version 1.241, 2016/08/29 17:17:25
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version 1.248, 2016/09/07 14:10:18
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/* $Id$ |
/* $Id$ |
$State$ |
$State$ |
$Log$ |
$Log$ |
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Revision 1.248 2016/09/07 14:10:18 brouard |
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*** empty log message *** |
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Revision 1.247 2016/09/02 11:11:21 brouard |
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*** empty log message *** |
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Revision 1.246 2016/09/02 08:49:22 brouard |
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*** empty log message *** |
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Revision 1.245 2016/09/02 07:25:01 brouard |
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*** empty log message *** |
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Revision 1.244 2016/09/02 07:17:34 brouard |
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*** empty log message *** |
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Revision 1.243 2016/09/02 06:45:35 brouard |
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*** empty log message *** |
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Revision 1.242 2016/08/30 15:01:20 brouard |
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Summary: Fixing a lots |
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Revision 1.241 2016/08/29 17:17:25 brouard |
Revision 1.241 2016/08/29 17:17:25 brouard |
Summary: gnuplot problem in Back projection to fix |
Summary: gnuplot problem in Back projection to fix |
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Line 2219 void powell(double p[], double **xi, int
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Line 2240 void powell(double p[], double **xi, int
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/* printf("\n"); */ |
/* printf("\n"); */ |
/* fprintf(ficlog,"\n"); */ |
/* fprintf(ficlog,"\n"); */ |
} |
} |
if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /* Did we reach enough precision? */ |
/* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */ |
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if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */ |
/* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */ |
/* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */ |
/* By adding age*age in a model, the new -2LL should be lower and the difference follows a */ |
/* By adding age*age in a model, the new -2LL should be lower and the difference follows a */ |
/* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */ |
/* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */ |
Line 2545 Earliest age to start was %d-%d=%d, ncvl
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Line 2567 Earliest age to start was %d-%d=%d, ncvl
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/* double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ageminpar, double agemaxpar, double **oldm, double **savm, double **dnewm, double **doldm, double **dsavm, double ftolpl, int *ncvyear, int ij) */ |
/* double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ageminpar, double agemaxpar, double **oldm, double **savm, double **dnewm, double **doldm, double **dsavm, double ftolpl, int *ncvyear, int ij) */ |
/* double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double **oldm, double **savm, double **dnewm, double **doldm, double **dsavm, double ftolpl, int *ncvyear, int ij) */ |
/* double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double **oldm, double **savm, double **dnewm, double **doldm, double **dsavm, double ftolpl, int *ncvyear, int ij) */ |
double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij) |
double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres) |
{ |
{ |
/* Computes the prevalence limit in each live state at age x and covariate ij by left multiplying the unit |
/* Computes the prevalence limit in each live state at age x and covariate ij by left multiplying the unit |
matrix by transitions matrix until convergence is reached with precision ftolpl */ |
matrix by transitions matrix until convergence is reached with precision ftolpl */ |
Line 2568 Earliest age to start was %d-%d=%d, ncvl
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Line 2590 Earliest age to start was %d-%d=%d, ncvl
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/* If we start from prlim again, prlim tends to a constant matrix */ |
/* If we start from prlim again, prlim tends to a constant matrix */ |
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int i, ii,j,k; |
int i, ii,j,k; |
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int first=0; |
double *min, *max, *meandiff, maxmax,sumnew=0.; |
double *min, *max, *meandiff, maxmax,sumnew=0.; |
/* double **matprod2(); */ /* test */ |
/* double **matprod2(); */ /* test */ |
double **out, cov[NCOVMAX+1], **bmij(); |
double **out, cov[NCOVMAX+1], **bmij(); |
Line 2604 Earliest age to start was %d-%d=%d, ncvl
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Line 2627 Earliest age to start was %d-%d=%d, ncvl
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cov[2]=agefin; |
cov[2]=agefin; |
if(nagesqr==1) |
if(nagesqr==1) |
cov[3]= agefin*agefin;; |
cov[3]= agefin*agefin;; |
for (k=1; k<=cptcovn;k++) { |
for (k=1; k<=nsd;k++) { /* For single dummy covariates only */ |
/* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */ |
/* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */ |
cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; |
cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)]; |
/* printf("prevalim ij=%d k=%d Tvar[%d]=%d nbcode=%d cov=%lf codtabm(%d,Tvar[%d])=%d \n",ij,k, k, Tvar[k],nbcode[Tvar[k]][codtabm(ij,Tvar[k])],cov[2+k], ij, k, codtabm(ij,Tvar[k])]); */ |
/* printf("bprevalim Dummy combi=%d k=%d TvarsD[%d]=V%d TvarsDind[%d]=%d nbcode=%d cov=%lf codtabm(%d,Tvar[%d])=%d \n",ij,k, k, TvarsD[k],k,TvarsDind[k],nbcode[TvarsD[k]][codtabm(ij,k)],cov[2+nagesqr+TvarsDind[k]], ij, k, codtabm(ij,k)); */ |
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} |
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/* for (k=1; k<=cptcovn;k++) { */ |
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/* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */ |
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/* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */ |
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/* /\* printf("prevalim ij=%d k=%d Tvar[%d]=%d nbcode=%d cov=%lf codtabm(%d,Tvar[%d])=%d \n",ij,k, k, Tvar[k],nbcode[Tvar[k]][codtabm(ij,Tvar[k])],cov[2+k], ij, k, codtabm(ij,Tvar[k])]); *\/ */ |
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/* } */ |
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for (k=1; k<=nsq;k++) { /* For single varying covariates only */ |
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/* Here comes the value of quantitative after renumbering k with single quantitative covariates */ |
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cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; |
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/* printf("prevalim Quantitative k=%d TvarsQind[%d]=%d, TvarsQ[%d]=V%d,Tqresult[%d][%d]=%f\n",k,k,TvarsQind[k],k,TvarsQ[k],nres,k,Tqresult[nres][k]); */ |
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} |
