1: /* $Id: imach.c,v 1.73 2003/04/08 14:06:50 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, quarter,
36: semester or year) is modelled 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 0.94, February 2003, 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
860: 'nhstepm*hstepm*stepm' months (i.e. until
861: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
862: nhstepm*hstepm matrices.
863: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
864: (typically every 2 years instead of every month which is too big
865: for the memory).
866: Model is determined by parameters x and covariates have to be
867: included manually here.
868:
869: */
870:
871: int i, j, d, h, k;
872: double **out, cov[NCOVMAX];
873: double **newm;
874:
875: /* Hstepm could be zero and should return the unit matrix */
876: for (i=1;i<=nlstate+ndeath;i++)
877: for (j=1;j<=nlstate+ndeath;j++){
878: oldm[i][j]=(i==j ? 1.0 : 0.0);
879: po[i][j][0]=(i==j ? 1.0 : 0.0);
880: }
881: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
882: for(h=1; h <=nhstepm; h++){
883: for(d=1; d <=hstepm; d++){
884: newm=savm;
885: /* Covariates have to be included here again */
886: cov[1]=1.;
887: cov[2]=age+((h-1)*hstepm + (d-1))*stepm/YEARM;
888: for (k=1; k<=cptcovn;k++) cov[2+k]=nbcode[Tvar[k]][codtab[ij][Tvar[k]]];
889: for (k=1; k<=cptcovage;k++)
890: cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2];
891: for (k=1; k<=cptcovprod;k++)
892: cov[2+Tprod[k]]=nbcode[Tvard[k][1]][codtab[ij][Tvard[k][1]]]*nbcode[Tvard[k][2]][codtab[ij][Tvard[k][2]]];
893:
894:
895: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
896: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
897: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
898: pmij(pmmij,cov,ncovmodel,x,nlstate));
899: savm=oldm;
900: oldm=newm;
901: }
902: for(i=1; i<=nlstate+ndeath; i++)
903: for(j=1;j<=nlstate+ndeath;j++) {
904: po[i][j][h]=newm[i][j];
905: /*printf("i=%d j=%d h=%d po[i][j][h]=%f ",i,j,h,po[i][j][h]);
906: */
907: }
908: } /* end h */
909: return po;
910: }
911:
912:
913: /*************** log-likelihood *************/
914: double func( double *x)
915: {
916: int i, ii, j, k, mi, d, kk;
917: double l, ll[NLSTATEMAX], cov[NCOVMAX];
918: double **out;
919: double sw; /* Sum of weights */
920: double lli; /* Individual log likelihood */
921: int s1, s2;
922: double bbh, survp;
923: long ipmx;
924: /*extern weight */
925: /* We are differentiating ll according to initial status */
926: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
927: /*for(i=1;i<imx;i++)
928: printf(" %d\n",s[4][i]);
929: */
930: cov[1]=1.;
931:
932: for(k=1; k<=nlstate; k++) ll[k]=0.;
933:
934: if(mle==1){
935: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
936: for (k=1; k<=cptcovn;k++) cov[2+k]=covar[Tvar[k]][i];
937: for(mi=1; mi<= wav[i]-1; mi++){
938: for (ii=1;ii<=nlstate+ndeath;ii++)
939: for (j=1;j<=nlstate+ndeath;j++){
940: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
941: savm[ii][j]=(ii==j ? 1.0 : 0.0);
942: }
943: for(d=0; d<dh[mi][i]; d++){
944: newm=savm;
945: cov[2]=agev[mw[mi][i]][i]+d*stepm/YEARM;
946: for (kk=1; kk<=cptcovage;kk++) {
947: cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
948: }
949: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
950: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
951: savm=oldm;
952: oldm=newm;
953: } /* end mult */
954:
955: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
956: /* But now since version 0.9 we anticipate for bias and large stepm.
957: * If stepm is larger than one month (smallest stepm) and if the exact delay
958: * (in months) between two waves is not a multiple of stepm, we rounded to
959: * the nearest (and in case of equal distance, to the lowest) interval but now
960: * we keep into memory the bias bh[mi][i] and also the previous matrix product
961: * (i.e to dh[mi][i]-1) saved in 'savm'. The we inter(extra)polate the
962: * probability in order to take into account the bias as a fraction of the way
963: * from savm to out if bh is neagtive or even beyond if bh is positive. bh varies
964: * -stepm/2 to stepm/2 .
965: * For stepm=1 the results are the same as for previous versions of Imach.
966: * For stepm > 1 the results are less biased than in previous versions.
967: */
968: s1=s[mw[mi][i]][i];
969: s2=s[mw[mi+1][i]][i];
970: bbh=(double)bh[mi][i]/(double)stepm;
971: /* bias is positive if real duration
972: * is higher than the multiple of stepm and negative otherwise.
973: */
974: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
975: if( s2 > nlstate){
976: /* i.e. if s2 is a death state and if the date of death is known then the contribution
977: to the likelihood is the probability to die between last step unit time and current
978: step unit time, which is also the differences between probability to die before dh
979: and probability to die before dh-stepm .
980: In version up to 0.92 likelihood was computed
981: as if date of death was unknown. Death was treated as any other
982: health state: the date of the interview describes the actual state
983: and not the date of a change in health state. The former idea was
984: to consider that at each interview the state was recorded
985: (healthy, disable or death) and IMaCh was corrected; but when we
986: introduced the exact date of death then we should have modified
987: the contribution of an exact death to the likelihood. This new
988: contribution is smaller and very dependent of the step unit
989: stepm. It is no more the probability to die between last interview
990: and month of death but the probability to survive from last
991: interview up to one month before death multiplied by the
992: probability to die within a month. Thanks to Chris
993: Jackson for correcting this bug. Former versions increased
994: mortality artificially. The bad side is that we add another loop
995: which slows down the processing. The difference can be up to 10%
996: lower mortality.
997: */
998: lli=log(out[s1][s2] - savm[s1][s2]);
999: }else{
1000: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1001: /* 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 */
1002: }
1003: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
1004: /*if(lli ==000.0)*/
1005: /*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); */
1006: ipmx +=1;
1007: sw += weight[i];
1008: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1009: } /* end of wave */
1010: } /* end of individual */
1011: } else if(mle==2){
1012: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1013: for (k=1; k<=cptcovn;k++) cov[2+k]=covar[Tvar[k]][i];
1014: for(mi=1; mi<= wav[i]-1; mi++){
1015: for (ii=1;ii<=nlstate+ndeath;ii++)
1016: for (j=1;j<=nlstate+ndeath;j++){
1017: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
1018: savm[ii][j]=(ii==j ? 1.0 : 0.0);
1019: }
1020: for(d=0; d<=dh[mi][i]; d++){
1021: newm=savm;
1022: cov[2]=agev[mw[mi][i]][i]+d*stepm/YEARM;
1023: for (kk=1; kk<=cptcovage;kk++) {
1024: cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
1025: }
1026: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
1027: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
1028: savm=oldm;
1029: oldm=newm;
1030: } /* end mult */
1031:
1032: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
1033: /* But now since version 0.9 we anticipate for bias and large stepm.
1034: * If stepm is larger than one month (smallest stepm) and if the exact delay
1035: * (in months) between two waves is not a multiple of stepm, we rounded to
1036: * the nearest (and in case of equal distance, to the lowest) interval but now
1037: * we keep into memory the bias bh[mi][i] and also the previous matrix product
1038: * (i.e to dh[mi][i]-1) saved in 'savm'. The we inter(extra)polate the
1039: * probability in order to take into account the bias as a fraction of the way
1040: * from savm to out if bh is neagtive or even beyond if bh is positive. bh varies
1041: * -stepm/2 to stepm/2 .
1042: * For stepm=1 the results are the same as for previous versions of Imach.
1043: * For stepm > 1 the results are less biased than in previous versions.
1044: */
1045: s1=s[mw[mi][i]][i];
1046: s2=s[mw[mi+1][i]][i];
1047: bbh=(double)bh[mi][i]/(double)stepm;
1048: /* bias is positive if real duration
1049: * is higher than the multiple of stepm and negative otherwise.
1050: */
1051: 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 */
1052: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
1053: /*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 */
1054: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
1055: /*if(lli ==000.0)*/
1056: /*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); */
1057: ipmx +=1;
1058: sw += weight[i];
1059: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1060: } /* end of wave */
1061: } /* end of individual */
1062: } else if(mle==3){ /* exponential inter-extrapolation */
1063: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1064: for (k=1; k<=cptcovn;k++) cov[2+k]=covar[Tvar[k]][i];
1065: for(mi=1; mi<= wav[i]-1; mi++){
1066: for (ii=1;ii<=nlstate+ndeath;ii++)
1067: for (j=1;j<=nlstate+ndeath;j++){
1068: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
1069: savm[ii][j]=(ii==j ? 1.0 : 0.0);
1070: }
1071: for(d=0; d<dh[mi][i]; d++){
1072: newm=savm;
1073: cov[2]=agev[mw[mi][i]][i]+d*stepm/YEARM;
1074: for (kk=1; kk<=cptcovage;kk++) {
1075: cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
1076: }
1077: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
1078: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
1079: savm=oldm;
1080: oldm=newm;
1081: } /* end mult */
1082:
1083: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
1084: /* But now since version 0.9 we anticipate for bias and large stepm.
1085: * If stepm is larger than one month (smallest stepm) and if the exact delay
1086: * (in months) between two waves is not a multiple of stepm, we rounded to
1087: * the nearest (and in case of equal distance, to the lowest) interval but now
1088: * we keep into memory the bias bh[mi][i] and also the previous matrix product
1089: * (i.e to dh[mi][i]-1) saved in 'savm'. The we inter(extra)polate the
1090: * probability in order to take into account the bias as a fraction of the way
1091: * from savm to out if bh is neagtive or even beyond if bh is positive. bh varies
1092: * -stepm/2 to stepm/2 .
1093: * For stepm=1 the results are the same as for previous versions of Imach.
1094: * For stepm > 1 the results are less biased than in previous versions.
1095: */
1096: s1=s[mw[mi][i]][i];
1097: s2=s[mw[mi+1][i]][i];
1098: bbh=(double)bh[mi][i]/(double)stepm;
1099: /* bias is positive if real duration
1100: * is higher than the multiple of stepm and negative otherwise.
1101: */
1102: /* 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 */
1103: 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 */
1104: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
1105: /*if(lli ==000.0)*/
1106: /*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); */
1107: ipmx +=1;
1108: sw += weight[i];
1109: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1110: } /* end of wave */
1111: } /* end of individual */
1112: }else{ /* ml=4 no inter-extrapolation */
1113: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1114: for (k=1; k<=cptcovn;k++) cov[2+k]=covar[Tvar[k]][i];
1115: for(mi=1; mi<= wav[i]-1; mi++){
1116: for (ii=1;ii<=nlstate+ndeath;ii++)
1117: for (j=1;j<=nlstate+ndeath;j++){
1118: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
1119: savm[ii][j]=(ii==j ? 1.0 : 0.0);
1120: }
1121: for(d=0; d<dh[mi][i]; d++){
1122: newm=savm;
1123: cov[2]=agev[mw[mi][i]][i]+d*stepm/YEARM;
1124: for (kk=1; kk<=cptcovage;kk++) {
1125: cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
1126: }
1127:
1128: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
1129: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
1130: savm=oldm;
1131: oldm=newm;
1132: } /* end mult */
1133:
1134: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
1135: ipmx +=1;
1136: sw += weight[i];
1137: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1138: } /* end of wave */
1139: } /* end of individual */
1140: } /* End of if */
1141: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
1142: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
1143: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
1144: return -l;
1145: }
1146:
1147:
1148: /*********** Maximum Likelihood Estimation ***************/
1149:
1150: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
1151: {
1152: int i,j, iter;
1153: double **xi,*delti;
1154: double fret;
1155: xi=matrix(1,npar,1,npar);
1156: for (i=1;i<=npar;i++)
1157: for (j=1;j<=npar;j++)
1158: xi[i][j]=(i==j ? 1.0 : 0.0);
1159: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1160: powell(p,xi,npar,ftol,&iter,&fret,func);
1161:
1162: printf("\n#Number of iterations = %d, -2 Log likelihood = %.12f\n",iter,func(p));
1163: fprintf(ficlog,"\n#Number of iterations = %d, -2 Log likelihood = %.12f \n",iter,func(p));
1164: fprintf(ficres,"#Number of iterations = %d, -2 Log likelihood = %.12f \n",iter,func(p));
1165:
1166: }
1167:
1168: /**** Computes Hessian and covariance matrix ***/
1169: void hesscov(double **matcov, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1170: {
1171: double **a,**y,*x,pd;
1172: double **hess;
1173: int i, j,jk;
1174: int *indx;
1175:
1176: double hessii(double p[], double delta, int theta, double delti[]);
1177: double hessij(double p[], double delti[], int i, int j);
1178: void lubksb(double **a, int npar, int *indx, double b[]) ;
1179: void ludcmp(double **a, int npar, int *indx, double *d) ;
1180:
1181: hess=matrix(1,npar,1,npar);
1182:
1183: printf("\nCalculation of the hessian matrix. Wait...\n");
1184: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
1185: for (i=1;i<=npar;i++){
1186: printf("%d",i);fflush(stdout);
1187: fprintf(ficlog,"%d",i);fflush(ficlog);
1188: hess[i][i]=hessii(p,ftolhess,i,delti);
1189: /*printf(" %f ",p[i]);*/
1190: /*printf(" %lf ",hess[i][i]);*/
1191: }
1192:
1193: for (i=1;i<=npar;i++) {
1194: for (j=1;j<=npar;j++) {
1195: if (j>i) {
1196: printf(".%d%d",i,j);fflush(stdout);
1197: fprintf(ficlog,".%d%d",i,j);fflush(ficlog);
1198: hess[i][j]=hessij(p,delti,i,j);
1199: hess[j][i]=hess[i][j];
1200: /*printf(" %lf ",hess[i][j]);*/
1201: }
1202: }
1203: }
1204: printf("\n");
1205: fprintf(ficlog,"\n");
1206:
1207: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
1208: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
1209:
1210: a=matrix(1,npar,1,npar);
1211: y=matrix(1,npar,1,npar);
1212: x=vector(1,npar);
1213: indx=ivector(1,npar);
1214: for (i=1;i<=npar;i++)
1215: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
1216: ludcmp(a,npar,indx,&pd);
1217:
1218: for (j=1;j<=npar;j++) {
1219: for (i=1;i<=npar;i++) x[i]=0;
1220: x[j]=1;
1221: lubksb(a,npar,indx,x);
1222: for (i=1;i<=npar;i++){
1223: matcov[i][j]=x[i];
1224: }
1225: }
1226:
1227: printf("\n#Hessian matrix#\n");
1228: fprintf(ficlog,"\n#Hessian matrix#\n");
1229: for (i=1;i<=npar;i++) {
1230: for (j=1;j<=npar;j++) {
1231: printf("%.3e ",hess[i][j]);
1232: fprintf(ficlog,"%.3e ",hess[i][j]);
1233: }
1234: printf("\n");
1235: fprintf(ficlog,"\n");
1236: }
1237:
1238: /* Recompute Inverse */
1239: for (i=1;i<=npar;i++)
