]=x[thetaj]-delti[thetaj]/k;
1304: k2=func(p2)-fx;
1305:
1306: p2[thetai]=x[thetai]-delti[thetai]/k;
1307: p2[thetaj]=x[thetaj]+delti[thetaj]/k;
1308: k3=func(p2)-fx;
1309:
1310: p2[thetai]=x[thetai]-delti[thetai]/k;
1311: p2[thetaj]=x[thetaj]-delti[thetaj]/k;
1312: k4=func(p2)-fx;
1313: res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /* Because of L not 2*L */
1314: #ifdef DEBUG
1315: 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);
1316: 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);
1317: #endif
1318: }
1319: return res;
1320: }
1321:
1322: /************** Inverse of matrix **************/
1323: void ludcmp(double **a, int n, int *indx, double *d)
1324: {
1325: int i,imax,j,k;
1326: double big,dum,sum,temp;
1327: double *vv;
1328:
1329: vv=vector(1,n);
1330: *d=1.0;
1331: for (i=1;i<=n;i++) {
1332: big=0.0;
1333: for (j=1;j<=n;j++)
1334: if ((temp=fabs(a[i][j])) > big) big=temp;
1335: if (big == 0.0) nrerror("Singular matrix in routine ludcmp");
1336: vv[i]=1.0/big;
1337: }
1338: for (j=1;j<=n;j++) {
1339: for (i=1;i<j;i++) {
1340: sum=a[i][j];
1341: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
1342: a[i][j]=sum;
1343: }
1344: big=0.0;
1345: for (i=j;i<=n;i++) {
1346: sum=a[i][j];
1347: for (k=1;k<j;k++)
1348: sum -= a[i][k]*a[k][j];
1349: a[i][j]=sum;
1350: if ( (dum=vv[i]*fabs(sum)) >= big) {
1351: big=dum;
1352: imax=i;
1353: }
1354: }
1355: if (j != imax) {
1356: for (k=1;k<=n;k++) {
1357: dum=a[imax][k];
1358: a[imax][k]=a[j][k];
1359: a[j][k]=dum;
1360: }
1361: *d = -(*d);
1362: vv[imax]=vv[j];
1363: }
1364: indx[j]=imax;
1365: if (a[j][j] == 0.0) a[j][j]=TINY;
1366: if (j != n) {
1367: dum=1.0/(a[j][j]);
1368: for (i=j+1;i<=n;i++) a[i][j] *= dum;
1369: }
1370: }
1371: free_vector(vv,1,n); /* Doesn't work */
1372: ;
1373: }
1374:
1375: void lubksb(double **a, int n, int *indx, double b[])
1376: {
1377: int i,ii=0,ip,j;
1378: double sum;
1379:
1380: for (i=1;i<=n;i++) {
1381: ip=indx[i];
1382: sum=b[ip];
1383: b[ip]=b[i];
1384: if (ii)
1385: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
1386: else if (sum) ii=i;
1387: b[i]=sum;
1388: }
1389: for (i=n;i>=1;i--) {
1390: sum=b[i];
1391: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
1392: b[i]=sum/a[i][i];
1393: }
1394: }
1395:
1396: /************ Frequencies ********************/
1397: void freqsummary(char fileres[], int agemin, int agemax, int **s, double **agev, int nlstate, int imx, int *Tvaraff, int **nbcode, int *ncodemax,double **mint,double **anint, double dateprev1,double dateprev2,double jprev1, double mprev1,double anprev1,double jprev2, double mprev2,double anprev2)
1398: { /* Some frequencies */
1399:
1400: int i, m, jk, k1,i1, j1, bool, z1,z2,j;
1401: int first;
1402: double ***freq; /* Frequencies */
1403: double *pp;
1404: double pos, k2, dateintsum=0,k2cpt=0;
1405: FILE *ficresp;
1406: char fileresp[FILENAMELENGTH];
1407:
1408: pp=vector(1,nlstate);
1409: probs= ma3x(1,AGESUP,1,NCOVMAX, 1,NCOVMAX);
1410: strcpy(fileresp,"p");
1411: strcat(fileresp,fileres);
1412: if((ficresp=fopen(fileresp,"w"))==NULL) {
1413: printf("Problem with prevalence resultfile: %s\n", fileresp);
1414: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
1415: exit(0);
1416: }
1417: freq= ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,agemin,agemax+3);
1418: j1=0;
1419:
1420: j=cptcoveff;
1421: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1422:
1423: first=1;
1424:
1425: for(k1=1; k1<=j;k1++){
1426: for(i1=1; i1<=ncodemax[k1];i1++){
1427: j1++;
1428: /*printf("cptcoveff=%d Tvaraff=%d", cptcoveff,Tvaraff[1]);
1429: scanf("%d", i);*/
1430: for (i=-1; i<=nlstate+ndeath; i++)
1431: for (jk=-1; jk<=nlstate+ndeath; jk++)
1432: for(m=agemin; m <= agemax+3; m++)
1433: freq[i][jk][m]=0;
1434:
1435: dateintsum=0;
1436: k2cpt=0;
1437: for (i=1; i<=imx; i++) {
1438: bool=1;
1439: if (cptcovn>0) {
1440: for (z1=1; z1<=cptcoveff; z1++)
1441: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtab[j1][z1]])
1442: bool=0;
1443: }
1444: if (bool==1){
1445: for(m=firstpass; m<=lastpass; m++){
1446: k2=anint[m][i]+(mint[m][i]/12.);
1447: if ((k2>=dateprev1) && (k2<=dateprev2)) {
1448: if(agev[m][i]==0) agev[m][i]=agemax+1;
1449: if(agev[m][i]==1) agev[m][i]=agemax+2;
1450: if (m<lastpass) {
1451: freq[s[m][i]][s[m+1][i]][(int)agev[m][i]] += weight[i];
1452: freq[s[m][i]][s[m+1][i]][(int) agemax+3] += weight[i];
1453: }
1454:
1455: if ((agev[m][i]>1) && (agev[m][i]< (agemax+3))) {
1456: dateintsum=dateintsum+k2;
1457: k2cpt++;
1458: }
1459: }
1460: }
1461: }
1462: }
1463:
1464: fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);
1465:
1466: if (cptcovn>0) {
1467: fprintf(ficresp, "\n#********** Variable ");
1468: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtab[j1][z1]]);
1469: fprintf(ficresp, "**********\n#");
1470: }
1471: for(i=1; i<=nlstate;i++)
1472: fprintf(ficresp, " Age Prev(%d) N(%d) N",i,i);
1473: fprintf(ficresp, "\n");
1474:
1475: for(i=(int)agemin; i <= (int)agemax+3; i++){
1476: if(i==(int)agemax+3){
1477: fprintf(ficlog,"Total");
1478: }else{
1479: if(first==1){
1480: first=0;
1481: printf("See log file for details...\n");
1482: }
1483: fprintf(ficlog,"Age %d", i);
1484: }
1485: for(jk=1; jk <=nlstate ; jk++){
1486: for(m=-1, pp[jk]=0; m <=nlstate+ndeath ; m++)
1487: pp[jk] += freq[jk][m][i];
1488: }
1489: for(jk=1; jk <=nlstate ; jk++){
1490: for(m=-1, pos=0; m <=0 ; m++)
1491: pos += freq[jk][m][i];
1492: if(pp[jk]>=1.e-10){
1493: if(first==1){
1494: printf(" %d.=%.0f loss[%d]=%.1f%%",jk,pp[jk],jk,100*pos/pp[jk]);
1495: }
1496: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",jk,pp[jk],jk,100*pos/pp[jk]);
1497: }else{
1498: if(first==1)
1499: printf(" %d.=%.0f loss[%d]=NaNQ%%",jk,pp[jk],jk);
1500: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",jk,pp[jk],jk);
1501: }
1502: }
1503:
1504: for(jk=1; jk <=nlstate ; jk++){
1505: for(m=0, pp[jk]=0; m <=nlstate+ndeath; m++)
1506: pp[jk] += freq[jk][m][i];
1507: }
1508:
1509: for(jk=1,pos=0; jk <=nlstate ; jk++)
1510: pos += pp[jk];
1511: for(jk=1; jk <=nlstate ; jk++){
1512: if(pos>=1.e-5){
1513: if(first==1)
1514: printf(" %d.=%.0f prev[%d]=%.1f%%",jk,pp[jk],jk,100*pp[jk]/pos);
1515: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",jk,pp[jk],jk,100*pp[jk]/pos);
1516: }else{
1517: if(first==1)
1518: printf(" %d.=%.0f prev[%d]=NaNQ%%",jk,pp[jk],jk);
1519: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",jk,pp[jk],jk);
1520: }
1521: if( i <= (int) agemax){
1522: if(pos>=1.e-5){
1523: fprintf(ficresp," %d %.5f %.0f %.0f",i,pp[jk]/pos, pp[jk],pos);
1524: probs[i][jk][j1]= pp[jk]/pos;
1525: /*printf("\ni=%d jk=%d j1=%d %.5f %.0f %.0f %f",i,jk,j1,pp[jk]/pos, pp[jk],pos,probs[i][jk][j1]);*/
1526: }
1527: else
1528: fprintf(ficresp," %d NaNq %.0f %.0f",i,pp[jk],pos);
1529: }
1530: }
1531:
1532: for(jk=-1; jk <=nlstate+ndeath; jk++)
1533: for(m=-1; m <=nlstate+ndeath; m++)
1534: if(freq[jk][m][i] !=0 ) {
1535: if(first==1)
1536: printf(" %d%d=%.0f",jk,m,freq[jk][m][i]);
1537: fprintf(ficlog," %d%d=%.0f",jk,m,freq[jk][m][i]);
1538: }
1539: if(i <= (int) agemax)
1540: fprintf(ficresp,"\n");
1541: if(first==1)
1542: printf("Others in log...\n");
1543: fprintf(ficlog,"\n");
1544: }
1545: }
1546: }
1547: dateintmean=dateintsum/k2cpt;
1548:
1549: fclose(ficresp);
1550: free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath,(int) agemin,(int) agemax+3);
1551: free_vector(pp,1,nlstate);
1552:
1553: /* End of Freq */
1554: }
1555:
1556: /************ Prevalence ********************/
1557: void prevalence(int agemin, float agemax, int **s, double **agev, int nlstate, int imx, int *Tvar, int **nbcode, int *ncodemax,double **mint,double **anint, double dateprev1,double dateprev2, double calagedate)
1558: { /* Some frequencies */
1559:
1560: int i, m, jk, k1, i1, j1, bool, z1,z2,j;
1561: double ***freq; /* Frequencies */
1562: double *pp;
1563: double pos, k2;
1564:
1565: pp=vector(1,nlstate);
1566:
1567: freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,agemin,agemax+3);
1568: j1=0;
1569:
1570: j=cptcoveff;
1571: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1572:
1573: for(k1=1; k1<=j;k1++){
1574: for(i1=1; i1<=ncodemax[k1];i1++){
1575: j1++;
1576:
1577: for (i=-1; i<=nlstate+ndeath; i++)
1578: for (jk=-1; jk<=nlstate+ndeath; jk++)
1579: for(m=agemin; m <= agemax+3; m++)
1580: freq[i][jk][m]=0;
1581:
1582: for (i=1; i<=imx; i++) {
1583: bool=1;
1584: if (cptcovn>0) {
1585: for (z1=1; z1<=cptcoveff; z1++)
1586: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtab[j1][z1]])
1587: bool=0;
1588: }
1589: if (bool==1) {
1590: for(m=firstpass; m<=lastpass; m++){
1591: k2=anint[m][i]+(mint[m][i]/12.);
1592: if ((k2>=dateprev1) && (k2<=dateprev2)) {
1593: if(agev[m][i]==0) agev[m][i]=agemax+1;
1594: if(agev[m][i]==1) agev[m][i]=agemax+2;
1595: if (m<lastpass) {
1596: if (calagedate>0)
1597: freq[s[m][i]][s[m+1][i]][(int)(agev[m][i]+1-((int)calagedate %12)/12.)] += weight[i];
1598: else
1599: freq[s[m][i]][s[m+1][i]][(int)agev[m][i]] += weight[i];
1600: freq[s[m][i]][s[m+1][i]][(int)(agemax+3)] += weight[i];
1601: }
1602: }
1603: }
1604: }
1605: }
1606: for(i=(int)agemin; i <= (int)agemax+3; i++){
1607: for(jk=1; jk <=nlstate ; jk++){
1608: for(m=-1, pp[jk]=0; m <=nlstate+ndeath ; m++)
1609: pp[jk] += freq[jk][m][i];
1610: }
1611: for(jk=1; jk <=nlstate ; jk++){
1612: for(m=-1, pos=0; m <=0 ; m++)
1613: pos += freq[jk][m][i];
1614: }
1615:
1616: for(jk=1; jk <=nlstate ; jk++){
1617: for(m=0, pp[jk]=0; m <=nlstate+ndeath; m++)
1618: pp[jk] += freq[jk][m][i];
1619: }
1620:
1621: for(jk=1,pos=0; jk <=nlstate ; jk++) pos += pp[jk];
1622:
1623: for(jk=1; jk <=nlstate ; jk++){
1624: if( i <= (int) agemax){
1625: if(pos>=1.e-5){
1626: probs[i][jk][j1]= pp[jk]/pos;
1627: }
1628: }
1629: }/* end jk */
1630: }/* end i */
1631: } /* end i1 */
1632: } /* end k1 */
1633:
1634:
1635: free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath,(int) agemin,(int) agemax+3);
1636: free_vector(pp,1,nlstate);
1637:
1638: } /* End of Freq */
1639:
1640: /************* Waves Concatenation ***************/
1641:
1642: 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)
1643: {
1644: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
1645: Death is a valid wave (if date is known).
1646: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
1647: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
1648: and mw[mi+1][i]. dh depends on stepm.
1649: */
1650:
1651: int i, mi, m;
1652: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
1653: double sum=0., jmean=0.;*/
1654: int first;
1655: int j, k=0,jk, ju, jl;
1656: double sum=0.;
1657: first=0;
1658: jmin=1e+5;
1659: jmax=-1;
1660: jmean=0.;
1661: for(i=1; i<=imx; i++){
1662: mi=0;
1663: m=firstpass;
1664: while(s[m][i] <= nlstate){
1665: if(s[m][i]>=1)
1666: mw[++mi][i]=m;
1667: if(m >=lastpass)
1668: break;
1669: else
1670: m++;
1671: }/* end while */
1672: if (s[m][i] > nlstate){
1673: mi++; /* Death is another wave */
1674: /* if(mi==0) never been interviewed correctly before death */
1675: /* Only death is a correct wave */
1676: mw[mi][i]=m;
1677: }
1678:
1679: wav[i]=mi;
1680: if(mi==0){
1681: if(first==0){
1682: printf("Warning, no any valid information for:%d line=%d and may be others, see log file\n",num[i],i);
1683: first=1;
1684: }
1685: if(first==1){
1686: fprintf(ficlog,"Warning, no any valid information for:%d line=%d\n",num[i],i);
1687: }
1688: } /* end mi==0 */
1689: }
1690:
1691: for(i=1; i<=imx; i++){
1692: for(mi=1; mi<wav[i];mi++){
1693: if (stepm <=0)
1694: dh[mi][i]=1;
1695: else{
1696: if (s[mw[mi+1][i]][i] > nlstate) {
1697: if (agedc[i] < 2*AGESUP) {
1698: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
1699: if(j==0) j=1; /* Survives at least one month after exam */
1700: k=k+1;
1701: if (j >= jmax) jmax=j;
1702: if (j <= jmin) jmin=j;
1703: sum=sum+j;
1704: /*if (j<0) printf("j=%d num=%d \n",j,i); */
1705: }
1706: }
1707: else{
1708: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1709: k=k+1;
1710: if (j >= jmax) jmax=j;
1711: else if (j <= jmin)jmin=j;
1712: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
1713: sum=sum+j;
1714: }
1715: jk= j/stepm;
1716: jl= j -jk*stepm;
1717: ju= j -(jk+1)*stepm;
1718: if(mle <=1){
1719: if(jl==0){
1720: dh[mi][i]=jk;
1721: bh[mi][i]=0;
1722: }else{ /* We want a negative bias in order to only have interpolation ie
1723: * at the price of an extra matrix product in likelihood */
1724: dh[mi][i]=jk+1;
1725: bh[mi][i]=ju;
1726: }
1727: }else{
1728: if(jl <= -ju){
1729: dh[mi][i]=jk;
1730: bh[mi][i]=jl; /* bias is positive if real duration
1731: * is higher than the multiple of stepm and negative otherwise.
