--- imach096d/src/imach.c 2002/11/18 23:01:13 1.59 +++ imach096d/src/imach.c 2003/02/04 12:40:59 1.68 @@ -1,4 +1,4 @@ -/* $Id: imach.c,v 1.59 2002/11/18 23:01:13 brouard Exp $ +/* $Id: imach.c,v 1.68 2003/02/04 12:40:59 lievre Exp $ Interpolated Markov Chain Short summary of the programme: @@ -32,8 +32,8 @@ hPijx is the probability to be observed in state i at age x+h conditional to the observed state i at age x. The delay 'h' can be split into an exact number (nh*stepm) of unobserved intermediate - states. This elementary transition (by month or quarter trimester, - semester or year) is model as a multinomial logistic. The hPx + states. This elementary transition (by month, quarter, + semester or year) is modelled as a multinomial logistic. The hPx matrix is simply the matrix product of nh*stepm elementary matrices and the contribution of each individual to the likelihood is simply hPijx. @@ -83,7 +83,7 @@ #define ODIRSEPARATOR '\\' #endif -char version[80]="Imach version 0.9, November 2002, INED-EUROREVES "; +char version[80]="Imach version 0.91, November 2002, INED-EUROREVES "; int erreur; /* Error number */ int nvar; int cptcovn=0, cptcovage=0, cptcoveff=0,cptcov; @@ -856,11 +856,13 @@ double **matprod2(double **out, double * double ***hpxij(double ***po, int nhstepm, double age, int hstepm, double *x, int nlstate, int stepm, double **oldm, double **savm, int ij ) { - /* Computes the transition matrix starting at age 'age' over 'nhstepm*hstepm*stepm' month - duration (i.e. until - age (in years) age+nhstepm*stepm/12) by multiplying nhstepm*hstepm matrices. + /* Computes the transition matrix starting at age 'age' over + 'nhstepm*hstepm*stepm' months (i.e. until + age (in years) age+nhstepm*hstepm*stepm/12) by multiplying + nhstepm*hstepm matrices. Output is stored in matrix po[i][j][h] for h every 'hstepm' step - (typically every 2 years instead of every month which is too big). + (typically every 2 years instead of every month which is too big + for the memory). Model is determined by parameters x and covariates have to be included manually here. @@ -917,7 +919,7 @@ double func( double *x) double sw; /* Sum of weights */ double lli; /* Individual log likelihood */ int s1, s2; - double bbh; + double bbh, survp; long ipmx; /*extern weight */ /* We are differentiating ll according to initial status */ @@ -928,56 +930,195 @@ double func( double *x) cov[1]=1.; for(k=1; k<=nlstate; k++) ll[k]=0.; - for (i=1,ipmx=0, sw=0.; i<=imx; i++){ - for (k=1; k<=cptcovn;k++) cov[2+k]=covar[Tvar[k]][i]; - for(mi=1; mi<= wav[i]-1; mi++){ - for (ii=1;ii<=nlstate+ndeath;ii++) - for (j=1;j<=nlstate+ndeath;j++){ - oldm[ii][j]=(ii==j ? 1.0 : 0.0); - savm[ii][j]=(ii==j ? 1.0 : 0.0); - } - for(d=0; d 1 the results are less biased than in previous versions. + */ + s1=s[mw[mi][i]][i]; + s2=s[mw[mi+1][i]][i]; + bbh=(double)bh[mi][i]/(double)stepm; + /* bias is positive if real duration + * is higher than the multiple of stepm and negative otherwise. + */ + /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/ + /* if s2=-2 lli=out[1][1]+out[1][2];*/ + if (s2==-2) { + for (j=1,survp=0. ; j<=nlstate; j++) + survp += out[s1][j]; + lli= survp; } + + else + 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 */ + /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/ + /*if(lli ==000.0)*/ + /*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); */ + ipmx +=1; + sw += weight[i]; + ll[s[mw[mi][i]][i]] += 2*weight[i]*lli; + } /* end of wave */ + } /* end of individual */ + } else if(mle==2){ + for (i=1,ipmx=0, sw=0.; i<=imx; i++){ + for (k=1; k<=cptcovn;k++) cov[2+k]=covar[Tvar[k]][i]; + for(mi=1; mi<= wav[i]-1; mi++){ + for (ii=1;ii<=nlstate+ndeath;ii++) + for (j=1;j<=nlstate+ndeath;j++){ + oldm[ii][j]=(ii==j ? 1.0 : 0.0); + savm[ii][j]=(ii==j ? 