1240: for (j=1;j<=npar;j++) a[i][j]=matcov[i][j];
1241: ludcmp(a,npar,indx,&pd);
1242:
1243: /* printf("\n#Hessian matrix recomputed#\n");
1244:
1245: for (j=1;j<=npar;j++) {
1246: for (i=1;i<=npar;i++) x[i]=0;
1247: x[j]=1;
1248: lubksb(a,npar,indx,x);
1249: for (i=1;i<=npar;i++){
1250: y[i][j]=x[i];
1251: printf("%.3e ",y[i][j]);
1252: fprintf(ficlog,"%.3e ",y[i][j]);
1253: }
1254: printf("\n");
1255: fprintf(ficlog,"\n");
1256: }
1257: */
1258:
1259: free_matrix(a,1,npar,1,npar);
1260: free_matrix(y,1,npar,1,npar);
1261: free_vector(x,1,npar);
1262: free_ivector(indx,1,npar);
1263: free_matrix(hess,1,npar,1,npar);
1264:
1265:
1266: }
1267:
1268: /*************** hessian matrix ****************/
1269: double hessii( double x[], double delta, int theta, double delti[])
1270: {
1271: int i;
1272: int l=1, lmax=20;
1273: double k1,k2;
1274: double p2[NPARMAX+1];
1275: double res;
1276: double delt, delts, nkhi=10.,nkhif=1., khi=1.e-4;
1277: double fx;
1278: int k=0,kmax=10;
1279: double l1;
1280:
1281: fx=func(x);
1282: for (i=1;i<=npar;i++) p2[i]=x[i];
1283: for(l=0 ; l <=lmax; l++){
1284: l1=pow(10,l);
1285: delts=delt;
1286: for(k=1 ; k <kmax; k=k+1){
1287: delt = delta*(l1*k);
1288: p2[theta]=x[theta] +delt;
1289: k1=func(p2)-fx;
1290: p2[theta]=x[theta]-delt;
1291: k2=func(p2)-fx;
1292: /*res= (k1-2.0*fx+k2)/delt/delt; */
1293: res= (k1+k2)/delt/delt/2.; /* Divided by because L and not 2*L */
1294:
1295: #ifdef DEBUG
1296: 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);
1297: 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);
1298: #endif
1299: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
1300: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
1301: k=kmax;
1302: }
1303: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1304: k=kmax; l=lmax*10.;
1305: }
1306: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
1307: delts=delt;
1308: }
1309: }
1310: }
1311: delti[theta]=delts;
1312: return res;
1313:
1314: }
1315:
1316: double hessij( double x[], double delti[], int thetai,int thetaj)
1317: {
1318: int i;
1319: int l=1, l1, lmax=20;
1320: double k1,k2,k3,k4,res,fx;
1321: double p2[NPARMAX+1];
1322: int k;
1323:
1324: fx=func(x);
1325: for (k=1; k<=2; k++) {
1326: for (i=1;i<=npar;i++) p2[i]=x[i];
1327: p2[thetai]=x[thetai]+delti[thetai]/k;
1328: p2[thetaj]=x[thetaj]+delti[thetaj]/k;
1329: k1=func(p2)-fx;
1330:
1331: p2[thetai]=x[thetai]+delti[thetai]/k;
1332: p2[thetaj]=x[thetaj]-delti[thetaj]/k;
1333: k2=func(p2)-fx;
1334:
1335: p2[thetai]=x[thetai]-delti[thetai]/k;
1336: p2[thetaj]=x[thetaj]+delti[thetaj]/k;
1337: k3=func(p2)-fx;
1338:
1339: p2[thetai]=x[thetai]-delti[thetai]/k;
1340: p2[thetaj]=x[thetaj]-delti[thetaj]/k;
1341: k4=func(p2)-fx;
1342: res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /* Because of L not 2*L */
1343: #ifdef DEBUG
1344: 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);
1345: 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);
1346: #endif
1347: }
1348: return res;
1349: }
1350:
1351: /************** Inverse of matrix **************/
1352: void ludcmp(double **a, int n, int *indx, double *d)
1353: {
1354: int i,imax,j,k;
1355: double big,dum,sum,temp;
1356: double *vv;
1357:
1358: vv=vector(1,n);
1359: *d=1.0;
1360: for (i=1;i<=n;i++) {
1361: big=0.0;
1362: for (j=1;j<=n;j++)
1363: if ((temp=fabs(a[i][j])) > big) big=temp;
1364: if (big == 0.0) nrerror("Singular matrix in routine ludcmp");
1365: vv[i]=1.0/big;
1366: }
1367: for (j=1;j<=n;j++) {
1368: for (i=1;i<j;i++) {
1369: sum=a[i][j];
1370: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
1371: a[i][j]=sum;
1372: }
1373: big=0.0;
1374: for (i=j;i<=n;i++) {
1375: sum=a[i][j];
1376: for (k=1;k<j;k++)
1377: sum -= a[i][k]*a[k][j];
1378: a[i][j]=sum;
1379: if ( (dum=vv[i]*fabs(sum)) >= big) {
1380: big=dum;
1381: imax=i;
1382: }
1383: }
1384: if (j != imax) {
1385: for (k=1;k<=n;k++) {
1386: dum=a[imax][k];
1387: a[imax][k]=a[j][k];
1388: a[j][k]=dum;
1389: }
1390: *d = -(*d);
1391: vv[imax]=vv[j];
1392: }
1393: indx[j]=imax;
1394: if (a[j][j] == 0.0) a[j][j]=TINY;
1395: if (j != n) {
1396: dum=1.0/(a[j][j]);
1397: for (i=j+1;i<=n;i++) a[i][j] *= dum;
1398: }
1399: }
1400: free_vector(vv,1,n); /* Doesn't work */
1401: ;
1402: }
1403:
1404: void lubksb(double **a, int n, int *indx, double b[])
1405: {
1406: int i,ii=0,ip,j;
1407: double sum;
1408:
1409: for (i=1;i<=n;i++) {
1410: ip=indx[i];
1411: sum=b[ip];
1412: b[ip]=b[i];
1413: if (ii)
1414: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
1415: else if (sum) ii=i;
1416: b[i]=sum;
1417: }
1418: for (i=n;i>=1;i--) {
1419: sum=b[i];
1420: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
1421: b[i]=sum/a[i][i];
1422: }
1423: }
1424:
1425: /************ Frequencies ********************/
1426: 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)
1427: { /* Some frequencies */
1428:
1429: int i, m, jk, k1,i1, j1, bool, z1,z2,j;
1430: int first;
1431: double ***freq; /* Frequencies */
1432: double *pp, **prop;
1433: double pos,posprop, k2, dateintsum=0,k2cpt=0;
1434: FILE *ficresp;
1435: char fileresp[FILENAMELENGTH];
1436:
1437: pp=vector(1,nlstate);
1438: prop=matrix(1,nlstate,agemin,agemax+3);
1439: probs= ma3x(1,AGESUP,1,NCOVMAX, 1,NCOVMAX);
1440: strcpy(fileresp,"p");
1441: strcat(fileresp,fileres);
1442: if((ficresp=fopen(fileresp,"w"))==NULL) {
1443: printf("Problem with prevalence resultfile: %s\n", fileresp);
1444: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
1445: exit(0);
1446: }
1447: freq= ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,agemin,agemax+3);
1448: j1=0;
1449:
1450: j=cptcoveff;
1451: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1452:
1453: first=1;
1454:
1455: for(k1=1; k1<=j;k1++){
1456: for(i1=1; i1<=ncodemax[k1];i1++){
1457: j1++;
1458: /*printf("cptcoveff=%d Tvaraff=%d", cptcoveff,Tvaraff[1]);
1459: scanf("%d", i);*/
1460: for (i=-1; i<=nlstate+ndeath; i++)
1461: for (jk=-1; jk<=nlstate+ndeath; jk++)
1462: for(m=agemin; m <= agemax+3; m++)
1463: freq[i][jk][m]=0;
1464:
1465: for (i=1; i<=nlstate; i++)
1466: for(m=agemin; m <= agemax+3; m++)
1467: prop[i][m]=0;
1468:
1469: dateintsum=0;
1470: k2cpt=0;
1471: for (i=1; i<=imx; i++) {
1472: bool=1;
1473: if (cptcovn>0) {
1474: for (z1=1; z1<=cptcoveff; z1++)
1475: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtab[j1][z1]])
1476: bool=0;
1477: }
1478: if (bool==1){
1479: for(m=firstpass; m<=lastpass; m++){
1480: k2=anint[m][i]+(mint[m][i]/12.);
1481: if ((k2>=dateprev1) && (k2<=dateprev2)) {
1482: if(agev[m][i]==0) agev[m][i]=agemax+1;
1483: if(agev[m][i]==1) agev[m][i]=agemax+2;
1484: if (s[m][i]>0 && s[m][i]<=nlstate) prop[s[m][i]][(int)agev[m][i]] += weight[i];
1485: if (m<lastpass) {
1486: freq[s[m][i]][s[m+1][i]][(int)agev[m][i]] += weight[i];
1487: freq[s[m][i]][s[m+1][i]][(int) agemax+3] += weight[i];
1488: }
1489:
1490: if ((agev[m][i]>1) && (agev[m][i]< (agemax+3))) {
1491: dateintsum=dateintsum+k2;
1492: k2cpt++;
1493: }
1494: }
1495: }
1496: }
1497: }
1498:
1499: fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);
1500:
1501: if (cptcovn>0) {
1502: fprintf(ficresp, "\n#********** Variable ");
1503: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtab[j1][z1]]);
1504: fprintf(ficresp, "**********\n#");
1505: }
1506: for(i=1; i<=nlstate;i++)
1507: fprintf(ficresp, " Age Prev(%d) N(%d) N",i,i);
1508: fprintf(ficresp, "\n");
1509:
1510: for(i=(int)agemin; i <= (int)agemax+3; i++){
1511: if(i==(int)agemax+3){
1512: fprintf(ficlog,"Total");
1513: }else{
1514: if(first==1){
1515: first=0;
1516: printf("See log file for details...\n");
1517: }
1518: fprintf(ficlog,"Age %d", i);
1519: }
1520: for(jk=1; jk <=nlstate ; jk++){
1521: for(m=-1, pp[jk]=0; m <=nlstate+ndeath ; m++)
1522: pp[jk] += freq[jk][m][i];
1523: }
1524: for(jk=1; jk <=nlstate ; jk++){
1525: for(m=-1, pos=0; m <=0 ; m++)
1526: pos += freq[jk][m][i];
1527: if(pp[jk]>=1.e-10){
1528: if(first==1){
1529: printf(" %d.=%.0f loss[%d]=%.1f%%",jk,pp[jk],jk,100*pos/pp[jk]);
1530: }
1531: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",jk,pp[jk],jk,100*pos/pp[jk]);
1532: }else{
1533: if(first==1)
1534: printf(" %d.=%.0f loss[%d]=NaNQ%%",jk,pp[jk],jk);
1535: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",jk,pp[jk],jk);
1536: }
1537: }
1538:
1539: for(jk=1; jk <=nlstate ; jk++){
1540: for(m=0, pp[jk]=0; m <=nlstate+ndeath; m++)
1541: pp[jk] += freq[jk][m][i];
1542: }
1543: for(jk=1,pos=0,posprop=0; jk <=nlstate ; jk++){
1544: pos += pp[jk];
1545: posprop += prop[jk][i];
1546: }
1547: for(jk=1; jk <=nlstate ; jk++){
1548: if(pos>=1.e-5){
1549: if(first==1)
1550: printf(" %d.=%.0f prev[%d]=%.1f%%",jk,pp[jk],jk,100*pp[jk]/pos);
1551: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",jk,pp[jk],jk,100*pp[jk]/pos);
1552: }else{
1553: if(first==1)
1554: printf(" %d.=%.0f prev[%d]=NaNQ%%",jk,pp[jk],jk);
1555: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",jk,pp[jk],jk);
1556: }
1557: if( i <= (int) agemax){
1558: if(pos>=1.e-5){
1559: fprintf(ficresp," %d %.5f %.0f %.0f",i,prop[jk][i]/posprop, prop[jk][i],posprop);
1560: probs[i][jk][j1]= pp[jk]/pos;
1561: /*printf("\ni=%d jk=%d j1=%d %.5f %.0f %.0f %f",i,jk,j1,pp[jk]/pos, pp[jk],pos,probs[i][jk][j1]);*/
1562: }
1563: else
1564: fprintf(ficresp," %d NaNq %.0f %.0f",i,prop[jk][i],posprop);
1565: }
1566: }
1567:
1568: for(jk=-1; jk <=nlstate+ndeath; jk++)
1569: for(m=-1; m <=nlstate+ndeath; m++)
1570: if(freq[jk][m][i] !=0 ) {
1571: if(first==1)
1572: printf(" %d%d=%.0f",jk,m,freq[jk][m][i]);
1573: fprintf(ficlog," %d%d=%.0f",jk,m,freq[jk][m][i]);
1574: }
1575: if(i <= (int) agemax)
1576: fprintf(ficresp,"\n");
1577: if(first==1)
1578: printf("Others in log...\n");
1579: fprintf(ficlog,"\n");
1580: }
1581: }
1582: }
1583: dateintmean=dateintsum/k2cpt;
1584:
1585: fclose(ficresp);
1586: free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath,(int) agemin,(int) agemax+3);
1587: free_vector(pp,1,nlstate);
1588: free_matrix(prop,1,nlstate,(int) agemin,(int) agemax+3);
1589: /* End of Freq */
1590: }
1591:
1592: /************ Prevalence ********************/
1593: 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, int firstpass, int lastpass)
1594: {
1595: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
1596: in each health status at the date of interview (if between dateprev1 and dateprev2).
1597: We still use firstpass and lastpass as another selection.
1598: */
1599:
1600: int i, m, jk, k1, i1, j1, bool, z1,z2,j;
1601: double ***freq; /* Frequencies */
1602: double *pp, **prop;
1603: double pos,posprop;
1604: double y2; /* in fractional years */
1605:
1606: pp=vector(1,nlstate);
1607: prop=matrix(1,nlstate,agemin,agemax+3);
1608: freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,agemin,agemax+3);
1609: j1=0;
1610:
1611: j=cptcoveff;
1612: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1613:
1614: for(k1=1; k1<=j;k1++){
1615: for(i1=1; i1<=ncodemax[k1];i1++){
1616: j1++;
1617:
1618: for (i=1; i<=nlstate; i++)
1619: for(m=agemin; m <= agemax+3; m++)
1620: prop[i][m]=0;
1621:
1622: for (i=1; i<=imx; i++) { /* Each individual */
1623: bool=1;
1624: if (cptcovn>0) {
1625: for (z1=1; z1<=cptcoveff; z1++)
1626: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtab[j1][z1]])
1627: bool=0;
1628: }
1629: if (bool==1) {
1630: for(m=firstpass; m<=lastpass; m++){/* Other selection (we can limit to certain interviews*/
1631: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
1632: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
1633: if(agev[m][i]==0) agev[m][i]=agemax+1;
1634: if(agev[m][i]==1) agev[m][i]=agemax+2;
1635: if (s[m][i]>0 && s[m][i]<=nlstate) {
1636: prop[s[m][i]][(int)agev[m][i]] += weight[i];
1637: prop[s[m][i]][(int)(agemax+3)] += weight[i];
1638: }
1639: }
1640: } /* end selection of waves */
1641: }
1642: }
1643: for(i=(int)agemin; i <= (int)agemax+3; i++){
1644:
1645: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
1646: posprop += prop[jk][i];
1647: }
1648:
1649: for(jk=1; jk <=nlstate ; jk++){
1650: if( i <= (int) agemax){
1651: if(posprop>=1.e-5){
1652: probs[i][jk][j1]= prop[jk][i]/posprop;
1653: }
1654: }
1655: }/* end jk */
1656: }/* end i */
1657: } /* end i1 */
1658: } /* end k1 */
1659:
1660:
1661: free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath,(int) agemin,(int) agemax+3);
1662: free_vector(pp,1,nlstate);
1663: free_matrix(prop,1,nlstate,(int) agemin,(int) agemax+3);
1664: } /* End of Freq */
1665:
1666: /************* Waves Concatenation ***************/
1667:
1668: 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)
1669: {
1670: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
1671: Death is a valid wave (if date is known).
1672: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
1673: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
1674: and mw[mi+1][i]. dh depends on stepm.
1675: */
1676:
1677: int i, mi, m;
1678: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
1679: double sum=0., jmean=0.;*/
1680: int first;
1681: int j, k=0,jk, ju, jl;
1682: double sum=0.;
1683: first=0;
1684: jmin=1e+5;
1685: jmax=-1;
1686: jmean=0.;
1687: for(i=1; i<=imx; i++){
1688: mi=0;
1689: m=firstpass;
1690: while(s[m][i] <= nlstate){
1691: if(s[m][i]>=1)
1692: mw[++mi][i]=m;
1693: if(m >=lastpass)
1694: break;
1695: else
1696: m++;
1697: }/* end while */
1698: if (s[m][i] > nlstate){
1699: mi++; /* Death is another wave */
1700: /* if(mi==0) never been interviewed correctly before death */
1701: /* Only death is a correct wave */
1702: mw[mi][i]=m;
1703: }
1704:
1705: wav[i]=mi;
1706: if(mi==0){
1707: if(first==0){
1708: printf("Warning, no any valid information for:%d line=%d and may be others, see log file\n",num[i],i);
1709: first=1;
1710: }
1711: if(first==1){
1712: fprintf(ficlog,"Warning, no any valid information for:%d line=%d\n",num[i],i);
1713: }
1714: } /* end mi==0 */
1715: }
1716:
1717: for(i=1; i<=imx; i++){
1718: for(mi=1; mi<wav[i];mi++){
1719: if (stepm <=0)
1720: dh[mi][i]=1;
1721: else{
1722: if (s[mw[mi+1][i]][i] > nlstate) {
1723: if (agedc[i] < 2*AGESUP) {
1724: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
1725: if(j==0) j=1; /* Survives at least one month after exam */
1726: k=k+1;
1727: if (j >= jmax) jmax=j;
1728: if (j <= jmin) jmin=j;
1729: sum=sum+j;
1730: /*if (j<0) printf("j=%d num=%d \n",j,i); */
1731: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
1732: /*printf("%d %lf %d %d %d\n", i,agev[mw[mi][i]][i],j,s[mw[mi][i]][i] ,s[mw[mi+1][i]][i]);*/
1733: }
1734: }
1735: else{
1736: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1737: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
1738: k=k+1;
1739: if (j >= jmax) jmax=j;
1740: else if (j <= jmin)jmin=j;
1741: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
1742: /*printf("%d %lf %d %d %d\n", i,agev[mw[mi][i]][i],j,s[mw[mi][i]][i] ,s[mw[mi+1][i]][i]);*/
1743: sum=sum+j;
1744: }
1745: jk= j/stepm;
1746: jl= j -jk*stepm;
1747: ju= j -(jk+1)*stepm;
1748: if(mle <=1){
1749: if(jl==0){
1750: dh[mi][i]=jk;
1751: bh[mi][i]=0;
1752: }else{ /* We want a negative bias in order to only have interpolation ie
1753: * at the price of an extra matrix product in likelihood */
1754: dh[mi][i]=jk+1;
1755: bh[mi][i]=ju;
1756: }
1757: }else{
1758: if(jl <= -ju){
1759: dh[mi][i]=jk;
1760: bh[mi][i]=jl; /* bias is positive if real duration
1761: * is higher than the multiple of stepm and negative otherwise.