1732: */
1733: }
1734: else{
1735: dh[mi][i]=jk+1;
1736: bh[mi][i]=ju;
1737: }
1738: if(dh[mi][i]==0){
1739: dh[mi][i]=1; /* At least one step */
1740: bh[mi][i]=ju; /* At least one step */
1741: 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);
1742: }
1743: if(i==298 || i==287 || i==763 ||i==1061)printf(" bh=%d ju=%d jl=%d dh=%d jk=%d stepm=%d",bh[mi][i],ju,jl,dh[mi][i],jk,stepm);
1744: }
1745: } /* end if mle */
1746: } /* end wave */
1747: }
1748: jmean=sum/k;
1749: printf("Delay (in months) between two waves Min=%d Max=%d Mean=%f\n\n ",jmin, jmax,jmean);
1750: fprintf(ficlog,"Delay (in months) between two waves Min=%d Max=%d Mean=%f\n\n ",jmin, jmax,jmean);
1751: }
1752:
1753: /*********** Tricode ****************************/
1754: void tricode(int *Tvar, int **nbcode, int imx)
1755: {
1756:
1757: int Ndum[20],ij=1, k, j, i, maxncov=19;
1758: int cptcode=0;
1759: cptcoveff=0;
1760:
1761: for (k=0; k<maxncov; k++) Ndum[k]=0;
1762: for (k=1; k<=7; k++) ncodemax[k]=0;
1763:
1764: for (j=1; j<=(cptcovn+2*cptcovprod); j++) {
1765: for (i=1; i<=imx; i++) { /*reads the data file to get the maximum
1766: modality*/
1767: ij=(int)(covar[Tvar[j]][i]); /* ij is the modality of this individual*/
1768: Ndum[ij]++; /*store the modality */
1769: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
1770: if (ij > cptcode) cptcode=ij; /* getting the maximum of covariable
1771: Tvar[j]. If V=sex and male is 0 and
1772: female is 1, then cptcode=1.*/
1773: }
1774:
1775: for (i=0; i<=cptcode; i++) {
1776: if(Ndum[i]!=0) ncodemax[j]++; /* Nomber of modalities of the j th covariates. In fact ncodemax[j]=2 (dichotom. variables) but it can be more */
1777: }
1778:
1779: ij=1;
1780: for (i=1; i<=ncodemax[j]; i++) {
1781: for (k=0; k<= maxncov; k++) {
1782: if (Ndum[k] != 0) {
1783: nbcode[Tvar[j]][ij]=k;
1784: /* store the modality in an array. k is a modality. If we have model=V1+V1*sex then: nbcode[1][1]=0 ; nbcode[1][2]=1; nbcode[2][1]=0 ; nbcode[2][2]=1; */
1785:
1786: ij++;
1787: }
1788: if (ij > ncodemax[j]) break;
1789: }
1790: }
1791: }
1792:
1793: for (k=0; k< maxncov; k++) Ndum[k]=0;
1794:
1795: for (i=1; i<=ncovmodel-2; i++) {
1796: /* Listing of all covariables in staement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
1797: ij=Tvar[i];
1798: Ndum[ij]++;
1799: }
1800:
1801: ij=1;
1802: for (i=1; i<= maxncov; i++) {
1803: if((Ndum[i]!=0) && (i<=ncovcol)){
1804: Tvaraff[ij]=i; /*For printing */
1805: ij++;
1806: }
1807: }
1808:
1809: cptcoveff=ij-1; /*Number of simple covariates*/
1810: }
1811:
1812: /*********** Health Expectancies ****************/
1813:
1814: void evsij(char fileres[], double ***eij, double x[], int nlstate, int stepm, int bage, int fage, double **oldm, double **savm, int ij, int estepm,double delti[],double **matcov )
1815:
1816: {
1817: /* Health expectancies */
1818: int i, j, nhstepm, hstepm, h, nstepm, k, cptj;
1819: double age, agelim, hf;
1820: double ***p3mat,***varhe;
1821: double **dnewm,**doldm;
1822: double *xp;
1823: double **gp, **gm;
1824: double ***gradg, ***trgradg;
1825: int theta;
1826:
1827: varhe=ma3x(1,nlstate*2,1,nlstate*2,(int) bage, (int) fage);
1828: xp=vector(1,npar);
1829: dnewm=matrix(1,nlstate*2,1,npar);
1830: doldm=matrix(1,nlstate*2,1,nlstate*2);
1831:
1832: fprintf(ficreseij,"# Health expectancies\n");
1833: fprintf(ficreseij,"# Age");
1834: for(i=1; i<=nlstate;i++)
1835: for(j=1; j<=nlstate;j++)
1836: fprintf(ficreseij," %1d-%1d (SE)",i,j);
1837: fprintf(ficreseij,"\n");
1838:
1839: if(estepm < stepm){
1840: printf ("Problem %d lower than %d\n",estepm, stepm);
1841: }
1842: else hstepm=estepm;
1843: /* We compute the life expectancy from trapezoids spaced every estepm months
1844: * This is mainly to measure the difference between two models: for example
1845: * if stepm=24 months pijx are given only every 2 years and by summing them
1846: * we are calculating an estimate of the Life Expectancy assuming a linear
1847: * progression inbetween and thus overestimating or underestimating according
1848: * to the curvature of the survival function. If, for the same date, we
1849: * estimate the model with stepm=1 month, we can keep estepm to 24 months
1850: * to compare the new estimate of Life expectancy with the same linear
1851: * hypothesis. A more precise result, taking into account a more precise
1852: * curvature will be obtained if estepm is as small as stepm. */
1853:
1854: /* For example we decided to compute the life expectancy with the smallest unit */
1855: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
1856: nhstepm is the number of hstepm from age to agelim
1857: nstepm is the number of stepm from age to agelin.
1858: Look at hpijx to understand the reason of that which relies in memory size
1859: and note for a fixed period like estepm months */
1860: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
1861: survival function given by stepm (the optimization length). Unfortunately it
1862: means that if the survival funtion is printed only each two years of age and if
1863: you sum them up and add 1 year (area under the trapezoids) you won't get the same
1864: results. So we changed our mind and took the option of the best precision.
1865: */
1866: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
1867:
1868: agelim=AGESUP;
1869: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
1870: /* nhstepm age range expressed in number of stepm */
1871: nstepm=(int) rint((agelim-age)*YEARM/stepm);
1872: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
1873: /* if (stepm >= YEARM) hstepm=1;*/
1874: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
1875: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
1876: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*2);
1877: gp=matrix(0,nhstepm,1,nlstate*2);
1878: gm=matrix(0,nhstepm,1,nlstate*2);
1879:
1880: /* Computed by stepm unit matrices, product of hstepm matrices, stored
1881: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
1882: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, ij);
1883:
1884:
1885: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1886:
1887: /* Computing Variances of health expectancies */
1888:
1889: for(theta=1; theta <=npar; theta++){
1890: for(i=1; i<=npar; i++){
1891: xp[i] = x[i] + (i==theta ?delti[theta]:0);
1892: }
1893: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij);
1894:
1895: cptj=0;
1896: for(j=1; j<= nlstate; j++){
1897: for(i=1; i<=nlstate; i++){
1898: cptj=cptj+1;
1899: for(h=0, gp[h][cptj]=0.; h<=nhstepm-1; h++){
1900: gp[h][cptj] = (p3mat[i][j][h]+p3mat[i][j][h+1])/2.;
1901: }
1902: }
1903: }
1904:
1905:
1906: for(i=1; i<=npar; i++)
1907: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1908: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij);
1909:
1910: cptj=0;
1911: for(j=1; j<= nlstate; j++){
1912: for(i=1;i<=nlstate;i++){
1913: cptj=cptj+1;
1914: for(h=0, gm[h][cptj]=0.; h<=nhstepm-1; h++){
1915: gm[h][cptj] = (p3mat[i][j][h]+p3mat[i][j][h+1])/2.;
1916: }
1917: }
1918: }
1919: for(j=1; j<= nlstate*2; j++)
1920: for(h=0; h<=nhstepm-1; h++){
1921: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
1922: }
1923: }
1924:
1925: /* End theta */
1926:
1927: trgradg =ma3x(0,nhstepm,1,nlstate*2,1,npar);
1928:
1929: for(h=0; h<=nhstepm-1; h++)
1930: for(j=1; j<=nlstate*2;j++)
1931: for(theta=1; theta <=npar; theta++)
1932: trgradg[h][j][theta]=gradg[h][theta][j];
1933:
1934:
1935: for(i=1;i<=nlstate*2;i++)
1936: for(j=1;j<=nlstate*2;j++)
1937: varhe[i][j][(int)age] =0.;
1938:
1939: printf("%d|",(int)age);fflush(stdout);
1940: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
1941: for(h=0;h<=nhstepm-1;h++){
1942: for(k=0;k<=nhstepm-1;k++){
1943: matprod2(dnewm,trgradg[h],1,nlstate*2,1,npar,1,npar,matcov);
1944: matprod2(doldm,dnewm,1,nlstate*2,1,npar,1,nlstate*2,gradg[k]);
1945: for(i=1;i<=nlstate*2;i++)
1946: for(j=1;j<=nlstate*2;j++)
1947: varhe[i][j][(int)age] += doldm[i][j]*hf*hf;
1948: }
1949: }
1950: /* Computing expectancies */
1951: for(i=1; i<=nlstate;i++)
1952: for(j=1; j<=nlstate;j++)
1953: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
1954: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
1955:
1956: /* 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]);*/
1957:
1958: }
1959:
1960: fprintf(ficreseij,"%3.0f",age );
1961: cptj=0;
1962: for(i=1; i<=nlstate;i++)
1963: for(j=1; j<=nlstate;j++){
1964: cptj++;
1965: fprintf(ficreseij," %9.4f (%.4f)", eij[i][j][(int)age], sqrt(varhe[cptj][cptj][(int)age]) );
1966: }
1967: fprintf(ficreseij,"\n");
1968:
1969: free_matrix(gm,0,nhstepm,1,nlstate*2);
1970: free_matrix(gp,0,nhstepm,1,nlstate*2);
1971: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*2);
1972: free_ma3x(trgradg,0,nhstepm,1,nlstate*2,1,npar);
1973: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
1974: }
1975: printf("\n");
1976: fprintf(ficlog,"\n");
1977:
1978: free_vector(xp,1,npar);
1979: free_matrix(dnewm,1,nlstate*2,1,npar);
1980: free_matrix(doldm,1,nlstate*2,1,nlstate*2);
1981: free_ma3x(varhe,1,nlstate*2,1,nlstate*2,(int) bage, (int)fage);
1982: }
1983:
1984: /************ Variance ******************/
1985: 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 ij, int estepm, int cptcov, int cptcod, int popbased, int mobilav)
1986: {
1987: /* Variance of health expectancies */
1988: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);*/
1989: /* double **newm;*/
1990: double **dnewm,**doldm;
1991: double **dnewmp,**doldmp;
1992: int i, j, nhstepm, hstepm, h, nstepm ;
1993: int k, cptcode;
1994: double *xp;
1995: double **gp, **gm; /* for var eij */
1996: double ***gradg, ***trgradg; /*for var eij */
1997: double **gradgp, **trgradgp; /* for var p point j */
1998: double *gpp, *gmp; /* for var p point j */
1999: double **varppt; /* for var p point j nlstate to nlstate+ndeath */
2000: double ***p3mat;
2001: double age,agelim, hf;
2002: double ***mobaverage;
2003: int theta;
2004: char digit[4];
2005: char digitp[25];
2006:
2007: char fileresprobmorprev[FILENAMELENGTH];
2008:
2009: if(popbased==1){
2010: if(mobilav!=0)
2011: strcpy(digitp,"-populbased-mobilav-");
2012: else strcpy(digitp,"-populbased-nomobil-");
2013: }
2014: else
2015: strcpy(digitp,"-stablbased-");
2016:
2017: if (mobilav!=0) {
2018: mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX);
2019: if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){
2020: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
2021: printf(" Error in movingaverage mobilav=%d\n",mobilav);
2022: }
2023: }
2024:
2025: strcpy(fileresprobmorprev,"prmorprev");
2026: sprintf(digit,"%-d",ij);
2027: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
2028: strcat(fileresprobmorprev,digit); /* Tvar to be done */
2029: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
2030: strcat(fileresprobmorprev,fileres);
2031: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
2032: printf("Problem with resultfile: %s\n", fileresprobmorprev);
2033: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
2034: }
2035: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
2036: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
2037: fprintf(ficresprobmorprev,"# probabilities of dying during a year and weighted mean w1*p1j+w2*p2j+... stand dev in()\n");
2038: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
2039: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
2040: fprintf(ficresprobmorprev," p.%-d SE",j);
2041: for(i=1; i<=nlstate;i++)
2042: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
2043: }
2044: fprintf(ficresprobmorprev,"\n");
2045: if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) {
2046: printf("Problem with gnuplot file: %s\n", optionfilegnuplot);
2047: fprintf(ficlog,"Problem with gnuplot file: %s\n", optionfilegnuplot);
2048: exit(0);
2049: }
2050: else{
2051: fprintf(ficgp,"\n# Routine varevsij");
2052: }
2053: if((fichtm=fopen(optionfilehtm,"a"))==NULL) {
2054: printf("Problem with html file: %s\n", optionfilehtm);
2055: fprintf(ficlog,"Problem with html file: %s\n", optionfilehtm);
2056: exit(0);
2057: }
2058: else{
2059: fprintf(fichtm,"\n<li><h4> Computing probabilities of dying as a weighted average (i.e global mortality independent of initial healh state)</h4></li>\n");
2060: fprintf(fichtm,"\n<br>%s (à revoir) <br>\n",digitp);
2061: }
2062: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
2063:
2064: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are the stable prevalence in health states i\n");
2065: fprintf(ficresvij,"# Age");
2066: for(i=1; i<=nlstate;i++)
2067: for(j=1; j<=nlstate;j++)
2068: fprintf(ficresvij," Cov(e%1d, e%1d)",i,j);
2069: fprintf(ficresvij,"\n");
2070:
2071: xp=vector(1,npar);
2072: dnewm=matrix(1,nlstate,1,npar);
2073: doldm=matrix(1,nlstate,1,nlstate);
2074: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
2075: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
2076:
2077: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
2078: gpp=vector(nlstate+1,nlstate+ndeath);
2079: gmp=vector(nlstate+1,nlstate+ndeath);
2080: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
2081:
2082: if(estepm < stepm){
2083: printf ("Problem %d lower than %d\n",estepm, stepm);
2084: }
2085: else hstepm=estepm;
2086: /* For example we decided to compute the life expectancy with the smallest unit */
2087: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
2088: nhstepm is the number of hstepm from age to agelim
2089: nstepm is the number of stepm from age to agelin.
2090: Look at hpijx to understand the reason of that which relies in memory size
2091: and note for a fixed period like k years */
2092: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
2093: survival function given by stepm (the optimization length). Unfortunately it
2094: means that if the survival funtion is printed only each two years of age and if
2095: you sum them up and add 1 year (area under the trapezoids) you won't get the same
2096: results. So we changed our mind and took the option of the best precision.