1.0 : 0.0); + } + for(d=0; d<=dh[mi][i]; d++){ + newm=savm; + cov[2]=agev[mw[mi][i]][i]+d*stepm/YEARM; + for (kk=1; kk<=cptcovage;kk++) { + cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2]; + } + out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, + 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); + savm=oldm; + oldm=newm; + } /* end mult */ + + /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */ + /* But now since version 0.9 we anticipate for bias and large stepm. + * If stepm is larger than one month (smallest stepm) and if the exact delay + * (in months) between two waves is not a multiple of stepm, we rounded to + * the nearest (and in case of equal distance, to the lowest) interval but now + * we keep into memory the bias bh[mi][i] and also the previous matrix product + * (i.e to dh[mi][i]-1) saved in 'savm'. The we inter(extra)polate the + * probability in order to take into account the bias as a fraction of the way + * from savm to out if bh is neagtive or even beyond if bh is positive. bh varies + * -stepm/2 to stepm/2 . + * For stepm=1 the results are the same as for previous versions of Imach. + * For stepm > 1 the results are less biased than in previous versions. + */ + s1=s[mw[mi][i]][i]; + s2=s[mw[mi+1][i]][i]; + bbh=(double)bh[mi][i]/(double)stepm; + /* bias is positive if real duration + * is higher than the multiple of stepm and negative otherwise. + */ + 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 */ + /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/ + /*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 */ + /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/ + /*if(lli ==000.0)*/ + /*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); */ + ipmx +=1; + sw += weight[i]; + ll[s[mw[mi][i]][i]] += 2*weight[i]*lli; + } /* end of wave */ + } /* end of individual */ + } else if(mle==3){ /* exponential inter-extrapolation */ + for (i=1,ipmx=0, sw=0.; i<=imx; i++){ + for (k=1; k<=cptcovn;k++) cov[2+k]=covar[Tvar[k]][i]; + for(mi=1; mi<= wav[i]-1; mi++){ + for (ii=1;ii<=nlstate+ndeath;ii++) + for (j=1;j<=nlstate+ndeath;j++){ + oldm[ii][j]=(ii==j ? 1.0 : 0.0); + savm[ii][j]=(ii==j ? 1.0 : 0.0); + } + for(d=0; d 1 the results are less biased than in previous versions. + */ + s1=s[mw[mi][i]][i]; + s2=s[mw[mi+1][i]][i]; + bbh=(double)bh[mi][i]/(double)stepm; + /* bias is positive if real duration + * is higher than the multiple of stepm and negative otherwise. + */ + /* 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 */ + 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 */ + /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/ + /*if(lli ==000.0)*/ + /*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); */ + ipmx +=1; + sw += weight[i]; + ll[s[mw[mi][i]][i]] += 2*weight[i]*lli; + } /* end of wave */ + } /* end of individual */ + }else{ /* ml=4 no inter-extrapolation */ + for (i=1,ipmx=0, sw=0.; i<=imx; i++){ + for (k=1; k<=cptcovn;k++) cov[2+k]=covar[Tvar[k]][i]; + for(mi=1; mi<= wav[i]-1; mi++){ + for (ii=1;ii<=nlstate+ndeath;ii++) + for (j=1;j<=nlstate+ndeath;j++){ + oldm[ii][j]=(ii==j ? 1.0 : 0.0); + savm[ii][j]=(ii==j ? 1.0 : 0.0); + } + for(d=0; d 1 the results are less biased than in previous versions. - */ - s1=s[mw[mi][i]][i]; - s2=s[mw[mi+1][i]][i]; - bbh=(double)bh[mi][i]/(double)stepm; - lli= (savm[s1][s2]>(double)1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.-bbh)*out[s1][s2])); - /*lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.