1762: */
1763: }
1764: else{
1765: dh[mi][i]=jk+1;
1766: bh[mi][i]=ju;
1767: }
1768: if(dh[mi][i]==0){
1769: dh[mi][i]=1; /* At least one step */
1770: bh[mi][i]=ju; /* At least one step */
1771: /* 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);*/
1772: }
1773: }
1774: } /* end if mle */
1775: } /* end wave */
1776: }
1777: jmean=sum/k;
1778: printf("Delay (in months) between two waves Min=%d Max=%d Mean=%f\n\n ",jmin, jmax,jmean);
1779: fprintf(ficlog,"Delay (in months) between two waves Min=%d Max=%d Mean=%f\n\n ",jmin, jmax,jmean);
1780: }
1781:
1782: /*********** Tricode ****************************/
1783: void tricode(int *Tvar, int **nbcode, int imx)
1784: {
1785:
1786: int Ndum[20],ij=1, k, j, i, maxncov=19;
1787: int cptcode=0;
1788: cptcoveff=0;
1789:
1790: for (k=0; k<maxncov; k++) Ndum[k]=0;
1791: for (k=1; k<=7; k++) ncodemax[k]=0;
1792:
1793: for (j=1; j<=(cptcovn+2*cptcovprod); j++) {
1794: for (i=1; i<=imx; i++) { /*reads the data file to get the maximum
1795: modality*/
1796: ij=(int)(covar[Tvar[j]][i]); /* ij is the modality of this individual*/
1797: Ndum[ij]++; /*store the modality */
1798: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
1799: if (ij > cptcode) cptcode=ij; /* getting the maximum of covariable
1800: Tvar[j]. If V=sex and male is 0 and
1801: female is 1, then cptcode=1.*/
1802: }
1803:
1804: for (i=0; i<=cptcode; i++) {
1805: 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 */
1806: }
1807:
1808: ij=1;
1809: for (i=1; i<=ncodemax[j]; i++) {
1810: for (k=0; k<= maxncov; k++) {
1811: if (Ndum[k] != 0) {
1812: nbcode[Tvar[j]][ij]=k;
1813: /* 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; */
1814:
1815: ij++;
1816: }
1817: if (ij > ncodemax[j]) break;
1818: }
1819: }
1820: }
1821:
1822: for (k=0; k< maxncov; k++) Ndum[k]=0;
1823:
1824: for (i=1; i<=ncovmodel-2; i++) {
1825: /* Listing of all covariables in staement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
1826: ij=Tvar[i];
1827: Ndum[ij]++;
1828: }
1829:
1830: ij=1;
1831: for (i=1; i<= maxncov; i++) {
1832: if((Ndum[i]!=0) && (i<=ncovcol)){
1833: Tvaraff[ij]=i; /*For printing */
1834: ij++;
1835: }
1836: }
1837:
1838: cptcoveff=ij-1; /*Number of simple covariates*/
1839: }
1840:
1841: /*********** Health Expectancies ****************/
1842:
1843: 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 )
1844:
1845: {
1846: /* Health expectancies */
1847: int i, j, nhstepm, hstepm, h, nstepm, k, cptj;
1848: double age, agelim, hf;
1849: double ***p3mat,***varhe;
1850: double **dnewm,**doldm;
1851: double *xp;
1852: double **gp, **gm;
1853: double ***gradg, ***trgradg;
1854: int theta;
1855:
1856: varhe=ma3x(1,nlstate*2,1,nlstate*2,(int) bage, (int) fage);
1857: xp=vector(1,npar);
1858: dnewm=matrix(1,nlstate*2,1,npar);
1859: doldm=matrix(1,nlstate*2,1,nlstate*2);
1860:
1861: fprintf(ficreseij,"# Health expectancies\n");
1862: fprintf(ficreseij,"# Age");
1863: for(i=1; i<=nlstate;i++)
1864: for(j=1; j<=nlstate;j++)
1865: fprintf(ficreseij," %1d-%1d (SE)",i,j);
1866: fprintf(ficreseij,"\n");
1867:
1868: if(estepm < stepm){
1869: printf ("Problem %d lower than %d\n",estepm, stepm);
1870: }
1871: else hstepm=estepm;
1872: /* We compute the life expectancy from trapezoids spaced every estepm months
1873: * This is mainly to measure the difference between two models: for example
1874: * if stepm=24 months pijx are given only every 2 years and by summing them
1875: * we are calculating an estimate of the Life Expectancy assuming a linear
1876: * progression in between and thus overestimating or underestimating according
1877: * to the curvature of the survival function. If, for the same date, we
1878: * estimate the model with stepm=1 month, we can keep estepm to 24 months
1879: * to compare the new estimate of Life expectancy with the same linear
1880: * hypothesis. A more precise result, taking into account a more precise
1881: * curvature will be obtained if estepm is as small as stepm. */
1882:
1883: /* For example we decided to compute the life expectancy with the smallest unit */
1884: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
1885: nhstepm is the number of hstepm from age to agelim
1886: nstepm is the number of stepm from age to agelin.
1887: Look at hpijx to understand the reason of that which relies in memory size
1888: and note for a fixed period like estepm months */
1889: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
1890: survival function given by stepm (the optimization length). Unfortunately it
1891: means that if the survival funtion is printed only each two years of age and if
1892: you sum them up and add 1 year (area under the trapezoids) you won't get the same
1893: results. So we changed our mind and took the option of the best precision.
1894: */
1895: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
1896:
1897: agelim=AGESUP;
1898: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
1899: /* nhstepm age range expressed in number of stepm */
1900: nstepm=(int) rint((agelim-age)*YEARM/stepm);
1901: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
1902: /* if (stepm >= YEARM) hstepm=1;*/
1903: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
1904: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
1905: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*2);
1906: gp=matrix(0,nhstepm,1,nlstate*2);
1907: gm=matrix(0,nhstepm,1,nlstate*2);
1908:
1909: /* Computed by stepm unit matrices, product of hstepm matrices, stored
1910: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
1911: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, ij);
1912:
1913:
1914: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1915:
1916: /* Computing Variances of health expectancies */
1917:
1918: for(theta=1; theta <=npar; theta++){
1919: for(i=1; i<=npar; i++){
1920: xp[i] = x[i] + (i==theta ?delti[theta]:0);
1921: }
1922: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij);
1923:
1924: cptj=0;
1925: for(j=1; j<= nlstate; j++){
1926: for(i=1; i<=nlstate; i++){
1927: cptj=cptj+1;
1928: for(h=0, gp[h][cptj]=0.; h<=nhstepm-1; h++){
1929: gp[h][cptj] = (p3mat[i][j][h]+p3mat[i][j][h+1])/2.;
1930: }
1931: }
1932: }
1933:
1934:
1935: for(i=1; i<=npar; i++)
1936: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1937: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij);
1938:
1939: cptj=0;
1940: for(j=1; j<= nlstate; j++){
1941: for(i=1;i<=nlstate;i++){
1942: cptj=cptj+1;
1943: for(h=0, gm[h][cptj]=0.; h<=nhstepm-1; h++){
1944: gm[h][cptj] = (p3mat[i][j][h]+p3mat[i][j][h+1])/2.;
1945: }
1946: }
1947: }
1948: for(j=1; j<= nlstate*2; j++)
1949: for(h=0; h<=nhstepm-1; h++){
1950: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
1951: }
1952: }
1953:
1954: /* End theta */
1955:
1956: trgradg =ma3x(0,nhstepm,1,nlstate*2,1,npar);
1957:
1958: for(h=0; h<=nhstepm-1; h++)
1959: for(j=1; j<=nlstate*2;j++)
1960: for(theta=1; theta <=npar; theta++)
1961: trgradg[h][j][theta]=gradg[h][theta][j];
1962:
1963:
1964: for(i=1;i<=nlstate*2;i++)
1965: for(j=1;j<=nlstate*2;j++)
1966: varhe[i][j][(int)age] =0.;
1967:
1968: printf("%d|",(int)age);fflush(stdout);
1969: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
1970: for(h=0;h<=nhstepm-1;h++){
1971: for(k=0;k<=nhstepm-1;k++){
1972: matprod2(dnewm,trgradg[h],1,nlstate*2,1,npar,1,npar,matcov);
1973: matprod2(doldm,dnewm,1,nlstate*2,1,npar,1,nlstate*2,gradg[k]);
1974: for(i=1;i<=nlstate*2;i++)
1975: for(j=1;j<=nlstate*2;j++)
1976: varhe[i][j][(int)age] += doldm[i][j]*hf*hf;
1977: }
1978: }
1979: /* Computing expectancies */
1980: for(i=1; i<=nlstate;i++)
1981: for(j=1; j<=nlstate;j++)
1982: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
1983: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
1984:
1985: /* 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]);*/
1986:
1987: }
1988:
1989: fprintf(ficreseij,"%3.0f",age );
1990: cptj=0;
1991: for(i=1; i<=nlstate;i++)
1992: for(j=1; j<=nlstate;j++){
1993: cptj++;
1994: fprintf(ficreseij," %9.4f (%.4f)", eij[i][j][(int)age], sqrt(varhe[cptj][cptj][(int)age]) );
1995: }
1996: fprintf(ficreseij,"\n");
1997:
1998: free_matrix(gm,0,nhstepm,1,nlstate*2);
1999: free_matrix(gp,0,nhstepm,1,nlstate*2);
2000: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*2);
2001: free_ma3x(trgradg,0,nhstepm,1,nlstate*2,1,npar);
2002: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
2003: }
2004: printf("\n");
2005: fprintf(ficlog,"\n");
2006:
2007: free_vector(xp,1,npar);
2008: free_matrix(dnewm,1,nlstate*2,1,npar);
2009: free_matrix(doldm,1,nlstate*2,1,nlstate*2);
2010: free_ma3x(varhe,1,nlstate*2,1,nlstate*2,(int) bage, (int)fage);
2011: }
2012:
2013: /************ Variance ******************/
2014: 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)
2015: {
2016: /* Variance of health expectancies */
2017: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);*/
2018: /* double **newm;*/
2019: double **dnewm,**doldm;
2020: double **dnewmp,**doldmp;
2021: int i, j, nhstepm, hstepm, h, nstepm ;
2022: int k, cptcode;
2023: double *xp;
2024: double **gp, **gm; /* for var eij */
2025: double ***gradg, ***trgradg; /*for var eij */
2026: double **gradgp, **trgradgp; /* for var p point j */
2027: double *gpp, *gmp; /* for var p point j */
2028: double **varppt; /* for var p point j nlstate to nlstate+ndeath */
2029: double ***p3mat;
2030: double age,agelim, hf;
2031: double ***mobaverage;
2032: int theta;
2033: char digit[4];
2034: char digitp[25];
2035:
2036: char fileresprobmorprev[FILENAMELENGTH];
2037:
2038: if(popbased==1){
2039: if(mobilav!=0)
2040: strcpy(digitp,"-populbased-mobilav-");
2041: else strcpy(digitp,"-populbased-nomobil-");
2042: }
2043: else
2044: strcpy(digitp,"-stablbased-");
2045:
2046: if (mobilav!=0) {
2047: mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX);
2048: if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){
2049: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
2050: printf(" Error in movingaverage mobilav=%d\n",mobilav);
2051: }
2052: }
2053:
2054: strcpy(fileresprobmorprev,"prmorprev");
2055: sprintf(digit,"%-d",ij);
2056: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
2057: strcat(fileresprobmorprev,digit); /* Tvar to be done */
2058: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
2059: strcat(fileresprobmorprev,fileres);
2060: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
2061: printf("Problem with resultfile: %s\n", fileresprobmorprev);
2062: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
2063: }
2064: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
2065: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
2066: fprintf(ficresprobmorprev,"# probabilities of dying before estepm=%d months for people of exact age and weighted probabilities w1*p1j+w2*p2j+... stand dev in()\n",estepm);
2067: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
2068: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
2069: fprintf(ficresprobmorprev," p.%-d SE",j);
2070: for(i=1; i<=nlstate;i++)
2071: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
2072: }
2073: fprintf(ficresprobmorprev,"\n");
2074: if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) {
2075: printf("Problem with gnuplot file: %s\n", optionfilegnuplot);
2076: fprintf(ficlog,"Problem with gnuplot file: %s\n", optionfilegnuplot);
2077: exit(0);
2078: }
2079: else{
2080: fprintf(ficgp,"\n# Routine varevsij");
2081: }
2082: if((fichtm=fopen(optionfilehtm,"a"))==NULL) {
2083: printf("Problem with html file: %s\n", optionfilehtm);
2084: fprintf(ficlog,"Problem with html file: %s\n", optionfilehtm);
2085: exit(0);
2086: }
2087: else{
2088: fprintf(fichtm,"\n<li><h4> Computing probabilities of dying over estepm months as a weighted average (i.e global mortality independent of initial healh state)</h4></li>\n");
2089: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
2090: }
2091: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
2092:
2093: 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");
2094: fprintf(ficresvij,"# Age");
2095: for(i=1; i<=nlstate;i++)
2096: for(j=1; j<=nlstate;j++)
2097: fprintf(ficresvij," Cov(e%1d, e%1d)",i,j);
2098: fprintf(ficresvij,"\n");
2099:
2100: xp=vector(1,npar);
2101: dnewm=matrix(1,nlstate,1,npar);
2102: doldm=matrix(1,nlstate,1,nlstate);
2103: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
2104: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
2105:
2106: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
2107: gpp=vector(nlstate+1,nlstate+ndeath);
2108: gmp=vector(nlstate+1,nlstate+ndeath);
2109: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
2110:
2111: if(estepm < stepm){
2112: printf ("Problem %d lower than %d\n",estepm, stepm);
2113: }
2114: else hstepm=estepm;
2115: /* For example we decided to compute the life expectancy with the smallest unit */
2116: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
2117: nhstepm is the number of hstepm from age to agelim
2118: nstepm is the number of stepm from age to agelin.
2119: Look at hpijx to understand the reason of that which relies in memory size
2120: and note for a fixed period like k years */
2121: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
2122: survival function given by stepm (the optimization length). Unfortunately it
2123: means that if the survival funtion is printed every two years of age and if
2124: you sum them up and add 1 year (area under the trapezoids) you won't get the same
2125: results. So we changed our mind and took the option of the best precision.
2126: */
2127: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
2128: agelim = AGESUP;
2129: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
2130: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
2131: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
2132: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
2133: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
2134: gp=matrix(0,nhstepm,1,nlstate);
2135: gm=matrix(0,nhstepm,1,nlstate);
2136:
2137:
2138: for(theta=1; theta <=npar; theta++){
2139: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
2140: xp[i] = x[i] + (i==theta ?delti[theta]:0);
2141: }
2142: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij);
2143: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ij);
2144:
2145: if (popbased==1) {
2146: if(mobilav ==0){
2147: for(i=1; i<=nlstate;i++)
2148: prlim[i][i]=probs[(int)age][i][ij];
2149: }else{ /* mobilav */
2150: for(i=1; i<=nlstate;i++)
2151: prlim[i][i]=mobaverage[(int)age][i][ij];
2152: }
2153: }
2154:
2155: for(j=1; j<= nlstate; j++){
2156: for(h=0; h<=nhstepm; h++){
2157: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
2158: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
2159: }
2160: }
2161: /* This for computing probability of death (h=1 means
2162: computed over hstepm matrices product = hstepm*stepm months)
2163: as a weighted average of prlim.
2164: */
2165: for(j=nlstate+1;j<=nlstate+ndeath;j++){
2166: for(i=1,gpp[j]=0.; i<= nlstate; i++)
2167: gpp[j] += prlim[i][i]*p3mat[i][j][1];
2168: }
2169: /* end probability of death */
2170:
2171: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
2172: xp[i] = x[i] - (i==theta ?delti[theta]:0);
2173: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij);
2174: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ij);
2175:
2176: if (popbased==1) {
2177: if(mobilav ==0){
2178: for(i=1; i<=nlstate;i++)
2179: prlim[i][i]=probs[(int)age][i][ij];
2180: }else{ /* mobilav */
2181: for(i=1; i<=nlstate;i++)
2182: prlim[i][i]=mobaverage[(int)age][i][ij];
2183: }
2184: }
2185:
2186: for(j=1; j<= nlstate; j++){
2187: for(h=0; h<=nhstepm; h++){
2188: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
2189: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
2190: }
2191: }
2192: /* This for computing probability of death (h=1 means
2193: computed over hstepm matrices product = hstepm*stepm months)
2194: as a weighted average of prlim.
2195: */
2196: for(j=nlstate+1;j<=nlstate+ndeath;j++){
2197: for(i=1,gmp[j]=0.; i<= nlstate; i++)
2198: gmp[j] += prlim[i][i]*p3mat[i][j][1];
2199: }
2200: /* end probability of death */
2201:
2202: for(j=1; j<= nlstate; j++) /* vareij */
2203: for(h=0; h<=nhstepm; h++){
2204: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
2205: }
2206:
2207: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu */
2208: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
2209: }
2210:
2211: } /* End theta */
2212:
2213: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
2214:
2215: for(h=0; h<=nhstepm; h++) /* veij */
2216: for(j=1; j<=nlstate;j++)
2217: for(theta=1; theta <=npar; theta++)
2218: trgradg[h][j][theta]=gradg[h][theta][j];
2219:
2220: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
2221: for(theta=1; theta <=npar; theta++)
2222: trgradgp[j][theta]=gradgp[theta][j];
2223:
2224:
2225: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
2226: for(i=1;i<=nlstate;i++)
2227: for(j=1;j<=nlstate;j++)
2228: vareij[i][j][(int)age] =0.;
2229:
2230: for(h=0;h<=nhstepm;h++){
2231: for(k=0;k<=nhstepm;k++){
2232: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
2233: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
2234: for(i=1;i<=nlstate;i++)
2235: for(j=1;j<=nlstate;j++)
2236: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
2237: }
2238: }
2239:
2240: /* pptj */
2241: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
2242: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
2243: for(j=nlstate+1;j<=nlstate+ndeath;j++)
2244: for(i=nlstate+1;i<=nlstate+ndeath;i++)
2245: varppt[j][i]=doldmp[j][i];
2246: /* end ppptj */
2247: /* x centered again */
2248: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij);
2249: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ij);
2250:
2251: if (popbased==1) {
2252: if(mobilav ==0){
2253: for(i=1; i<=nlstate;i++)
2254: prlim[i][i]=probs[(int)age][i][ij];
2255: }else{ /* mobilav */
2256: for(i=1; i<=nlstate;i++)
2257: prlim[i][i]=mobaverage[(int)age][i][ij];
2258: }
2259: }
2260:
2261: /* This for computing probability of death (h=1 means
2262: computed over hstepm (estepm) matrices product = hstepm*stepm months)
2263: as a weighted average of prlim.