2097: */
2098: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
2099: agelim = AGESUP;
2100: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
2101: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
2102: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
2103: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
2104: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
2105: gp=matrix(0,nhstepm,1,nlstate);
2106: gm=matrix(0,nhstepm,1,nlstate);
2107:
2108:
2109: for(theta=1; theta <=npar; theta++){
2110: for(i=1; i<=npar; i++){ /* Computes gradient */
2111: xp[i] = x[i] + (i==theta ?delti[theta]:0);
2112: }
2113: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij);
2114: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ij);
2115:
2116: if (popbased==1) {
2117: if(mobilav ==0){
2118: for(i=1; i<=nlstate;i++)
2119: prlim[i][i]=probs[(int)age][i][ij];
2120: }else{ /* mobilav */
2121: for(i=1; i<=nlstate;i++)
2122: prlim[i][i]=mobaverage[(int)age][i][ij];
2123: }
2124: }
2125:
2126: for(j=1; j<= nlstate; j++){
2127: for(h=0; h<=nhstepm; h++){
2128: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
2129: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
2130: }
2131: }
2132: /* This for computing forces of mortality (h=1)as a weighted average */
2133: for(j=nlstate+1,gpp[j]=0.;j<=nlstate+ndeath;j++){
2134: for(i=1; i<= nlstate; i++)
2135: gpp[j] += prlim[i][i]*p3mat[i][j][1];
2136: }
2137: /* end force of mortality */
2138:
2139: for(i=1; i<=npar; i++) /* Computes gradient */
2140: xp[i] = x[i] - (i==theta ?delti[theta]:0);
2141: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij);
2142: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ij);
2143:
2144: if (popbased==1) {
2145: if(mobilav ==0){
2146: for(i=1; i<=nlstate;i++)
2147: prlim[i][i]=probs[(int)age][i][ij];
2148: }else{ /* mobilav */
2149: for(i=1; i<=nlstate;i++)
2150: prlim[i][i]=mobaverage[(int)age][i][ij];
2151: }
2152: }
2153:
2154: for(j=1; j<= nlstate; j++){
2155: for(h=0; h<=nhstepm; h++){
2156: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
2157: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
2158: }
2159: }
2160: /* This for computing force of mortality (h=1)as a weighted average */
2161: for(j=nlstate+1,gmp[j]=0.;j<=nlstate+ndeath;j++){
2162: for(i=1; i<= nlstate; i++)
2163: gmp[j] += prlim[i][i]*p3mat[i][j][1];
2164: }
2165: /* end force of mortality */
2166:
2167: for(j=1; j<= nlstate; j++) /* vareij */
2168: for(h=0; h<=nhstepm; h++){
2169: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
2170: }
2171: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu */
2172: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
2173: }
2174:
2175: } /* End theta */
2176:
2177: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
2178:
2179: for(h=0; h<=nhstepm; h++) /* veij */
2180: for(j=1; j<=nlstate;j++)
2181: for(theta=1; theta <=npar; theta++)
2182: trgradg[h][j][theta]=gradg[h][theta][j];
2183:
2184: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
2185: for(theta=1; theta <=npar; theta++)
2186: trgradgp[j][theta]=gradgp[theta][j];
2187:
2188: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
2189: for(i=1;i<=nlstate;i++)
2190: for(j=1;j<=nlstate;j++)
2191: vareij[i][j][(int)age] =0.;
2192:
2193: for(h=0;h<=nhstepm;h++){
2194: for(k=0;k<=nhstepm;k++){
2195: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
2196: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
2197: for(i=1;i<=nlstate;i++)
2198: for(j=1;j<=nlstate;j++)
2199: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
2200: }
2201: }
2202:
2203: /* pptj */
2204: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
2205: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
2206: for(j=nlstate+1;j<=nlstate+ndeath;j++)
2207: for(i=nlstate+1;i<=nlstate+ndeath;i++)
2208: varppt[j][i]=doldmp[j][i];
2209: /* end ppptj */
2210: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij);
2211: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ij);
2212:
2213: if (popbased==1) {
2214: if(mobilav ==0){
2215: for(i=1; i<=nlstate;i++)
2216: prlim[i][i]=probs[(int)age][i][ij];
2217: }else{ /* mobilav */
2218: for(i=1; i<=nlstate;i++)
2219: prlim[i][i]=mobaverage[(int)age][i][ij];
2220: }
2221: }
2222:
2223: /* This for computing force of mortality (h=1)as a weighted average */
2224: for(j=nlstate+1,gmp[j]=0.;j<=nlstate+ndeath;j++){
2225: for(i=1; i<= nlstate; i++)
2226: gmp[j] += prlim[i][i]*p3mat[i][j][1];
2227: }
2228: /* end force of mortality */
2229:
2230: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
2231: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
2232: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
2233: for(i=1; i<=nlstate;i++){
2234: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
2235: }
2236: }
2237: fprintf(ficresprobmorprev,"\n");
2238:
2239: fprintf(ficresvij,"%.0f ",age );
2240: for(i=1; i<=nlstate;i++)
2241: for(j=1; j<=nlstate;j++){
2242: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
2243: }
2244: fprintf(ficresvij,"\n");
2245: free_matrix(gp,0,nhstepm,1,nlstate);
2246: free_matrix(gm,0,nhstepm,1,nlstate);
2247: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
2248: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
2249: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
2250: } /* End age */
2251: free_vector(gpp,nlstate+1,nlstate+ndeath);
2252: free_vector(gmp,nlstate+1,nlstate+ndeath);
2253: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
2254: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
2255: fprintf(ficgp,"\nset noparametric;set nolabel; set ter png small;set size 0.65, 0.65");
2256: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
2257: fprintf(ficgp,"\n set log y; set nolog x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
2258: fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm);
2259: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm);
2260: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm);
2261: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",fileresprobmorprev,fileresprobmorprev);
2262: fprintf(fichtm,"\n<br> Probability is computed over estepm=%d months. <br> <img src=\"varmuptjgr%s%s.png\"> <br>\n", stepm,digitp,digit);
2263: /* 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.png\"> <br>\n", stepm,YEARM,digitp,digit);
2264: */
2265: fprintf(ficgp,"\nset out \"varmuptjgr%s%s.png\";replot;",digitp,digit);
2266:
2267: free_vector(xp,1,npar);
2268: free_matrix(doldm,1,nlstate,1,nlstate);
2269: free_matrix(dnewm,1,nlstate,1,npar);
2270: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
2271: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
2272: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
2273: if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX);
2274: fclose(ficresprobmorprev);
2275: fclose(ficgp);
2276: fclose(fichtm);
2277: }
2278:
2279: /************ Variance of prevlim ******************/
2280: 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 ij)
2281: {
2282: /* Variance of prevalence limit */
2283: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
2284: double **newm;
2285: double **dnewm,**doldm;
2286: int i, j, nhstepm, hstepm;
2287: int k, cptcode;
2288: double *xp;
2289: double *gp, *gm;
2290: double **gradg, **trgradg;
2291: double age,agelim;
2292: int theta;
2293:
2294: fprintf(ficresvpl,"# Standard deviation of stable prevalences \n");
2295: fprintf(ficresvpl,"# Age");
2296: for(i=1; i<=nlstate;i++)
2297: fprintf(ficresvpl," %1d-%1d",i,i);
2298: fprintf(ficresvpl,"\n");
2299:
2300: xp=vector(1,npar);
2301: dnewm=matrix(1,nlstate,1,npar);
2302: doldm=matrix(1,nlstate,1,nlstate);
2303:
2304: hstepm=1*YEARM; /* Every year of age */
2305: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
2306: agelim = AGESUP;
2307: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
2308: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
2309: if (stepm >= YEARM) hstepm=1;
2310: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
2311: gradg=matrix(1,npar,1,nlstate);
2312: gp=vector(1,nlstate);
2313: gm=vector(1,nlstate);
2314:
2315: for(theta=1; theta <=npar; theta++){
2316: for(i=1; i<=npar; i++){ /* Computes gradient */
2317: xp[i] = x[i] + (i==theta ?delti[theta]:0);
2318: }
2319: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ij);
2320: for(i=1;i<=nlstate;i++)
2321: gp[i] = prlim[i][i];
2322:
2323: for(i=1; i<=npar; i++) /* Computes gradient */
2324: xp[i] = x[i] - (i==theta ?delti[theta]:0);
2325: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ij);
2326: for(i=1;i<=nlstate;i++)
2327: gm[i] = prlim[i][i];
2328:
2329: for(i=1;i<=nlstate;i++)
2330: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
2331: } /* End theta */
2332:
2333: trgradg =matrix(1,nlstate,1,npar);
2334:
2335: for(j=1; j<=nlstate;j++)
2336: for(theta=1; theta <=npar; theta++)
2337: trgradg[j][theta]=gradg[theta][j];
2338:
2339: for(i=1;i<=nlstate;i++)
2340: varpl[i][(int)age] =0.;
2341: matprod2(dnewm,trgradg,1,nlstate,1,npar,1,npar,matcov);
2342: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg);
2343: for(i=1;i<=nlstate;i++)
2344: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
2345:
2346: fprintf(ficresvpl,"%.0f ",age );
2347: for(i=1; i<=nlstate;i++)
2348: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
2349: fprintf(ficresvpl,"\n");
2350: free_vector(gp,1,nlstate);
2351: free_vector(gm,1,nlstate);
2352: free_matrix(gradg,1,npar,1,nlstate);
2353: free_matrix(trgradg,1,nlstate,1,npar);
2354: } /* End age */
2355:
2356: free_vector(xp,1,npar);
2357: free_matrix(doldm,1,nlstate,1,npar);
2358: free_matrix(dnewm,1,nlstate,1,nlstate);
2359:
2360: }
2361:
2362: /************ Variance of one-step probabilities ******************/
2363: void varprob(char optionfilefiname[], double **matcov, double x[], double delti[], int nlstate, double bage, double fage, int ij, int *Tvar, int **nbcode, int *ncodemax)
2364: {
2365: int i, j=0, i1, k1, l1, t, tj;
2366: int k2, l2, j1, z1;
2367: int k=0,l, cptcode;
2368: int first=1, first1;
2369: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
2370: double **dnewm,**doldm;
2371: double *xp;
2372: double *gp, *gm;
2373: double **gradg, **trgradg;
2374: double **mu;
2375: double age,agelim, cov[NCOVMAX];
2376: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
2377: int theta;
2378: char fileresprob[FILENAMELENGTH];
2379: char fileresprobcov[FILENAMELENGTH];
2380: char fileresprobcor[FILENAMELENGTH];
2381:
2382: double ***varpij;
2383:
2384: strcpy(fileresprob,"prob");
2385: strcat(fileresprob,fileres);
2386: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
2387: printf("Problem with resultfile: %s\n", fileresprob);
2388: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
2389: }
2390: strcpy(fileresprobcov,"probcov");
2391: strcat(fileresprobcov,fileres);
2392: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
2393: printf("Problem with resultfile: %s\n", fileresprobcov);
2394: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
2395: }
2396: strcpy(fileresprobcor,"probcor");
2397: strcat(fileresprobcor,fileres);
2398: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
2399: printf("Problem with resultfile: %s\n", fileresprobcor);
2400: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
2401: }
2402: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
2403: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
2404: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
2405: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
2406: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
2407: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
2408:
2409: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
2410: fprintf(ficresprob,"# Age");
2411: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
2412: fprintf(ficresprobcov,"# Age");
2413: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
2414: fprintf(ficresprobcov,"# Age");
2415:
2416:
2417: for(i=1; i<=nlstate;i++)
2418: for(j=1; j<=(nlstate+ndeath);j++){
2419: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
2420: fprintf(ficresprobcov," p%1d-%1d ",i,j);
2421: fprintf(ficresprobcor," p%1d-%1d ",i,j);
2422: }
2423: fprintf(ficresprob,"\n");
2424: fprintf(ficresprobcov,"\n");
2425: fprintf(ficresprobcor,"\n");
2426: xp=vector(1,npar);
2427: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
2428: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
2429: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
2430: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
2431: first=1;
2432: if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) {
2433: printf("Problem with gnuplot file: %s\n", optionfilegnuplot);
2434: fprintf(ficlog,"Problem with gnuplot file: %s\n", optionfilegnuplot);
2435: exit(0);
2436: }
2437: else{
2438: fprintf(ficgp,"\n# Routine varprob");
2439: }
2440: if((fichtm=fopen(optionfilehtm,"a"))==NULL) {
2441: printf("Problem with html file: %s\n", optionfilehtm);
2442: fprintf(ficlog,"Problem with html file: %s\n", optionfilehtm);
2443: exit(0);
2444: }
2445: else{
2446: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
2447: fprintf(fichtm,"\n");
2448:
2449: fprintf(fichtm,"\n<li><h4> Computing matrix of variance-covariance of step probabilities</h4></li>\n");
2450: fprintf(fichtm,"\nWe have drawn ellipsoids of confidence around the p<inf>ij</inf>, p<inf>kl</inf> to understand the covariance between two incidences. They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
2451: fprintf(fichtm,"\n<br> We have drawn x'cov<sup>-1</sup>x = 4 where x is the column vector (pij,pkl). It means that if pij and pkl where uncorrelated the (2X2) matrix would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 standard deviations wide on each axis. <br> When both incidences are correlated we diagonalised the inverse of the covariance matrix and made the appropriate rotation.<br> \n");
2452:
2453: }
2454:
2455: cov[1]=1;
2456: tj=cptcoveff;
2457: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
2458: j1=0;
2459: for(t=1; t<=tj;t++){
2460: for(i1=1; i1<=ncodemax[t];i1++){
2461: j1++;
2462: if (cptcovn>0) {
2463: fprintf(ficresprob, "\n#********** Variable ");
2464: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtab[j1][z1]]);
