version 1.61, 2002/11/19 14:08:13
|
version 1.66, 2003/01/28 17:23:35
|
Line 32
|
Line 32
|
hPijx is the probability to be observed in state i at age x+h |
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 |
conditional to the observed state i at age x. The delay 'h' can be |
split into an exact number (nh*stepm) of unobserved intermediate |
split into an exact number (nh*stepm) of unobserved intermediate |
states. This elementary transition (by month or quarter trimester, |
states. This elementary transition (by month, quarter, |
semester or year) is model as a multinomial logistic. The hPx |
semester or year) is modelled as a multinomial logistic. The hPx |
matrix is simply the matrix product of nh*stepm elementary matrices |
matrix is simply the matrix product of nh*stepm elementary matrices |
and the contribution of each individual to the likelihood is simply |
and the contribution of each individual to the likelihood is simply |
hPijx. |
hPijx. |
Line 83
|
Line 83
|
#define ODIRSEPARATOR '\\' |
#define ODIRSEPARATOR '\\' |
#endif |
#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 erreur; /* Error number */ |
int nvar; |
int nvar; |
int cptcovn=0, cptcovage=0, cptcoveff=0,cptcov; |
int cptcovn=0, cptcovage=0, cptcoveff=0,cptcov; |
Line 856 double **matprod2(double **out, double *
|
Line 856 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 ) |
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 |
/* Computes the transition matrix starting at age 'age' over |
duration (i.e. until |
'nhstepm*hstepm*stepm' months (i.e. until |
age (in years) age+nhstepm*stepm/12) by multiplying nhstepm*hstepm matrices. |
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 |
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 |
Model is determined by parameters x and covariates have to be |
included manually here. |
included manually here. |
|
|
Line 944 double func( double *x)
|
Line 946 double func( double *x)
|
for (kk=1; kk<=cptcovage;kk++) { |
for (kk=1; kk<=cptcovage;kk++) { |
cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2]; |
cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2]; |
} |
} |
|
|
out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, |
out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, |
1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); |
1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); |
savm=oldm; |
savm=oldm; |
oldm=newm; |
oldm=newm; |
|
|
|
|
} /* end mult */ |
} /* end mult */ |
|
|
/*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */ |
/*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */ |
Line 968 double func( double *x)
|
Line 967 double func( double *x)
|
*/ |
*/ |
s1=s[mw[mi][i]][i]; |
s1=s[mw[mi][i]][i]; |
s2=s[mw[mi+1][i]][i]; |
s2=s[mw[mi+1][i]][i]; |
bbh=(double)bh[mi][i]/(double)stepm; |
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])); |
/* bias is positive if real duration |
/*lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.-bbh)*out[s1][s2]));*/ |
* 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]));*/ |
|
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]);*/ |
/*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/ |
/*if(lli ==000.0)*/ |
/*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); */ |
/*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); */ |
Line 979 double func( double *x)
|
Line 1032 double func( double *x)
|
ll[s[mw[mi][i]][i]] += 2*weight[i]*lli; |
ll[s[mw[mi][i]][i]] += 2*weight[i]*lli; |
} /* end of wave */ |
} /* end of wave */ |
} /* end of individual */ |
} /* end of individual */ |
} else{ |
} 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<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])); /* 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 (i=1,ipmx=0, sw=0.; i<=imx; i++){ |
for (k=1; k<=cptcovn;k++) cov[2+k]=covar[Tvar[k]][i]; |
for (k=1; k<=cptcovn;k++) cov[2+k]=covar[Tvar[k]][i]; |
for(mi=1; mi<= wav[i]-1; mi++){ |
for(mi=1; mi<= wav[i]-1; mi++){ |
Line 1030 void mlikeli(FILE *ficres,double p[], in