-bbh)*out[s1][s2]));*/ - /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/ - /*if(lli ==000.0)*/ - /*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); */ - ipmx +=1; - sw += weight[i]; - ll[s[mw[mi][i]][i]] += 2*weight[i]*lli; - } /* end of wave */ - } /* end of individual */ - + lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */ + ipmx +=1; + sw += weight[i]; + ll[s[mw[mi][i]][i]] += 2*weight[i]*lli; + } /* end of wave */ + } /* end of individual */ + } /* End of if */ for(k=1,l=0.; k<=nlstate; k++) l += ll[k]; /* printf("l1=%f l2=%f ",ll[1],ll[2]); */ l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */ @@ -1000,7 +1141,7 @@ void mlikeli(FILE *ficres,double p[], in powell(p,xi,npar,ftol,&iter,&fret,func); printf("\n#Number of iterations = %d, -2 Log likelihood = %.12f\n",iter,func(p)); - fprintf(ficlog,"#Number of iterations = %d, -2 Log likelihood = %.12f \n",iter,func(p)); + fprintf(ficlog,"\n#Number of iterations = %d, -2 Log likelihood = %.12f \n",iter,func(p)); fprintf(ficres,"#Number of iterations = %d, -2 Log likelihood = %.12f \n",iter,func(p)); } @@ -1283,7 +1424,7 @@ void freqsummary(char fileres[], int ag fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp); exit(0); } - freq= ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,agemin,agemax+3); + freq= ma3x(-2,nlstate+ndeath,-2,nlstate+ndeath,agemin,agemax+3); j1=0; j=cptcoveff; @@ -1398,8 +1539,8 @@ void freqsummary(char fileres[], int ag } } - for(jk=-1; jk <=nlstate+ndeath; jk++) - for(m=-1; m <=nlstate+ndeath; m++) + for(jk=-2; jk <=nlstate+ndeath; jk++) + for(m=-2; m <=nlstate+ndeath; m++) if(freq[jk][m][i] !=0 ) { if(first==1) printf(" %d%d=%.0f",jk,m,freq[jk][m][i]); @@ -1416,7 +1557,7 @@ void freqsummary(char fileres[], int ag dateintmean=dateintsum/k2cpt; fclose(ficresp); - free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath,(int) agemin,(int) agemax+3); + free_ma3x(freq,-2,nlstate+ndeath,-2,nlstate+ndeath,(int) agemin,(int) agemax+3); free_vector(pp,1,nlstate); /* End of Freq */ @@ -1433,7 +1574,7 @@ void prevalence(int agemin, float agemax pp=vector(1,nlstate); - freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,agemin,agemax+3); + freq=ma3x(-2,nlstate+ndeath,-2,nlstate+ndeath,agemin,agemax+3); j1=0; j=cptcoveff; @@ -1443,8 +1584,8 @@ void prevalence(int agemin, float agemax for(i1=1; i1<=ncodemax[k1];i1++){ j1++; - for (i=-1; i<=nlstate+ndeath; i++) - for (jk=-1; jk<=nlstate+ndeath; jk++) + for (i=-2; i<=nlstate+ndeath; i++) + for (jk=-2; jk<=nlstate+ndeath; jk++) for(m=agemin; m <= agemax+3; m++) freq[i][jk][m]=0; @@ -1501,7 +1642,7 @@ void prevalence(int agemin, float agemax } /* end k1 */ - free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath,(int) agemin,(int) agemax+3); + free_ma3x(freq,-2,nlstate+ndeath,-2,nlstate+ndeath,(int) agemin,(int) agemax+3); free_vector(pp,1,nlstate); } /* End of Freq */ @@ -1531,7 +1672,7 @@ void concatwav(int wav[], int **dh, int mi=0; m=firstpass; while(s[m][i] <= nlstate){ - if(s[m][i]>=1) + if(s[m][i]>=1 || s[m][i]==-2) mw[++mi][i]=m; if(m >=lastpass) break; @@ -1571,10 +1712,12 @@ void concatwav(int wav[], int **dh, int if (j <= jmin) jmin=j; sum=sum+j; /*if (j<0) printf("j=%d num=%d \n",j,i); */ + /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/ } } else{ j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12)); + /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/ k=k+1; if (j >= jmax) jmax=j; else if (j <= jmin)jmin=j; @@ -1584,22 +1727,34 @@ void concatwav(int wav[], int **dh, int jk= j/stepm; jl= j -jk*stepm; ju= j -(jk+1)*stepm; - if(jl <= -ju){ - dh[mi][i]=jk; - bh[mi][i]=jl; - } - else{ - dh[mi][i]=jk+1; - bh[mi][i]=ju; - } - if(dh[mi][i]==0){ - dh[mi][i]=1; /* At least one step */ - bh[mi][i]=ju; /* At least one step */ - 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); + if(mle <=1){ + if(jl==0){ + dh[mi][i]=jk; + bh[mi][i]=0; + }else{ /* We want a negative bias in order to only have interpolation ie + * at the price of an extra matrix product in likelihood */ + dh[mi][i]=jk+1; + bh[mi][i]=ju; + } + }else{ + if(jl <= -ju){ + dh[mi][i]=jk; + bh[mi][i]=jl; /* bias is positive if real duration + * is higher than the multiple of stepm and negative