2465: fprintf(ficresprob, "**********\n#");
2466: fprintf(ficresprobcov, "\n#********** Variable ");
2467: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcov, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtab[j1][z1]]);
2468: fprintf(ficresprobcov, "**********\n#");
2469:
2470: fprintf(ficgp, "\n#********** Variable ");
2471: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficgp, "# V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtab[j1][z1]]);
2472: fprintf(ficgp, "**********\n#");
2473:
2474:
2475: fprintf(fichtm, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
2476: for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtm, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtab[j1][z1]]);
2477: fprintf(fichtm, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
2478:
2479: fprintf(ficresprobcor, "\n#********** Variable ");
2480: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcor, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtab[j1][z1]]);
2481: fprintf(ficgp, "**********\n#");
2482: }
2483:
2484: for (age=bage; age<=fage; age ++){
2485: cov[2]=age;
2486: for (k=1; k<=cptcovn;k++) {
2487: cov[2+k]=nbcode[Tvar[k]][codtab[j1][Tvar[k]]];
2488: }
2489: for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2];
2490: for (k=1; k<=cptcovprod;k++)
2491: cov[2+Tprod[k]]=nbcode[Tvard[k][1]][codtab[ij][Tvard[k][1]]]*nbcode[Tvard[k][2]][codtab[ij][Tvard[k][2]]];
2492:
2493: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
2494: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
2495: gp=vector(1,(nlstate)*(nlstate+ndeath));
2496: gm=vector(1,(nlstate)*(nlstate+ndeath));
2497:
2498: for(theta=1; theta <=npar; theta++){
2499: for(i=1; i<=npar; i++)
2500: xp[i] = x[i] + (i==theta ?delti[theta]:0);
2501:
2502: pmij(pmmij,cov,ncovmodel,xp,nlstate);
2503:
2504: k=0;
2505: for(i=1; i<= (nlstate); i++){
2506: for(j=1; j<=(nlstate+ndeath);j++){
2507: k=k+1;
2508: gp[k]=pmmij[i][j];
2509: }
2510: }
2511:
2512: for(i=1; i<=npar; i++)
2513: xp[i] = x[i] - (i==theta ?delti[theta]:0);
2514:
2515: pmij(pmmij,cov,ncovmodel,xp,nlstate);
2516: k=0;
2517: for(i=1; i<=(nlstate); i++){
2518: for(j=1; j<=(nlstate+ndeath);j++){
2519: k=k+1;
2520: gm[k]=pmmij[i][j];
2521: }
2522: }
2523:
2524: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
2525: gradg[theta][i]=(gp[i]-gm[i])/2./delti[theta];
2526: }
2527:
2528: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
2529: for(theta=1; theta <=npar; theta++)
2530: trgradg[j][theta]=gradg[theta][j];
2531:
2532: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
2533: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
2534: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
2535: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
2536: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
2537: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
2538:
2539: pmij(pmmij,cov,ncovmodel,x,nlstate);
2540:
2541: k=0;
2542: for(i=1; i<=(nlstate); i++){
2543: for(j=1; j<=(nlstate+ndeath);j++){
2544: k=k+1;
2545: mu[k][(int) age]=pmmij[i][j];
2546: }
2547: }
2548: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
2549: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
2550: varpij[i][j][(int)age] = doldm[i][j];
2551:
2552: /*printf("\n%d ",(int)age);
2553: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
2554: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
2555: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
2556: }*/
2557:
2558: fprintf(ficresprob,"\n%d ",(int)age);
2559: fprintf(ficresprobcov,"\n%d ",(int)age);
2560: fprintf(ficresprobcor,"\n%d ",(int)age);
2561:
2562: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
2563: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
2564: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
2565: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
2566: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
2567: }
2568: i=0;
2569: for (k=1; k<=(nlstate);k++){
2570: for (l=1; l<=(nlstate+ndeath);l++){
2571: i=i++;
2572: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
2573: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
2574: for (j=1; j<=i;j++){
2575: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
2576: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
2577: }
2578: }
2579: }/* end of loop for state */
2580: } /* end of loop for age */
2581:
2582: /* Confidence intervalle of pij */
2583: /*
2584: fprintf(ficgp,"\nset noparametric;unset label");
2585: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
2586: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
2587: 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);
2588: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
2589: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
2590: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
2591: */
2592:
2593: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
2594: first1=1;
2595: for (k2=1; k2<=(nlstate);k2++){
2596: for (l2=1; l2<=(nlstate+ndeath);l2++){
2597: if(l2==k2) continue;
2598: j=(k2-1)*(nlstate+ndeath)+l2;
2599: for (k1=1; k1<=(nlstate);k1++){
2600: for (l1=1; l1<=(nlstate+ndeath);l1++){
2601: if(l1==k1) continue;
2602: i=(k1-1)*(nlstate+ndeath)+l1;
2603: if(i<=j) continue;
2604: for (age=bage; age<=fage; age ++){
2605: if ((int)age %5==0){
2606: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
2607: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
2608: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
2609: mu1=mu[i][(int) age]/stepm*YEARM ;
2610: mu2=mu[j][(int) age]/stepm*YEARM;
2611: c12=cv12/sqrt(v1*v2);
2612: /* Computing eigen value of matrix of covariance */
2613: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
2614: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
2615: /* Eigen vectors */
2616: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
2617: /*v21=sqrt(1.-v11*v11); *//* error */
2618: v21=(lc1-v1)/cv12*v11;
2619: v12=-v21;
2620: v22=v11;
2621: tnalp=v21/v11;
2622: if(first1==1){
2623: first1=0;
2624: 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);
2625: }
2626: 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);
2627: /*printf(fignu*/
2628: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
2629: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
2630: if(first==1){
2631: first=0;
2632: fprintf(ficgp,"\nset parametric;unset label");
2633: 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);
2634: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
2635: fprintf(fichtm,"\n<br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup> :<a href=\"varpijgr%s%d%1d%1d-%1d%1d.png\">varpijgr%s%d%1d%1d-%1d%1d.png</A>, ",k1,l1,k2,l2,optionfilefiname, j1,k1,l1,k2,l2,optionfilefiname, j1,k1,l1,k2,l2);
2636: fprintf(fichtm,"\n<br><img src=\"varpijgr%s%d%1d%1d-%1d%1d.png\"> ",optionfilefiname, j1,k1,l1,k2,l2);
2637: fprintf(fichtm,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
2638: fprintf(ficgp,"\nset out \"varpijgr%s%d%1d%1d-%1d%1d.png\"",optionfilefiname, j1,k1,l1,k2,l2);
2639: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
2640: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
2641: 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",\
2642: mu1,std,v11,sqrt(lc1),v12,sqrt(lc2),\
2643: mu2,std,v21,sqrt(lc1),v22,sqrt(lc2));
2644: }else{
2645: first=0;
2646: fprintf(fichtm," %d (%.3f),",(int) age, c12);
2647: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
2648: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
2649: 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",\
2650: mu1,std,v11,sqrt(lc1),v12,sqrt(lc2),\
2651: mu2,std,v21,sqrt(lc1),v22,sqrt(lc2));
2652: }/* if first */
2653: } /* age mod 5 */
2654: } /* end loop age */
2655: fprintf(ficgp,"\nset out \"varpijgr%s%d%1d%1d-%1d%1d.png\";replot;",optionfilefiname, j1,k1,l1,k2,l2);
2656: first=1;
2657: } /*l12 */
2658: } /* k12 */
2659: } /*l1 */
2660: }/* k1 */
2661: } /* loop covariates */
2662: }
2663: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
2664: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
2665: free_vector(xp,1,npar);
2666: fclose(ficresprob);
2667: fclose(ficresprobcov);
2668: fclose(ficresprobcor);
2669: fclose(ficgp);
2670: fclose(fichtm);
2671: }
2672:
2673:
2674: /******************* Printing html file ***********/
2675: void printinghtml(char fileres[], char title[], char datafile[], int firstpass, \
2676: int lastpass, int stepm, int weightopt, char model[],\
2677: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
2678: int popforecast, int estepm ,\
2679: double jprev1, double mprev1,double anprev1, \
2680: double jprev2, double mprev2,double anprev2){
2681: int jj1, k1, i1, cpt;
2682: /*char optionfilehtm[FILENAMELENGTH];*/
2683: if((fichtm=fopen(optionfilehtm,"a"))==NULL) {
2684: printf("Problem with %s \n",optionfilehtm), exit(0);
2685: fprintf(ficlog,"Problem with %s \n",optionfilehtm), exit(0);
2686: }
2687:
2688: fprintf(fichtm,"<ul><li><h4>Result files (first order: no variance)</h4>\n
2689: - Observed prevalence in each state (during the period defined between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf): <a href=\"p%s\">p%s</a> <br>\n
2690: - Estimated transition probabilities over %d (stepm) months: <a href=\"pij%s\">pij%s</a><br>\n
2691: - Stable prevalence in each health state: <a href=\"pl%s\">pl%s</a> <br>\n
2692: - Life expectancies by age and initial health status (estepm=%2d months):
2693: <a href=\"e%s\">e%s</a> <br>\n</li>", \
2694: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,fileres,fileres,stepm,fileres,fileres,fileres,fileres,estepm,fileres,fileres);
2695:
2696: fprintf(fichtm," \n<ul><li><b>Graphs</b></li><p>");
2697:
2698: m=cptcoveff;
2699: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
2700:
2701: jj1=0;
2702: for(k1=1; k1<=m;k1++){
2703: for(i1=1; i1<=ncodemax[k1];i1++){
2704: jj1++;
2705: if (cptcovn > 0) {
2706: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
2707: for (cpt=1; cpt<=cptcoveff;cpt++)
2708: fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtab[jj1][cpt]]);
2709: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
2710: }
2711: /* Pij */
2712: fprintf(fichtm,"<br>- Pij or Conditional probabilities to be observed in state j being in state i %d (stepm) months before: pe%s%d1.png<br>
2713: <img src=\"pe%s%d1.png\">",stepm,strtok(optionfile, "."),jj1,strtok(optionfile, "."),jj1);
2714: /* Quasi-incidences */
2715: fprintf(fichtm,"<br>- Pij or Conditional probabilities to be observed in state j being in state i %d (stepm) months before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too: pe%s%d2.png<br>
2716: <img src=\"pe%s%d2.png\">",stepm,strtok(optionfile, "."),jj1,strtok(optionfile, "."),jj1);
2717: /* Stable prevalence in each health state */
2718: for(cpt=1; cpt<nlstate;cpt++){
2719: fprintf(fichtm,"<br>- Stable prevalence in each health state : p%s%d%d.png<br>
2720: <img src=\"p%s%d%d.png\">",strtok(optionfile, "."),cpt,jj1,strtok(optionfile, "."),cpt,jj1);
2721: }
2722: for(cpt=1; cpt<=nlstate;cpt++) {
2723: fprintf(fichtm,"\n<br>- Health life expectancies by age and initial health state (%d): exp%s%d%d.png <br>
2724: <img src=\"exp%s%d%d.png\">",cpt,strtok(optionfile, "."),cpt,jj1,strtok(optionfile, "."),cpt,jj1);
2725: }
2726: fprintf(fichtm,"\n<br>- Total life expectancy by age and
2727: health expectancies in states (1) and (2): e%s%d.png<br>
2728: <img src=\"e%s%d.png\">",strtok(optionfile, "."),jj1,strtok(optionfile, "."),jj1);
2729: } /* end i1 */
2730: }/* End k1 */
2731: fprintf(fichtm,"</ul>");
2732:
2733:
2734: fprintf(fichtm,"\n<br><li><h4> Result files (second order: variances)</h4>\n
2735: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br>\n
2736: - Variance of one-step probabilities: <a href=\"prob%s\">prob%s</a> <br>\n
2737: - Variance-covariance of one-step probabilities: <a href=\"probcov%s\">probcov%s</a> <br>\n
2738: - Correlation matrix of one-step probabilities: <a href=\"probcor%s\">probcor%s</a> <br>\n
2739: - Variances and covariances of life expectancies by age and initial health status (estepm=%d months): <a href=\"v%s\">v%s</a><br>\n
2740: - Health expectancies with their variances (no covariance): <a href=\"t%s\">t%s</a> <br>\n
2741: - Standard deviation of stable prevalences: <a href=\"vpl%s\">vpl%s</a> <br>\n",rfileres,rfileres,fileres,fileres,fileres,fileres,fileres,fileres, estepm, fileres,fileres,fileres,fileres,fileres,fileres);
2742:
2743: if(popforecast==1) fprintf(fichtm,"\n
2744: - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n
2745: - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n
2746: <br>",fileres,fileres,fileres,fileres);
2747: else
2748: 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);
2749: fprintf(fichtm," <ul><li><b>Graphs</b></li><p>");
2750:
2751: m=cptcoveff;
2752: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
2753:
2754: jj1=0;
2755: for(k1=1; k1<=m;k1++){
2756: for(i1=1; i1<=ncodemax[k1];i1++){
2757: jj1++;
2758: if (cptcovn > 0) {
2759: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
2760: for (cpt=1; cpt<=cptcoveff;cpt++)
2761: fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtab[jj1][cpt]]);
2762: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
2763: }
2764: for(cpt=1; cpt<=nlstate;cpt++) {
2765: fprintf(fichtm,"<br>- Observed and stationary prevalence (with confident
2766: interval) in state (%d): v%s%d%d.png <br>
2767: <img src=\"v%s%d%d.png\">",cpt,strtok(optionfile, "."),cpt,jj1,strtok(optionfile, "."),cpt,jj1);
2768: }
2769: } /* end i1 */
2770: }/* End k1 */
2771: fprintf(fichtm,"</ul>");
2772: fclose(fichtm);
2773: }
2774:
2775: /******************* Gnuplot file **************/
2776: void printinggnuplot(char fileres[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
2777:
2778: int m,cpt,k1,i,k,j,jk,k2,k3,ij,l;
2779: int ng;
2780: if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) {
2781: printf("Problem with file %s",optionfilegnuplot);
2782: fprintf(ficlog,"Problem with file %s",optionfilegnuplot);
2783: }
2784:
2785: /*#ifdef windows */
2786: fprintf(ficgp,"cd \"%s\" \n",pathc);
2787: /*#endif */
2788: m=pow(2,cptcoveff);
2789:
2790: /* 1eme*/
2791: for (cpt=1; cpt<= nlstate ; cpt ++) {
2792: for (k1=1; k1<= m ; k1 ++) {