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/* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; */ |
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/* for (k=1; k<=cptcovprod;k++) /\* Useless *\/ */ |
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/* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\/ */ |
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/* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */ |
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for (k=1; k<=cptcovage;k++){ /* For product with age */ |
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if(Dummy[Tvar[Tage[k]]]){ |
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cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; |
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} else{ |
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cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; |
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} |
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/* printf("prevalim Age combi=%d k=%d Tage[%d]=V%d Tqresult[%d][%d]=%f\n",ij,k,k,Tage[k],nres,k,Tqresult[nres][k]); */ |
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} |
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for (k=1; k<=cptcovprod;k++){ /* For product without age */ |
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/* printf("prevalim Prod ij=%d k=%d Tprod[%d]=%d Tvard[%d][1]=V%d, Tvard[%d][2]=V%d\n",ij,k,k,Tprod[k], k,Tvard[k][1], k,Tvard[k][2]); */ |
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if(Dummy[Tvard[k][1]==0]){ |
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if(Dummy[Tvard[k][2]==0]){ |
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cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; |
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}else{ |
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cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; |
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} |
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}else{ |
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if(Dummy[Tvard[k][2]==0]){ |
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cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; |
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}else{ |
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cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; |
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} |
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} |
} |
} |
for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; |
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for (k=1; k<=cptcovprod;k++) /* Useless */ |
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/* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */ |
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cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; |
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/*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/ |
/*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/ |
/*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/ |
/*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/ |
Line 2659 Earliest age to start was %d-%d=%d, ncvl
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Line 2716 Earliest age to start was %d-%d=%d, ncvl
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} |
} |
} /* age loop */ |
} /* age loop */ |
/* After some age loop it doesn't converge */ |
/* After some age loop it doesn't converge */ |
printf("Warning: the back stable prevalence at age %d did not converge with the required precision (%g > ftolpl=%g) within %.0f years. Try to lower 'ftolpl'. \n\ |
if(first){ |
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first=1; |
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printf("Warning: the back stable prevalence at age %d did not converge with the required precision (%g > ftolpl=%g) within %.0f years. Try to lower 'ftolpl'. Others in log file only...\n\ |
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Oldest age to start was %d-%d=%d, ncvloop=%d, ncvyear=%d\n", (int)age, maxmax, ftolpl, delaymax, (int)age, (int)delaymax, (int)agefin, ncvloop, *ncvyear); |
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} |
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fprintf(ficlog,"Warning: the back stable prevalence at age %d did not converge with the required precision (%g > ftolpl=%g) within %.0f years. Try to lower 'ftolpl'. \n\ |
Oldest age to start was %d-%d=%d, ncvloop=%d, ncvyear=%d\n", (int)age, maxmax, ftolpl, delaymax, (int)age, (int)delaymax, (int)agefin, ncvloop, *ncvyear); |
Oldest age to start was %d-%d=%d, ncvloop=%d, ncvyear=%d\n", (int)age, maxmax, ftolpl, delaymax, (int)age, (int)delaymax, (int)agefin, ncvloop, *ncvyear); |
/* Try to lower 'ftol', for example from 1.e-8 to 6.e-9.\n", ftolpl, (int)age, (int)delaymax, (int)agefin, ncvloop, (int)age-(int)agefin); */ |
/* Try to lower 'ftol', for example from 1.e-8 to 6.e-9.\n", ftolpl, (int)age, (int)delaymax, (int)agefin, ncvloop, (int)age-(int)agefin); */ |
free_vector(min,1,nlstate); |
free_vector(min,1,nlstate); |
Line 2792 double **pmij(double **ps, double *cov,
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Line 2854 double **pmij(double **ps, double *cov,
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/* }else */ |
/* }else */ |
doldm[ii][j]=(ii==j ? 1./sumnew : 0.0); |
doldm[ii][j]=(ii==j ? 1./sumnew : 0.0); |
}else{ |
}else{ |
printf("ii=%d, i=%d, doldm=%lf dsavm=%lf, probs=%lf, sumnew=%lf,agefin=%d\n",ii,j,doldm[ii][j],dsavm[ii][j],prevacurrent[(int)agefin][ii][ij],sumnew, (int)agefin); |
; |
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/* printf("ii=%d, i=%d, doldm=%lf dsavm=%lf, probs=%lf, sumnew=%lf,agefin=%d\n",ii,j,doldm[ii][j],dsavm[ii][j],prevacurrent[(int)agefin][ii][ij],sumnew, (int)agefin); */ |
} |
} |
} /*End ii */ |
} /*End ii */ |
} /* End j, At the end doldm is diag[1/(w_1p1i+w_2 p2i)] */ |
} /* End j, At the end doldm is diag[1/(w_1p1i+w_2 p2i)] */ |
Line 3175 double func( double *x)
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Line 3238 double func( double *x)
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Then computes with function pmij which return a matrix p[i][j] giving the elementary probability |
Then computes with function pmij which return a matrix p[i][j] giving the elementary probability |
to be observed in j being in i according to the model. |
to be observed in j being in i according to the model. |
*/ |
*/ |
ioffset=2+nagesqr+cptcovage; |
ioffset=2+nagesqr ; |
/* Fixed */ |
/* Fixed */ |
for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */ |
for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */ |
cov[ioffset+TvarFind[k]]=covar[Tvar[TvarFind[k]]][i];/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, only V1 is fixed (k=6)*/ |
cov[ioffset+TvarFind[k]]=covar[Tvar[TvarFind[k]]][i];/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, only V1 is fixed (k=6)*/ |
Line 3194 double func( double *x)
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Line 3257 double func( double *x)
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*/ |
*/ |
for(mi=1; mi<= wav[i]-1; mi++){ |
for(mi=1; mi<= wav[i]-1; mi++){ |
for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/ |
for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/ |
cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; |
/* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */ |
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cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; |
} |
} |
for (ii=1;ii<=nlstate+ndeath;ii++) |
for (ii=1;ii<=nlstate+ndeath;ii++) |
for (j=1;j<=nlstate+ndeath;j++){ |
for (j=1;j<=nlstate+ndeath;j++){ |
Line 3208 double func( double *x)
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Line 3272 double func( double *x)
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if(nagesqr==1) |
if(nagesqr==1) |
cov[3]= agexact*agexact; /* Should be changed here */ |
cov[3]= agexact*agexact; /* Should be changed here */ |
for (kk=1; kk<=cptcovage;kk++) { |
for (kk=1; kk<=cptcovage;kk++) { |
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if(!FixedV[Tvar[Tage[kk]]]) |
cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */ |
cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */ |
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else |
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cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact; |
} |
} |
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)); |
Line 3490 double funcone( double *x)
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Line 3557 double funcone( double *x)
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for(k=1; k<=nlstate; k++) ll[k]=0.; |
for(k=1; k<=nlstate; k++) ll[k]=0.; |
ioffset=0; |
ioffset=0; |
for (i=1,ipmx=0, sw=0.; i<=imx; i++){ |
for (i=1,ipmx=0, sw=0.; i<=imx; i++){ |
ioffset=2+nagesqr+cptcovage; |
/* ioffset=2+nagesqr+cptcovage; */ |
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ioffset=2+nagesqr; |
/* Fixed */ |
/* Fixed */ |
/* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */ |
/* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */ |
/* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */ |
/* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */ |
Line 3517 double funcone( double *x)
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Line 3585 double funcone( double *x)
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for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */ |
for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */ |
/* Wave varying (but not age varying) */ |
/* Wave varying (but not age varying) */ |
for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/ |
for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/ |
cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; |
/* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */ |
} |
cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; |
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} |
/* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates (single??)*\/ */ |
/* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates (single??)*\/ */ |
/* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; /\* Counting the # varying covariate from 1 to ntveff *\/ */ |
/* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; /\* Counting the # varying covariate from 1 to ntveff *\/ */ |
/* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; */ |
/* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; */ |
/* k=ioffset-2-nagesqr-cptcovage+itv; /\* position in simple model *\/ */ |
/* k=ioffset-2-nagesqr-cptcovage+itv; /\* position in simple model *\/ */ |
/* cov[ioffset+itv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; */ |
/* cov[ioffset+itv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; */ |
/* printf(" i=%d,mi=%d,itv=%d,TmodelInvind[itv]=%d,cotvar[mw[mi][i]][TmodelInvind[itv]][i]=%f\n", i, mi, itv, TmodelInvind[itv],cotvar[mw[mi][i]][TmodelInvind[itv]][i]); */ |
/* printf(" i=%d,mi=%d,itv=%d,TmodelInvind[itv]=%d,cotvar[mw[mi][i]][TmodelInvind[itv]][i]=%f\n", i, mi, itv, TmodelInvind[itv],cotvar[mw[mi][i]][TmodelInvind[itv]][i]); */ |
/* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */ |
/* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */ |
/* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */ |
/* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */ |
/* /\* printf(" i=%d,mi=%d,iqtv=%d,TmodelInvQind[iqtv]=%d,cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]=%f\n", i, mi, iqtv, TmodelInvQind[iqtv],cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]); *\/ */ |
/* /\* printf(" i=%d,mi=%d,iqtv=%d,TmodelInvQind[iqtv]=%d,cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]=%f\n", i, mi, iqtv, TmodelInvQind[iqtv],cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]); *\/ */ |
/* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */ |
/* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */ |
/* } */ |
/* } */ |
for (ii=1;ii<=nlstate+ndeath;ii++) |
for (ii=1;ii<=nlstate+ndeath;ii++) |
for (j=1;j<=nlstate+ndeath;j++){ |
for (j=1;j<=nlstate+ndeath;j++){ |
oldm[ii][j]=(ii==j ? 1.0 : 0.0); |
oldm[ii][j]=(ii==j ? 1.0 : 0.0); |
savm[ii][j]=(ii==j ? 1.0 : 0.0); |
savm[ii][j]=(ii==j ? 1.0 : 0.0); |
} |
} |
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agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */ |
agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */ |
ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */ |
ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */ |
for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */ |
for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */ |
/*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i] |
/* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */ |
and mw[mi+1][i]. dh depends on stepm.*/ |
/*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i] |
newm=savm; |
and mw[mi+1][i]. dh depends on stepm.*/ |
agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; |
newm=savm; |
cov[2]=agexact; |
agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */ |
if(nagesqr==1) |
cov[2]=agexact; |
cov[3]= agexact*agexact; |
if(nagesqr==1) |
for (kk=1; kk<=cptcovage;kk++) { |
cov[3]= agexact*agexact; |
cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; |
for (kk=1; kk<=cptcovage;kk++) { |
} |
if(!FixedV[Tvar[Tage[kk]]]) |
/* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */ |
cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; |
/* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */ |
else |
out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, |
cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact; |
1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); |
} |
/* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */ |
/* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */ |
/* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */ |
/* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */ |
savm=oldm; |
out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, |
oldm=newm; |
1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); |
|
/* 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 */ |
} /* end mult */ |
|
|
s1=s[mw[mi][i]][i]; |
s1=s[mw[mi][i]][i]; |
Line 3570 double funcone( double *x)
|
Line 3643 double funcone( double *x)
|
* is higher than the multiple of stepm and negative otherwise. |
* is higher than the multiple of stepm and negative otherwise. |
*/ |
*/ |
if( s2 > nlstate && (mle <5) ){ /* Jackson */ |
if( s2 > nlstate && (mle <5) ){ /* Jackson */ |
lli=log(out[s1][s2] - savm[s1][s2]); |
lli=log(out[s1][s2] - savm[s1][s2]); |
} else if ( s2==-1 ) { /* alive */ |
} else if ( s2==-1 ) { /* alive */ |
for (j=1,survp=0. ; j<=nlstate; j++) |
for (j=1,survp=0. ; j<=nlstate; j++) |
survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; |
survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; |
lli= log(survp); |
lli= log(survp); |