2264: */
2265: for(j=nlstate+1;j<=nlstate+ndeath;j++){
2266: for(i=1,gmp[j]=0.;i<= nlstate; i++)
2267: gmp[j] += prlim[i][i]*p3mat[i][j][1];
2268: }
2269: /* end probability of death */
2270:
2271: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
2272: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
2273: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
2274: for(i=1; i<=nlstate;i++){
2275: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
2276: }
2277: }
2278: fprintf(ficresprobmorprev,"\n");
2279:
2280: fprintf(ficresvij,"%.0f ",age );
2281: for(i=1; i<=nlstate;i++)
2282: for(j=1; j<=nlstate;j++){
2283: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
2284: }
2285: fprintf(ficresvij,"\n");
2286: free_matrix(gp,0,nhstepm,1,nlstate);
2287: free_matrix(gm,0,nhstepm,1,nlstate);
2288: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
2289: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
2290: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
2291: } /* End age */
2292: free_vector(gpp,nlstate+1,nlstate+ndeath);
2293: free_vector(gmp,nlstate+1,nlstate+ndeath);
2294: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
2295: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
2296: fprintf(ficgp,"\nset noparametric;set nolabel; set ter png small;set size 0.65, 0.65");
2297: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
2298: fprintf(ficgp,"\n set log y; set nolog x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
2299: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
2300: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
2301: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
2302: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l 1 ",fileresprobmorprev);
2303: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95\%% interval\" w l 2 ",fileresprobmorprev);
2304: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l 2 ",fileresprobmorprev);
2305: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",fileresprobmorprev,fileresprobmorprev);
2306: fprintf(fichtm,"\n<br> Probability is computed over estepm=%d months. <br> <img src=\"varmuptjgr%s%s%s.png\"> <br>\n", estepm,digitp,optionfilefiname,digit);
2307: /* 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);
2308: */
2309: fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.png\";replot;",digitp,optionfilefiname,digit);
2310:
2311: free_vector(xp,1,npar);
2312: free_matrix(doldm,1,nlstate,1,nlstate);
2313: free_matrix(dnewm,1,nlstate,1,npar);
2314: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
2315: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
2316: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
2317: if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX);
2318: fclose(ficresprobmorprev);
2319: fclose(ficgp);
2320: fclose(fichtm);
2321: }
2322:
2323: /************ Variance of prevlim ******************/
2324: 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)
2325: {
2326: /* Variance of prevalence limit */
2327: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
2328: double **newm;
2329: double **dnewm,**doldm;
2330: int i, j, nhstepm, hstepm;
2331: int k, cptcode;
2332: double *xp;
2333: double *gp, *gm;
2334: double **gradg, **trgradg;
2335: double age,agelim;
2336: int theta;
2337:
2338: fprintf(ficresvpl,"# Standard deviation of stable prevalences \n");
2339: fprintf(ficresvpl,"# Age");
2340: for(i=1; i<=nlstate;i++)
2341: fprintf(ficresvpl," %1d-%1d",i,i);
2342: fprintf(ficresvpl,"\n");
2343:
2344: xp=vector(1,npar);
2345: dnewm=matrix(1,nlstate,1,npar);
2346: doldm=matrix(1,nlstate,1,nlstate);
2347:
2348: hstepm=1*YEARM; /* Every year of age */
2349: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
2350: agelim = AGESUP;
2351: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
2352: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
2353: if (stepm >= YEARM) hstepm=1;
2354: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
2355: gradg=matrix(1,npar,1,nlstate);
2356: gp=vector(1,nlstate);
2357: gm=vector(1,nlstate);
2358:
2359: for(theta=1; theta <=npar; theta++){
2360: for(i=1; i<=npar; i++){ /* Computes gradient */
2361: xp[i] = x[i] + (i==theta ?delti[theta]:0);
2362: }
2363: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ij);
2364: for(i=1;i<=nlstate;i++)
2365: gp[i] = prlim[i][i];
2366:
2367: for(i=1; i<=npar; i++) /* Computes gradient */
2368: xp[i] = x[i] - (i==theta ?delti[theta]:0);
2369: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ij);
2370: for(i=1;i<=nlstate;i++)
2371: gm[i] = prlim[i][i];
2372:
2373: for(i=1;i<=nlstate;i++)
2374: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
2375: } /* End theta */
2376:
2377: trgradg =matrix(1,nlstate,1,npar);
2378:
2379: for(j=1; j<=nlstate;j++)
2380: for(theta=1; theta <=npar; theta++)
2381: trgradg[j][theta]=gradg[theta][j];
2382:
2383: for(i=1;i<=nlstate;i++)
2384: varpl[i][(int)age] =0.;
2385: matprod2(dnewm,trgradg,1,nlstate,1,npar,1,npar,matcov);
2386: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg);
2387: for(i=1;i<=nlstate;i++)
2388: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
2389:
2390: fprintf(ficresvpl,"%.0f ",age );
2391: for(i=1; i<=nlstate;i++)
2392: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
2393: fprintf(ficresvpl,"\n");
2394: free_vector(gp,1,nlstate);
2395: free_vector(gm,1,nlstate);
2396: free_matrix(gradg,1,npar,1,nlstate);
2397: free_matrix(trgradg,1,nlstate,1,npar);
2398: } /* End age */
2399:
2400: free_vector(xp,1,npar);
2401: free_matrix(doldm,1,nlstate,1,npar);
2402: free_matrix(dnewm,1,nlstate,1,nlstate);
2403:
2404: }
2405:
2406: /************ Variance of one-step probabilities ******************/
2407: void varprob(char optionfilefiname[], double **matcov, double x[], double delti[], int nlstate, double bage, double fage, int ij, int *Tvar, int **nbcode, int *ncodemax)
2408: {
2409: int i, j=0, i1, k1, l1, t, tj;
2410: int k2, l2, j1, z1;
2411: int k=0,l, cptcode;
2412: int first=1, first1;
2413: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
2414: double **dnewm,**doldm;
2415: double *xp;
2416: double *gp, *gm;
2417: double **gradg, **trgradg;
2418: double **mu;
2419: double age,agelim, cov[NCOVMAX];
2420: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
2421: int theta;
2422: char fileresprob[FILENAMELENGTH];
2423: char fileresprobcov[FILENAMELENGTH];
2424: char fileresprobcor[FILENAMELENGTH];
2425:
2426: double ***varpij;
2427:
2428: strcpy(fileresprob,"prob");
2429: strcat(fileresprob,fileres);
2430: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
2431: printf("Problem with resultfile: %s\n", fileresprob);
2432: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
2433: }
2434: strcpy(fileresprobcov,"probcov");
2435: strcat(fileresprobcov,fileres);
2436: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
2437: printf("Problem with resultfile: %s\n", fileresprobcov);
2438: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
2439: }
2440: strcpy(fileresprobcor,"probcor");
2441: strcat(fileresprobcor,fileres);
2442: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
2443: printf("Problem with resultfile: %s\n", fileresprobcor);
2444: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
2445: }
2446: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
2447: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
2448: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
2449: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
2450: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
2451: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
2452:
2453: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
2454: fprintf(ficresprob,"# Age");
2455: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
2456: fprintf(ficresprobcov,"# Age");
2457: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
2458: fprintf(ficresprobcov,"# Age");
2459:
2460:
2461: for(i=1; i<=nlstate;i++)
2462: for(j=1; j<=(nlstate+ndeath);j++){
2463: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
2464: fprintf(ficresprobcov," p%1d-%1d ",i,j);
2465: fprintf(ficresprobcor," p%1d-%1d ",i,j);
2466: }
2467: /* fprintf(ficresprob,"\n");
2468: fprintf(ficresprobcov,"\n");
2469: fprintf(ficresprobcor,"\n");
2470: */
2471: xp=vector(1,npar);
2472: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
2473: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
2474: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
2475: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
2476: first=1;
2477: if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) {
2478: printf("Problem with gnuplot file: %s\n", optionfilegnuplot);
2479: fprintf(ficlog,"Problem with gnuplot file: %s\n", optionfilegnuplot);
2480: exit(0);
2481: }
2482: else{
2483: fprintf(ficgp,"\n# Routine varprob");
2484: }
2485: if((fichtm=fopen(optionfilehtm,"a"))==NULL) {
2486: printf("Problem with html file: %s\n", optionfilehtm);
2487: fprintf(ficlog,"Problem with html file: %s\n", optionfilehtm);
2488: exit(0);
2489: }
2490: else{
2491: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
2492: fprintf(fichtm,"\n");
2493:
2494: fprintf(fichtm,"\n<li><h4> Computing matrix of variance-covariance of step probabilities</h4></li>\n");
2495: 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");
2496: 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");
2497:
2498: }
2499:
2500: cov[1]=1;
2501: tj=cptcoveff;
2502: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
2503: j1=0;
2504: for(t=1; t<=tj;t++){
2505: for(i1=1; i1<=ncodemax[t];i1++){
2506: j1++;
2507: if (cptcovn>0) {
2508: fprintf(ficresprob, "\n#********** Variable ");
2509: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtab[j1][z1]]);
2510: fprintf(ficresprob, "**********\n#\n");
2511: fprintf(ficresprobcov, "\n#********** Variable ");
2512: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcov, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtab[j1][z1]]);
2513: fprintf(ficresprobcov, "**********\n#\n");
2514:
2515: fprintf(ficgp, "\n#********** Variable ");
2516: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficgp, " V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtab[j1][z1]]);
2517: fprintf(ficgp, "**********\n#\n");
2518:
2519:
2520: fprintf(fichtm, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
2521: for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtm, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtab[j1][z1]]);
2522: fprintf(fichtm, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
2523:
2524: fprintf(ficresprobcor, "\n#********** Variable ");
2525: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcor, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtab[j1][z1]]);
2526: fprintf(ficresprobcor, "**********\n#");
2527: }
2528:
2529: for (age=bage; age<=fage; age ++){
2530: cov[2]=age;
2531: for (k=1; k<=cptcovn;k++) {
2532: cov[2+k]=nbcode[Tvar[k]][codtab[j1][Tvar[k]]];
2533: }
2534: for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2];
2535: for (k=1; k<=cptcovprod;k++)
2536: cov[2+Tprod[k]]=nbcode[Tvard[k][1]][codtab[ij][Tvard[k][1]]]*nbcode[Tvard[k][2]][codtab[ij][Tvard[k][2]]];
2537:
2538: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
2539: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
2540: gp=vector(1,(nlstate)*(nlstate+ndeath));
2541: gm=vector(1,(nlstate)*(nlstate+ndeath));
2542:
2543: for(theta=1; theta <=npar; theta++){
2544: for(i=1; i<=npar; i++)
2545: xp[i] = x[i] + (i==theta ?delti[theta]:0);
2546:
2547: pmij(pmmij,cov,ncovmodel,xp,nlstate);
2548:
2549: k=0;
2550: for(i=1; i<= (nlstate); i++){
2551: for(j=1; j<=(nlstate+ndeath);j++){
2552: k=k+1;
2553: gp[k]=pmmij[i][j];
2554: }
2555: }
2556:
2557: for(i=1; i<=npar; i++)
2558: xp[i] = x[i] - (i==theta ?delti[theta]:0);
2559:
2560: pmij(pmmij,cov,ncovmodel,xp,nlstate);
2561: k=0;
2562: for(i=1; i<=(nlstate); i++){
2563: for(j=1; j<=(nlstate+ndeath);j++){
2564: k=k+1;
2565: gm[k]=pmmij[i][j];
2566: }
2567: }
2568:
2569: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
2570: gradg[theta][i]=(gp[i]-gm[i])/2./delti[theta];
2571: }
2572:
2573: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
2574: for(theta=1; theta <=npar; theta++)
2575: trgradg[j][theta]=gradg[theta][j];
2576:
2577: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
2578: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
2579: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
2580: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
2581: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
2582: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
2583:
2584: pmij(pmmij,cov,ncovmodel,x,nlstate);
2585:
2586: k=0;
2587: for(i=1; i<=(nlstate); i++){
2588: for(j=1; j<=(nlstate+ndeath);j++){
2589: k=k+1;
2590: mu[k][(int) age]=pmmij[i][j];
2591: }
2592: }
2593: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
2594: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
2595: varpij[i][j][(int)age] = doldm[i][j];
2596:
2597: /*printf("\n%d ",(int)age);
2598: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
2599: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
2600: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
2601: }*/
2602:
2603: fprintf(ficresprob,"\n%d ",(int)age);
2604: fprintf(ficresprobcov,"\n%d ",(int)age);
2605: fprintf(ficresprobcor,"\n%d ",(int)age);
2606:
2607: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
2608: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
2609: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
2610: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
2611: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
2612: }
2613: i=0;
2614: for (k=1; k<=(nlstate);k++){
2615: for (l=1; l<=(nlstate+ndeath);l++){
2616: i=i++;
2617: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
2618: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
2619: for (j=1; j<=i;j++){
2620: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
2621: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
2622: }
2623: }
2624: }/* end of loop for state */
2625: } /* end of loop for age */
2626:
2627: /* Confidence intervalle of pij */
2628: /*
2629: fprintf(ficgp,"\nset noparametric;unset label");
2630: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
2631: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
2632: 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);
2633: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
2634: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
2635: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
2636: */
2637:
2638: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
2639: first1=1;
2640: for (k2=1; k2<=(nlstate);k2++){
2641: for (l2=1; l2<=(nlstate+ndeath);l2++){
2642: if(l2==k2) continue;
2643: j=(k2-1)*(nlstate+ndeath)+l2;
2644: for (k1=1; k1<=(nlstate);k1++){
2645: for (l1=1; l1<=(nlstate+ndeath);l1++){
2646: if(l1==k1) continue;
2647: i=(k1-1)*(nlstate+ndeath)+l1;
2648: if(i<=j) continue;
2649: for (age=bage; age<=fage; age ++){
2650: if ((int)age %5==0){
2651: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
2652: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
2653: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
2654: mu1=mu[i][(int) age]/stepm*YEARM ;
2655: mu2=mu[j][(int) age]/stepm*YEARM;
2656: c12=cv12/sqrt(v1*v2);
2657: /* Computing eigen value of matrix of covariance */
2658: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
2659: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
2660: /* Eigen vectors */
2661: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
2662: /*v21=sqrt(1.-v11*v11); *//* error */
2663: v21=(lc1-v1)/cv12*v11;
2664: v12=-v21;
2665: v22=v11;
2666: tnalp=v21/v11;
2667: if(first1==1){