2793: fprintf(ficgp,"\nset out \"v%s%d%d.png\" \n",strtok(optionfile, "."),cpt,k1);
2794: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \nset ter png small\nset size 0.65,0.65\nplot [%.f:%.f] \"vpl%s\" every :::%d::%d u 1:2 \"\%%lf",ageminpar,fage,fileres,k1-1,k1-1);
2795:
2796: for (i=1; i<= nlstate ; i ++) {
2797: if (i==cpt) fprintf(ficgp," \%%lf (\%%lf)");
2798: else fprintf(ficgp," \%%*lf (\%%*lf)");
2799: }
2800: fprintf(ficgp,"\" t\"Stable prevalence\" w l 0,\"vpl%s\" every :::%d::%d u 1:($2+2*$3) \"\%%lf",fileres,k1-1,k1-1);
2801: for (i=1; i<= nlstate ; i ++) {
2802: if (i==cpt) fprintf(ficgp," \%%lf (\%%lf)");
2803: else fprintf(ficgp," \%%*lf (\%%*lf)");
2804: }
2805: fprintf(ficgp,"\" t\"95\%% CI\" w l 1,\"vpl%s\" every :::%d::%d u 1:($2-2*$3) \"\%%lf",fileres,k1-1,k1-1);
2806: for (i=1; i<= nlstate ; i ++) {
2807: if (i==cpt) fprintf(ficgp," \%%lf (\%%lf)");
2808: else fprintf(ficgp," \%%*lf (\%%*lf)");
2809: }
2810: fprintf(ficgp,"\" t\"\" w l 1,\"p%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence \" w l 2",fileres,k1-1,k1-1,2+4*(cpt-1));
2811: }
2812: }
2813: /*2 eme*/
2814:
2815: for (k1=1; k1<= m ; k1 ++) {
2816: fprintf(ficgp,"\nset out \"e%s%d.png\" \n",strtok(optionfile, "."),k1);
2817: fprintf(ficgp,"set ylabel \"Years\" \nset ter png small\nset size 0.65,0.65\nplot [%.f:%.f] ",ageminpar,fage);
2818:
2819: for (i=1; i<= nlstate+1 ; i ++) {
2820: k=2*i;
2821: fprintf(ficgp,"\"t%s\" every :::%d::%d u 1:2 \"\%%lf",fileres,k1-1,k1-1);
2822: for (j=1; j<= nlstate+1 ; j ++) {
2823: if (j==i) fprintf(ficgp," \%%lf (\%%lf)");
2824: else fprintf(ficgp," \%%*lf (\%%*lf)");
2825: }
2826: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l ,");
2827: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l ,",i-1);
2828: fprintf(ficgp,"\"t%s\" every :::%d::%d u 1:($2-$3*2) \"\%%lf",fileres,k1-1,k1-1);
2829: for (j=1; j<= nlstate+1 ; j ++) {
2830: if (j==i) fprintf(ficgp," \%%lf (\%%lf)");
2831: else fprintf(ficgp," \%%*lf (\%%*lf)");
2832: }
2833: fprintf(ficgp,"\" t\"\" w l 0,");
2834: fprintf(ficgp,"\"t%s\" every :::%d::%d u 1:($2+$3*2) \"\%%lf",fileres,k1-1,k1-1);
2835: for (j=1; j<= nlstate+1 ; j ++) {
2836: if (j==i) fprintf(ficgp," \%%lf (\%%lf)");
2837: else fprintf(ficgp," \%%*lf (\%%*lf)");
2838: }
2839: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l 0");
2840: else fprintf(ficgp,"\" t\"\" w l 0,");
2841: }
2842: }
2843:
2844: /*3eme*/
2845:
2846: for (k1=1; k1<= m ; k1 ++) {
2847: for (cpt=1; cpt<= nlstate ; cpt ++) {
2848: k=2+nlstate*(2*cpt-2);
2849: fprintf(ficgp,"\nset out \"exp%s%d%d.png\" \n",strtok(optionfile, "."),cpt,k1);
2850: fprintf(ficgp,"set ter png small\nset size 0.65,0.65\nplot [%.f:%.f] \"e%s\" every :::%d::%d u 1:%d t \"e%d1\" w l",ageminpar,fage,fileres,k1-1,k1-1,k,cpt);
2851: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
2852: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
2853: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
2854: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
2855: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
2856: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
2857:
2858: */
2859: for (i=1; i< nlstate ; i ++) {
2860: fprintf(ficgp," ,\"e%s\" every :::%d::%d u 1:%d t \"e%d%d\" w l",fileres,k1-1,k1-1,k+2*i,cpt,i+1);
2861:
2862: }
2863: }
2864: }
2865:
2866: /* CV preval stat */
2867: for (k1=1; k1<= m ; k1 ++) {
2868: for (cpt=1; cpt<nlstate ; cpt ++) {
2869: k=3;
2870: fprintf(ficgp,"\nset out \"p%s%d%d.png\" \n",strtok(optionfile, "."),cpt,k1);
2871: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \nset ter png small\nset size 0.65,0.65\nplot [%.f:%.f] \"pij%s\" u ($1==%d ? ($3):1/0):($%d/($%d",ageminpar,agemaxpar,fileres,k1,k+cpt+1,k+1);
2872:
2873: for (i=1; i< nlstate ; i ++)
2874: fprintf(ficgp,"+$%d",k+i+1);
2875: fprintf(ficgp,")) t\"prev(%d,%d)\" w l",cpt,cpt+1);
2876:
2877: l=3+(nlstate+ndeath)*cpt;
2878: fprintf(ficgp,",\"pij%s\" u ($1==%d ? ($3):1/0):($%d/($%d",fileres,k1,l+cpt+1,l+1);
2879: for (i=1; i< nlstate ; i ++) {
2880: l=3+(nlstate+ndeath)*cpt;
2881: fprintf(ficgp,"+$%d",l+i+1);
2882: }
2883: fprintf(ficgp,")) t\"prev(%d,%d)\" w l\n",cpt+1,cpt+1);
2884: }
2885: }
2886:
2887: /* proba elementaires */
2888: for(i=1,jk=1; i <=nlstate; i++){
2889: for(k=1; k <=(nlstate+ndeath); k++){
2890: if (k != i) {
2891: for(j=1; j <=ncovmodel; j++){
2892: fprintf(ficgp,"p%d=%f ",jk,p[jk]);
2893: jk++;
2894: fprintf(ficgp,"\n");
2895: }
2896: }
2897: }
2898: }
2899:
2900: for(ng=1; ng<=2;ng++){ /* Number of graphics: first is probabilities second is incidence per year*/
2901: for(jk=1; jk <=m; jk++) {
2902: fprintf(ficgp,"\nset out \"pe%s%d%d.png\" \n",strtok(optionfile, "."),jk,ng);
2903: if (ng==2)
2904: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
2905: else
2906: fprintf(ficgp,"\nset title \"Probability\"\n");
2907: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65\nset log y\nplot [%.f:%.f] ",ageminpar,agemaxpar);
2908: i=1;
2909: for(k2=1; k2<=nlstate; k2++) {
2910: k3=i;
2911: for(k=1; k<=(nlstate+ndeath); k++) {
2912: if (k != k2){
2913: if(ng==2)
2914: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
2915: else
2916: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
2917: ij=1;
2918: for(j=3; j <=ncovmodel; j++) {
2919: if(((j-2)==Tage[ij]) &&(ij <=cptcovage)) {
2920: fprintf(ficgp,"+p%d*%d*x",i+j-1,nbcode[Tvar[j-2]][codtab[jk][Tvar[j-2]]]);
2921: ij++;
2922: }
2923: else
2924: fprintf(ficgp,"+p%d*%d",i+j-1,nbcode[Tvar[j-2]][codtab[jk][j-2]]);
2925: }
2926: fprintf(ficgp,")/(1");
2927:
2928: for(k1=1; k1 <=nlstate; k1++){
2929: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(k1-1)*ncovmodel,k3+(k1-1)*ncovmodel+1);
2930: ij=1;
2931: for(j=3; j <=ncovmodel; j++){
2932: if(((j-2)==Tage[ij]) &&(ij <=cptcovage)) {
2933: fprintf(ficgp,"+p%d*%d*x",k3+(k1-1)*ncovmodel+1+j-2,nbcode[Tvar[j-2]][codtab[jk][Tvar[j-2]]]);
2934: ij++;
2935: }
2936: else
2937: fprintf(ficgp,"+p%d*%d",k3+(k1-1)*ncovmodel+1+j-2,nbcode[Tvar[j-2]][codtab[jk][j-2]]);
2938: }
2939: fprintf(ficgp,")");
2940: }
2941: fprintf(ficgp,") t \"p%d%d\" ", k2,k);
2942: if ((k+k2)!= (nlstate*2+ndeath)) fprintf(ficgp,",");
2943: i=i+ncovmodel;
2944: }
2945: } /* end k */
2946: } /* end k2 */
2947: } /* end jk */
2948: } /* end ng */
2949: fclose(ficgp);
2950: } /* end gnuplot */
2951:
2952:
2953: /*************** Moving average **************/
2954: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav){
2955:
2956: int i, cpt, cptcod;
2957: int modcovmax =1;
2958: int mobilavrange, mob;
2959: double age;
2960:
2961: modcovmax=2*cptcoveff;/* Max number of modalities. We suppose
2962: a covariate has 2 modalities */
2963: if (cptcovn<1) modcovmax=1; /* At least 1 pass */
2964:
2965: if(mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
2966: if(mobilav==1) mobilavrange=5; /* default */
2967: else mobilavrange=mobilav;
2968: for (age=bage; age<=fage; age++)
2969: for (i=1; i<=nlstate;i++)
2970: for (cptcod=1;cptcod<=modcovmax;cptcod++)
2971: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
2972: /* We keep the original values on the extreme ages bage, fage and for
2973: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
2974: we use a 5 terms etc. until the borders are no more concerned.
2975: */
2976: for (mob=3;mob <=mobilavrange;mob=mob+2){
2977: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
2978: for (i=1; i<=nlstate;i++){
2979: for (cptcod=1;cptcod<=modcovmax;cptcod++){
2980: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
2981: for (cpt=1;cpt<=(mob-1)/2;cpt++){
2982: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
2983: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
2984: }
2985: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
2986: }
2987: }
2988: }/* end age */
2989: }/* end mob */
2990: }else return -1;
2991: return 0;
2992: }/* End movingaverage */
2993:
2994:
2995: /************** Forecasting ******************/
2996: prevforecast(char fileres[], double anproj1,double mproj1,double jproj1,double ageminpar, double agemax,double dateprev1, double dateprev2, int mobilav, double agedeb, double fage, int popforecast, char popfile[], double anproj2,double p[], int i2){
2997:
2998: int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h;
2999: int *popage;
3000: double calagedate, agelim, kk1, kk2, yp,yp1,yp2,jprojmean,mprojmean,anprojmean;
3001: double *popeffectif,*popcount;
3002: double ***p3mat;
3003: double ***mobaverage;
3004: char fileresf[FILENAMELENGTH];
3005:
3006: agelim=AGESUP;
3007: calagedate=(anproj1+mproj1/12.+jproj1/365.-dateintmean)*YEARM;
3008:
3009: prevalence(ageminpar, agemax, s, agev, nlstate, imx,Tvar,nbcode, ncodemax,mint,anint,dateprev1,dateprev2, calagedate);
3010:
3011:
3012: strcpy(fileresf,"f");
3013: strcat(fileresf,fileres);
3014: if((ficresf=fopen(fileresf,"w"))==NULL) {
3015: printf("Problem with forecast resultfile: %s\n", fileresf);
3016: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
3017: }
3018: printf("Computing forecasting: result on file '%s' \n", fileresf);
3019: fprintf(ficlog,"Computing forecasting: result on file '%s' \n", fileresf);
3020:
3021: if (cptcoveff==0) ncodemax[cptcoveff]=1;
3022:
3023: if (mobilav!=0) {
3024: mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX);
3025: if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){
3026: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
3027: printf(" Error in movingaverage mobilav=%d\n",mobilav);
3028: }
3029: }
3030:
3031: stepsize=(int) (stepm+YEARM-1)/YEARM;
3032: if (stepm<=12) stepsize=1;
3033:
3034: agelim=AGESUP;
3035:
3036: hstepm=1;
3037: hstepm=hstepm/stepm;
3038: yp1=modf(dateintmean,&yp);
3039: anprojmean=yp;
3040: yp2=modf((yp1*12),&yp);
3041: mprojmean=yp;
3042: yp1=modf((yp2*30.5),&yp);
3043: jprojmean=yp;
3044: if(jprojmean==0) jprojmean=1;
3045: if(mprojmean==0) jprojmean=1;
3046:
3047: fprintf(ficresf,"# Estimated date of observed prevalence: %.lf/%.lf/%.lf ",jprojmean,mprojmean,anprojmean);
3048:
3049: for(cptcov=1;cptcov<=i2;cptcov++){
3050: for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){
3051: k=k+1;
3052: fprintf(ficresf,"\n#******");
3053: for(j=1;j<=cptcoveff;j++) {
3054: fprintf(ficresf," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtab[k][j]]);
3055: }
3056: fprintf(ficresf,"******\n");
3057: fprintf(ficresf,"# StartingAge FinalAge");
3058: for(j=1; j<=nlstate+ndeath;j++) fprintf(ficresf," P.%d",j);
3059:
3060:
3061: for (cpt=0; cpt<=(anproj2-anproj1);cpt++) {
3062: fprintf(ficresf,"\n");
3063: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jproj1,mproj1,anproj1+cpt);
3064:
3065: for (agedeb=(fage-((int)calagedate %12/12.)); agedeb>=(ageminpar-((int)calagedate %12)/12.); agedeb--){
3066: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm);
3067: nhstepm = nhstepm/hstepm;
3068:
3069: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
3070: oldm=oldms;savm=savms;
3071: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k);
3072:
3073: for (h=0; h<=nhstepm; h++){
3074: if (h==(int) (calagedate+YEARM*cpt)) {
3075: fprintf(ficresf,"\n %.f %.f ",anproj1+cpt,agedeb+h*hstepm/YEARM*stepm);
3076: }
3077: for(j=1; j<=nlstate+ndeath;j++) {
3078: kk1=0.;kk2=0;
3079: for(i=1; i<=nlstate;i++) {
3080: if (mobilav==1)
3081: kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod];
3082: else {
3083: kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod];
3084: }
3085:
3086: }
3087: if (h==(int)(calagedate+12*cpt)){
3088: fprintf(ficresf," %.3f", kk1);
3089:
3090: }
3091: }
3092: }
3093: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
3094: }
3095: }
3096: }
3097: }
3098:
3099: if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX);
3100:
3101: fclose(ficresf);
3102: }
3103: /************** Forecasting ******************/
3104: populforecast(char fileres[], double anpyram,double mpyram,double jpyram,double ageminpar, double agemax,double dateprev1, double dateprev2, int mobilav, double agedeb, double fage, int popforecast, char popfile[], double anpyram1,double p[], int i2){
3105:
3106: int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h;
3107: int *popage;
3108: double calagedate, agelim, kk1, kk2;
3109: double *popeffectif,*popcount;
3110: double ***p3mat,***tabpop,***tabpopprev;
3111: double ***mobaverage;
3112: char filerespop[FILENAMELENGTH];
3113:
3114: tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX);
3115: tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX);
3116: agelim=AGESUP;
3117: calagedate=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM;
3118:
3119: prevalence(ageminpar, agemax, s, agev, nlstate, imx,Tvar,nbcode, ncodemax,mint,anint,dateprev1,dateprev2, calagedate);
3120:
3121:
3122: strcpy(filerespop,"pop");
3123: strcat(filerespop,fileres);
3124: if((ficrespop=fopen(filerespop,"w"))==NULL) {
3125: printf("Problem with forecast resultfile: %s\n", filerespop);
3126: fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop);
3127: }
3128: printf("Computing forecasting: result on file '%s' \n", filerespop);
3129: fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop);
3130:
3131: if (cptcoveff==0) ncodemax[cptcoveff]=1;
3132:
3133: if (mobilav!=0) {
3134: mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX);
3135: if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){
3136: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
3137: printf(" Error in movingaverage mobilav=%d\n",mobilav);
3138: }
3139: }
3140:
3141: stepsize=(int) (stepm+YEARM-1)/YEARM;
3142: if (stepm<=12) stepsize=1;
3143:
3144: agelim=AGESUP;
3145:
3146: hstepm=1;
3147: hstepm=hstepm/stepm;
3148:
3149: if (popforecast==1) {
3150: if((ficpop=fopen(popfile,"r"))==NULL) {
3151: printf("Problem with population file : %s\n",popfile);exit(0);
3152: fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0);
3153: }
3154: popage=ivector(0,AGESUP);
3155: popeffectif=vector(0,AGESUP);
3156: popcount=vector(0,AGESUP);
3157:
3158: i=1;
3159: while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1;
3160:
3161: imx=i;
3162: for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i];
3163: }
3164:
3165: for(cptcov=1;cptcov<=i2;cptcov++){
3166: for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){
3167: k=k+1;
3168: fprintf(ficrespop,"\n#******");