|
Line 1133 void mlikeli(FILE *ficres,double p[], in
|
powell(p,xi,npar,ftol,&iter,&fret,func); |
powell(p,xi,npar,ftol,&iter,&fret,func); |
|
|
printf("\n#Number of iterations = %d, -2 Log likelihood = %.12f\n",iter,func(p)); |
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)); |
fprintf(ficres,"#Number of iterations = %d, -2 Log likelihood = %.12f \n",iter,func(p)); |
|
|
} |
} |
Line 1614 void concatwav(int wav[], int **dh, int
|
Line 1717 void concatwav(int wav[], int **dh, int
|
jk= j/stepm; |
jk= j/stepm; |
jl= j -jk*stepm; |
jl= j -jk*stepm; |
ju= j -(jk+1)*stepm; |
ju= j -(jk+1)*stepm; |
if(jl <= -ju){ |
if(mle <=1){ |
dh[mi][i]=jk; |
if(jl==0){ |
bh[mi][i]=jl; |
dh[mi][i]=jk; |
} |
bh[mi][i]=0; |
else{ |
}else{ /* We want a negative bias in order to only have interpolation ie |
dh[mi][i]=jk+1; |
* at the price of an extra matrix product in likelihood */ |
bh[mi][i]=ju; |
dh[mi][i]=jk+1; |
} |
bh[mi][i]=ju; |
if(dh[mi][i]==0){ |
} |
dh[mi][i]=1; /* At least one step */ |
}else{ |
bh[mi][i]=ju; /* At least one step */ |
if(jl <= -ju){ |
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); |
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); |
} |
} |
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; |
jmean=sum/k; |
printf("Delay (in months) between two waves Min=%d Max=%d Mean=%f\n\n ",jmin, jmax,jmean); |
printf("Delay (in months) between two waves Min=%d Max=%d Mean=%f\n\n ",jmin, jmax,jmean); |
Line 1730 void evsij(char fileres[], double ***eij
|
Line 1846 void evsij(char fileres[], double ***eij
|
* This is mainly to measure the difference between two models: for example |
* 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 |
* 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 |
* 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 |
* 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 |
* 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 |
* to compare the new estimate of Life expectancy with the same linear |
Line 1920 void varevsij(char optionfilefiname[], d
|
Line 2036 void varevsij(char optionfilefiname[], d
|
} |
} |
printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev); |
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(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); |
fprintf(ficresprobmorprev,"# Age cov=%-d",ij); |
for(j=nlstate+1; j<=(nlstate+ndeath);j++){ |
for(j=nlstate+1; j<=(nlstate+ndeath);j++){ |
fprintf(ficresprobmorprev," p.%-d SE",j); |
fprintf(ficresprobmorprev," p.%-d SE",j); |
Line 1977 void varevsij(char optionfilefiname[], d
|
Line 2093 void varevsij(char optionfilefiname[], d
|
and note for a fixed period like k years */ |
and note for a fixed period like k years */ |
/* We decided (b) to get a life expectancy respecting the most precise curvature of the |
/* 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 |
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 |
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. |
results. So we changed our mind and took the option of the best precision. |
*/ |
*/ |
Line 1993 void varevsij(char optionfilefiname[], d
|
Line 2109 void varevsij(char optionfilefiname[], d
|
|
|
|
|
for(theta=1; theta <=npar; theta++){ |
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); |
xp[i] = x[i] + (i==theta ?delti[theta]:0); |
} |
} |
hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij); |
hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij); |
Line 2015 void varevsij(char optionfilefiname[], d
|
Line 2131 void varevsij(char optionfilefiname[], d
|
gp[h][j] += prlim[i][i]*p3mat[i][j][h]; |
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(j=nlstate+1,gpp[j]=0.;j<=nlstate+ndeath;j++){ |
for(i=1; i<= nlstate; i++) |
for(i=1; i<= nlstate; i++) |
gpp[j] += prlim[i][i]*p3mat[i][j][1]; |
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); |
xp[i] = x[i] - (i==theta ?delti[theta]:0); |
hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij); |
hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij); |
prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ij); |
prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ij); |
Line 2043 void varevsij(char optionfilefiname[], d
|
Line 2162 void varevsij(char optionfilefiname[], d
|
gm[h][j] += prlim[i][i]*p3mat[i][j][h]; |
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(j=nlstate+1,gmp[j]=0.;j<=nlstate+ndeath;j++){ |
for(i=1; i<= nlstate; i++) |
for(i=1; i<= nlstate; i++) |
gmp[j] += prlim[i][i]*p3mat[i][j][1]; |
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(j=1; j<= nlstate; j++) /* vareij */ |
for(h=0; h<=nhstepm; h++){ |
for(h=0; h<=nhstepm; h++){ |
Line 2093 void varevsij(char optionfilefiname[], d
|
Line 2215 void varevsij(char optionfilefiname[], d
|
for(i=nlstate+1;i<=nlstate+ndeath;i++) |
for(i=nlstate+1;i<=nlstate+ndeath;i++) |
varppt[j][i]=doldmp[j][i]; |
varppt[j][i]=doldmp[j][i]; |
/* end ppptj */ |
/* end ppptj */ |
|
/* x centered again */ |
hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij); |
hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij); |
prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ij); |
prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ij); |
|
|
Line 2106 void varevsij(char optionfilefiname[], d
|
Line 2229 void varevsij(char optionfilefiname[], d
|
} |
} |
} |
} |
|
|
/* This for computing force of mortality (h=1)as a weighted average */ |
/* 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,gmp[j]=0.;j<=nlstate+ndeath;j++){ |
for(j=nlstate+1,gmp[j]=0.;j<=nlstate+ndeath;j++){ |
for(i=1; i<= nlstate; i++) |
for(i=1; i<= nlstate; i++) |
gmp[j] += prlim[i][i]*p3mat[i][j][1]; |
gmp[j] += prlim[i][i]*p3mat[i][j][1]; |
} |
} |
/* end force of mortality */ |
/* end probability of death */ |
|
|
fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij); |
fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij); |
for(j=nlstate+1; j<=(nlstate+ndeath);j++){ |
for(j=nlstate+1; j<=(nlstate+ndeath);j++){ |
Line 2145 void varevsij(char optionfilefiname[], d
|
Line 2271 void varevsij(char optionfilefiname[], d
|
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) 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 replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); |
fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",fileresprobmorprev,fileresprobmorprev); |
fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",fileresprobmorprev,fileresprobmorprev); |
fprintf(fichtm,"\n<br> Probability is computed over estepm=%d months. <br> <img src=\"varmuptjgr%s%s.png\"> <br>\n", stepm,digitp,digit); |
fprintf(fichtm,"\n<br> Probability is computed over estepm=%d months. <br> <img src=\"varmuptjgr%s%s.png\"> <br>\n", estepm,digitp,digit); |
/* 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); |
/* 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); |
*/ |
*/ |
fprintf(ficgp,"\nset out \"varmuptjgr%s%s.png\";replot;",digitp,digit); |
fprintf(ficgp,"\nset out \"varmuptjgr%s%s.png\";replot;",digitp,digit); |
Line 3896 Interval (in months) between two waves:
|
Line 4022 Interval (in months) between two waves:
|
free_imatrix(mw,1,lastpass-firstpass+1,1,imx); |
free_imatrix(mw,1,lastpass-firstpass+1,1,imx); |
free_ivector(num,1,n); |
free_ivector(num,1,n); |
free_vector(agedc,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);*/ |
/*free_matrix(covar,1,NCOVMAX,1,n);*/ |
fclose(ficparo); |
fclose(ficparo); |
fclose(ficres); |
fclose(ficres); |
Line 4179 Interval (in months) between two waves:
|
Line 4305 Interval (in months) between two waves:
|
free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath); |
free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath); |
free_matrix(newms, 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(savms, 1,nlstate+ndeath,1,nlstate+ndeath); |
|
|
|
free_matrix(covar,0,NCOVMAX,1,n); |
free_matrix(matcov,1,npar,1,npar); |
free_matrix(matcov,1,npar,1,npar); |
free_vector(delti,1,npar); |
free_vector(delti,1,npar); |
free_matrix(agev,1,maxwav,1,imx); |
free_matrix(agev,1,maxwav,1,imx); |