2668: first1=0;
2669: 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);
2670: }
2671: 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);
2672: /*printf(fignu*/
2673: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
2674: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
2675: if(first==1){
2676: first=0;
2677: fprintf(ficgp,"\nset parametric;unset label");
2678: 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);
2679: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
2680: 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);
2681: fprintf(fichtm,"\n<br><img src=\"varpijgr%s%d%1d%1d-%1d%1d.png\"> ",optionfilefiname, j1,k1,l1,k2,l2);
2682: fprintf(fichtm,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
2683: fprintf(ficgp,"\nset out \"varpijgr%s%d%1d%1d-%1d%1d.png\"",optionfilefiname, j1,k1,l1,k2,l2);
2684: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
2685: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
2686: 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",\
2687: mu1,std,v11,sqrt(lc1),v12,sqrt(lc2),\
2688: mu2,std,v21,sqrt(lc1),v22,sqrt(lc2));
2689: }else{
2690: first=0;
2691: fprintf(fichtm," %d (%.3f),",(int) age, c12);
2692: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
2693: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
2694: 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",\
2695: mu1,std,v11,sqrt(lc1),v12,sqrt(lc2),\
2696: mu2,std,v21,sqrt(lc1),v22,sqrt(lc2));
2697: }/* if first */
2698: } /* age mod 5 */
2699: } /* end loop age */
2700: fprintf(ficgp,"\nset out \"varpijgr%s%d%1d%1d-%1d%1d.png\";replot;",optionfilefiname, j1,k1,l1,k2,l2);
2701: first=1;
2702: } /*l12 */
2703: } /* k12 */
2704: } /*l1 */
2705: }/* k1 */
2706: } /* loop covariates */
2707: }
2708: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
2709: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
2710: free_vector(xp,1,npar);
2711: fclose(ficresprob);
2712: fclose(ficresprobcov);
2713: fclose(ficresprobcor);
2714: fclose(ficgp);
2715: fclose(fichtm);
2716: }
2717:
2718:
2719: /******************* Printing html file ***********/
2720: void printinghtml(char fileres[], char title[], char datafile[], int firstpass, \
2721: int lastpass, int stepm, int weightopt, char model[],\
2722: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
2723: int popforecast, int estepm ,\
2724: double jprev1, double mprev1,double anprev1, \
2725: double jprev2, double mprev2,double anprev2){
2726: int jj1, k1, i1, cpt;
2727: /*char optionfilehtm[FILENAMELENGTH];*/
2728: if((fichtm=fopen(optionfilehtm,"a"))==NULL) {
2729: printf("Problem with %s \n",optionfilehtm), exit(0);
2730: fprintf(ficlog,"Problem with %s \n",optionfilehtm), exit(0);
2731: }
2732:
2733: fprintf(fichtm,"<ul><li><h4>Result files (first order: no variance)</h4>\n
2734: - 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
2735: - Estimated transition probabilities over %d (stepm) months: <a href=\"pij%s\">pij%s</a><br>\n
2736: - Stable prevalence in each health state: <a href=\"pl%s\">pl%s</a> <br>\n
2737: - Life expectancies by age and initial health status (estepm=%2d months):
2738: <a href=\"e%s\">e%s</a> <br>\n</li>", \
2739: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,fileres,fileres,stepm,fileres,fileres,fileres,fileres,estepm,fileres,fileres);
2740:
2741: fprintf(fichtm," \n<ul><li><b>Graphs</b></li><p>");
2742:
2743: m=cptcoveff;
2744: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
2745:
2746: jj1=0;
2747: for(k1=1; k1<=m;k1++){
2748: for(i1=1; i1<=ncodemax[k1];i1++){
2749: jj1++;
2750: if (cptcovn > 0) {
2751: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
2752: for (cpt=1; cpt<=cptcoveff;cpt++)
2753: fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtab[jj1][cpt]]);
2754: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
2755: }
2756: /* Pij */
2757: 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>
2758: <img src=\"pe%s%d1.png\">",stepm,strtok(optionfile, "."),jj1,strtok(optionfile, "."),jj1);
2759: /* Quasi-incidences */
2760: 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>
2761: <img src=\"pe%s%d2.png\">",stepm,strtok(optionfile, "."),jj1,strtok(optionfile, "."),jj1);
2762: /* Stable prevalence in each health state */
2763: for(cpt=1; cpt<nlstate;cpt++){
2764: fprintf(fichtm,"<br>- Stable prevalence in each health state : p%s%d%d.png<br>
2765: <img src=\"p%s%d%d.png\">",strtok(optionfile, "."),cpt,jj1,strtok(optionfile, "."),cpt,jj1);
2766: }
2767: for(cpt=1; cpt<=nlstate;cpt++) {
2768: fprintf(fichtm,"\n<br>- Health life expectancies by age and initial health state (%d): exp%s%d%d.png <br>
2769: <img src=\"exp%s%d%d.png\">",cpt,strtok(optionfile, "."),cpt,jj1,strtok(optionfile, "."),cpt,jj1);
2770: }
2771: fprintf(fichtm,"\n<br>- Total life expectancy by age and
2772: health expectancies in states (1) and (2): e%s%d.png<br>
2773: <img src=\"e%s%d.png\">",strtok(optionfile, "."),jj1,strtok(optionfile, "."),jj1);
2774: } /* end i1 */
2775: }/* End k1 */
2776: fprintf(fichtm,"</ul>");
2777:
2778:
2779: fprintf(fichtm,"\n<br><li><h4> Result files (second order: variances)</h4>\n
2780: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br>\n
2781: - Variance of one-step probabilities: <a href=\"prob%s\">prob%s</a> <br>\n
2782: - Variance-covariance of one-step probabilities: <a href=\"probcov%s\">probcov%s</a> <br>\n
2783: - Correlation matrix of one-step probabilities: <a href=\"probcor%s\">probcor%s</a> <br>\n
2784: - Variances and covariances of life expectancies by age and initial health status (estepm=%d months): <a href=\"v%s\">v%s</a><br>\n
2785: - Health expectancies with their variances (no covariance): <a href=\"t%s\">t%s</a> <br>\n
2786: - 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);
2787:
2788: if(popforecast==1) fprintf(fichtm,"\n
2789: - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n
2790: - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n
2791: <br>",fileres,fileres,fileres,fileres);
2792: else
2793: 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);
2794: fprintf(fichtm," <ul><li><b>Graphs</b></li><p>");
2795:
2796: m=cptcoveff;
2797: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
2798:
2799: jj1=0;
2800: for(k1=1; k1<=m;k1++){
2801: for(i1=1; i1<=ncodemax[k1];i1++){
2802: jj1++;
2803: if (cptcovn > 0) {
2804: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
2805: for (cpt=1; cpt<=cptcoveff;cpt++)
2806: fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtab[jj1][cpt]]);
2807: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
2808: }
2809: for(cpt=1; cpt<=nlstate;cpt++) {
2810: fprintf(fichtm,"<br>- Observed and stationary prevalence (with confident
2811: interval) in state (%d): v%s%d%d.png <br>
2812: <img src=\"v%s%d%d.png\">",cpt,strtok(optionfile, "."),cpt,jj1,strtok(optionfile, "."),cpt,jj1);
2813: }
2814: } /* end i1 */
2815: }/* End k1 */
2816: fprintf(fichtm,"</ul>");
2817: fclose(fichtm);
2818: }
2819:
2820: /******************* Gnuplot file **************/
2821: void printinggnuplot(char fileres[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
2822:
2823: int m,cpt,k1,i,k,j,jk,k2,k3,ij,l;
2824: int ng;
2825: if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) {
2826: printf("Problem with file %s",optionfilegnuplot);
2827: fprintf(ficlog,"Problem with file %s",optionfilegnuplot);
2828: }
2829:
2830: /*#ifdef windows */
2831: fprintf(ficgp,"cd \"%s\" \n",pathc);
2832: /*#endif */
2833: m=pow(2,cptcoveff);
2834:
2835: /* 1eme*/
2836: for (cpt=1; cpt<= nlstate ; cpt ++) {
2837: for (k1=1; k1<= m ; k1 ++) {
2838: fprintf(ficgp,"\nset out \"v%s%d%d.png\" \n",strtok(optionfile, "."),cpt,k1);
2839: 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);
2840:
2841: for (i=1; i<= nlstate ; i ++) {
2842: if (i==cpt) fprintf(ficgp," \%%lf (\%%lf)");
2843: else fprintf(ficgp," \%%*lf (\%%*lf)");
2844: }
2845: fprintf(ficgp,"\" t\"Stable prevalence\" w l 0,\"vpl%s\" every :::%d::%d u 1:($2+1.96*$3) \"\%%lf",fileres,k1-1,k1-1);
2846: for (i=1; i<= nlstate ; i ++) {
2847: if (i==cpt) fprintf(ficgp," \%%lf (\%%lf)");
2848: else fprintf(ficgp," \%%*lf (\%%*lf)");
2849: }
2850: fprintf(ficgp,"\" t\"95\%% CI\" w l 1,\"vpl%s\" every :::%d::%d u 1:($2-1.96*$3) \"\%%lf",fileres,k1-1,k1-1);
2851: for (i=1; i<= nlstate ; i ++) {
2852: if (i==cpt) fprintf(ficgp," \%%lf (\%%lf)");
2853: else fprintf(ficgp," \%%*lf (\%%*lf)");
2854: }
2855: fprintf(ficgp,"\" t\"\" w l 1,\"p%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence \" w l 2",fileres,k1-1,k1-1,2+4*(cpt-1));
2856: }
2857: }
2858: /*2 eme*/
2859:
2860: for (k1=1; k1<= m ; k1 ++) {
2861: fprintf(ficgp,"\nset out \"e%s%d.png\" \n",strtok(optionfile, "."),k1);
2862: fprintf(ficgp,"set ylabel \"Years\" \nset ter png small\nset size 0.65,0.65\nplot [%.f:%.f] ",ageminpar,fage);
2863:
2864: for (i=1; i<= nlstate+1 ; i ++) {
2865: k=2*i;
2866: fprintf(ficgp,"\"t%s\" every :::%d::%d u 1:2 \"\%%lf",fileres,k1-1,k1-1);
2867: for (j=1; j<= nlstate+1 ; j ++) {
2868: if (j==i) fprintf(ficgp," \%%lf (\%%lf)");
2869: else fprintf(ficgp," \%%*lf (\%%*lf)");
2870: }
2871: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l ,");
2872: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l ,",i-1);
2873: fprintf(ficgp,"\"t%s\" every :::%d::%d u 1:($2-$3*2) \"\%%lf",fileres,k1-1,k1-1);
2874: for (j=1; j<= nlstate+1 ; j ++) {
2875: if (j==i) fprintf(ficgp," \%%lf (\%%lf)");
2876: else fprintf(ficgp," \%%*lf (\%%*lf)");
2877: }
2878: fprintf(ficgp,"\" t\"\" w l 0,");
2879: fprintf(ficgp,"\"t%s\" every :::%d::%d u 1:($2+$3*2) \"\%%lf",fileres,k1-1,k1-1);
2880: for (j=1; j<= nlstate+1 ; j ++) {
2881: if (j==i) fprintf(ficgp," \%%lf (\%%lf)");
2882: else fprintf(ficgp," \%%*lf (\%%*lf)");
2883: }
2884: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l 0");
2885: else fprintf(ficgp,"\" t\"\" w l 0,");
2886: }
2887: }
2888:
2889: /*3eme*/
2890:
2891: for (k1=1; k1<= m ; k1 ++) {
2892: for (cpt=1; cpt<= nlstate ; cpt ++) {
2893: k=2+nlstate*(2*cpt-2);
2894: fprintf(ficgp,"\nset out \"exp%s%d%d.png\" \n",strtok(optionfile, "."),cpt,k1);
2895: fprintf(ficgp,"set ter png small\nset size 0.65,0.65\nplot [%.f:%.f] \"e%s\" every :::%d::%d u 1:%d t \"e%d1\" w l",ageminpar,fage,fileres,k1-1,k1-1,k,cpt);
2896: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
2897: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
2898: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
2899: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
2900: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
2901: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
2902:
2903: */
2904: for (i=1; i< nlstate ; i ++) {
2905: 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);
2906:
2907: }
2908: }
2909: }
2910:
2911: /* CV preval stat */
2912: for (k1=1; k1<= m ; k1 ++) {
2913: for (cpt=1; cpt<nlstate ; cpt ++) {
2914: k=3;
2915: fprintf(ficgp,"\nset out \"p%s%d%d.png\" \n",strtok(optionfile, "."),cpt,k1);
2916: 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/($%d",ageminpar,agemaxpar,fileres,k1,k+cpt+1,k+1);
2917:
2918: for (i=1; i< nlstate ; i ++)
2919: fprintf(ficgp,"+$%d",k+i+1);
2920: fprintf(ficgp,")) t\"prev(%d,%d)\" w l",cpt,cpt+1);
2921:
2922: l=3+(nlstate+ndeath)*cpt;
2923: fprintf(ficgp,",\"pij%s\" u ($1==%d ? ($3):1/0):($%d/($%d",fileres,k1,l+cpt+1,l+1);
2924: for (i=1; i< nlstate ; i ++) {
2925: l=3+(nlstate+ndeath)*cpt;
2926: fprintf(ficgp,"+$%d",l+i+1);
2927: }
2928: fprintf(ficgp,")) t\"prev(%d,%d)\" w l\n",cpt+1,cpt+1);
2929: }
2930: }
2931:
2932: /* proba elementaires */
2933: for(i=1,jk=1; i <=nlstate; i++){
2934: for(k=1; k <=(nlstate+ndeath); k++){
2935: if (k != i) {
2936: for(j=1; j <=ncovmodel; j++){
2937: fprintf(ficgp,"p%d=%f ",jk,p[jk]);
2938: jk++;
2939: fprintf(ficgp,"\n");
2940: }
2941: }
2942: }
2943: }
2944:
2945: for(ng=1; ng<=2;ng++){ /* Number of graphics: first is probabilities second is incidence per year*/
2946: for(jk=1; jk <=m; jk++) {
2947: fprintf(ficgp,"\nset out \"pe%s%d%d.png\" \n",strtok(optionfile, "."),jk,ng);
2948: if (ng==2)
2949: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
2950: else
2951: fprintf(ficgp,"\nset title \"Probability\"\n");
2952: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65\nset log y\nplot [%.f:%.f] ",ageminpar,agemaxpar);
2953: i=1;
2954: for(k2=1; k2<=nlstate; k2++) {
2955: k3=i;
2956: for(k=1; k<=(nlstate+ndeath); k++) {
2957: if (k != k2){
2958: if(ng==2)
2959: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
2960: else
2961: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
2962: ij=1;
2963: for(j=3; j <=ncovmodel; j++) {
2964: if(((j-2)==Tage[ij]) &&(ij <=cptcovage)) {
2965: fprintf(ficgp,"+p%d*%d*x",i+j-1,nbcode[Tvar[j-2]][codtab[jk][Tvar[j-2]]]);
2966: ij++;
2967: }
2968: else
2969: fprintf(ficgp,"+p%d*%d",i+j-1,nbcode[Tvar[j-2]][codtab[jk][j-2]]);
2970: }
2971: fprintf(ficgp,")/(1");
2972:
2973: for(k1=1; k1 <=nlstate; k1++){
2974: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(k1-1)*ncovmodel,k3+(k1-1)*ncovmodel+1);
2975: ij=1;
2976: for(j=3; j <=ncovmodel; j++){
2977: if(((j-2)==Tage[ij]) &&(ij <=cptcovage)) {
2978: fprintf(ficgp,"+p%d*%d*x",k3+(k1-1)*ncovmodel+1+j-2,nbcode[Tvar[j-2]][codtab[jk][Tvar[j-2]]]);
2979: ij++;
2980: }
2981: else
2982: fprintf(ficgp,"+p%d*%d",k3+(k1-1)*ncovmodel+1+j-2,nbcode[Tvar[j-2]][codtab[jk][j-2]]);
2983: }
2984: fprintf(ficgp,")");
2985: }
2986: fprintf(ficgp,") t \"p%d%d\" ", k2,k);
2987: if ((k+k2)!= (nlstate*2+ndeath)) fprintf(ficgp,",");
2988: i=i+ncovmodel;
2989: }
2990: } /* end k */
2991: } /* end k2 */
2992: } /* end jk */
2993: } /* end ng */
2994: fclose(ficgp);
2995: } /* end gnuplot */
2996:
2997:
2998: /*************** Moving average **************/
2999: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav){
3000:
3001: int i, cpt, cptcod;
3002: int modcovmax =1;
3003: int mobilavrange, mob;
3004: double age;
3005:
3006: modcovmax=2*cptcoveff;/* Max number of modalities. We suppose
3007: a covariate has 2 modalities */
3008: if (cptcovn<1) modcovmax=1; /* At least 1 pass */
3009:
3010: if(mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
3011: if(mobilav==1) mobilavrange=5; /* default */
3012: else mobilavrange=mobilav;
3013: for (age=bage; age<=fage; age++)
3014: for (i=1; i<=nlstate;i++)
3015: for (cptcod=1;cptcod<=modcovmax;cptcod++)
3016: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
3017: /* We keep the original values on the extreme ages bage, fage and for
3018: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
3019: we use a 5 terms etc. until the borders are no more concerned.
3020: */
3021: for (mob=3;mob <=mobilavrange;mob=mob+2){
3022: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
3023: for (i=1; i<=nlstate;i++){
3024: for (cptcod=1;cptcod<=modcovmax;cptcod++){
3025: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
3026: for (cpt=1;cpt<=(mob-1)/2;cpt++){
3027: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
3028: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
3029: }
3030: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
3031: }
3032: }
3033: }/* end age */
3034: }/* end mob */
3035: }else return -1;
3036: return 0;
3037: }/* End movingaverage */
3038:
3039:
3040: /************** Forecasting ******************/
3041: prevforecast(char fileres[], double anproj1, double mproj1, double jproj1, double ageminpar, double agemax, double dateprev1, double dateprev2, int mobilav, double bage, double fage, int firstpass, int lastpass, double anproj2, double p[], int cptcoveff){
3042: /* proj1, year, month, day of starting projection
3043: agemin, agemax range of age
3044: dateprev1 dateprev2 range of dates during which prevalence is computed
3045: anproj2 year of en of projection (same day and month as proj1).