}else if (mle==1){ |
}else if (mle==1){ |
lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */ |
lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */ |
} else if(mle==2){ |
} else if(mle==2){ |
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]>(double)1.e-8 ?log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]):log((1.+bbh)*out[s1][s2])); /* linear interpolation */ |
} else if(mle==3){ /* exponential inter-extrapolation */ |
} else if(mle==3){ /* exponential inter-extrapolation */ |
lli= (savm[s1][s2]>(double)1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2])); /* exponential inter-extrapolation */ |
lli= (savm[s1][s2]>(double)1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2])); /* exponential inter-extrapolation */ |
} else if (mle==4){ /* mle=4 no inter-extrapolation */ |
} else if (mle==4){ /* mle=4 no inter-extrapolation */ |
lli=log(out[s1][s2]); /* Original formula */ |
lli=log(out[s1][s2]); /* Original formula */ |
} else{ /* mle=0 back to 1 */ |
} else{ /* mle=0 back to 1 */ |
lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */ |
lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */ |
/*lli=log(out[s1][s2]); */ /* Original formula */ |
/*lli=log(out[s1][s2]); */ /* Original formula */ |
} /* End of if */ |
} /* End of if */ |
ipmx +=1; |
ipmx +=1; |
sw += weight[i]; |
sw += weight[i]; |
ll[s[mw[mi][i]][i]] += 2*weight[i]*lli; |
ll[s[mw[mi][i]][i]] += 2*weight[i]*lli; |
/*printf("i=%6d s1=%1d s2=%1d mi=%1d mw=%1d dh=%3d prob=%10.6f w=%6.4f out=%10.6f sav=%10.6f\n",i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],out[s1][s2],savm[s1][s2]); */ |
/*printf("i=%6d s1=%1d s2=%1d mi=%1d mw=%1d dh=%3d prob=%10.6f w=%6.4f out=%10.6f sav=%10.6f\n",i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],out[s1][s2],savm[s1][s2]); */ |
if(globpr){ |
if(globpr){ |
fprintf(ficresilk,"%9ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\ |
fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\ |
%11.6f %11.6f %11.6f ", \ |
%11.6f %11.6f %11.6f ", \ |
num[i], agebegin, ageend, i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],weight[i]*gipmx/gsw, |
num[i], agebegin, ageend, i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],weight[i]*gipmx/gsw, |
2*weight[i]*lli,out[s1][s2],savm[s1][s2]); |
2*weight[i]*lli,out[s1][s2],savm[s1][s2]); |
for(k=1,llt=0.,l=0.; k<=nlstate; k++){ |
for(k=1,llt=0.,l=0.; k<=nlstate; k++){ |
llt +=ll[k]*gipmx/gsw; |
llt +=ll[k]*gipmx/gsw; |
fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw); |
fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw); |
} |
} |
fprintf(ficresilk," %10.6f\n", -llt); |
fprintf(ficresilk," %10.6f\n", -llt); |
} |
} |
} /* end of wave */ |
} /* end of wave */ |
} /* end of individual */ |
} /* end of individual */ |
Line 3950 double hessij( double x[], double **hess
|
Line 4023 double hessij( double x[], double **hess
|
kmax=kmax+10; |
kmax=kmax+10; |
} |
} |
if(kmax >=10 || firstime ==1){ |
if(kmax >=10 || firstime ==1){ |
printf("Warning: directions %d-%d, you are not estimating the Hessian at the exact maximum likelihood; you may increase ftol=%.2e\n",thetai,thetaj, ftol); |
printf("Warning: directions %d-%d, you are not estimating the Hessian at the exact maximum likelihood; you could increase ftol=%.2e\n",thetai,thetaj, ftol); |
fprintf(ficlog,"Warning: directions %d-%d, you are not estimating the Hessian at the exact maximum likelihood; you may increase ftol=%.2e\n",thetai,thetaj, ftol); |
fprintf(ficlog,"Warning: directions %d-%d, you are not estimating the Hessian at the exact maximum likelihood; you could increase ftol=%.2e\n",thetai,thetaj, ftol); |
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); |
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); |
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); |
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); |
} |
} |
Line 4791 void concatwav(int wav[], int **dh, int
|
Line 4864 void concatwav(int wav[], int **dh, int
|
|
|
/*********** Tricode ****************************/ |
/*********** Tricode ****************************/ |
void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum) |
void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum) |
{ |
{ |
/**< Uses cptcovn+2*cptcovprod as the number of covariates */ |
/**< Uses cptcovn+2*cptcovprod as the number of covariates */ |
/* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1 |
/* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1 |
* Boring subroutine which should only output nbcode[Tvar[j]][k] |
* Boring subroutine which should only output nbcode[Tvar[j]][k] |
* Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable |
* Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable |
* nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually); |
* nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually); |
*/ |
*/ |
|
|
int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX; |
int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX; |
int modmaxcovj=0; /* Modality max of covariates j */ |
int modmaxcovj=0; /* Modality max of covariates j */ |
int cptcode=0; /* Modality max of covariates j */ |
int cptcode=0; /* Modality max of covariates j */ |
int modmincovj=0; /* Modality min of covariates j */ |
int modmincovj=0; /* Modality min of covariates j */ |
|
|
|
|
/* cptcoveff=0; */ |
/* cptcoveff=0; */ |
/* *cptcov=0; */ |
/* *cptcov=0; */ |
|
|
for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */ |
for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */ |
|
|
/* Loop on covariates without age and products and no quantitative variable */ |
/* Loop on covariates without age and products and no quantitative variable */ |
/* for (j=1; j<=(cptcovs); j++) { /\* From model V1 + V2*age+ V3 + V3*V4 keeps V1 + V3 = 2 only *\/ */ |
/* for (j=1; j<=(cptcovs); j++) { /\* From model V1 + V2*age+ V3 + V3*V4 keeps V1 + V3 = 2 only *\/ */ |
for (k=1; k<=cptcovt; k++) { /* From model V1 + V2*age + V3 + V3*V4 keeps V1 + V3 = 2 only */ |
for (k=1; k<=cptcovt; k++) { /* From model V1 + V2*age + V3 + V3*V4 keeps V1 + V3 = 2 only */ |
for (j=-1; (j < maxncov); j++) Ndum[j]=0; |
for (j=-1; (j < maxncov); j++) Ndum[j]=0; |
if(Dummy[k]==0 && Typevar[k] !=1){ /* Dummy covariate and not age product */ |
if(Dummy[k]==0 && Typevar[k] !=1){ /* Dummy covariate and not age product */ |
switch(Fixed[k]) { |
switch(Fixed[k]) { |
case 0: /* Testing on fixed dummy covariate, simple or product of fixed */ |
case 0: /* Testing on fixed dummy covariate, simple or product of fixed */ |
for (i=1; i<=imx; i++) { /* Loop on individuals: reads the data file to get the maximum value of the modality of this covariate Vj*/ |
for (i=1; i<=imx; i++) { /* Loop on individuals: reads the data file to get the maximum value of the modality of this covariate Vj*/ |
ij=(int)(covar[Tvar[k]][i]); |
ij=(int)(covar[Tvar[k]][i]); |
/* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i |
/* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i |
* If product of Vn*Vm, still boolean *: |
* If product of Vn*Vm, still boolean *: |
* If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables |
* If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables |
* 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */ |
* 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */ |
/* Finds for covariate j, n=Tvar[j] of Vn . ij is the |
/* Finds for covariate j, n=Tvar[j] of Vn . ij is the |
modality of the nth covariate of individual i. */ |
modality of the nth covariate of individual i. */ |
if (ij > modmaxcovj) |
if (ij > modmaxcovj) |