3169: for(j=1;j<=cptcoveff;j++) {
3170: fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtab[k][j]]);
3171: }
3172: fprintf(ficrespop,"******\n");
3173: fprintf(ficrespop,"# Age");
3174: for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j);
3175: if (popforecast==1) fprintf(ficrespop," [Population]");
3176:
3177: for (cpt=0; cpt<=0;cpt++) {
3178: fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt);
3179:
3180: for (agedeb=(fage-((int)calagedate %12/12.)); agedeb>=(ageminpar-((int)calagedate %12)/12.); agedeb--){
3181: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm);
3182: nhstepm = nhstepm/hstepm;
3183:
3184: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
3185: oldm=oldms;savm=savms;
3186: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k);
3187:
3188: for (h=0; h<=nhstepm; h++){
3189: if (h==(int) (calagedate+YEARM*cpt)) {
3190: fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm);
3191: }
3192: for(j=1; j<=nlstate+ndeath;j++) {
3193: kk1=0.;kk2=0;
3194: for(i=1; i<=nlstate;i++) {
3195: if (mobilav==1)
3196: kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod];
3197: else {
3198: kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod];
3199: }
3200: }
3201: if (h==(int)(calagedate+12*cpt)){
3202: tabpop[(int)(agedeb)][j][cptcod]=kk1;
3203: /*fprintf(ficrespop," %.3f", kk1);
3204: if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*/
3205: }
3206: }
3207: for(i=1; i<=nlstate;i++){
3208: kk1=0.;
3209: for(j=1; j<=nlstate;j++){
3210: kk1= kk1+tabpop[(int)(agedeb)][j][cptcod];
3211: }
3212: tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedate+12*cpt)*hstepm/YEARM*stepm-1)];
3213: }
3214:
3215: if (h==(int)(calagedate+12*cpt)) for(j=1; j<=nlstate;j++)
3216: fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]);
3217: }
3218: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
3219: }
3220: }
3221:
3222: /******/
3223:
3224: for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) {
3225: fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt);
3226: for (agedeb=(fage-((int)calagedate %12/12.)); agedeb>=(ageminpar-((int)calagedate %12)/12.); agedeb--){
3227: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm);
3228: nhstepm = nhstepm/hstepm;
3229:
3230: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
3231: oldm=oldms;savm=savms;
3232: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k);
3233: for (h=0; h<=nhstepm; h++){
3234: if (h==(int) (calagedate+YEARM*cpt)) {
3235: fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm);
3236: }
3237: for(j=1; j<=nlstate+ndeath;j++) {
3238: kk1=0.;kk2=0;
3239: for(i=1; i<=nlstate;i++) {
3240: kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod];
3241: }
3242: if (h==(int)(calagedate+12*cpt)) fprintf(ficresf," %15.2f", kk1);
3243: }
3244: }
3245: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
3246: }
3247: }
3248: }
3249: }
3250:
3251: if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX);
3252:
3253: if (popforecast==1) {
3254: free_ivector(popage,0,AGESUP);
3255: free_vector(popeffectif,0,AGESUP);
3256: free_vector(popcount,0,AGESUP);
3257: }
3258: free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX);
3259: free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX);
3260: fclose(ficrespop);
3261: }
3262:
3263: /***********************************************/
3264: /**************** Main Program *****************/
3265: /***********************************************/
3266:
3267: int main(int argc, char *argv[])
3268: {
3269: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
3270: int i,j, k, n=MAXN,iter,m,size,cptcode, cptcod;
3271: double agedeb, agefin,hf;
3272: double ageminpar=1.e20,agemin=1.e20, agemaxpar=-1.e20, agemax=-1.e20;
3273:
3274: double fret;
3275: double **xi,tmp,delta;
3276:
3277: double dum; /* Dummy variable */
3278: double ***p3mat;
3279: double ***mobaverage;
3280: int *indx;
3281: char line[MAXLINE], linepar[MAXLINE];
3282: char path[80],pathc[80],pathcd[80],pathtot[80],model[80];
3283: int firstobs=1, lastobs=10;
3284: int sdeb, sfin; /* Status at beginning and end */
3285: int c, h , cpt,l;
3286: int ju,jl, mi;
3287: int i1,j1, k1,k2,k3,jk,aa,bb, stepsize, ij;
3288: int jnais,jdc,jint4,jint1,jint2,jint3,**outcome,*tab;
3289: int mobilav=0,popforecast=0;
3290: int hstepm, nhstepm;
3291: double jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,jpyram, mpyram,anpyram,jpyram1, mpyram1,anpyram1, calagedate;
3292:
3293: double bage, fage, age, agelim, agebase;
3294: double ftolpl=FTOL;
3295: double **prlim;
3296: double *severity;
3297: double ***param; /* Matrix of parameters */
3298: double *p;
3299: double **matcov; /* Matrix of covariance */
3300: double ***delti3; /* Scale */
3301: double *delti; /* Scale */
3302: double ***eij, ***vareij;
3303: double **varpl; /* Variances of prevalence limits by age */
3304: double *epj, vepp;
3305: double kk1, kk2;
3306: double dateprev1, dateprev2,jproj1,mproj1,anproj1,jproj2,mproj2,anproj2;
3307:
3308: char *alph[]={"a","a","b","c","d","e"}, str[4];
3309:
3310:
3311: char z[1]="c", occ;
3312: #include <sys/time.h>
3313: #include <time.h>
3314: char stra[80], strb[80], strc[80], strd[80],stre[80],modelsav[80];
3315:
3316: /* long total_usecs;
3317: struct timeval start_time, end_time;
3318:
3319: gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
3320: getcwd(pathcd, size);
3321:
3322: printf("\n%s",version);
3323: if(argc <=1){
3324: printf("\nEnter the parameter file name: ");
3325: scanf("%s",pathtot);
3326: }
3327: else{
3328: strcpy(pathtot,argv[1]);
3329: }
3330: /*if(getcwd(pathcd, 80)!= NULL)printf ("Error pathcd\n");*/
3331: /*cygwin_split_path(pathtot,path,optionfile);
3332: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
3333: /* cutv(path,optionfile,pathtot,'\\');*/
3334:
3335: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
3336: printf("pathtot=%s, path=%s, optionfile=%s optionfilext=%s optionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
3337: chdir(path);
3338: replace(pathc,path);
3339:
3340: /*-------- arguments in the command line --------*/
3341:
3342: /* Log file */
3343: strcat(filelog, optionfilefiname);
3344: strcat(filelog,".log"); /* */
3345: if((ficlog=fopen(filelog,"w"))==NULL) {
3346: printf("Problem with logfile %s\n",filelog);
3347: goto end;
3348: }
3349: fprintf(ficlog,"Log filename:%s\n",filelog);
3350: fprintf(ficlog,"\n%s",version);
3351: fprintf(ficlog,"\nEnter the parameter file name: ");
3352: fprintf(ficlog,"pathtot=%s, path=%s, optionfile=%s optionfilext=%s optionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
3353: fflush(ficlog);
3354:
3355: /* */
3356: strcpy(fileres,"r");
3357: strcat(fileres, optionfilefiname);
3358: strcat(fileres,".txt"); /* Other files have txt extension */
3359:
3360: /*---------arguments file --------*/
3361:
3362: if((ficpar=fopen(optionfile,"r"))==NULL) {
3363: printf("Problem with optionfile %s\n",optionfile);
3364: fprintf(ficlog,"Problem with optionfile %s\n",optionfile);
3365: goto end;
3366: }
3367:
3368: strcpy(filereso,"o");
3369: strcat(filereso,fileres);
3370: if((ficparo=fopen(filereso,"w"))==NULL) {
3371: printf("Problem with Output resultfile: %s\n", filereso);
3372: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
3373: goto end;
3374: }
3375:
3376: /* Reads comments: lines beginning with '#' */
3377: while((c=getc(ficpar))=='#' && c!= EOF){
3378: ungetc(c,ficpar);
3379: fgets(line, MAXLINE, ficpar);
3380: puts(line);
3381: fputs(line,ficparo);
3382: }
3383: ungetc(c,ficpar);
3384:
3385: 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=%s\n",title, datafile, &lastobs, &firstpass,&lastpass,&ftol, &stepm, &ncovcol, &nlstate,&ndeath, &maxwav, &mle, &weightopt,model);
3386: 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=%s\n", title, datafile, lastobs, firstpass,lastpass,ftol, stepm, ncovcol, nlstate,ndeath, maxwav, mle, weightopt,model);
3387: fprintf(ficparo,"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=%s\n", title, datafile, lastobs, firstpass,lastpass,ftol,stepm,ncovcol,nlstate,ndeath,maxwav, mle, weightopt,model);
3388: while((c=getc(ficpar))=='#' && c!= EOF){
3389: ungetc(c,ficpar);
3390: fgets(line, MAXLINE, ficpar);
3391: puts(line);
3392: fputs(line,ficparo);
3393: }
3394: ungetc(c,ficpar);
3395:
3396:
3397: covar=matrix(0,NCOVMAX,1,n);
3398: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement*/
3399: if (strlen(model)>1) cptcovn=nbocc(model,'+')+1;
3400:
3401: ncovmodel=2+cptcovn; /*Number of variables = cptcovn + intercept + age */
3402: nvar=ncovmodel-1; /* Suppressing age as a basic covariate */
3403:
3404: /* Read guess parameters */
3405: /* Reads comments: lines beginning with '#' */
3406: while((c=getc(ficpar))=='#' && c!= EOF){
3407: ungetc(c,ficpar);
3408: fgets(line, MAXLINE, ficpar);
3409: puts(line);
3410: fputs(line,ficparo);
3411: }
3412: ungetc(c,ficpar);
3413:
3414: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
3415: for(i=1; i <=nlstate; i++)
3416: for(j=1; j <=nlstate+ndeath-1; j++){
3417: fscanf(ficpar,"%1d%1d",&i1,&j1);
3418: fprintf(ficparo,"%1d%1d",i1,j1);
3419: if(mle==1)
3420: printf("%1d%1d",i,j);
3421: fprintf(ficlog,"%1d%1d",i,j);
3422: for(k=1; k<=ncovmodel;k++){
3423: fscanf(ficpar," %lf",¶m[i][j][k]);
3424: if(mle==1){
3425: printf(" %lf",param[i][j][k]);
3426: fprintf(ficlog," %lf",param[i][j][k]);
3427: }
3428: else
3429: fprintf(ficlog," %lf",param[i][j][k]);
3430: fprintf(ficparo," %lf",param[i][j][k]);
3431: }
3432: fscanf(ficpar,"\n");
3433: if(mle==1)
3434: printf("\n");
3435: fprintf(ficlog,"\n");
3436: fprintf(ficparo,"\n");
3437: }
3438:
3439: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
3440:
3441: p=param[1][1];
3442:
3443: /* Reads comments: lines beginning with '#' */
3444: while((c=getc(ficpar))=='#' && c!= EOF){
3445: ungetc(c,ficpar);
3446: fgets(line, MAXLINE, ficpar);
3447: puts(line);
3448: fputs(line,ficparo);
3449: }
3450: ungetc(c,ficpar);
3451:
3452: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
3453: delti=vector(1,npar); /* Scale of each paramater (output from hesscov) */
3454: for(i=1; i <=nlstate; i++){
3455: for(j=1; j <=nlstate+ndeath-1; j++){
3456: fscanf(ficpar,"%1d%1d",&i1,&j1);
3457: printf("%1d%1d",i,j);
3458: fprintf(ficparo,"%1d%1d",i1,j1);
3459: for(k=1; k<=ncovmodel;k++){
3460: fscanf(ficpar,"%le",&delti3[i][j][k]);
3461: printf(" %le",delti3[i][j][k]);
3462: fprintf(ficparo," %le",delti3[i][j][k]);
3463: }
3464: fscanf(ficpar,"\n");
3465: printf("\n");
3466: fprintf(ficparo,"\n");
3467: }
3468: }
3469: delti=delti3[1][1];
3470:
3471: /* Reads comments: lines beginning with '#' */
3472: while((c=getc(ficpar))=='#' && c!= EOF){
3473: ungetc(c,ficpar);
3474: fgets(line, MAXLINE, ficpar);
3475: puts(line);
3476: fputs(line,ficparo);
3477: }
3478: ungetc(c,ficpar);
3479:
3480: matcov=matrix(1,npar,1,npar);
3481: for(i=1; i <=npar; i++){
3482: fscanf(ficpar,"%s",&str);
3483: if(mle==1)
3484: printf("%s",str);
3485: fprintf(ficlog,"%s",str);
3486: fprintf(ficparo,"%s",str);
3487: for(j=1; j <=i; j++){
3488: fscanf(ficpar," %le",&matcov[i][j]);
3489: if(mle==1){
3490: printf(" %.5le",matcov[i][j]);
3491: fprintf(ficlog," %.5le",matcov[i][j]);
3492: }
3493: else
3494: fprintf(ficlog," %.5le",matcov[i][j]);
3495: fprintf(ficparo," %.5le",matcov[i][j]);
3496: }
3497: fscanf(ficpar,"\n");
3498: if(mle==1)
3499: printf("\n");
3500: fprintf(ficlog,"\n");
3501: fprintf(ficparo,"\n");
3502: }
3503: for(i=1; i <=npar; i++)
3504: for(j=i+1;j<=npar;j++)
3505: matcov[i][j]=matcov[j][i];
3506:
3507: if(mle==1)
3508: printf("\n");
3509: fprintf(ficlog,"\n");
3510:
3511:
3512: /*-------- Rewriting paramater file ----------*/
3513: strcpy(rfileres,"r"); /* "Rparameterfile */
3514: strcat(rfileres,optionfilefiname); /* Parameter file first name*/
3515: strcat(rfileres,"."); /* */
3516: strcat(rfileres,optionfilext); /* Other files have txt extension */
3517: if((ficres =fopen(rfileres,"w"))==NULL) {
3518: printf("Problem writing new parameter file: %s\n", fileres);goto end;
3519: fprintf(ficlog,"Problem writing new parameter file: %s\n", fileres);goto end;
3520: }
3521: fprintf(ficres,"#%s\n",version);
3522:
3523: /*-------- data file ----------*/
3524: if((fic=fopen(datafile,"r"))==NULL) {
3525: printf("Problem with datafile: %s\n", datafile);goto end;
3526: fprintf(ficlog,"Problem with datafile: %s\n", datafile);goto end;
3527: }
3528:
3529: n= lastobs;
3530: severity = vector(1,maxwav);
3531: outcome=imatrix(1,maxwav+1,1,n);
3532: num=ivector(1,n);
3533: moisnais=vector(1,n);
3534: annais=vector(1,n);
3535: moisdc=vector(1,n);
3536: andc=vector(1,n);
3537: agedc=vector(1,n);
3538: cod=ivector(1,n);
3539: weight=vector(1,n);
3540: for(i=1;i<=n;i++) weight[i]=1.0; /* Equal weights, 1 by default */
3541: mint=matrix(1,maxwav,1,n);
3542: anint=matrix(1,maxwav,1,n);
3543: s=imatrix(1,maxwav+1,1,n);
3544: tab=ivector(1,NCOVMAX);
3545: ncodemax=ivector(1,8);
3546:
3547: i=1;
3548: while (fgets(line, MAXLINE, fic) != NULL) {
3549: if ((i >= firstobs) && (i <=lastobs)) {
3550:
3551: for (j=maxwav;j>=1;j--){
3552: cutv(stra, strb,line,' '); s[j][i]=atoi(strb);
3553: strcpy(line,stra);
3554: cutv(stra, strb,line,'/'); anint[j][i]=(double)(atoi(strb)); strcpy(line,stra);
3555: cutv(stra, strb,line,' '); mint[j][i]=(double)(atoi(strb)); strcpy(line,stra);
3556: }
3557:
3558: cutv(stra, strb,line,'/'); andc[i]=(double)(atoi(strb)); strcpy(line,stra);
3559: cutv(stra, strb,line,' '); moisdc[i]=(double)(atoi(strb)); strcpy(line,stra);
3560:
3561: cutv(stra, strb,line,'/'); annais[i]=(double)(atoi(strb)); strcpy(line,stra);
3562: cutv(stra, strb,line,' '); moisnais[i]=(double)(atoi(strb)); strcpy(line,stra);
3563:
3564: cutv(stra, strb,line,' '); weight[i]=(double)(atoi(strb)); strcpy(line,stra);
3565: for (j=ncovcol;j>=1;j--){
3566: cutv(stra, strb,line,' '); covar[j][i]=(double)(atoi(strb)); strcpy(line,stra);
3567: }
3568: num[i]=atol(stra);
3569:
3570: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
3571: printf("%d %.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;}*/
3572:
3573: i=i+1;
3574: }
3575: }
3576: /* printf("ii=%d", ij);
3577: scanf("%d",i);*/
3578: imx=i-1; /* Number of individuals */
3579:
3580: /* for (i=1; i<=imx; i++){