3046: */
3047: int yearp, stepsize, hstepm, nhstepm, j, k, c, cptcod, i, h, i1;
3048: int *popage;
3049: double agec; /* generic age */
3050: double agelim, ppij, yp,yp1,yp2,jprojmean,mprojmean,anprojmean;
3051: double *popeffectif,*popcount;
3052: double ***p3mat;
3053: double ***mobaverage;
3054: char fileresf[FILENAMELENGTH];
3055:
3056: agelim=AGESUP;
3057: prevalence(ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
3058:
3059: strcpy(fileresf,"f");
3060: strcat(fileresf,fileres);
3061: if((ficresf=fopen(fileresf,"w"))==NULL) {
3062: printf("Problem with forecast resultfile: %s\n", fileresf);
3063: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
3064: }
3065: printf("Computing forecasting: result on file '%s' \n", fileresf);
3066: fprintf(ficlog,"Computing forecasting: result on file '%s' \n", fileresf);
3067:
3068: if (cptcoveff==0) ncodemax[cptcoveff]=1;
3069:
3070: if (mobilav!=0) {
3071: mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX);
3072: if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){
3073: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
3074: printf(" Error in movingaverage mobilav=%d\n",mobilav);
3075: }
3076: }
3077:
3078: stepsize=(int) (stepm+YEARM-1)/YEARM;
3079: if (stepm<=12) stepsize=1;
3080:
3081: hstepm=1;
3082: hstepm=hstepm/stepm;
3083: yp1=modf(dateintmean,&yp);/* extracts integral of datemean in yp and
3084: fractional in yp1 */
3085: anprojmean=yp;
3086: yp2=modf((yp1*12),&yp);
3087: mprojmean=yp;
3088: yp1=modf((yp2*30.5),&yp);
3089: jprojmean=yp;
3090: if(jprojmean==0) jprojmean=1;
3091: if(mprojmean==0) jprojmean=1;
3092:
3093: i1=cptcoveff;
3094: if (cptcovn < 1){i1=1;}
3095:
3096: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
3097:
3098: fprintf(ficresf,"#****** Routine prevforecast **\n");
3099:
3100: for(cptcov=1, k=0;cptcov<=i1;cptcov++){
3101: for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){
3102: k=k+1;
3103: fprintf(ficresf,"\n#******");
3104: for(j=1;j<=cptcoveff;j++) {
3105: fprintf(ficresf," V%d=%d, hpijx=probability over h years, hp.jx is weighted by observed prev ",Tvaraff[j],nbcode[Tvaraff[j]][codtab[k][j]]);
3106: }
3107: fprintf(ficresf,"******\n");
3108: fprintf(ficresf,"# Covariate valuofcovar yearproj age");
3109: for(j=1; j<=nlstate+ndeath;j++){
3110: for(i=1; i<=nlstate;i++)
3111: fprintf(ficresf," p%d%d",i,j);
3112: fprintf(ficresf," p.%d",j);
3113: }
3114: for (yearp=0; yearp<=(anproj2-anproj1);yearp++) {
3115: fprintf(ficresf,"\n");
3116: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jproj1,mproj1,anproj1+yearp);
3117:
3118: for (agec=fage; agec>=(ageminpar-1); agec--){
3119: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
3120: nhstepm = nhstepm/hstepm;
3121: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
3122: oldm=oldms;savm=savms;
3123: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k);
3124:
3125: for (h=0; h<=nhstepm; h++){
3126: if (h==(int) (YEARM*yearp)) {
3127: fprintf(ficresf,"\n");
3128: for(j=1;j<=cptcoveff;j++)
3129: fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtab[k][j]]);
3130: fprintf(ficresf,"%.f %.f ",anproj1+yearp,agec+h*hstepm/YEARM*stepm);
3131: }
3132: for(j=1; j<=nlstate+ndeath;j++) {
3133: ppij=0.;
3134: for(i=1; i<=nlstate;i++) {
3135: if (mobilav==1)
3136: ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][i][cptcod];
3137: else {
3138: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][cptcod];
3139: }
3140: if (h==(int)(YEARM*yearp))
3141: fprintf(ficresf," %.3f", p3mat[i][j][h]);
3142: }
3143: if (h==(int)(YEARM*yearp)){
3144: fprintf(ficresf," %.3f", ppij);
3145: }
3146: }
3147: }
3148: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
3149: }
3150: }
3151: }
3152: }
3153:
3154: if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX);
3155:
3156: fclose(ficresf);
3157: }
3158:
3159: /************** Forecasting *****not tested NB*************/
3160: 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){
3161:
3162: int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h;
3163: int *popage;
3164: double calagedatem, agelim, kk1, kk2;
3165: double *popeffectif,*popcount;
3166: double ***p3mat,***tabpop,***tabpopprev;
3167: double ***mobaverage;
3168: char filerespop[FILENAMELENGTH];
3169:
3170: tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX);
3171: tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX);
3172: agelim=AGESUP;
3173: calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM;
3174:
3175: prevalence(ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
3176:
3177:
3178: strcpy(filerespop,"pop");
3179: strcat(filerespop,fileres);
3180: if((ficrespop=fopen(filerespop,"w"))==NULL) {
3181: printf("Problem with forecast resultfile: %s\n", filerespop);
3182: fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop);
3183: }
3184: printf("Computing forecasting: result on file '%s' \n", filerespop);
3185: fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop);
3186:
3187: if (cptcoveff==0) ncodemax[cptcoveff]=1;
3188:
3189: if (mobilav!=0) {
3190: mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX);
3191: if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){
3192: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
3193: printf(" Error in movingaverage mobilav=%d\n",mobilav);
3194: }
3195: }
3196:
3197: stepsize=(int) (stepm+YEARM-1)/YEARM;
3198: if (stepm<=12) stepsize=1;
3199:
3200: agelim=AGESUP;
3201:
3202: hstepm=1;
3203: hstepm=hstepm/stepm;
3204:
3205: if (popforecast==1) {
3206: if((ficpop=fopen(popfile,"r"))==NULL) {
3207: printf("Problem with population file : %s\n",popfile);exit(0);
3208: fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0);
3209: }
3210: popage=ivector(0,AGESUP);
3211: popeffectif=vector(0,AGESUP);
3212: popcount=vector(0,AGESUP);
3213:
3214: i=1;
3215: while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1;
3216:
3217: imx=i;
3218: for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i];
3219: }
3220:
3221: for(cptcov=1,k=0;cptcov<=i2;cptcov++){
3222: for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){
3223: k=k+1;
3224: fprintf(ficrespop,"\n#******");
3225: for(j=1;j<=cptcoveff;j++) {
3226: fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtab[k][j]]);
3227: }
3228: fprintf(ficrespop,"******\n");
3229: fprintf(ficrespop,"# Age");
3230: for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j);
3231: if (popforecast==1) fprintf(ficrespop," [Population]");
3232:
3233: for (cpt=0; cpt<=0;cpt++) {
3234: fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt);
3235:
3236: for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){
3237: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm);
3238: nhstepm = nhstepm/hstepm;
3239:
3240: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
3241: oldm=oldms;savm=savms;
3242: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k);
3243:
3244: for (h=0; h<=nhstepm; h++){
3245: if (h==(int) (calagedatem+YEARM*cpt)) {
3246: fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm);
3247: }
3248: for(j=1; j<=nlstate+ndeath;j++) {
3249: kk1=0.;kk2=0;
3250: for(i=1; i<=nlstate;i++) {
3251: if (mobilav==1)
3252: kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod];
3253: else {
3254: kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod];
3255: }
3256: }
3257: if (h==(int)(calagedatem+12*cpt)){
3258: tabpop[(int)(agedeb)][j][cptcod]=kk1;
3259: /*fprintf(ficrespop," %.3f", kk1);
3260: if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*/
3261: }
3262: }
3263: for(i=1; i<=nlstate;i++){
3264: kk1=0.;
3265: for(j=1; j<=nlstate;j++){
3266: kk1= kk1+tabpop[(int)(agedeb)][j][cptcod];
3267: }
3268: tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)];
3269: }
3270:
3271: if (h==(int)(calagedatem+12*cpt)) for(j=1; j<=nlstate;j++)
3272: fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]);
3273: }
3274: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
3275: }
3276: }
3277:
3278: /******/
3279:
3280: for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) {
3281: fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt);
3282: for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){
3283: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm);
3284: nhstepm = nhstepm/hstepm;
3285:
3286: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
3287: oldm=oldms;savm=savms;
3288: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k);
3289: for (h=0; h<=nhstepm; h++){
3290: if (h==(int) (calagedatem+YEARM*cpt)) {
3291: fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm);
3292: }
3293: for(j=1; j<=nlstate+ndeath;j++) {
3294: kk1=0.;kk2=0;
3295: for(i=1; i<=nlstate;i++) {
3296: kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod];
3297: }
3298: if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1);
3299: }
3300: }
3301: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
3302: }
3303: }
3304: }
3305: }
3306:
3307: if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX);
3308:
3309: if (popforecast==1) {
3310: free_ivector(popage,0,AGESUP);
3311: free_vector(popeffectif,0,AGESUP);
3312: free_vector(popcount,0,AGESUP);
3313: }
3314: free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX);
3315: free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX);
3316: fclose(ficrespop);
3317: }
3318:
3319: /***********************************************/
3320: /**************** Main Program *****************/
3321: /***********************************************/
3322:
3323: int main(int argc, char *argv[])
3324: {
3325: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
3326: int i,j, k, n=MAXN,iter,m,size,cptcode, cptcod;
3327: double agedeb, agefin,hf;
3328: double ageminpar=1.e20,agemin=1.e20, agemaxpar=-1.e20, agemax=-1.e20;
3329:
3330: double fret;
3331: double **xi,tmp,delta;
3332:
3333: double dum; /* Dummy variable */
3334: double ***p3mat;
3335: double ***mobaverage;
3336: int *indx;
3337: char line[MAXLINE], linepar[MAXLINE];
3338: char path[80],pathc[80],pathcd[80],pathtot[80],model[80];
3339: int firstobs=1, lastobs=10;
3340: int sdeb, sfin; /* Status at beginning and end */
3341: int c, h , cpt,l;
3342: int ju,jl, mi;
3343: int i1,j1, k1,k2,k3,jk,aa,bb, stepsize, ij;
3344: int jnais,jdc,jint4,jint1,jint2,jint3,**outcome,*tab;
3345: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
3346: int mobilav=0,popforecast=0;
3347: int hstepm, nhstepm;
3348: double jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,jpyram, mpyram,anpyram,jpyram1, mpyram1,anpyram1;
3349:
3350: double bage, fage, age, agelim, agebase;
3351: double ftolpl=FTOL;
3352: double **prlim;
3353: double *severity;
3354: double ***param; /* Matrix of parameters */
3355: double *p;
3356: double **matcov; /* Matrix of covariance */
3357: double ***delti3; /* Scale */
3358: double *delti; /* Scale */
3359: double ***eij, ***vareij;
3360: double **varpl; /* Variances of prevalence limits by age */
3361: double *epj, vepp;
3362: double kk1, kk2;
3363: double dateprev1, dateprev2,jproj1,mproj1,anproj1,jproj2,mproj2,anproj2;
3364:
3365: char *alph[]={"a","a","b","c","d","e"}, str[4];
3366:
3367:
3368: char z[1]="c", occ;
3369: #include <sys/time.h>
3370: #include <time.h>
3371: char stra[80], strb[80], strc[80], strd[80],stre[80],modelsav[80];
3372:
3373: /* long total_usecs;
3374: struct timeval start_time, end_time;
3375:
3376: gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
3377: getcwd(pathcd, size);
3378:
3379: printf("\n%s",version);
3380: if(argc <=1){
3381: printf("\nEnter the parameter file name: ");
3382: scanf("%s",pathtot);
3383: }
3384: else{
3385: strcpy(pathtot,argv[1]);
3386: }
3387: /*if(getcwd(pathcd, 80)!= NULL)printf ("Error pathcd\n");*/
3388: /*cygwin_split_path(pathtot,path,optionfile);
3389: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
3390: /* cutv(path,optionfile,pathtot,'\\');*/
3391:
3392: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
3393: printf("pathtot=%s, path=%s, optionfile=%s optionfilext=%s optionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
3394: chdir(path);
3395: replace(pathc,path);
3396:
3397: /*-------- arguments in the command line --------*/
3398:
3399: /* Log file */
3400: strcat(filelog, optionfilefiname);
3401: strcat(filelog,".log"); /* */
3402: if((ficlog=fopen(filelog,"w"))==NULL) {
3403: printf("Problem with logfile %s\n",filelog);
3404: goto end;
3405: }
3406: fprintf(ficlog,"Log filename:%s\n",filelog);
3407: fprintf(ficlog,"\n%s",version);
3408: fprintf(ficlog,"\nEnter the parameter file name: ");
3409: fprintf(ficlog,"pathtot=%s, path=%s, optionfile=%s optionfilext=%s optionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
3410: fflush(ficlog);
3411:
3412: /* */
3413: strcpy(fileres,"r");
3414: strcat(fileres, optionfilefiname);
3415: strcat(fileres,".txt"); /* Other files have txt extension */
3416:
3417: /*---------arguments file --------*/
3418:
3419: if((ficpar=fopen(optionfile,"r"))==NULL) {
3420: printf("Problem with optionfile %s\n",optionfile);
3421: fprintf(ficlog,"Problem with optionfile %s\n",optionfile);
3422: goto end;
3423: }
3424:
3425: strcpy(filereso,"o");
3426: strcat(filereso,fileres);
3427: if((ficparo=fopen(filereso,"w"))==NULL) {
3428: printf("Problem with Output resultfile: %s\n", filereso);
3429: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
3430: goto end;
3431: }
3432:
3433: /* Reads comments: lines beginning with '#' */
3434: while((c=getc(ficpar))=='#' && c!= EOF){
3435: ungetc(c,ficpar);
3436: fgets(line, MAXLINE, ficpar);
3437: puts(line);
3438: fputs(line,ficparo);
3439: }
3440: ungetc(c,ficpar);
3441:
3442: 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);
3443: 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);
3444: 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);
3445: while((c=getc(ficpar))=='#' && c!= EOF){
3446: ungetc(c,ficpar);
3447: fgets(line, MAXLINE, ficpar);
3448: puts(line);
3449: fputs(line,ficparo);
3450: }
3451: ungetc(c,ficpar);
3452:
3453:
3454: covar=matrix(0,NCOVMAX,1,n);
3455: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement*/
3456: if (strlen(model)>1) cptcovn=nbocc(model,'+')+1;
3457:
3458: ncovmodel=2+cptcovn; /*Number of variables = cptcovn + intercept + age */
3459: nvar=ncovmodel-1; /* Suppressing age as a basic covariate */
3460:
3461: /* Read guess parameters */
3462: /* Reads comments: lines beginning with '#' */
3463: while((c=getc(ficpar))=='#' && c!= EOF){
3464: ungetc(c,ficpar);
3465: fgets(line, MAXLINE, ficpar);
3466: puts(line);
3467: fputs(line,ficparo);
3468: }
3469: ungetc(c,ficpar);
3470:
3471: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
3472: for(i=1; i <=nlstate; i++)
3473: for(j=1; j <=nlstate+ndeath-1; j++){
3474: fscanf(ficpar,"%1d%1d",&i1,&j1);
3475: fprintf(ficparo,"%1d%1d",i1,j1);
3476: if(mle==1)
3477: printf("%1d%1d",i,j);
3478: fprintf(ficlog,"%1d%1d",i,j);
3479: for(k=1; k<=ncovmodel;k++){
3480: fscanf(ficpar," %lf",¶m[i][j][k]);
3481: if(mle==1){
3482: printf(" %lf",param[i][j][k]);
3483: fprintf(ficlog," %lf",param[i][j][k]);
3484: }
3485: else
3486: fprintf(ficlog," %lf",param[i][j][k]);
3487: fprintf(ficparo," %lf",param[i][j][k]);
3488: }
3489: fscanf(ficpar,"\n");
3490: if(mle==1)
3491: printf("\n");
3492: fprintf(ficlog,"\n");
3493: fprintf(ficparo,"\n");
3494: }
3495:
3496: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
3497:
3498: p=param[1][1];
3499:
3500: /* Reads comments: lines beginning with '#' */
3501: while((c=getc(ficpar))=='#' && c!= EOF){
3502: ungetc(c,ficpar);
3503: fgets(line, MAXLINE, ficpar);
3504: puts(line);
3505: fputs(line,ficparo);
3506: }
3507: ungetc(c,ficpar);
3508:
3509: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
3510: delti=vector(1,npar); /* Scale of each paramater (output from hesscov) */
3511: for(i=1; i <=nlstate; i++){
3512: for(j=1; j <=nlstate+ndeath-1; j++){
3513: fscanf(ficpar,"%1d%1d",&i1,&j1);
3514: printf("%1d%1d",i,j);
3515: fprintf(ficparo,"%1d%1d",i1,j1);
3516: for(k=1; k<=ncovmodel;k++){
3517: fscanf(ficpar,"%le",&delti3[i][j][k]);
3518: printf(" %le",delti3[i][j][k]);
3519: fprintf(ficparo," %le",delti3[i][j][k]);
3520: }
3521: fscanf(ficpar,"\n");
3522: printf("\n");
3523: fprintf(ficparo,"\n");
3524: }
3525: }
3526: delti=delti3[1][1];
3527:
3528: /* Reads comments: lines beginning with '#' */