modmaxcovj=ij; |
modmaxcovj=ij; |
else if (ij < modmincovj) |
else if (ij < modmincovj) |
modmincovj=ij; |
modmincovj=ij; |
if ((ij < -1) && (ij > NCOVMAX)){ |
if ((ij < -1) && (ij > NCOVMAX)){ |
printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX ); |
printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX ); |
exit(1); |
exit(1); |
}else |
}else |
Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/ |
Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/ |
/* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */ |
/* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */ |
/*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/ |
/*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/ |
/* getting the maximum value of the modality of the covariate |
/* getting the maximum value of the modality of the covariate |
(should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and |
(should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and |
female ies 1, then modmaxcovj=1. |
female ies 1, then modmaxcovj=1. |
*/ |
*/ |
} /* end for loop on individuals i */ |
} /* end for loop on individuals i */ |
printf(" Minimal and maximal values of %d th covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj); |
printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj); |
fprintf(ficlog," Minimal and maximal values of %d th covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj); |
fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj); |
cptcode=modmaxcovj; |
cptcode=modmaxcovj; |
/* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */ |
/* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */ |
/*for (i=0; i<=cptcode; i++) {*/ |
/*for (i=0; i<=cptcode; i++) {*/ |
for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */ |
for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */ |
printf("Frequencies of covariates %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]); |
printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]); |
fprintf(ficlog, "Frequencies of covariates %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]); |
fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]); |
if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */ |
if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */ |
if( j != -1){ |
if( j != -1){ |
ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th |
ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th |
covariate for which somebody answered excluding |
covariate for which somebody answered excluding |
undefined. Usually 2: 0 and 1. */ |
undefined. Usually 2: 0 and 1. */ |
} |
} |
ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th |
ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th |
covariate for which somebody answered including |
covariate for which somebody answered including |
undefined. Usually 3: -1, 0 and 1. */ |
undefined. Usually 3: -1, 0 and 1. */ |
} /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for |
} /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for |
* historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */ |
* historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */ |
} /* Ndum[-1] number of undefined modalities */ |
} /* Ndum[-1] number of undefined modalities */ |
|
|
/* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */ |
/* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */ |
/* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */ |
/* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */ |
/* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */ |
/* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */ |
/* modmincovj=3; modmaxcovj = 7; */ |
/* modmincovj=3; modmaxcovj = 7; */ |
/* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */ |
/* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */ |
/* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */ |
/* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */ |
/* defining two dummy variables: variables V1_1 and V1_2.*/ |
/* defining two dummy variables: variables V1_1 and V1_2.*/ |
/* nbcode[Tvar[j]][ij]=k; */ |
/* nbcode[Tvar[j]][ij]=k; */ |
/* nbcode[Tvar[j]][1]=0; */ |
/* nbcode[Tvar[j]][1]=0; */ |
/* nbcode[Tvar[j]][2]=1; */ |
/* nbcode[Tvar[j]][2]=1; */ |
/* nbcode[Tvar[j]][3]=2; */ |
/* nbcode[Tvar[j]][3]=2; */ |
/* To be continued (not working yet). */ |
/* To be continued (not working yet). */ |
ij=0; /* ij is similar to i but can jump over null modalities */ |
ij=0; /* ij is similar to i but can jump over null modalities */ |
for (i=modmincovj; i<=modmaxcovj; i++) { /* i= 1 to 2 for dichotomous, or from 1 to 3 or from -1 or 0 to 1 currently*/ |
for (i=modmincovj; i<=modmaxcovj; i++) { /* i= 1 to 2 for dichotomous, or from 1 to 3 or from -1 or 0 to 1 currently*/ |
if (Ndum[i] == 0) { /* If nobody responded to this modality k */ |
if (Ndum[i] == 0) { /* If nobody responded to this modality k */ |
break; |
break; |
} |
} |
ij++; |
ij++; |
nbcode[Tvar[k]][ij]=i; /* stores the original value of modality i in an array nbcode, ij modality from 1 to last non-nul modality. nbcode[1][1]=0 nbcode[1][2]=1*/ |
nbcode[Tvar[k]][ij]=i; /* stores the original value of modality i in an array nbcode, ij modality from 1 to last non-nul modality. nbcode[1][1]=0 nbcode[1][2]=1*/ |
cptcode = ij; /* New max modality for covar j */ |
cptcode = ij; /* New max modality for covar j */ |
} /* end of loop on modality i=-1 to 1 or more */ |
} /* end of loop on modality i=-1 to 1 or more */ |
break; |
break; |
case 1: /* Testing on varying covariate, could be simple and |
case 1: /* Testing on varying covariate, could be simple and |
* should look at waves or product of fixed * |
* should look at waves or product of fixed * |
* varying. No time to test -1, assuming 0 and 1 only */ |
* varying. No time to test -1, assuming 0 and 1 only */ |
ij=0; |
ij=0; |
for(i=0; i<=1;i++){ |
for(i=0; i<=1;i++){ |
nbcode[Tvar[k]][++ij]=i; |
nbcode[Tvar[k]][++ij]=i; |
} |
} |
break; |
break; |
default: |
default: |
break; |
break; |
} /* end switch */ |
} /* end switch */ |
} /* end dummy test */ |
} /* end dummy test */ |
|
|
/* for (k=0; k<= cptcode; k++) { /\* k=-1 ? k=0 to 1 *\//\* Could be 1 to 4 *\//\* cptcode=modmaxcovj *\/ */ |
/* for (k=0; k<= cptcode; k++) { /\* k=-1 ? k=0 to 1 *\//\* Could be 1 to 4 *\//\* cptcode=modmaxcovj *\/ */ |
/* /\*recode from 0 *\/ */ |
/* /\*recode from 0 *\/ */ |
/* k is a modality. If we have model=V1+V1*sex */ |
/* 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; */ |
/* then: nbcode[1][1]=0 ; nbcode[1][2]=1; nbcode[2][1]=0 ; nbcode[2][2]=1; */ |
/* But if some modality were not used, it is recoded from 0 to a newer modmaxcovj=cptcode *\/ */ |
/* But if some modality were not used, it is recoded from 0 to a newer modmaxcovj=cptcode *\/ */ |
/* } */ |
/* } */ |
/* /\* cptcode = ij; *\/ /\* New max modality for covar j *\/ */ |
/* /\* cptcode = ij; *\/ /\* New max modality for covar j *\/ */ |
/* if (ij > ncodemax[j]) { */ |
/* if (ij > ncodemax[j]) { */ |
/* printf( " Error ij=%d > ncodemax[%d]=%d\n", ij, j, ncodemax[j]); */ |
/* printf( " Error ij=%d > ncodemax[%d]=%d\n", ij, j, ncodemax[j]); */ |
/* fprintf(ficlog, " Error ij=%d > ncodemax[%d]=%d\n", ij, j, ncodemax[j]); */ |
/* fprintf(ficlog, " Error ij=%d > ncodemax[%d]=%d\n", ij, j, ncodemax[j]); */ |
/* break; */ |
/* break; */ |
/* } */ |
/* } */ |
/* } /\* end of loop on modality k *\/ */ |
/* } /\* end of loop on modality k *\/ */ |
} /* end of loop on model-covariate j. nbcode[Tvarj][1]=0 and nbcode[Tvarj][2]=1 sets the value of covariate j*/ |