3581: if ((s[1][i]==3) && (s[2][i]==2)) s[2][i]=3;
3582: if ((s[2][i]==3) && (s[3][i]==2)) s[3][i]=3;
3583: if ((s[3][i]==3) && (s[4][i]==2)) s[4][i]=3;
3584: }*/
3585: /* for (i=1; i<=imx; i++){
3586: if (s[4][i]==9) s[4][i]=-1;
3587: printf("%d %.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]));}*/
3588:
3589:
3590: /* Calculation of the number of parameter from char model*/
3591: Tvar=ivector(1,15); /* stores the number n of the covariates in Vm+Vn at 1 and m at 2 */
3592: Tprod=ivector(1,15);
3593: Tvaraff=ivector(1,15);
3594: Tvard=imatrix(1,15,1,2);
3595: Tage=ivector(1,15);
3596:
3597: if (strlen(model) >1){ /* If there is at least 1 covariate */
3598: j=0, j1=0, k1=1, k2=1;
3599: j=nbocc(model,'+'); /* j=Number of '+' */
3600: j1=nbocc(model,'*'); /* j1=Number of '*' */
3601: cptcovn=j+1;
3602: cptcovprod=j1; /*Number of products */
3603:
3604: strcpy(modelsav,model);
3605: if ((strcmp(model,"age")==0) || (strcmp(model,"age*age")==0)){
3606: printf("Error. Non available option model=%s ",model);
3607: fprintf(ficlog,"Error. Non available option model=%s ",model);
3608: goto end;
3609: }
3610:
3611: /* This loop fills the array Tvar from the string 'model'.*/
3612:
3613: for(i=(j+1); i>=1;i--){
3614: cutv(stra,strb,modelsav,'+'); /* keeps in strb after the last + */
3615: if (nbocc(modelsav,'+')==0) strcpy(strb,modelsav); /* and analyzes it */
3616: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
3617: /*scanf("%d",i);*/
3618: if (strchr(strb,'*')) { /* Model includes a product */
3619: cutv(strd,strc,strb,'*'); /* strd*strc Vm*Vn (if not *age)*/
3620: if (strcmp(strc,"age")==0) { /* Vn*age */
3621: cptcovprod--;
3622: cutv(strb,stre,strd,'V');
3623: Tvar[i]=atoi(stre); /* computes n in Vn and stores in Tvar*/
3624: cptcovage++;
3625: Tage[cptcovage]=i;
3626: /*printf("stre=%s ", stre);*/
3627: }
3628: else if (strcmp(strd,"age")==0) { /* or age*Vn */
3629: cptcovprod--;
3630: cutv(strb,stre,strc,'V');
3631: Tvar[i]=atoi(stre);
3632: cptcovage++;
3633: Tage[cptcovage]=i;
3634: }
3635: else { /* Age is not in the model */
3636: cutv(strb,stre,strc,'V'); /* strc= Vn, stre is n*/
3637: Tvar[i]=ncovcol+k1;
3638: cutv(strb,strc,strd,'V'); /* strd was Vm, strc is m */
3639: Tprod[k1]=i;
3640: Tvard[k1][1]=atoi(strc); /* m*/
3641: Tvard[k1][2]=atoi(stre); /* n */
3642: Tvar[cptcovn+k2]=Tvard[k1][1];
3643: Tvar[cptcovn+k2+1]=Tvard[k1][2];
3644: for (k=1; k<=lastobs;k++)
3645: covar[ncovcol+k1][k]=covar[atoi(stre)][k]*covar[atoi(strc)][k];
3646: k1++;
3647: k2=k2+2;
3648: }
3649: }
3650: else { /* no more sum */
3651: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
3652: /* scanf("%d",i);*/
3653: cutv(strd,strc,strb,'V');
3654: Tvar[i]=atoi(strc);
3655: }
3656: strcpy(modelsav,stra);
3657: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
3658: scanf("%d",i);*/
3659: } /* end of loop + */
3660: } /* end model */
3661:
3662: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
3663: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
3664:
3665: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
3666: printf("cptcovprod=%d ", cptcovprod);
3667: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
3668:
3669: scanf("%d ",i);
3670: fclose(fic);*/
3671:
3672: /* if(mle==1){*/
3673: if (weightopt != 1) { /* Maximisation without weights*/
3674: for(i=1;i<=n;i++) weight[i]=1.0;
3675: }
3676: /*-calculation of age at interview from date of interview and age at death -*/
3677: agev=matrix(1,maxwav,1,imx);
3678:
3679: for (i=1; i<=imx; i++) {
3680: for(m=2; (m<= maxwav); m++) {
3681: if ((mint[m][i]== 99) && (s[m][i] <= nlstate)){
3682: anint[m][i]=9999;
3683: s[m][i]=-1;
3684: }
3685: if(moisdc[i]==99 && andc[i]==9999 & s[m][i]>nlstate) s[m][i]=-1;
3686: }
3687: }
3688:
3689: for (i=1; i<=imx; i++) {
3690: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
3691: for(m=1; (m<= maxwav); m++){
3692: if(s[m][i] >0){
3693: if (s[m][i] >= nlstate+1) {
3694: if(agedc[i]>0)
3695: if(moisdc[i]!=99 && andc[i]!=9999)
3696: agev[m][i]=agedc[i];
3697: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
3698: else {
3699: if (andc[i]!=9999){
3700: printf("Warning negative age at death: %d line:%d\n",num[i],i);
3701: fprintf(ficlog,"Warning negative age at death: %d line:%d\n",num[i],i);
3702: agev[m][i]=-1;
3703: }
3704: }
3705: }
3706: else if(s[m][i] !=9){ /* Should no more exist */
3707: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
3708: if(mint[m][i]==99 || anint[m][i]==9999)
3709: agev[m][i]=1;
3710: else if(agev[m][i] <agemin){
3711: agemin=agev[m][i];
3712: /*printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], agemin);*/
3713: }
3714: else if(agev[m][i] >agemax){
3715: agemax=agev[m][i];
3716: /* printf(" anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.0f\n",m,i,anint[m][i], i,annais[i], agemax);*/
3717: }
3718: /*agev[m][i]=anint[m][i]-annais[i];*/
3719: /* agev[m][i] = age[i]+2*m;*/
3720: }
3721: else { /* =9 */
3722: agev[m][i]=1;
3723: s[m][i]=-1;
3724: }
3725: }
3726: else /*= 0 Unknown */
3727: agev[m][i]=1;
3728: }
3729:
3730: }
3731: for (i=1; i<=imx; i++) {
3732: for(m=1; (m<= maxwav); m++){
3733: if (s[m][i] > (nlstate+ndeath)) {
3734: 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);
3735: 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);
3736: goto end;
3737: }
3738: }
3739: }
3740:
3741: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, agemin, agemax);
3742: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, agemin, agemax);
3743:
3744: free_vector(severity,1,maxwav);
3745: free_imatrix(outcome,1,maxwav+1,1,n);
3746: free_vector(moisnais,1,n);
3747: free_vector(annais,1,n);
3748: /* free_matrix(mint,1,maxwav,1,n);
3749: free_matrix(anint,1,maxwav,1,n);*/
3750: free_vector(moisdc,1,n);
3751: free_vector(andc,1,n);
3752:
3753:
3754: wav=ivector(1,imx);
3755: dh=imatrix(1,lastpass-firstpass+1,1,imx);
3756: bh=imatrix(1,lastpass-firstpass+1,1,imx);
3757: mw=imatrix(1,lastpass-firstpass+1,1,imx);
3758:
3759: /* Concatenates waves */
3760: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
3761:
3762: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
3763:
3764: Tcode=ivector(1,100);
3765: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
3766: ncodemax[1]=1;
3767: if (cptcovn > 0) tricode(Tvar,nbcode,imx);
3768:
3769: codtab=imatrix(1,100,1,10); /* Cross tabulation to get the order of
3770: the estimations*/
3771: h=0;
3772: m=pow(2,cptcoveff);
3773:
3774: for(k=1;k<=cptcoveff; k++){
3775: for(i=1; i <=(m/pow(2,k));i++){
3776: for(j=1; j <= ncodemax[k]; j++){
3777: for(cpt=1; cpt <=(m/pow(2,cptcoveff+1-k)); cpt++){
3778: h++;
3779: if (h>m) h=1;codtab[h][k]=j;codtab[h][Tvar[k]]=j;
3780: /* printf("h=%d k=%d j=%d codtab[h][k]=%d tvar[k]=%d \n",h, k,j,codtab[h][k],Tvar[k]);*/
3781: }
3782: }
3783: }
3784: }
3785: /* printf("codtab[1][2]=%d codtab[2][2]=%d",codtab[1][2],codtab[2][2]);
3786: codtab[1][2]=1;codtab[2][2]=2; */
3787: /* for(i=1; i <=m ;i++){
3788: for(k=1; k <=cptcovn; k++){
3789: printf("i=%d k=%d %d %d ",i,k,codtab[i][k], cptcoveff);
3790: }
3791: printf("\n");
3792: }
3793: scanf("%d",i);*/
3794:
3795: /* Calculates basic frequencies. Computes observed prevalence at single age
3796: and prints on file fileres'p'. */
3797:
3798: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
3799: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
3800: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
3801: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
3802: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
3803:
3804:
3805: /* For Powell, parameters are in a vector p[] starting at p[1]
3806: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
3807: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
3808:
3809: if(mle>=1){ /* Could be 1 or 2 */
3810: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
3811: }
3812:
3813: /*--------- results files --------------*/
3814: fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\nftol=%e stepm=%d ncovcol=%d nlstate=%d ndeath=%d maxwav=%d mle= 0 weight=%d\nmodel=%s\n", title, datafile, lastobs, firstpass,lastpass,ftol, stepm, ncovcol, nlstate, ndeath, maxwav, weightopt,model);
3815:
3816:
3817: jk=1;
3818: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
3819: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
3820: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
3821: for(i=1,jk=1; i <=nlstate; i++){
3822: for(k=1; k <=(nlstate+ndeath); k++){
3823: if (k != i)
3824: {
3825: printf("%d%d ",i,k);
3826: fprintf(ficlog,"%d%d ",i,k);
3827: fprintf(ficres,"%1d%1d ",i,k);
3828: for(j=1; j <=ncovmodel; j++){
3829: printf("%f ",p[jk]);
3830: fprintf(ficlog,"%f ",p[jk]);
3831: fprintf(ficres,"%f ",p[jk]);
3832: jk++;
3833: }
3834: printf("\n");
3835: fprintf(ficlog,"\n");
3836: fprintf(ficres,"\n");
3837: }
3838: }
3839: }
3840: if(mle==1){
3841: /* Computing hessian and covariance matrix */
3842: ftolhess=ftol; /* Usually correct */
3843: hesscov(matcov, p, npar, delti, ftolhess, func);
3844: }
3845: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
3846: printf("# Scales (for hessian or gradient estimation)\n");
3847: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
3848: for(i=1,jk=1; i <=nlstate; i++){
3849: for(j=1; j <=nlstate+ndeath; j++){
3850: if (j!=i) {
3851: fprintf(ficres,"%1d%1d",i,j);
3852: printf("%1d%1d",i,j);
3853: fprintf(ficlog,"%1d%1d",i,j);
3854: for(k=1; k<=ncovmodel;k++){
3855: printf(" %.5e",delti[jk]);
3856: fprintf(ficlog," %.5e",delti[jk]);
3857: fprintf(ficres," %.5e",delti[jk]);
3858: jk++;
3859: }
3860: printf("\n");
3861: fprintf(ficlog,"\n");
3862: fprintf(ficres,"\n");
3863: }
3864: }
3865: }
3866:
3867: 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");
3868: if(mle==1)
3869: 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");
3870: 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");
3871: for(i=1,k=1;i<=npar;i++){
3872: /* if (k>nlstate) k=1;
3873: i1=(i-1)/(ncovmodel*nlstate)+1;
3874: fprintf(ficres,"%s%d%d",alph[k],i1,tab[i]);
3875: printf("%s%d%d",alph[k],i1,tab[i]);
3876: */
3877: fprintf(ficres,"%3d",i);
3878: if(mle==1)
3879: printf("%3d",i);
3880: fprintf(ficlog,"%3d",i);
3881: for(j=1; j<=i;j++){
3882: fprintf(ficres," %.5e",matcov[i][j]);
3883: if(mle==1)
3884: printf(" %.5e",matcov[i][j]);
3885: fprintf(ficlog," %.5e",matcov[i][j]);
3886: }
3887: fprintf(ficres,"\n");
3888: if(mle==1)
3889: printf("\n");
3890: fprintf(ficlog,"\n");
3891: k++;
3892: }
3893:
3894: while((c=getc(ficpar))=='#' && c!= EOF){
3895: ungetc(c,ficpar);
3896: fgets(line, MAXLINE, ficpar);
3897: puts(line);
3898: fputs(line,ficparo);
3899: }
3900: ungetc(c,ficpar);
3901:
3902: estepm=0;
3903: fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm);
3904: if (estepm==0 || estepm < stepm) estepm=stepm;
3905: if (fage <= 2) {
3906: bage = ageminpar;
3907: fage = agemaxpar;
3908: }
3909:
3910: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
3911: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d\n",ageminpar,agemaxpar,bage,fage, estepm);
3912: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d\n",ageminpar,agemaxpar,bage,fage, estepm);
3913:
3914: while((c=getc(ficpar))=='#' && c!= EOF){
3915: ungetc(c,ficpar);
3916: fgets(line, MAXLINE, ficpar);
3917: puts(line);
3918: fputs(line,ficparo);
3919: }
3920: ungetc(c,ficpar);
3921:
3922: 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);
3923: 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);
3924: 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);
3925:
3926: while((c=getc(ficpar))=='#' && c!= EOF){
3927: ungetc(c,ficpar);
3928: fgets(line, MAXLINE, ficpar);
3929: puts(line);
3930: fputs(line,ficparo);
3931: }
3932: ungetc(c,ficpar);
3933:
3934:
3935: dateprev1=anprev1+mprev1/12.+jprev1/365.;
3936: dateprev2=anprev2+mprev2/12.+jprev2/365.;
3937:
3938: fscanf(ficpar,"pop_based=%d\n",&popbased);
3939: fprintf(ficparo,"pop_based=%d\n",popbased);
3940: fprintf(ficres,"pop_based=%d\n",popbased);
3941:
3942: while((c=getc(ficpar))=='#' && c!= EOF){
3943: ungetc(c,ficpar);
3944: fgets(line, MAXLINE, ficpar);
3945: puts(line);
3946: fputs(line,ficparo);
3947: }
3948: ungetc(c,ficpar);
3949:
3950: fscanf(ficpar,"starting-proj-date=%lf/%lf/%lf final-proj-date=%lf/%lf/%lf\n",&jproj1,&mproj1,&anproj1,&jproj2,&mproj2,&anproj2);
3951: fprintf(ficparo,"starting-proj-date=%.lf/%.lf/%.lf final-proj-date=%.lf/%.lf/%.lf\n",jproj1,mproj1,anproj1,jproj2,mproj2,anproj2);
3952: fprintf(ficres,"starting-proj-date=%.lf/%.lf/%.lf final-proj-date=%.lf/%.lf/%.lf\n",jproj1,mproj1,anproj1,jproj2,mproj2,anproj2);
3953:
3954:
3955: while((c=getc(ficpar))=='#' && c!= EOF){
3956: ungetc(c,ficpar);
3957: fgets(line, MAXLINE, ficpar);
3958: puts(line);
3959: fputs(line,ficparo);
3960: }
3961: ungetc(c,ficpar);
3962:
3963: fscanf(ficpar,"popforecast=%d popfile=%s popfiledate=%lf/%lf/%lf last-popfiledate=%lf/%lf/%lf\n",&popforecast,popfile,&jpyram,&mpyram,&anpyram,&jpyram1,&mpyram1,&anpyram1);
3964: fprintf(ficparo,"popforecast=%d popfile=%s popfiledate=%.lf/%.lf/%.lf last-popfiledate=%.lf/%.lf/%.lf\n",popforecast,popfile,jpyram,mpyram,anpyram,jpyram1,mpyram1,anpyram1);
3965: fprintf(ficres,"popforecast=%d popfile=%s popfiledate=%.lf/%.lf/%.lf last-popfiledate=%.lf/%.lf/%.lf\n",popforecast,popfile,jpyram,mpyram,anpyram,jpyram1,mpyram1,anpyram1);
3966:
3967: freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);
3968:
3969: /*------------ gnuplot -------------*/
3970: strcpy(optionfilegnuplot,optionfilefiname);
3971: strcat(optionfilegnuplot,".gp");
3972: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
3973: printf("Problem with file %s",optionfilegnuplot);
3974: }
3975: else{
3976: fprintf(ficgp,"\n# %s\n", version);
3977: fprintf(ficgp,"# %s\n", optionfilegnuplot);
3978: fprintf(ficgp,"set missing 'NaNq'\n");
3979: }
3980: fclose(ficgp);
3981: printinggnuplot(fileres, ageminpar,agemaxpar,fage, pathc,p);
3982: /*--------- index.htm --------*/
3983:
3984: strcpy(optionfilehtm,optionfile);
3985: strcat(optionfilehtm,".htm");
3986: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
3987: printf("Problem with %s \n",optionfilehtm), exit(0);
3988: }
3989:
3990: fprintf(fichtm,"<body> <font size=\"2\">%s </font> <hr size=\"2\" color=\"#EC5E5E\"> \n