3529: while((c=getc(ficpar))=='#' && c!= EOF){
3530: ungetc(c,ficpar);
3531: fgets(line, MAXLINE, ficpar);
3532: puts(line);
3533: fputs(line,ficparo);
3534: }
3535: ungetc(c,ficpar);
3536:
3537: matcov=matrix(1,npar,1,npar);
3538: for(i=1; i <=npar; i++){
3539: fscanf(ficpar,"%s",&str);
3540: if(mle==1)
3541: printf("%s",str);
3542: fprintf(ficlog,"%s",str);
3543: fprintf(ficparo,"%s",str);
3544: for(j=1; j <=i; j++){
3545: fscanf(ficpar," %le",&matcov[i][j]);
3546: if(mle==1){
3547: printf(" %.5le",matcov[i][j]);
3548: fprintf(ficlog," %.5le",matcov[i][j]);
3549: }
3550: else
3551: fprintf(ficlog," %.5le",matcov[i][j]);
3552: fprintf(ficparo," %.5le",matcov[i][j]);
3553: }
3554: fscanf(ficpar,"\n");
3555: if(mle==1)
3556: printf("\n");
3557: fprintf(ficlog,"\n");
3558: fprintf(ficparo,"\n");
3559: }
3560: for(i=1; i <=npar; i++)
3561: for(j=i+1;j<=npar;j++)
3562: matcov[i][j]=matcov[j][i];
3563:
3564: if(mle==1)
3565: printf("\n");
3566: fprintf(ficlog,"\n");
3567:
3568:
3569: /*-------- Rewriting paramater file ----------*/
3570: strcpy(rfileres,"r"); /* "Rparameterfile */
3571: strcat(rfileres,optionfilefiname); /* Parameter file first name*/
3572: strcat(rfileres,"."); /* */
3573: strcat(rfileres,optionfilext); /* Other files have txt extension */
3574: if((ficres =fopen(rfileres,"w"))==NULL) {
3575: printf("Problem writing new parameter file: %s\n", fileres);goto end;
3576: fprintf(ficlog,"Problem writing new parameter file: %s\n", fileres);goto end;
3577: }
3578: fprintf(ficres,"#%s\n",version);
3579:
3580: /*-------- data file ----------*/
3581: if((fic=fopen(datafile,"r"))==NULL) {
3582: printf("Problem with datafile: %s\n", datafile);goto end;
3583: fprintf(ficlog,"Problem with datafile: %s\n", datafile);goto end;
3584: }
3585:
3586: n= lastobs;
3587: severity = vector(1,maxwav);
3588: outcome=imatrix(1,maxwav+1,1,n);
3589: num=ivector(1,n);
3590: moisnais=vector(1,n);
3591: annais=vector(1,n);
3592: moisdc=vector(1,n);
3593: andc=vector(1,n);
3594: agedc=vector(1,n);
3595: cod=ivector(1,n);
3596: weight=vector(1,n);
3597: for(i=1;i<=n;i++) weight[i]=1.0; /* Equal weights, 1 by default */
3598: mint=matrix(1,maxwav,1,n);
3599: anint=matrix(1,maxwav,1,n);
3600: s=imatrix(1,maxwav+1,1,n);
3601: tab=ivector(1,NCOVMAX);
3602: ncodemax=ivector(1,8);
3603:
3604: i=1;
3605: while (fgets(line, MAXLINE, fic) != NULL) {
3606: if ((i >= firstobs) && (i <=lastobs)) {
3607:
3608: for (j=maxwav;j>=1;j--){
3609: cutv(stra, strb,line,' '); s[j][i]=atoi(strb);
3610: strcpy(line,stra);
3611: cutv(stra, strb,line,'/'); anint[j][i]=(double)(atoi(strb)); strcpy(line,stra);
3612: cutv(stra, strb,line,' '); mint[j][i]=(double)(atoi(strb)); strcpy(line,stra);
3613: }
3614:
3615: cutv(stra, strb,line,'/'); andc[i]=(double)(atoi(strb)); strcpy(line,stra);
3616: cutv(stra, strb,line,' '); moisdc[i]=(double)(atoi(strb)); strcpy(line,stra);
3617:
3618: cutv(stra, strb,line,'/'); annais[i]=(double)(atoi(strb)); strcpy(line,stra);
3619: cutv(stra, strb,line,' '); moisnais[i]=(double)(atoi(strb)); strcpy(line,stra);
3620:
3621: cutv(stra, strb,line,' '); weight[i]=(double)(atoi(strb)); strcpy(line,stra);
3622: for (j=ncovcol;j>=1;j--){
3623: cutv(stra, strb,line,' '); covar[j][i]=(double)(atoi(strb)); strcpy(line,stra);
3624: }
3625: num[i]=atol(stra);
3626:
3627: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
3628: 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;}*/
3629:
3630: i=i+1;
3631: }
3632: }
3633: /* printf("ii=%d", ij);
3634: scanf("%d",i);*/
3635: imx=i-1; /* Number of individuals */
3636:
3637: /* for (i=1; i<=imx; i++){
3638: if ((s[1][i]==3) && (s[2][i]==2)) s[2][i]=3;
3639: if ((s[2][i]==3) && (s[3][i]==2)) s[3][i]=3;
3640: if ((s[3][i]==3) && (s[4][i]==2)) s[4][i]=3;
3641: }*/
3642: /* for (i=1; i<=imx; i++){
3643: if (s[4][i]==9) s[4][i]=-1;
3644: 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]));}*/
3645:
3646: for (i=1; i<=imx; i++)
3647:
3648: /*if ((s[3][i]==3) || (s[4][i]==3)) weight[i]=0.08;
3649: else weight[i]=1;*/
3650:
3651: /* Calculation of the number of parameter from char model*/
3652: Tvar=ivector(1,15); /* stores the number n of the covariates in Vm+Vn at 1 and m at 2 */
3653: Tprod=ivector(1,15);
3654: Tvaraff=ivector(1,15);
3655: Tvard=imatrix(1,15,1,2);
3656: Tage=ivector(1,15);
3657:
3658: if (strlen(model) >1){ /* If there is at least 1 covariate */
3659: j=0, j1=0, k1=1, k2=1;
3660: j=nbocc(model,'+'); /* j=Number of '+' */
3661: j1=nbocc(model,'*'); /* j1=Number of '*' */
3662: cptcovn=j+1;
3663: cptcovprod=j1; /*Number of products */
3664:
3665: strcpy(modelsav,model);
3666: if ((strcmp(model,"age")==0) || (strcmp(model,"age*age")==0)){
3667: printf("Error. Non available option model=%s ",model);
3668: fprintf(ficlog,"Error. Non available option model=%s ",model);
3669: goto end;
3670: }
3671:
3672: /* This loop fills the array Tvar from the string 'model'.*/
3673:
3674: for(i=(j+1); i>=1;i--){
3675: cutv(stra,strb,modelsav,'+'); /* keeps in strb after the last + */
3676: if (nbocc(modelsav,'+')==0) strcpy(strb,modelsav); /* and analyzes it */
3677: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
3678: /*scanf("%d",i);*/
3679: if (strchr(strb,'*')) { /* Model includes a product */
3680: cutv(strd,strc,strb,'*'); /* strd*strc Vm*Vn (if not *age)*/
3681: if (strcmp(strc,"age")==0) { /* Vn*age */
3682: cptcovprod--;
3683: cutv(strb,stre,strd,'V');
3684: Tvar[i]=atoi(stre); /* computes n in Vn and stores in Tvar*/
3685: cptcovage++;
3686: Tage[cptcovage]=i;
3687: /*printf("stre=%s ", stre);*/
3688: }
3689: else if (strcmp(strd,"age")==0) { /* or age*Vn */
3690: cptcovprod--;
3691: cutv(strb,stre,strc,'V');
3692: Tvar[i]=atoi(stre);
3693: cptcovage++;
3694: Tage[cptcovage]=i;
3695: }
3696: else { /* Age is not in the model */
3697: cutv(strb,stre,strc,'V'); /* strc= Vn, stre is n*/
3698: Tvar[i]=ncovcol+k1;
3699: cutv(strb,strc,strd,'V'); /* strd was Vm, strc is m */
3700: Tprod[k1]=i;
3701: Tvard[k1][1]=atoi(strc); /* m*/
3702: Tvard[k1][2]=atoi(stre); /* n */
3703: Tvar[cptcovn+k2]=Tvard[k1][1];
3704: Tvar[cptcovn+k2+1]=Tvard[k1][2];
3705: for (k=1; k<=lastobs;k++)
3706: covar[ncovcol+k1][k]=covar[atoi(stre)][k]*covar[atoi(strc)][k];
3707: k1++;
3708: k2=k2+2;
3709: }
3710: }
3711: else { /* no more sum */
3712: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
3713: /* scanf("%d",i);*/
3714: cutv(strd,strc,strb,'V');
3715: Tvar[i]=atoi(strc);
3716: }
3717: strcpy(modelsav,stra);
3718: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
3719: scanf("%d",i);*/
3720: } /* end of loop + */
3721: } /* end model */
3722:
3723: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
3724: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
3725:
3726: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
3727: printf("cptcovprod=%d ", cptcovprod);
3728: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
3729:
3730: scanf("%d ",i);
3731: fclose(fic);*/
3732:
3733: /* if(mle==1){*/
3734: if (weightopt != 1) { /* Maximisation without weights*/
3735: for(i=1;i<=n;i++) weight[i]=1.0;
3736: }
3737: /*-calculation of age at interview from date of interview and age at death -*/
3738: agev=matrix(1,maxwav,1,imx);
3739:
3740: for (i=1; i<=imx; i++) {
3741: for(m=2; (m<= maxwav); m++) {
3742: if ((mint[m][i]== 99) && (s[m][i] <= nlstate)){
3743: anint[m][i]=9999;
3744: s[m][i]=-1;
3745: }
3746: if(moisdc[i]==99 && andc[i]==9999 & s[m][i]>nlstate) s[m][i]=-1;
3747: }
3748: }
3749:
3750: for (i=1; i<=imx; i++) {
3751: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
3752: for(m=firstpass; (m<= lastpass); m++){
3753: if(s[m][i] >0){
3754: if (s[m][i] >= nlstate+1) {
3755: if(agedc[i]>0)
3756: if(moisdc[i]!=99 && andc[i]!=9999)
3757: agev[m][i]=agedc[i];
3758: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
3759: else {
3760: if (andc[i]!=9999){
3761: printf("Warning negative age at death: %d line:%d\n",num[i],i);
3762: fprintf(ficlog,"Warning negative age at death: %d line:%d\n",num[i],i);
3763: agev[m][i]=-1;
3764: }
3765: }
3766: }
3767: else if(s[m][i] !=9){ /* Standard case, age in fractional
3768: years but with the precision of a
3769: month */
3770: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
3771: if(mint[m][i]==99 || anint[m][i]==9999)
3772: agev[m][i]=1;
3773: else if(agev[m][i] <agemin){
3774: agemin=agev[m][i];
3775: /*printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], agemin);*/
3776: }
3777: else if(agev[m][i] >agemax){
3778: agemax=agev[m][i];
3779: /* printf(" anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.0f\n",m,i,anint[m][i], i,annais[i], agemax);*/
3780: }
3781: /*agev[m][i]=anint[m][i]-annais[i];*/
3782: /* agev[m][i] = age[i]+2*m;*/
3783: }
3784: else { /* =9 */
3785: agev[m][i]=1;
3786: s[m][i]=-1;
3787: }
3788: }
3789: else /*= 0 Unknown */
3790: agev[m][i]=1;
3791: }
3792:
3793: }
3794: for (i=1; i<=imx; i++) {
3795: for(m=firstpass; (m<=lastpass); m++){
3796: if (s[m][i] > (nlstate+ndeath)) {
3797: 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);
3798: 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);
3799: goto end;
3800: }
3801: }
3802: }
3803:
3804: /*for (i=1; i<=imx; i++){
3805: for (m=firstpass; (m<lastpass); m++){
3806: printf("%d %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
3807: }
3808:
3809: }*/
3810:
3811: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, agemin, agemax);
3812: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, agemin, agemax);
3813:
3814: free_vector(severity,1,maxwav);
3815: free_imatrix(outcome,1,maxwav+1,1,n);
3816: free_vector(moisnais,1,n);
3817: free_vector(annais,1,n);
3818: /* free_matrix(mint,1,maxwav,1,n);
3819: free_matrix(anint,1,maxwav,1,n);*/
3820: free_vector(moisdc,1,n);
3821: free_vector(andc,1,n);
3822:
3823:
3824: wav=ivector(1,imx);
3825: dh=imatrix(1,lastpass-firstpass+1,1,imx);
3826: bh=imatrix(1,lastpass-firstpass+1,1,imx);
3827: mw=imatrix(1,lastpass-firstpass+1,1,imx);
3828:
3829: /* Concatenates waves */
3830: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
3831:
3832: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
3833:
3834: Tcode=ivector(1,100);
3835: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
3836: ncodemax[1]=1;
3837: if (cptcovn > 0) tricode(Tvar,nbcode,imx);
3838:
3839: codtab=imatrix(1,100,1,10); /* Cross tabulation to get the order of
3840: the estimations*/
3841: h=0;
3842: m=pow(2,cptcoveff);
3843:
3844: for(k=1;k<=cptcoveff; k++){
3845: for(i=1; i <=(m/pow(2,k));i++){
3846: for(j=1; j <= ncodemax[k]; j++){
3847: for(cpt=1; cpt <=(m/pow(2,cptcoveff+1-k)); cpt++){
3848: h++;
3849: if (h>m) h=1;codtab[h][k]=j;codtab[h][Tvar[k]]=j;
3850: /* printf("h=%d k=%d j=%d codtab[h][k]=%d tvar[k]=%d \n",h, k,j,codtab[h][k],Tvar[k]);*/
3851: }
3852: }
3853: }
3854: }
3855: /* printf("codtab[1][2]=%d codtab[2][2]=%d",codtab[1][2],codtab[2][2]);
3856: codtab[1][2]=1;codtab[2][2]=2; */
3857: /* for(i=1; i <=m ;i++){
3858: for(k=1; k <=cptcovn; k++){
3859: printf("i=%d k=%d %d %d ",i,k,codtab[i][k], cptcoveff);
3860: }
3861: printf("\n");
3862: }
3863: scanf("%d",i);*/
3864:
3865: /* Calculates basic frequencies. Computes observed prevalence at single age
3866: and prints on file fileres'p'. */
3867:
3868: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
3869: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
3870: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
3871: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
3872: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
3873:
3874:
3875: /* For Powell, parameters are in a vector p[] starting at p[1]
3876: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
3877: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
3878:
3879: if(mle>=1){ /* Could be 1 or 2 */
3880: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
3881: }
3882:
3883: /*--------- results files --------------*/
3884: 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);
3885:
3886:
3887: jk=1;
3888: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
3889: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
3890: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
3891: for(i=1,jk=1; i <=nlstate; i++){
3892: for(k=1; k <=(nlstate+ndeath); k++){
3893: if (k != i)
3894: {
3895: printf("%d%d ",i,k);
3896: fprintf(ficlog,"%d%d ",i,k);
3897: fprintf(ficres,"%1d%1d ",i,k);
3898: for(j=1; j <=ncovmodel; j++){
3899: printf("%f ",p[jk]);
3900: fprintf(ficlog,"%f ",p[jk]);
3901: fprintf(ficres,"%f ",p[jk]);
3902: jk++;
3903: }
3904: printf("\n");
3905: fprintf(ficlog,"\n");
3906: fprintf(ficres,"\n");
3907: }
3908: }
3909: }
3910: if(mle==1){
3911: /* Computing hessian and covariance matrix */
3912: ftolhess=ftol; /* Usually correct */
3913: hesscov(matcov, p, npar, delti, ftolhess, func);
3914: }
3915: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
3916: printf("# Scales (for hessian or gradient estimation)\n");
3917: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
3918: for(i=1,jk=1; i <=nlstate; i++){
3919: for(j=1; j <=nlstate+ndeath; j++){
3920: if (j!=i) {
3921: fprintf(ficres,"%1d%1d",i,j);
3922: printf("%1d%1d",i,j);
3923: fprintf(ficlog,"%1d%1d",i,j);
3924: for(k=1; k<=ncovmodel;k++){
3925: printf(" %.5e",delti[jk]);
3926: fprintf(ficlog," %.5e",delti[jk]);
3927: fprintf(ficres," %.5e",delti[jk]);
3928: jk++;
3929: }
3930: printf("\n");
3931: fprintf(ficlog,"\n");
3932: fprintf(ficres,"\n");
3933: }
3934: }
3935: }
3936:
3937: 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");
3938: if(mle==1)
3939: 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");
3940: 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");
3941: for(i=1,k=1;i<=npar;i++){
3942: /* if (k>nlstate) k=1;
3943: i1=(i-1)/(ncovmodel*nlstate)+1;
3944: fprintf(ficres,"%s%d%d",alph[k],i1,tab[i]);
3945: printf("%s%d%d",alph[k],i1,tab[i]);
3946: */
3947: fprintf(ficres,"%3d",i);
3948: if(mle==1)
3949: printf("%3d",i);
3950: fprintf(ficlog,"%3d",i);
3951: for(j=1; j<=i;j++){
3952: fprintf(ficres," %.5e",matcov[i][j]);
3953: if(mle==1)
3954: printf(" %.5e",matcov[i][j]);
3955: fprintf(ficlog," %.5e",matcov[i][j]);
3956: }
3957: fprintf(ficres,"\n");
3958: if(mle==1)
3959: printf("\n");
3960: fprintf(ficlog,"\n");
3961: k++;
3962: }
3963:
3964: while((c=getc(ficpar))=='#' && c!= EOF){
3965: ungetc(c,ficpar);
3966: fgets(line, MAXLINE, ficpar);
3967: puts(line);
3968: fputs(line,ficparo);
3969: }
3970: ungetc(c,ficpar);
3971:
3972: estepm=0;
3973: fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm);
3974: if (estepm==0 || estepm < stepm) estepm=stepm;
3975: if (fage <= 2) {
3976: bage = ageminpar;
3977: fage = agemaxpar;
3978: }
3979:
3980: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
3981: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d\n",ageminpar,agemaxpar,bage,fage, estepm);
3982: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d\n",ageminpar,agemaxpar,bage,fage, estepm);
3983:
3984: while((c=getc(ficpar))=='#' && c!= EOF){
3985: ungetc(c,ficpar);
3986: fgets(line, MAXLINE, ficpar);
3987: puts(line);
3988: fputs(line,ficparo);
3989: }
3990: ungetc(c,ficpar);
3991:
3992: 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);
3993: 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);
3994: 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);
3995: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
3996: fprintf(ficlog,"begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
3997:
3998: while((c=getc(ficpar))=='#' && c!= EOF){
3999: ungetc(c,ficpar);
4000: fgets(line, MAXLINE, ficpar);
4001: puts(line);
4002: fputs(line,ficparo);
4003: }
4004: ungetc(c,ficpar);
4005:
4006:
4007: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
4008: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
4009:
4010: fscanf(ficpar,"pop_based=%d\n",&popbased);
4011: fprintf(ficparo,"pop_based=%d\n",popbased);
4012: fprintf(ficres,"pop_based=%d\n",popbased);
4013:
4014: while((c=getc(ficpar))=='#' && c!= EOF){
4015: ungetc(c,ficpar);
4016: fgets(line, MAXLINE, ficpar);
4017: puts(line);
4018: fputs(line,ficparo);
4019: }
4020: ungetc(c,ficpar);
4021:
4022: fscanf(ficpar,"prevforecast=%d starting-proj-date=%lf/%lf/%lf final-proj-date=%lf/%lf/%lf mobil_average=%d\n",&prevfcast,&jproj1,&mproj1,&anproj1,&jproj2,&mproj2,&anproj2,&mobilavproj);