} /* end of loop on model-covariate j. nbcode[Tvarj][1]=0 and nbcode[Tvarj][2]=1 sets the value of covariate j*/ |
|
|
for (k=-1; k< maxncov; k++) Ndum[k]=0; |
for (k=-1; k< maxncov; k++) Ndum[k]=0; |
/* Look at fixed dummy (single or product) covariates to check empty modalities */ |
/* Look at fixed dummy (single or product) covariates to check empty modalities */ |
for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */ |
for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */ |
/* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/ |
/* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/ |
ij=Tvar[i]; /* Tvar 5,4,3,6,5,7,1,4 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V4*age */ |
ij=Tvar[i]; /* Tvar 5,4,3,6,5,7,1,4 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V4*age */ |
Ndum[ij]++; /* Count the # of 1, 2 etc: {1,1,1,2,2,1,1} because V1 once, V2 once, two V4 and V5 in above */ |
Ndum[ij]++; /* Count the # of 1, 2 etc: {1,1,1,2,2,1,1} because V1 once, V2 once, two V4 and V5 in above */ |
/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */ |
/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */ |
} /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */ |
} /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */ |
|
|
ij=0; |
ij=0; |
/* for (i=0; i<= maxncov-1; i++) { /\* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) *\/ */ |
/* for (i=0; i<= maxncov-1; i++) { /\* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) *\/ */ |
for (k=1; k<= cptcovt; k++) { /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */ |
for (k=1; k<= cptcovt; k++) { /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */ |
/*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/ |
/*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/ |
/* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */ |
/* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */ |
if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy and non empty in the model */ |
if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy and non empty in the model */ |
/* If product not in single variable we don't print results */ |
/* If product not in single variable we don't print results */ |
/*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/ |
/*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/ |
++ij;/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, */ |
++ij;/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, */ |
Tvaraff[ij]=Tvar[k]; /* For printing combination *//* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, Tvar {5, 4, 3, 6, 5, 2, 7, 1, 1} Tvaraff={4, 3, 1} V4, V3, V1*/ |
Tvaraff[ij]=Tvar[k]; /* For printing combination *//* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, Tvar {5, 4, 3, 6, 5, 2, 7, 1, 1} Tvaraff={4, 3, 1} V4, V3, V1*/ |
Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */ |
Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */ |
TmodelInvind[ij]=Tvar[k]- ncovcol-nqv; /* Inverse TmodelInvind[2=V4]=2 second dummy varying cov (V4)4-1-1 {0, 2, 1, } TmodelInvind[3]=1 */ |
TmodelInvind[ij]=Tvar[k]- ncovcol-nqv; /* Inverse TmodelInvind[2=V4]=2 second dummy varying cov (V4)4-1-1 {0, 2, 1, } TmodelInvind[3]=1 */ |
if(Fixed[k]!=0) |
if(Fixed[k]!=0) |
anyvaryingduminmodel=1; |
anyvaryingduminmodel=1; |
/* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */ |
/* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */ |
/* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */ |
/* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */ |
/* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */ |
/* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */ |
/* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */ |
/* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */ |
/* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */ |
/* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */ |
/* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */ |
/* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */ |
} |
} |
} /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */ |
} /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */ |
/* ij--; */ |
/* ij--; */ |
/* cptcoveff=ij; /\*Number of total covariates*\/ */ |
/* cptcoveff=ij; /\*Number of total covariates*\/ */ |
*cptcov=ij; /*Number of total real effective covariates: effective |
*cptcov=ij; /*Number of total real effective covariates: effective |
* because they can be excluded from the model and real |
* because they can be excluded from the model and real |
* if in the model but excluded because missing values, but how to get k from ij?*/ |
* if in the model but excluded because missing values, but how to get k from ij?*/ |
for(j=ij+1; j<= cptcovt; j++){ |
for(j=ij+1; j<= cptcovt; j++){ |
Tvaraff[j]=0; |
Tvaraff[j]=0; |
Tmodelind[j]=0; |
Tmodelind[j]=0; |
} |
} |
for(j=ntveff+1; j<= cptcovt; j++){ |
for(j=ntveff+1; j<= cptcovt; j++){ |
TmodelInvind[j]=0; |
TmodelInvind[j]=0; |
} |
} |
/* To be sorted */ |
/* To be sorted */ |
; |
; |
} |
} |
|
|
|
|
/*********** Health Expectancies ****************/ |
/*********** Health Expectancies ****************/ |
Line 5414 void concatwav(int wav[], int **dh, int
|
Line 5487 void concatwav(int wav[], int **dh, int
|
xp[i] = x[i] + (i==theta ?delti[theta]:0); |
xp[i] = x[i] + (i==theta ?delti[theta]:0); |
} |
} |
|
|
prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nresult); |
prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres); |
|
|
if (popbased==1) { |
if (popbased==1) { |
if(mobilav ==0){ |
if(mobilav ==0){ |
Line 5446 void concatwav(int wav[], int **dh, int
|
Line 5519 void concatwav(int wav[], int **dh, int
|
for(i=1; i<=npar; i++) /* Computes gradient x - delta */ |
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); |
|
|
prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nresult); |
prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres); |
|
|
if (popbased==1) { |
if (popbased==1) { |
if(mobilav ==0){ |
if(mobilav ==0){ |
Line 5523 void concatwav(int wav[], int **dh, int
|
Line 5596 void concatwav(int wav[], int **dh, int
|
/* end ppptj */ |
/* end ppptj */ |
/* x centered again */ |
/* x centered again */ |
|
|
prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nresult); |
prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres); |
|
|
if (popbased==1) { |
if (popbased==1) { |
if(mobilav ==0){ |
if(mobilav ==0){ |
Line 6344 void printinggnuplot(char fileresu[], ch
|
Line 6417 void printinggnuplot(char fileresu[], ch
|
if(TKresult[nres]!= k1) |
if(TKresult[nres]!= k1) |
continue; |
continue; |
/* We are interested in selected combination by the resultline */ |
/* We are interested in selected combination by the resultline */ |
printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); |
/* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */ |
fprintf(ficgp,"\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); |
fprintf(ficgp,"\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); |
for (k=1; k<=cptcoveff; k++){ /* For each covariate k get corresponding value lv for combination k1 */ |
for (k=1; k<=cptcoveff; k++){ /* For each covariate k get corresponding value lv for combination k1 */ |
lv= decodtabm(k1,k,cptcoveff); /* Should be the value of the covariate corresponding to k1 combination */ |
lv= decodtabm(k1,k,cptcoveff); /* Should be the value of the covariate corresponding to k1 combination */ |
Line 6353 void printinggnuplot(char fileresu[], ch
|
Line 6426 void printinggnuplot(char fileresu[], ch
|
/* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */ |
/* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */ |
vlv= nbcode[Tvaraff[k]][lv]; /* vlv is the value of the covariate lv, 0 or 1 */ |
vlv= nbcode[Tvaraff[k]][lv]; /* vlv is the value of the covariate lv, 0 or 1 */ |
/* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv */ |
/* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv */ |
printf(" V%d=%d ",Tvaraff[k],vlv); |
/* printf(" V%d=%d ",Tvaraff[k],vlv); */ |
fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); |
fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); |
} |
} |
for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */ |
for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */ |
printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); |
/* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */ |
fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); |
fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); |
} |
} |
printf("\n#\n"); |
/* printf("\n#\n"); */ |
fprintf(ficgp,"\n#\n"); |
fprintf(ficgp,"\n#\n"); |
if(invalidvarcomb[k1]){ |
if(invalidvarcomb[k1]){ |
fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1); |
fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1); |
Line 6375 void printinggnuplot(char fileresu[], ch
|
Line 6448 void printinggnuplot(char fileresu[], ch
|
if (i==cpt) fprintf(ficgp," %%lf (%%lf)"); |
if (i==cpt) fprintf(ficgp," %%lf (%%lf)"); |
else fprintf(ficgp," %%*lf (%%*lf)"); |
else fprintf(ficgp," %%*lf (%%*lf)"); |
} |
} |
fprintf(ficgp,"\" t\"Period (stable) prevalence\" w l lt 0,\"%s\" every :::%d::%d u 1:($2==%d ? $4+1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),k1-1,k1-1,nres); |
fprintf(ficgp,"\" t\"Period (stable) prevalence\" w l lt 0,\"%s\" every :::%d::%d u 1:($2==%d ? $3+1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),k1-1,k1-1,nres); |
for (i=1; i<= nlstate ; i ++) { |
for (i=1; i<= nlstate ; i ++) { |
if (i==cpt) fprintf(ficgp," %%lf (%%lf)"); |
if (i==cpt) fprintf(ficgp," %%lf (%%lf)"); |
else fprintf(ficgp," %%*lf (%%*lf)"); |
else fprintf(ficgp," %%*lf (%%*lf)"); |
} |
} |
fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $4-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),k1-1,k1-1,nres); |
fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),k1-1,k1-1,nres); |
for (i=1; i<= nlstate ; i ++) { |
for (i=1; i<= nlstate ; i ++) { |
if (i==cpt) fprintf(ficgp," %%lf (%%lf)"); |
if (i==cpt) fprintf(ficgp," %%lf (%%lf)"); |
else fprintf(ficgp," %%*lf (%%*lf)"); |
else fprintf(ficgp," %%*lf (%%*lf)"); |
Line 6388 void printinggnuplot(char fileresu[], ch
|
Line 6461 void printinggnuplot(char fileresu[], ch
|
fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); |
fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); |
if(backcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */ |
if(backcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */ |
/* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */ |
/* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */ |
fprintf(ficgp,",\"%s\" u ($2==%d ?$1:1/0):(",subdirf2(fileresu,"PLB_"),nres); /* Age is in 1, nres in 2 to be fixed */ |
fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */ |
if(cptcoveff ==0){ |
if(cptcoveff ==0){ |
fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line ", 2+(cpt-1), cpt ); |
fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt ); |
}else{ |
}else{ |
kl=0; |
kl=0; |
for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */ |
for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */ |
Line 6405 void printinggnuplot(char fileresu[], ch
|
Line 6478 void printinggnuplot(char fileresu[], ch
|
/*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */ |
/*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */ |
/* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/ |
/* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/ |
if(k==cptcoveff){ |
if(k==cptcoveff){ |
fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \ |
fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \ |
4+(cpt-1), cpt ); /* 4 or 6 ?*/ |
2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/ |
}else{ |
}else{ |
fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]); |
fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]); |
kl++; |
kl++; |
Line 6475 void printinggnuplot(char fileresu[], ch
|
Line 6548 void printinggnuplot(char fileresu[], ch
|
else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n"); |
else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n"); |
} /* state */ |
} /* state */ |
} /* vpopbased */ |
} /* vpopbased */ |
fprintf(ficgp,"\nset out;set out \"%s_%d.svg\"; replot; set out; \n",subdirf2(optionfilefiname,"E_"),k1); /* Buggy gnuplot */ |
fprintf(ficgp,"\nset out;set out \"%s_%d-%d.svg\"; replot; set out; \n",subdirf2(optionfilefiname,"E_"),k1,nres); /* Buggy gnuplot */ |
} /* end nres */ |
} /* end nres */ |
} /* k1 end 2 eme*/ |
} /* k1 end 2 eme*/ |
|
|
Line 8532 Dummy[k] 0=dummy (0 1), 1 quantitative (
|
Line 8605 Dummy[k] 0=dummy (0 1), 1 quantitative (
|
TvarFind[ncovf]=k; |
TvarFind[ncovf]=k; |
TvarFQ[nqfveff]=Tvar[k]-ncovcol; /* TvarFQ[1]=V2-1=1st in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */ |
TvarFQ[nqfveff]=Tvar[k]-ncovcol; /* TvarFQ[1]=V2-1=1st in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */ |
TvarFQind[nqfveff]=k; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */ |
TvarFQind[nqfveff]=k; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */ |
}else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying variables */ |
}else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */ |
Fixed[k]= 1; |
Fixed[k]= 1; |
Dummy[k]= 0; |
Dummy[k]= 0; |
ntveff++; /* Only simple time varying dummy variable */ |
ntveff++; /* Only simple time varying dummy variable */ |
Line 8543 Dummy[k] 0=dummy (0 1), 1 quantitative (
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Line 8616 Dummy[k] 0=dummy (0 1), 1 quantitative (
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TvarsDind[nsd]=k; |
TvarsDind[nsd]=k; |
ncovv++; /* Only simple time varying variables */ |
ncovv++; /* Only simple time varying variables */ |
TvarV[ncovv]=Tvar[k]; |
TvarV[ncovv]=Tvar[k]; |
TvarVind[ncovv]=k; |
TvarVind[ncovv]=k; /* TvarVind[2]=2 TvarVind[3]=3 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Any time varying singele */ |
TvarVD[ntveff]=Tvar[k]; /* TvarVD[1]=V4 TvarVD[2]=V3 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple time varying dummy variable */ |
TvarVD[ntveff]=Tvar[k]; /* TvarVD[1]=V4 TvarVD[2]=V3 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple time varying dummy variable */ |
TvarVDind[ntveff]=k; /* TvarVDind[1]=2 TvarVDind[2]=3 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple time varying dummy variable */ |
TvarVDind[ntveff]=k; /* TvarVDind[1]=2 TvarVDind[2]=3 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple time varying dummy variable */ |
printf("Quasi Tmodelind[%d]=%d,Tvar[Tmodelind[%d]]=V%d, ncovcol=%d, nqv=%d,Tvar[k]- ncovcol-nqv=%d\n",ntveff,k,ntveff,Tvar[k], ncovcol, nqv,Tvar[k]- ncovcol-nqv); |
printf("Quasi Tmodelind[%d]=%d,Tvar[Tmodelind[%d]]=V%d, ncovcol=%d, nqv=%d,Tvar[k]- ncovcol-nqv=%d\n",ntveff,k,ntveff,Tvar[k], ncovcol, nqv,Tvar[k]- ncovcol-nqv); |
Line 8559 Dummy[k] 0=dummy (0 1), 1 quantitative (
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Line 8632 Dummy[k] 0=dummy (0 1), 1 quantitative (
|
TvarsQ[nsq]=Tvar[k]; |
TvarsQ[nsq]=Tvar[k]; |
TvarsQind[nsq]=k; |
TvarsQind[nsq]=k; |
TvarV[ncovv]=Tvar[k]; |
TvarV[ncovv]=Tvar[k]; |
TvarVind[ncovv]=k; |