3991: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=%s<br>\n
3992: \n
3993: Total number of observations=%d <br>\n
3994: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n
3995: <hr size=\"2\" color=\"#EC5E5E\">
3996: <ul><li><h4>Parameter files</h4>\n
3997: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n
3998: - Log file of the run: <a href=\"%s\">%s</a><br>\n
3999: - Gnuplot file name: <a href=\"%s\">%s</a></ul>\n",version,title,datafile,firstpass,lastpass,stepm, weightopt,model,imx,jmin,jmax,jmean,fileres,fileres,filelog,filelog,optionfilegnuplot,optionfilegnuplot);
4000: fclose(fichtm);
4001:
4002: printinghtml(fileres,title,datafile, firstpass, lastpass, stepm, weightopt,model,imx,jmin,jmax,jmean,rfileres,popforecast,estepm,jprev1,mprev1,anprev1,jprev2,mprev2,anprev2);
4003:
4004: /*------------ free_vector -------------*/
4005: chdir(path);
4006:
4007: free_ivector(wav,1,imx);
4008: free_imatrix(dh,1,lastpass-firstpass+1,1,imx);
4009: free_imatrix(bh,1,lastpass-firstpass+1,1,imx);
4010: free_imatrix(mw,1,lastpass-firstpass+1,1,imx);
4011: free_ivector(num,1,n);
4012: free_vector(agedc,1,n);
4013: /*free_matrix(covar,0,NCOVMAX,1,n);*/
4014: /*free_matrix(covar,1,NCOVMAX,1,n);*/
4015: fclose(ficparo);
4016: fclose(ficres);
4017:
4018:
4019: /*--------------- Prevalence limit (stable prevalence) --------------*/
4020:
4021: strcpy(filerespl,"pl");
4022: strcat(filerespl,fileres);
4023: if((ficrespl=fopen(filerespl,"w"))==NULL) {
4024: printf("Problem with stable prevalence resultfile: %s\n", filerespl);goto end;
4025: fprintf(ficlog,"Problem with stable prevalence resultfile: %s\n", filerespl);goto end;
4026: }
4027: printf("Computing stable prevalence: result on file '%s' \n", filerespl);
4028: fprintf(ficlog,"Computing stable prevalence: result on file '%s' \n", filerespl);
4029: fprintf(ficrespl,"#Stable prevalence \n");
4030: fprintf(ficrespl,"#Age ");
4031: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
4032: fprintf(ficrespl,"\n");
4033:
4034: prlim=matrix(1,nlstate,1,nlstate);
4035:
4036: agebase=ageminpar;
4037: agelim=agemaxpar;
4038: ftolpl=1.e-10;
4039: i1=cptcoveff;
4040: if (cptcovn < 1){i1=1;}
4041:
4042: for(cptcov=1,k=0;cptcov<=i1;cptcov++){
4043: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
4044: k=k+1;
4045: /*printf("cptcov=%d cptcod=%d codtab=%d nbcode=%d\n",cptcov, cptcod,Tcode[cptcode],codtab[cptcod][cptcov]);*/
4046: fprintf(ficrespl,"\n#******");
4047: printf("\n#******");
4048: fprintf(ficlog,"\n#******");
4049: for(j=1;j<=cptcoveff;j++) {
4050: fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtab[k][j]]);
4051: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtab[k][j]]);
4052: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtab[k][j]]);
4053: }
4054: fprintf(ficrespl,"******\n");
4055: printf("******\n");
4056: fprintf(ficlog,"******\n");
4057:
4058: for (age=agebase; age<=agelim; age++){
4059: prevalim(prlim, nlstate, p, age, oldm, savm,ftolpl,k);
4060: fprintf(ficrespl,"%.0f",age );
4061: for(i=1; i<=nlstate;i++)
4062: fprintf(ficrespl," %.5f", prlim[i][i]);
4063: fprintf(ficrespl,"\n");
4064: }
4065: }
4066: }
4067: fclose(ficrespl);
4068:
4069: /*------------- h Pij x at various ages ------------*/
4070:
4071: strcpy(filerespij,"pij"); strcat(filerespij,fileres);
4072: if((ficrespij=fopen(filerespij,"w"))==NULL) {
4073: printf("Problem with Pij resultfile: %s\n", filerespij);goto end;
4074: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij);goto end;
4075: }
4076: printf("Computing pij: result on file '%s' \n", filerespij);
4077: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
4078:
4079: stepsize=(int) (stepm+YEARM-1)/YEARM;
4080: /*if (stepm<=24) stepsize=2;*/
4081:
4082: agelim=AGESUP;
4083: hstepm=stepsize*YEARM; /* Every year of age */
4084: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
4085:
4086: /* hstepm=1; aff par mois*/
4087:
4088: for(cptcov=1,k=0;cptcov<=i1;cptcov++){
4089: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
4090: k=k+1;
4091: fprintf(ficrespij,"\n#****** ");
4092: for(j=1;j<=cptcoveff;j++)
4093: fprintf(ficrespij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtab[k][j]]);
4094: fprintf(ficrespij,"******\n");
4095:
4096: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
4097: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
4098: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
4099:
4100: /* nhstepm=nhstepm*YEARM; aff par mois*/
4101:
4102: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
4103: oldm=oldms;savm=savms;
4104: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k);
4105: fprintf(ficrespij,"# Age");
4106: for(i=1; i<=nlstate;i++)
4107: for(j=1; j<=nlstate+ndeath;j++)
4108: fprintf(ficrespij," %1d-%1d",i,j);
4109: fprintf(ficrespij,"\n");
4110: for (h=0; h<=nhstepm; h++){
4111: fprintf(ficrespij,"%d %f %f",k,agedeb, agedeb+ h*hstepm/YEARM*stepm );
4112: for(i=1; i<=nlstate;i++)
4113: for(j=1; j<=nlstate+ndeath;j++)
4114: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
4115: fprintf(ficrespij,"\n");
4116: }
4117: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
4118: fprintf(ficrespij,"\n");
4119: }
4120: }
4121: }
4122:
4123: varprob(optionfilefiname, matcov, p, delti, nlstate, (int) bage, (int) fage,k,Tvar,nbcode, ncodemax);
4124:
4125: fclose(ficrespij);
4126:
4127:
4128: /*---------- Forecasting ------------------*/
4129: if((stepm == 1) && (strcmp(model,".")==0)){
4130: prevforecast(fileres, anproj1,mproj1,jproj1, agemin,agemax, dateprev1, dateprev2,mobilav, agedeb, fage, popforecast, popfile, anproj2,p, i1);
4131: if (popforecast==1) populforecast(fileres, anpyram,mpyram,jpyram, agemin,agemax, dateprev1, dateprev2,mobilav, agedeb, fage, popforecast, popfile, anpyram1,p, i1);
4132: }
4133: else{
4134: erreur=108;
4135: printf("Warning %d!! You can only forecast the prevalences if the optimization\n has been performed with stepm = 1 (month) instead of %d or model=. instead of '%s'\n", erreur, stepm, model);
4136: fprintf(ficlog,"Warning %d!! You can only forecast the prevalences if the optimization\n has been performed with stepm = 1 (month) instead of %d or model=. instead of '%s'\n", erreur, stepm, model);
4137: }
4138:
4139:
4140: /*---------- Health expectancies and variances ------------*/
4141:
4142: strcpy(filerest,"t");
4143: strcat(filerest,fileres);
4144: if((ficrest=fopen(filerest,"w"))==NULL) {
4145: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
4146: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
4147: }
4148: printf("Computing Total LEs with variances: file '%s' \n", filerest);
4149: fprintf(ficlog,"Computing Total LEs with variances: file '%s' \n", filerest);
4150:
4151:
4152: strcpy(filerese,"e");
4153: strcat(filerese,fileres);
4154: if((ficreseij=fopen(filerese,"w"))==NULL) {
4155: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
4156: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
4157: }
4158: printf("Computing Health Expectancies: result on file '%s' \n", filerese);
4159: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' \n", filerese);
4160:
4161: strcpy(fileresv,"v");
4162: strcat(fileresv,fileres);
4163: if((ficresvij=fopen(fileresv,"w"))==NULL) {
4164: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
4165: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
4166: }
4167: printf("Computing Variance-covariance of DFLEs: file '%s' \n", fileresv);
4168: fprintf(ficlog,"Computing Variance-covariance of DFLEs: file '%s' \n", fileresv);
4169:
4170: calagedate=-1;
4171:
4172: prevalence(ageminpar, agemax, s, agev, nlstate, imx,Tvar,nbcode, ncodemax,mint,anint,dateprev1,dateprev2, calagedate);
4173:
4174: if (mobilav!=0) {
4175: mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX);
4176: if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){
4177: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
4178: printf(" Error in movingaverage mobilav=%d\n",mobilav);
4179: }
4180: }
4181:
4182: for(cptcov=1,k=0;cptcov<=i1;cptcov++){
4183: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
4184: k=k+1;
4185: fprintf(ficrest,"\n#****** ");
4186: for(j=1;j<=cptcoveff;j++)
4187: fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtab[k][j]]);
4188: fprintf(ficrest,"******\n");
4189:
4190: fprintf(ficreseij,"\n#****** ");
4191: for(j=1;j<=cptcoveff;j++)
4192: fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtab[k][j]]);
4193: fprintf(ficreseij,"******\n");
4194:
4195: fprintf(ficresvij,"\n#****** ");
4196: for(j=1;j<=cptcoveff;j++)
4197: fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtab[k][j]]);
4198: fprintf(ficresvij,"******\n");
4199:
4200: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
4201: oldm=oldms;savm=savms;
4202: evsij(fileres, eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov);
4203:
4204: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
4205: oldm=oldms;savm=savms;
4206: varevsij(optionfilefiname, vareij, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl,k, estepm, cptcov,cptcod,0, mobilav);
4207: if(popbased==1){
4208: varevsij(optionfilefiname, vareij, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl,k, estepm, cptcov,cptcod,popbased,mobilav);
4209: }
4210:
4211:
4212: fprintf(ficrest,"#Total LEs with variances: e.. (std) ");
4213: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
4214: fprintf(ficrest,"\n");
4215:
4216: epj=vector(1,nlstate+1);
4217: for(age=bage; age <=fage ;age++){
4218: prevalim(prlim, nlstate, p, age, oldm, savm,ftolpl,k);
4219: if (popbased==1) {
4220: if(mobilav ==0){
4221: for(i=1; i<=nlstate;i++)
4222: prlim[i][i]=probs[(int)age][i][k];
4223: }else{ /* mobilav */
4224: for(i=1; i<=nlstate;i++)
4225: prlim[i][i]=mobaverage[(int)age][i][k];
4226: }
4227: }
4228:
4229: fprintf(ficrest," %4.0f",age);
4230: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
4231: for(i=1, epj[j]=0.;i <=nlstate;i++) {
4232: epj[j] += prlim[i][i]*eij[i][j][(int)age];
4233: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
4234: }
4235: epj[nlstate+1] +=epj[j];
4236: }
4237:
4238: for(i=1, vepp=0.;i <=nlstate;i++)
4239: for(j=1;j <=nlstate;j++)
4240: vepp += vareij[i][j][(int)age];
4241: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
4242: for(j=1;j <=nlstate;j++){
4243: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
4244: }
4245: fprintf(ficrest,"\n");
4246: }
4247: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
4248: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
4249: free_vector(epj,1,nlstate+1);
4250: }
4251: }
4252: free_vector(weight,1,n);
4253: free_imatrix(Tvard,1,15,1,2);
4254: free_imatrix(s,1,maxwav+1,1,n);
4255: free_matrix(anint,1,maxwav,1,n);
4256: free_matrix(mint,1,maxwav,1,n);
4257: free_ivector(cod,1,n);
4258: free_ivector(tab,1,NCOVMAX);
4259: fclose(ficreseij);
4260: fclose(ficresvij);
4261: fclose(ficrest);
4262: fclose(ficpar);
4263:
4264: /*------- Variance of stable prevalence------*/
4265:
4266: strcpy(fileresvpl,"vpl");
4267: strcat(fileresvpl,fileres);
4268: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
4269: printf("Problem with variance of stable prevalence resultfile: %s\n", fileresvpl);
4270: exit(0);
4271: }
4272: printf("Computing Variance-covariance of stable prevalence: file '%s' \n", fileresvpl);
4273:
4274: for(cptcov=1,k=0;cptcov<=i1;cptcov++){
4275: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
4276: k=k+1;
4277: fprintf(ficresvpl,"\n#****** ");
4278: for(j=1;j<=cptcoveff;j++)
4279: fprintf(ficresvpl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtab[k][j]]);
4280: fprintf(ficresvpl,"******\n");
4281:
4282: varpl=matrix(1,nlstate,(int) bage, (int) fage);
4283: oldm=oldms;savm=savms;
4284: varprevlim(fileres, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl,k);
4285: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
4286: }
4287: }
4288:
4289: fclose(ficresvpl);
4290:
4291: /*---------- End : free ----------------*/
4292: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
4293: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
4294: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
4295: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
4296:
4297: free_matrix(covar,0,NCOVMAX,1,n);
4298: free_matrix(matcov,1,npar,1,npar);
4299: free_vector(delti,1,npar);
4300: free_matrix(agev,1,maxwav,1,imx);
4301: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
4302: if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX);
4303: free_ivector(ncodemax,1,8);
4304: free_ivector(Tvar,1,15);
4305: free_ivector(Tprod,1,15);
4306: free_ivector(Tvaraff,1,15);
4307: free_ivector(Tage,1,15);
4308: free_ivector(Tcode,1,100);
4309:
4310: fprintf(fichtm,"\n</body>");
4311: fclose(fichtm);
4312: fclose(ficgp);
4313:
4314:
4315: if(erreur >0){
4316: printf("End of Imach with error or warning %d\n",erreur);
4317: fprintf(ficlog,"End of Imach with error or warning %d\n",erreur);
4318: }else{
4319: printf("End of Imach\n");
4320: fprintf(ficlog,"End of Imach\n");
4321: }
4322: printf("See log file on %s\n",filelog);
4323: fclose(ficlog);
4324: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
4325:
4326: /* printf("Total time was %d Sec. %d uSec.\n", end_time.tv_sec -start_time.tv_sec, end_time.tv_usec -start_time.tv_usec);*/
4327: /*printf("Total time was %d uSec.\n", total_usecs);*/
4328: /*------ End -----------*/
4329:
4330: end:
4331: #ifdef windows
4332: /* chdir(pathcd);*/
4333: #endif
4334: /*system("wgnuplot graph.plt");*/
4335: /*system("../gp37mgw/wgnuplot graph.plt");*/
4336: /*system("cd ../gp37mgw");*/
4337: /* system("..\\gp37mgw\\wgnuplot graph.plt");*/
4338: strcpy(plotcmd,GNUPLOTPROGRAM);
4339: strcat(plotcmd," ");
4340: strcat(plotcmd,optionfilegnuplot);
4341: printf("Starting: %s\n",plotcmd);fflush(stdout);
4342: system(plotcmd);
4343:
4344: /*#ifdef windows*/
4345: while (z[0] != 'q') {
4346: /* chdir(path); */
4347: printf("\nType e to edit output files, g to graph again, c to start again, and q for exiting: ");
4348: scanf("%s",z);
4349: if (z[0] == 'c') system("./imach");
4350: else if (z[0] == 'e') system(optionfilehtm);
4351: else if (z[0] == 'g') system(plotcmd);
4352: else if (z[0] == 'q') exit(0);
4353: }
4354: /*#endif */
4355: }
4356:
4357:
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