--- imach/src/imach.c 2022/07/22 12:04:24 1.321 +++ imach/src/imach.c 2022/07/27 17:40:48 1.328 @@ -1,6 +1,30 @@ -/* $Id: imach.c,v 1.321 2022/07/22 12:04:24 brouard Exp $ +/* $Id: imach.c,v 1.328 2022/07/27 17:40:48 brouard Exp $ $State: Exp $ $Log: imach.c,v $ + Revision 1.328 2022/07/27 17:40:48 brouard + Summary: valgrind bug fixed by initializing to zero DummyV as well as Tage + + Revision 1.327 2022/07/27 14:47:35 brouard + Summary: Still a problem for one-step probabilities in case of quantitative variables + + Revision 1.326 2022/07/26 17:33:55 brouard + Summary: some test with nres=1 + + Revision 1.325 2022/07/25 14:27:23 brouard + Summary: r30 + + * imach.c (Module): Error cptcovn instead of nsd in bmij (was + coredumped, revealed by Feiuno, thank you. + + Revision 1.324 2022/07/23 17:44:26 brouard + *** empty log message *** + + Revision 1.323 2022/07/22 12:30:08 brouard + * imach.c (Module): Output of Wald test in the htm file and not only in the log. + + Revision 1.322 2022/07/22 12:27:48 brouard + * imach.c (Module): Output of Wald test in the htm file and not only in the log. + Revision 1.321 2022/07/22 12:04:24 brouard Summary: r28 @@ -863,7 +887,7 @@ The same imach parameter file can be used but the option for mle should be -3. - Agnès, who wrote this part of the code, tried to keep most of the + Agnès, who wrote this part of the code, tried to keep most of the former routines in order to include the new code within the former code. The output is very simple: only an estimate of the intercept and of @@ -1042,13 +1066,13 @@ Important routines - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities) and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually. - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables - o There are 2*cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if + o There are 2**cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless. - Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr). - Institut national d'études démographiques, Paris. + Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr). + Institut national d'études démographiques, Paris. This software have been partly granted by Euro-REVES, a concerted action from the European Union. It is copyrighted identically to a GNU software product, ie programme and @@ -1179,7 +1203,7 @@ typedef struct { #define NINTERVMAX 8 #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */ #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */ -#define NCOVMAX 30 /**< Maximum number of covariates, including generated covariates V1*V2 */ +#define NCOVMAX 30 /**< Maximum number of covariates used in the model, including generated covariates V1*V2 or V1*age */ #define codtabm(h,k) (1 & (h-1) >> (k-1))+1 /*#define decodtabm(h,k,cptcoveff)= (h <= (1<> (k-1)) & 1) +1 : -1)*/ #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1 @@ -1203,12 +1227,12 @@ typedef struct { #define ODIRSEPARATOR '\\' #endif -/* $Id: imach.c,v 1.321 2022/07/22 12:04:24 brouard Exp $ */ +/* $Id: imach.c,v 1.328 2022/07/27 17:40:48 brouard Exp $ */ /* $State: Exp $ */ #include "version.h" char version[]=__IMACH_VERSION__; -char copyright[]="May 2022,INED-EUROREVES-Institut de longevite-Japan Society for the Promotion of Science (Grant-in-Aid for Scientific Research 25293121), Intel Software 2015-2020, Nihon University 2021-202, INED 2000-2022"; -char fullversion[]="$Revision: 1.321 $ $Date: 2022/07/22 12:04:24 $"; +char copyright[]="July 2022,INED-EUROREVES-Institut de longevite-Japan Society for the Promotion of Science (Grant-in-Aid for Scientific Research 25293121), Intel Software 2015-2020, Nihon University 2021-202, INED 2000-2022"; +char fullversion[]="$Revision: 1.328 $ $Date: 2022/07/27 17:40:48 $"; char strstart[80]; char optionfilext[10], optionfilefiname[FILENAMELENGTH]; int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */ @@ -2410,16 +2434,16 @@ void powell(double p[], double **xi, int for (j=1;j<=n;j++) pt[j]=p[j]; rcurr_time = time(NULL); for (*iter=1;;++(*iter)) { - fp=(*fret); /* From former iteration or initial value */ ibig=0; del=0.0; rlast_time=rcurr_time; /* (void) gettimeofday(&curr_time,&tzp); */ rcurr_time = time(NULL); curr_time = *localtime(&rcurr_time); - printf("\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout); - fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog); + printf("\nPowell iter=%d -2*LL=%.12f gain=%.12f=%.3g %ld sec. %ld sec.",*iter,*fret, fp-*fret,fp-*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout); + fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f gain=%.12f=%.3g %ld sec. %ld sec.",*iter,*fret, fp-*fret,fp-*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog); /* fprintf(ficrespow,"%d %.12f %ld",*iter,*fret,curr_time.tm_sec-start_time.tm_sec); */ + fp=(*fret); /* From former iteration or initial value */ for (i=1;i<=n;i++) { fprintf(ficrespow," %.12lf", p[i]); } @@ -3129,7 +3153,7 @@ double **pmij(double **ps, double *cov, ps[i][i]=1./(s1+1.); /* Computing other pijs */ for(j=1; j0) { fprintf(ficresprob, "\n#********** Variable "); for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]); @@ -6914,8 +6954,11 @@ To be simple, these graphs help to under cov[2]=age; if(nagesqr==1) cov[3]= age*age; - for (k=1; k<=cptcovn;k++) { - cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)]; + /* for (k=1; k<=cptcovn;k++) { */ + /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)]; */ + for (k=1; k<=nsd;k++) { /* For single dummy covariates only */ + /* Here comes the value of the covariate 'j1' after renumbering k with