otherwise. + */ + } + else{ + dh[mi][i]=jk+1; + bh[mi][i]=ju; + } + if(dh[mi][i]==0){ + dh[mi][i]=1; /* At least one step */ + bh[mi][i]=ju; /* At least one step */ + 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); + } } - if(i==298 || i==287 || i==763 ||i==1061)printf(" bh=%d ju=%d jl=%d dh=%d jk=%d stepm=%d",bh[mi][i],ju,jl,dh[mi][i],jk,stepm); - } - } + } /* end if mle */ + } /* end wave */ } jmean=sum/k; printf("Delay (in months) between two waves Min=%d Max=%d Mean=%f\n\n ",jmin, jmax,jmean); @@ -1700,7 +1855,7 @@ void evsij(char fileres[], double ***eij * This is mainly to measure the difference between two models: for example * if stepm=24 months pijx are given only every 2 years and by summing them * we are calculating an estimate of the Life Expectancy assuming a linear - * progression inbetween and thus overestimating or underestimating according + * progression in between and thus overestimating or underestimating according * to the curvature of the survival function. If, for the same date, we * estimate the model with stepm=1 month, we can keep estepm to 24 months * to compare the new estimate of Life expectancy with the same linear @@ -1890,7 +2045,7 @@ void varevsij(char optionfilefiname[], d } printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev); fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev); - fprintf(ficresprobmorprev,"# probabilities of dying during a year and weighted mean w1*p1j+w2*p2j+... stand dev in()\n"); + 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); fprintf(ficresprobmorprev,"# Age cov=%-d",ij); for(j=nlstate+1; j<=(nlstate+ndeath);j++){ fprintf(ficresprobmorprev," p.%-d SE",j); @@ -1912,8 +2067,8 @@ void varevsij(char optionfilefiname[], d exit(0); } else{ - fprintf(fichtm,"\n

  • Computing probabilities of dying as a weighted average (i.e global mortality independent of initial healh state)

    • \n"); - fprintf(fichtm,"\n
    %s (à revoir)
    \n",digitp); + fprintf(fichtm,"\n

  • Computing probabilities of dying over estepm months as a weighted average (i.e global mortality independent of initial healh state)

    • \n"); + fprintf(fichtm,"\n
    %s
    \n",digitp); } varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath); @@ -1947,7 +2102,7 @@ void varevsij(char optionfilefiname[], d and note for a fixed period like k years */ /* We decided (b) to get a life expectancy respecting the most precise curvature of the survival function given by stepm (the optimization length). Unfortunately it - means that if the survival funtion is printed only each two years of age and if + means that if the survival funtion is printed every two years of age and if you sum them up and add 1 year (area under the trapezoids) you won't get the same results. So we changed our mind and took the option of the best precision. */ @@ -1963,7 +2118,7 @@ void varevsij(char optionfilefiname[], d for(theta=1; theta <=npar; theta++){ - for(i=1; i<=npar; i++){ /* Computes gradient */ + for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/ xp[i] = x[i] + (i==theta ?delti[theta]:0); } hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij); @@ -1985,14 +2140,17 @@ void varevsij(char optionfilefiname[], d gp[h][j] += prlim[i][i]*p3mat[i][j][h]; } } - /* This for computing forces of mortality (h=1)as a weighted average */ + /* This for computing probability of death (h=1 means + computed over hstepm matrices product = hstepm*stepm months) + as a weighted average of prlim. + */ for(j=nlstate+1,gpp[j]=0.;j<=nlstate+ndeath;j++){ - for(i=1; i<= nlstate; i++) + for(i=1,gpp[j]=0.; i<= nlstate; i++) gpp[j] += prlim[i][i]*p3mat[i][j][1]; } - /* end force of mortality */ + /* end probability of death */ - for(i=1; i<=npar; i++) /* Computes gradient */ + for(i=1; i<=npar; i++) /* Computes gradient x - delta */ xp[i] = x[i] - (i==theta ?delti[theta]:0); hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij); prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ij); @@ -2013,17 +2171,21 @@ void varevsij(char optionfilefiname[], d gm[h][j] += prlim[i][i]*p3mat[i][j][h]; } } - /* This for computing force of mortality (h=1)as a weighted average */ + /* This for computing probability of death (h=1 means + computed over hstepm matrices product = hstepm*stepm months) + as a weighted average of prlim. + */ for(j=nlstate+1,gmp[j]=0.;j<=nlstate+ndeath;j++){ - for(i=1; i<= nlstate; i++) - gmp[j] += prlim[i][i]*p3mat[i][j][1]; + for(i=1,gmp[j]=0.; i<= nlstate; i++) + gmp[j] += prlim[i][i]*p3mat[i][j][1]; } - /* end force of mortality */ + /* end probability of death */ for(j=1; j<= nlstate; j++) /* vareij */ for(h=0; h<=nhstepm; h++){ gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta]; } + for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu */ gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta]; } @@ -2038,8 +2200,9 @@ void varevsij(char optionfilefiname[], d trgradg[h][j][theta]=gradg[h][theta][j]; for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */ - for(theta=1; theta <=npar; theta++) + for(theta=1; theta <=npar; theta++) { trgradgp[j][theta]=gradgp[theta][j]; + } hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */ for(i=1;i<=nlstate;i++) @@ -2059,10 +2222,14 @@ void varevsij(char optionfilefiname[], d /* pptj */ matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov); matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp); - for(j=nlstate+1;j<=nlstate+ndeath;j++) - for(i=nlstate+1;i<=nlstate+ndeath;i++) + + for(j=nlstate+1;j<=nlstate+ndeath;j++) + for(i=nlstate+1;i<=nlstate+ndeath;i++){ varppt[j][i]=doldmp[j][i]; + } + /* end ppptj */ + /* x centered again */ hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij); prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ij); @@ -2076,12 +2243,15 @@ void varevsij(char optionfilefiname[], d } } - /* This for computing force of mortality (h=1)as a weighted average */ - for(j=nlstate+1,gmp[j]=0.;j<=nlstate+ndeath;j++){ - for(i=1; i<= nlstate; i++) + /* This for computing probability of death (h=1 means + computed over hstepm (estepm) matrices product = hstepm*stepm months) + as a weighted average of prlim. + */ + for(j=nlstate+1;j<=nlstate+ndeath;j++){ + for(i=1,gmp[j]=0.;i<= nlstate; i++) gmp[j] += prlim[i][i]*p3mat[i][j][1]; } - /* end force of mortality */ + /* end probability of death */ fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij); for(j=nlstate+1; j<=(nlstate+ndeath);j++){ @@ -2111,11 +2281,14 @@ void varevsij(char optionfilefiname[], d fprintf(ficgp,"\nset noparametric;set nolabel; set ter png small;set size 0.65, 0.65"); /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */ fprintf(ficgp,"\n set log y; set nolog x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";"); - fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); - fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); - fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); +/* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */ +/* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */ +/* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */ + fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l 1 ",fileresprobmorprev); + fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95\%% interval\" w l 2 ",fileresprobmorprev); + fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l 2 ",fileresprobmorprev); fprintf(fichtm,"\n
    File (multiple files are possible if covariates are present): %s\n",fileresprobmorprev,fileresprobmorprev); - fprintf(fichtm,"\n
    Probability is computed over estepm=%d months.

    \n", stepm,digitp,digit); + fprintf(fichtm,"\n
    Probability is computed over estepm=%d months.