4023: fprintf(ficparo,"prevforecast=%d starting-proj-date=%.lf/%.lf/%.lf final-proj-date=%.lf/%.lf/%.lf mobil_average=%d\n",prevfcast,jproj1,mproj1,anproj1,jproj2,mproj2,anproj2,mobilavproj);
4024: printf("prevforecast=%d starting-proj-date=%.lf/%.lf/%.lf final-proj-date=%.lf/%.lf/%.lf mobil_average=%d\n",prevfcast,jproj1,mproj1,anproj1,jproj2,mproj2,anproj2,mobilavproj);
4025: fprintf(ficlog,"prevforecast=%d starting-proj-date=%.lf/%.lf/%.lf final-proj-date=%.lf/%.lf/%.lf mobil_average=%d\n",prevfcast,jproj1,mproj1,anproj1,jproj2,mproj2,anproj2,mobilavproj);
4026: fprintf(ficres,"prevforecast=%d starting-proj-date=%.lf/%.lf/%.lf final-proj-date=%.lf/%.lf/%.lf mobil_average=%d\n",prevfcast,jproj1,mproj1,anproj1,jproj2,mproj2,anproj2,mobilavproj);
4027: /* day and month of proj2 are not used but only year anproj2.*/
4028:
4029: while((c=getc(ficpar))=='#' && c!= EOF){
4030: ungetc(c,ficpar);
4031: fgets(line, MAXLINE, ficpar);
4032: puts(line);
4033: fputs(line,ficparo);
4034: }
4035: ungetc(c,ficpar);
4036:
4037: fscanf(ficpar,"popforecast=%d popfile=%s popfiledate=%lf/%lf/%lf last-popfiledate=%lf/%lf/%lf\n",&popforecast,popfile,&jpyram,&mpyram,&anpyram,&jpyram1,&mpyram1,&anpyram1);
4038: fprintf(ficparo,"popforecast=%d popfile=%s popfiledate=%.lf/%.lf/%.lf last-popfiledate=%.lf/%.lf/%.lf\n",popforecast,popfile,jpyram,mpyram,anpyram,jpyram1,mpyram1,anpyram1);
4039: fprintf(ficres,"popforecast=%d popfile=%s popfiledate=%.lf/%.lf/%.lf last-popfiledate=%.lf/%.lf/%.lf\n",popforecast,popfile,jpyram,mpyram,anpyram,jpyram1,mpyram1,anpyram1);
4040:
4041: freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);
4042:
4043: /*------------ gnuplot -------------*/
4044: strcpy(optionfilegnuplot,optionfilefiname);
4045: strcat(optionfilegnuplot,".gp");
4046: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
4047: printf("Problem with file %s",optionfilegnuplot);
4048: }
4049: else{
4050: fprintf(ficgp,"\n# %s\n", version);
4051: fprintf(ficgp,"# %s\n", optionfilegnuplot);
4052: fprintf(ficgp,"set missing 'NaNq'\n");
4053: }
4054: fclose(ficgp);
4055: printinggnuplot(fileres, ageminpar,agemaxpar,fage, pathc,p);
4056: /*--------- index.htm --------*/
4057:
4058: strcpy(optionfilehtm,optionfile);
4059: strcat(optionfilehtm,".htm");
4060: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
4061: printf("Problem with %s \n",optionfilehtm), exit(0);
4062: }
4063:
4064: fprintf(fichtm,"<body> <font size=\"2\">%s </font> <hr size=\"2\" color=\"#EC5E5E\"> \n
4065: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=%s<br>\n
4066: \n
4067: Total number of observations=%d <br>\n
4068: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n
4069: <hr size=\"2\" color=\"#EC5E5E\">
4070: <ul><li><h4>Parameter files</h4>\n
4071: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n
4072: - Log file of the run: <a href=\"%s\">%s</a><br>\n
4073: - 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);
4074: fclose(fichtm);
4075:
4076: printinghtml(fileres,title,datafile, firstpass, lastpass, stepm, weightopt,model,imx,jmin,jmax,jmean,rfileres,popforecast,estepm,jprev1,mprev1,anprev1,jprev2,mprev2,anprev2);
4077:
4078: /*------------ free_vector -------------*/
4079: chdir(path);
4080:
4081: free_ivector(wav,1,imx);
4082: free_imatrix(dh,1,lastpass-firstpass+1,1,imx);
4083: free_imatrix(bh,1,lastpass-firstpass+1,1,imx);
4084: free_imatrix(mw,1,lastpass-firstpass+1,1,imx);
4085: free_ivector(num,1,n);
4086: free_vector(agedc,1,n);
4087: /*free_matrix(covar,0,NCOVMAX,1,n);*/
4088: /*free_matrix(covar,1,NCOVMAX,1,n);*/
4089: fclose(ficparo);
4090: fclose(ficres);
4091:
4092:
4093: /*--------------- Prevalence limit (stable prevalence) --------------*/
4094:
4095: strcpy(filerespl,"pl");
4096: strcat(filerespl,fileres);
4097: if((ficrespl=fopen(filerespl,"w"))==NULL) {
4098: printf("Problem with stable prevalence resultfile: %s\n", filerespl);goto end;
4099: fprintf(ficlog,"Problem with stable prevalence resultfile: %s\n", filerespl);goto end;
4100: }
4101: printf("Computing stable prevalence: result on file '%s' \n", filerespl);
4102: fprintf(ficlog,"Computing stable prevalence: result on file '%s' \n", filerespl);
4103: fprintf(ficrespl,"#Stable prevalence \n");
4104: fprintf(ficrespl,"#Age ");
4105: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
4106: fprintf(ficrespl,"\n");
4107:
4108: prlim=matrix(1,nlstate,1,nlstate);
4109:
4110: agebase=ageminpar;
4111: agelim=agemaxpar;
4112: ftolpl=1.e-10;
4113: i1=cptcoveff;
4114: if (cptcovn < 1){i1=1;}
4115:
4116: for(cptcov=1,k=0;cptcov<=i1;cptcov++){
4117: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
4118: k=k+1;
4119: /*printf("cptcov=%d cptcod=%d codtab=%d nbcode=%d\n",cptcov, cptcod,Tcode[cptcode],codtab[cptcod][cptcov]);*/
4120: fprintf(ficrespl,"\n#******");
4121: printf("\n#******");
4122: fprintf(ficlog,"\n#******");
4123: for(j=1;j<=cptcoveff;j++) {
4124: fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtab[k][j]]);
4125: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtab[k][j]]);
4126: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtab[k][j]]);
4127: }
4128: fprintf(ficrespl,"******\n");
4129: printf("******\n");
4130: fprintf(ficlog,"******\n");
4131:
4132: for (age=agebase; age<=agelim; age++){
4133: prevalim(prlim, nlstate, p, age, oldm, savm,ftolpl,k);
4134: fprintf(ficrespl,"%.0f ",age );
4135: for(j=1;j<=cptcoveff;j++)
4136: fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtab[k][j]]);
4137: for(i=1; i<=nlstate;i++)
4138: fprintf(ficrespl," %.5f", prlim[i][i]);
4139: fprintf(ficrespl,"\n");
4140: }
4141: }
4142: }
4143: fclose(ficrespl);
4144:
4145: /*------------- h Pij x at various ages ------------*/
4146:
4147: strcpy(filerespij,"pij"); strcat(filerespij,fileres);
4148: if((ficrespij=fopen(filerespij,"w"))==NULL) {
4149: printf("Problem with Pij resultfile: %s\n", filerespij);goto end;
4150: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij);goto end;
4151: }
4152: printf("Computing pij: result on file '%s' \n", filerespij);
4153: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
4154:
4155: stepsize=(int) (stepm+YEARM-1)/YEARM;
4156: /*if (stepm<=24) stepsize=2;*/
4157:
4158: agelim=AGESUP;
4159: hstepm=stepsize*YEARM; /* Every year of age */
4160: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
4161:
4162: /* hstepm=1; aff par mois*/
4163:
4164: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
4165: for(cptcov=1,k=0;cptcov<=i1;cptcov++){
4166: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
4167: k=k+1;
4168: fprintf(ficrespij,"\n#****** ");
4169: for(j=1;j<=cptcoveff;j++)
4170: fprintf(ficrespij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtab[k][j]]);
4171: fprintf(ficrespij,"******\n");
4172:
4173: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
4174: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
4175: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
4176:
4177: /* nhstepm=nhstepm*YEARM; aff par mois*/
4178:
4179: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
4180: oldm=oldms;savm=savms;
4181: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k);
4182: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
4183: for(i=1; i<=nlstate;i++)
4184: for(j=1; j<=nlstate+ndeath;j++)
4185: fprintf(ficrespij," %1d-%1d",i,j);
4186: fprintf(ficrespij,"\n");
4187: for (h=0; h<=nhstepm; h++){
4188: fprintf(ficrespij,"%d %3.f %3.f",k,agedeb, agedeb+ h*hstepm/YEARM*stepm );
4189: for(i=1; i<=nlstate;i++)
4190: for(j=1; j<=nlstate+ndeath;j++)
4191: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
4192: fprintf(ficrespij,"\n");
4193: }
4194: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
4195: fprintf(ficrespij,"\n");
4196: }
4197: }
4198: }
4199:
4200: varprob(optionfilefiname, matcov, p, delti, nlstate, (int) bage, (int) fage,k,Tvar,nbcode, ncodemax);
4201:
4202: fclose(ficrespij);
4203:
4204:
4205: /*---------- Forecasting ------------------*/
4206: /*if((stepm == 1) && (strcmp(model,".")==0)){*/
4207: if(prevfcast==1){
4208: if(stepm ==1){
4209: prevforecast(fileres, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);
4210: if (popforecast==1) populforecast(fileres, anpyram,mpyram,jpyram, agemin,agemax, dateprev1, dateprev2,mobilav, agedeb, fage, popforecast, popfile, anpyram1,p, i1);
4211: }
4212: else{
4213: erreur=108;
4214: 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);
4215: 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);
4216: }
4217: }
4218:
4219:
4220: /*---------- Health expectancies and variances ------------*/
4221:
4222: strcpy(filerest,"t");
4223: strcat(filerest,fileres);
4224: if((ficrest=fopen(filerest,"w"))==NULL) {
4225: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
4226: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
4227: }
4228: printf("Computing Total LEs with variances: file '%s' \n", filerest);
4229: fprintf(ficlog,"Computing Total LEs with variances: file '%s' \n", filerest);
4230:
4231:
4232: strcpy(filerese,"e");
4233: strcat(filerese,fileres);
4234: if((ficreseij=fopen(filerese,"w"))==NULL) {
4235: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
4236: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
4237: }
4238: printf("Computing Health Expectancies: result on file '%s' \n", filerese);
4239: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' \n", filerese);
4240:
4241: strcpy(fileresv,"v");
4242: strcat(fileresv,fileres);
4243: if((ficresvij=fopen(fileresv,"w"))==NULL) {
4244: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
4245: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
4246: }
4247: printf("Computing Variance-covariance of DFLEs: file '%s' \n", fileresv);
4248: fprintf(ficlog,"Computing Variance-covariance of DFLEs: file '%s' \n", fileresv);
4249:
4250: prevalence(ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
4251:
4252: if (mobilav!=0) {
4253: mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX);
4254: if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){
4255: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
4256: printf(" Error in movingaverage mobilav=%d\n",mobilav);
4257: }
4258: }
4259:
4260: for(cptcov=1,k=0;cptcov<=i1;cptcov++){
4261: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
4262: k=k+1;
4263: fprintf(ficrest,"\n#****** ");
4264: for(j=1;j<=cptcoveff;j++)
4265: fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtab[k][j]]);
4266: fprintf(ficrest,"******\n");
4267:
4268: fprintf(ficreseij,"\n#****** ");
4269: for(j=1;j<=cptcoveff;j++)
4270: fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtab[k][j]]);
4271: fprintf(ficreseij,"******\n");
4272:
4273: fprintf(ficresvij,"\n#****** ");
4274: for(j=1;j<=cptcoveff;j++)
4275: fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtab[k][j]]);
4276: fprintf(ficresvij,"******\n");
4277:
4278: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
4279: oldm=oldms;savm=savms;
4280: evsij(fileres, eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov);
4281:
4282: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
4283: oldm=oldms;savm=savms;
4284: varevsij(optionfilefiname, vareij, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl,k, estepm, cptcov,cptcod,0, mobilav);
4285: if(popbased==1){
4286: varevsij(optionfilefiname, vareij, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl,k, estepm, cptcov,cptcod,popbased,mobilav);
4287: }
4288:
4289:
4290: fprintf(ficrest,"#Total LEs with variances: e.. (std) ");
4291: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
4292: fprintf(ficrest,"\n");
4293:
4294: epj=vector(1,nlstate+1);
4295: for(age=bage; age <=fage ;age++){
4296: prevalim(prlim, nlstate, p, age, oldm, savm,ftolpl,k);
4297: if (popbased==1) {
4298: if(mobilav ==0){
4299: for(i=1; i<=nlstate;i++)
4300: prlim[i][i]=probs[(int)age][i][k];
4301: }else{ /* mobilav */
4302: for(i=1; i<=nlstate;i++)
4303: prlim[i][i]=mobaverage[(int)age][i][k];
4304: }
4305: }
4306:
4307: fprintf(ficrest," %4.0f",age);
4308: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
4309: for(i=1, epj[j]=0.;i <=nlstate;i++) {
4310: epj[j] += prlim[i][i]*eij[i][j][(int)age];
4311: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
4312: }
4313: epj[nlstate+1] +=epj[j];
4314: }
4315:
4316: for(i=1, vepp=0.;i <=nlstate;i++)
4317: for(j=1;j <=nlstate;j++)
4318: vepp += vareij[i][j][(int)age];
4319: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
4320: for(j=1;j <=nlstate;j++){
4321: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
4322: }
4323: fprintf(ficrest,"\n");
4324: }
4325: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
4326: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
4327: free_vector(epj,1,nlstate+1);
4328: }
4329: }
4330: free_vector(weight,1,n);
4331: free_imatrix(Tvard,1,15,1,2);
4332: free_imatrix(s,1,maxwav+1,1,n);
4333: free_matrix(anint,1,maxwav,1,n);
4334: free_matrix(mint,1,maxwav,1,n);
4335: free_ivector(cod,1,n);
4336: free_ivector(tab,1,NCOVMAX);
4337: fclose(ficreseij);
4338: fclose(ficresvij);
4339: fclose(ficrest);
4340: fclose(ficpar);
4341:
4342: /*------- Variance of stable prevalence------*/
4343:
4344: strcpy(fileresvpl,"vpl");
4345: strcat(fileresvpl,fileres);
4346: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
4347: printf("Problem with variance of stable prevalence resultfile: %s\n", fileresvpl);
4348: exit(0);
4349: }
4350: printf("Computing Variance-covariance of stable prevalence: file '%s' \n", fileresvpl);
4351:
4352: for(cptcov=1,k=0;cptcov<=i1;cptcov++){
4353: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
4354: k=k+1;
4355: fprintf(ficresvpl,"\n#****** ");
4356: for(j=1;j<=cptcoveff;j++)
4357: fprintf(ficresvpl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtab[k][j]]);
4358: fprintf(ficresvpl,"******\n");
4359:
4360: varpl=matrix(1,nlstate,(int) bage, (int) fage);
4361: oldm=oldms;savm=savms;
4362: varprevlim(fileres, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl,k);
4363: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
4364: }
4365: }
4366:
4367: fclose(ficresvpl);
4368:
4369: /*---------- End : free ----------------*/
4370: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
4371: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
4372: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
4373: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
4374:
4375: free_matrix(covar,0,NCOVMAX,1,n);
4376: free_matrix(matcov,1,npar,1,npar);
4377: free_vector(delti,1,npar);
4378: free_matrix(agev,1,maxwav,1,imx);
4379: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
4380: if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX);
4381: free_ivector(ncodemax,1,8);
4382: free_ivector(Tvar,1,15);
4383: free_ivector(Tprod,1,15);
4384: free_ivector(Tvaraff,1,15);
4385: free_ivector(Tage,1,15);
4386: free_ivector(Tcode,1,100);
4387:
4388: fprintf(fichtm,"\n</body>");
4389: fclose(fichtm);
4390: fclose(ficgp);
4391:
4392:
4393: if(erreur >0){
4394: printf("End of Imach with error or warning %d\n",erreur);
4395: fprintf(ficlog,"End of Imach with error or warning %d\n",erreur);
4396: }else{
4397: printf("End of Imach\n");
4398: fprintf(ficlog,"End of Imach\n");
4399: }
4400: printf("See log file on %s\n",filelog);
4401: fclose(ficlog);
4402: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
4403:
4404: /* 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);*/
4405: /*printf("Total time was %d uSec.\n", total_usecs);*/
4406: /*------ End -----------*/
4407:
4408: end:
4409: #ifdef windows
4410: /* chdir(pathcd);*/
4411: #endif
4412: /*system("wgnuplot graph.plt");*/
4413: /*system("../gp37mgw/wgnuplot graph.plt");*/
4414: /*system("cd ../gp37mgw");*/
4415: /* system("..\\gp37mgw\\wgnuplot graph.plt");*/
4416: strcpy(plotcmd,GNUPLOTPROGRAM);
4417: strcat(plotcmd," ");
4418: strcat(plotcmd,optionfilegnuplot);
4419: printf("Starting: %s\n",plotcmd);fflush(stdout);
4420: system(plotcmd);
4421:
4422: /*#ifdef windows*/
4423: while (z[0] != 'q') {
4424: /* chdir(path); */
4425: printf("\nType e to edit output files, g to graph again, c to start again, and q for exiting: ");
4426: scanf("%s",z);
4427: if (z[0] == 'c') system("./imach");
4428: else if (z[0] == 'e') system(optionfilehtm);
4429: else if (z[0] == 'g') system(plotcmd);
4430: else if (z[0] == 'q') exit(0);
4431: }
4432: /*#endif */
4433: }
4434:
4435:
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