TvarVind[ncovv]=k; /* TvarVind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Any time varying singele */ |
TvarVQ[nqtveff]=Tvar[k]; /* TvarVQ[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple time varying quantitative variable */ |
TvarVQ[nqtveff]=Tvar[k]; /* TvarVQ[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple time varying quantitative variable */ |
TvarVQind[nqtveff]=k; /* TvarVQind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple time varying quantitative variable */ |
TvarVQind[nqtveff]=k; /* TvarVQind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple time varying quantitative variable */ |
TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */ |
TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */ |
Line 8773 Dummy[k] 0=dummy (0 1), 1 quantitative (
|
Line 8846 Dummy[k] 0=dummy (0 1), 1 quantitative (
|
} |
} |
|
|
int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn ) |
int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn ) |
{ |
{/* Check ages at death */ |
int i, m; |
int i, m; |
int firstone=0; |
int firstone=0; |
|
|
Line 9246 int back_prevalence_limit(double *p, dou
|
Line 9319 int back_prevalence_limit(double *p, dou
|
if(mobilavproj > 0){ |
if(mobilavproj > 0){ |
/* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */ |
/* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */ |
/* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */ |
/* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */ |
bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k); |
bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres); |
}else if (mobilavproj == 0){ |
}else if (mobilavproj == 0){ |
printf("There is no chance to get back prevalence limit if data aren't non zero and summing to 1, please try a non null mobil_average(=%d) parameter or mobil_average=-1 if you want to try at your own risk.\n",mobilavproj); |
printf("There is no chance to get back prevalence limit if data aren't non zero and summing to 1, please try a non null mobil_average(=%d) parameter or mobil_average=-1 if you want to try at your own risk.\n",mobilavproj); |
fprintf(ficlog,"There is no chance to get back prevalence limit if data aren't non zero and summing to 1, please try a non null mobil_average(=%d) parameter or mobil_average=-1 if you want to try at your own risk.\n",mobilavproj); |
fprintf(ficlog,"There is no chance to get back prevalence limit if data aren't non zero and summing to 1, please try a non null mobil_average(=%d) parameter or mobil_average=-1 if you want to try at your own risk.\n",mobilavproj); |
exit(1); |
exit(1); |
}else{ |
}else{ |
/* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */ |
/* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */ |
bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k); |
bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres); |
} |
} |
fprintf(ficresplb,"%.0f ",age ); |
fprintf(ficresplb,"%.0f ",age ); |
for(j=1;j<=cptcoveff;j++) |
for(j=1;j<=cptcoveff;j++) |
Line 9817 int main(int argc, char *argv[])
|
Line 9890 int main(int argc, char *argv[])
|
delti=delti3[1][1]; |
delti=delti3[1][1]; |
/*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/ |
/*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/ |
if(mle==-1){ /* Print a wizard for help writing covariance matrix */ |
if(mle==-1){ /* Print a wizard for help writing covariance matrix */ |
|
/* We could also provide initial parameters values giving by simple logistic regression |
|
* only one way, that is without matrix product. We will have nlstate maximizations */ |
|
/* for(i=1;i<nlstate;i++){ */ |
|
/* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */ |
|
/* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */ |
|
/* } */ |
prwizard(ncovmodel, nlstate, ndeath, model, ficparo); |
prwizard(ncovmodel, nlstate, ndeath, model, ficparo); |
printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso); |
printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso); |
fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso); |
fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso); |
Line 9825 int main(int argc, char *argv[])
|
Line 9904 int main(int argc, char *argv[])
|
fclose (ficlog); |
fclose (ficlog); |
goto end; |
goto end; |
exit(0); |
exit(0); |
|
} else if(mle==-2) { /* Guessing from means */ |
|
prwizard(ncovmodel, nlstate, ndeath, model, ficparo); |
|
printf(" You chose mle=-2, look at file %s for a template of covariance matrix \n",filereso); |
|
fprintf(ficlog," You chose mle=-2, look at file %s for a template of covariance matrix \n",filereso); |
|
|
} else if(mle==-5) { /* Main Wizard */ |
} else if(mle==-5) { /* Main Wizard */ |
prwizard(ncovmodel, nlstate, ndeath, model, ficparo); |
prwizard(ncovmodel, nlstate, ndeath, model, ficparo); |
printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso); |
printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso); |
Line 10148 Please run with mle=-1 to get a correct
|
Line 10232 Please run with mle=-1 to get a correct
|
*/ |
*/ |
|
|
concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm); |
concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm); |
/* */ |
/* Concatenates waves */ |
|
|
free_vector(moisdc,1,n); |
free_vector(moisdc,1,n); |
free_vector(andc,1,n); |
free_vector(andc,1,n); |
Line 10351 Interval (in months) between two waves:
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Line 10435 Interval (in months) between two waves:
|
/* For mortality only */ |
/* For mortality only */ |
if (mle==-3){ |
if (mle==-3){ |
ximort=matrix(1,NDIM,1,NDIM); |
ximort=matrix(1,NDIM,1,NDIM); |
for(i=1;i<=NDIM;i++) |
for(i=1;i<=NDIM;i++) |
for(j=1;j<=NDIM;j++) |
for(j=1;j<=NDIM;j++) |
ximort[i][j]=0.; |
ximort[i][j]=0.; |
/* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */ |
/* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */ |
cens=ivector(1,n); |
cens=ivector(1,n); |
ageexmed=vector(1,n); |
ageexmed=vector(1,n); |
Line 10589 Please run with mle=-1 to get a correct
|
Line 10673 Please run with mle=-1 to get a correct
|
printf("\n"); |
printf("\n"); |
if(mle>=1){ /* Could be 1 or 2, Real Maximization */ |
if(mle>=1){ /* Could be 1 or 2, Real Maximization */ |
/* mlikeli uses func not funcone */ |
/* mlikeli uses func not funcone */ |
|
/* for(i=1;i<nlstate;i++){ */ |
|
/* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */ |
|
/* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */ |
|
/* } */ |
mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func); |
mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func); |
} |
} |
if(mle==0) {/* No optimization, will print the likelihoods for the datafile */ |
if(mle==0) {/* No optimization, will print the likelihoods for the datafile */ |
Line 11133 Please run with mle=-1 to get a correct
|
Line 11221 Please run with mle=-1 to get a correct
|
for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */ |
for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */ |
if(TKresult[nres]!= k) |
if(TKresult[nres]!= k) |
continue; |
continue; |
printf("\n#****** Selected:"); |
printf("\n#****** Result for:"); |
fprintf(ficrest,"\n#****** Selected:"); |
fprintf(ficrest,"\n#****** Result for:"); |
fprintf(ficlog,"\n#****** Selected:"); |
fprintf(ficlog,"\n#****** Result for:"); |
for(j=1;j<=cptcoveff;j++){ |
for(j=1;j<=cptcoveff;j++){ |
printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); |
printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); |
fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); |
fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); |