    \n", estepm,digitp,digit); /* fprintf(fichtm,"\n
    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

    \n", stepm,YEARM,digitp,digit); */ fprintf(ficgp,"\nset out \"varmuptjgr%s%s.png\";replot;",digitp,digit); @@ -3122,7 +3295,7 @@ populforecast(char fileres[], double anp int main(int argc, char *argv[]) { - + int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav); int i,j, k, n=MAXN,iter,m,size,cptcode, cptcod; double agedeb, agefin,hf; double ageminpar=1.e20,agemin=1.e20, agemaxpar=-1.e20, agemax=-1.e20; @@ -3160,7 +3333,6 @@ int main(int argc, char *argv[]) double *epj, vepp; double kk1, kk2; double dateprev1, dateprev2,jproj1,mproj1,anproj1,jproj2,mproj2,anproj2; - /*int *movingaverage; */ char *alph[]={"a","a","b","c","d","e"}, str[4]; @@ -3546,11 +3718,10 @@ int main(int argc, char *argv[]) for (i=1; i<=imx; i++) { agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]); for(m=1; (m<= maxwav); m++){ - if(s[m][i] >0){ + if(s[m][i] >0 || s[m][i]==-2){ if (s[m][i] >= nlstate+1) { if(agedc[i]>0) - if(moisdc[i]!=99 && andc[i]!=9999) - agev[m][i]=agedc[i]; + if(moisdc[i]!=99 && andc[i]!=9999) agev[m][i]=agedc[i]; /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/ else { if (andc[i]!=9999){ @@ -3612,7 +3783,8 @@ int main(int argc, char *argv[]) dh=imatrix(1,lastpass-firstpass+1,1,imx); bh=imatrix(1,lastpass-firstpass+1,1,imx); mw=imatrix(1,lastpass-firstpass+1,1,imx); - + + /* Concatenates waves */ concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm); @@ -3652,13 +3824,18 @@ int main(int argc, char *argv[]) /* Calculates basic frequencies. Computes observed prevalence at single age and prints on file fileres'p'. */ + pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */ + oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */ + newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */ + savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */ + oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */ /* For Powell, parameters are in a vector p[] starting at p[1] so we point p on param[1][1] so that p[1] maps on param[1][1][1] */ p=param[1][1]; /* *(*(*(param +1)+1)+0) */ - if(mle==1){ + if(mle>=1){ /* Could be 1 or 2 */ mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func); } @@ -3816,6 +3993,7 @@ int main(int argc, char *argv[]) fprintf(ficparo,"popforecast=%d popfile=%s popfiledate=%.lf/%.lf/%.lf last-popfiledate=%.lf/%.lf/%.lf\n",popforecast,popfile,jpyram,mpyram,anpyram,jpyram1,mpyram1,anpyram1); fprintf(ficres,"popforecast=%d popfile=%s popfiledate=%.lf/%.lf/%.lf last-popfiledate=%.lf/%.lf/%.lf\n",popforecast,popfile,jpyram,mpyram,anpyram,jpyram1,mpyram1,anpyram1); + freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); /*------------ gnuplot -------------*/ @@ -3862,7 +4040,7 @@ Interval (in months) between two waves: free_imatrix(mw,1,lastpass-firstpass+1,1,imx); free_ivector(num,1,n); free_vector(agedc,1,n); - free_matrix(covar,0,NCOVMAX,1,n); + /*free_matrix(covar,0,NCOVMAX,1,n);*/ /*free_matrix(covar,1,NCOVMAX,1,n);*/ fclose(ficparo); fclose(ficres); @@ -3884,11 +4062,6 @@ Interval (in months) between two waves: fprintf(ficrespl,"\n"); prlim=matrix(1,nlstate,1,nlstate); - pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */ - oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */ - newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */ - savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */ - oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */ agebase=ageminpar; agelim=agemaxpar; @@ -3983,7 +4156,7 @@ Interval (in months) between two waves: /*---------- Forecasting ------------------*/ - if((stepm == 1) && (strcmp(model,".")==0)){ + if((stepm == 1) && (strcmp(model,".")==0)){ prevforecast(fileres, anproj1,mproj1,jproj1, agemin,agemax, dateprev1, dateprev2,mobilav, agedeb, fage, popforecast, popfile, anproj2,p, i1); if (popforecast==1) populforecast(fileres, anpyram,mpyram,jpyram, agemin,agemax, dateprev1, dateprev2,mobilav, agedeb, fage, popforecast, popfile, anpyram1,p, i1); } @@ -3991,7 +4164,7 @@ Interval (in months) between two waves: erreur=108; 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); 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); - } + } /*---------- Health expectancies and variances ------------*/ @@ -4015,6 +4188,7 @@ Interval (in months) between two waves: printf("Computing Health Expectancies: result on file '%s' \n", filerese); fprintf(ficlog,"Computing Health Expectancies: result on file '%s' \n", filerese); + strcpy(fileresv,"v"); strcat(fileresv,fileres); if((ficresvij=fopen(fileresv,"w"))==NULL) { @@ -4150,7 +4324,8 @@ Interval (in months) between two waves: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath); free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath); free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath); - + + free_matrix(covar,0,NCOVMAX,1,n); free_matrix(matcov,1,npar,1,npar); free_vector(delti,1,npar); free_matrix(agev,1,maxwav,1,imx);