single dummy covariates */ + cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(j1,k)]; /*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*//* j1 1 2 3 4 * 1 1 1 1 1 * 2 2 1 1 1 @@ -6926,12 +6969,39 @@ To be simple, these graphs help to under /* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1, Tage[1]=2 */ /* ) p nbcode[Tvar[Tage[k]]][(1 & (ij-1) >> (k-1))+1] */ /*for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; */ - for (k=1; k<=cptcovage;k++) - cov[2+Tage[k]+nagesqr]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; - for (k=1; k<=cptcovprod;k++) - cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; - - + for (k=1; k<=cptcovage;k++){ /* For product with age */ + if(Dummy[Tage[k]]==2){ /* dummy with age */ + cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(j1,k)]*cov[2]; + /* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */ + } else if(Dummy[Tage[k]]==3){ /* quantitative with age */ + printf("Internal IMaCh error, don't know which value for quantitative covariate with age, Tage[k]%d, k=%d, Tvar[Tage[k]]=V%d, age=%d\n",Tage[k],k ,Tvar[Tage[k]], (int)cov[2]); + exit(1); + /* cov[2+nagesqr+Tage[k]]=meanq[k]/idq[k]*cov[2];/\* Using the mean of quantitative variable Tvar[Tage[k]] /\* Tqresult[nres][k]; *\/ */ + /* cov[++k1]=Tqresult[nres][k]; */ + } + /* cov[2+Tage[k]+nagesqr]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */ + } + for (k=1; k<=cptcovprod;k++){/* For product without age */ + if(Dummy[Tvard[k][1]==0]){ + if(Dummy[Tvard[k][2]==0]){ + cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(j1,k)] * nbcode[Tvard[k][2]][codtabm(j1,k)]; + /* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */ + }else{ /* Should we use the mean of the quantitative variables? */ + cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(j1,k)] * Tqresult[nres][k]; + /* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; */ + } + }else{ + if(Dummy[Tvard[k][2]==0]){ + cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(j1,k)] * Tqinvresult[nres][Tvard[k][1]]; + /* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; */ + }else{ + cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; + /* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */ + } + } + /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */ + } +/* For each age and combination of dummy covariates we slightly move the parameters of delti in order to get the gradient*/ for(theta=1; theta <=npar; theta++){ for(i=1; i<=npar; i++) xp[i] = x[i] + (i==theta ?delti[theta]:(double)0); @@ -7116,6 +7186,7 @@ To be simple, these graphs help to under } /* k12 */ } /*l1 */ }/* k1 */ + } /* loop on nres */ } /* loop on combination of covariates j1 */ free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage); free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage); @@ -7989,8 +8060,8 @@ set ter svg size 640, 480\nunset log y\n fprintf(ficgp,", '' "); /* l=(nlstate+ndeath)*(i-1)+1; */ l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */ - /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */ - /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l+(cpt-1)+i-1); /\* a vérifier *\/ */ + /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */ + /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l+(cpt-1)+i-1); /\* a vérifier *\/ */ fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */ /* for (j=2; j<= nlstate ; j ++) */ /* fprintf(ficgp,"+$%d",k+l+j-1); */ @@ -8340,9 +8411,9 @@ set ter svg size 640, 480\nunset log y\n for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */ /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */ if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */ - if(j==Tage[ij]) { /* Product by age To be looked at!!*/ + if(j==Tage[ij]) { /* Product by age To be looked at!!*//* Bug valgrind */ if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */ - if(DummyV[j]==0){ + if(DummyV[j]==0){/* Bug valgrind */ fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);; }else{ /* quantitative */ fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */ @@ -9532,6 +9603,10 @@ int readdata(char datafile[], int firsto DummyV=ivector(1,NCOVMAX); /* 1 to 3 */ FixedV=ivector(1,NCOVMAX); /* 1 to 3 */ + for(v=1;v16 */ ncodemaxwundef=ivector(1,NCOVMAX); /* Number of code per covariate; if - 1 O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */ @@ -11933,7 +12009,9 @@ Please run with mle=-1 to get a correct Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age 4 covariates (3 plus signs) Tage[1=V3*age]= 4; Tage[2=age*V4] = 3 - */ + */ + for(i=1;iDatafile=%s Firstpass=%d La optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model); } - fprintf(fichtm,"\n\n\nIMaCh %s\n IMaCh for Interpolated Markov Chain
\nSponsored by Copyright (C) 2002-2015 INED-EUROREVES-Institut de longévité-2013-2016-Japan Society for the Promotion of Sciences 日本学術振興会 (Grant-in-Aid for Scientific Research 25293121) - Intel Software 2015-2018
\ + fprintf(fichtm,"\n\n\nIMaCh %s\n IMaCh for Interpolated Markov Chain
\nSponsored by Copyright (C) 2002-2015 INED-EUROREVES-Institut de longévité-2013-2016-Japan Society for the Promotion of Sciences 日本学術振興会 (Grant-in-Aid for Scientific Research 25293121) - Intel Software 2015-2018
\
\n\ IMaCh-%s
%s \
\n\ @@ -12556,7 +12634,7 @@ Please run with mle=-1 to get a correct hesscov(matcov, hess, p, npar, delti, ftolhess, func); printf("Parameters and 95%% confidence intervals\n W is simply the result of the division of the parameter by the square root of covariance of the parameter.\n And Wald-based confidence intervals plus and minus 1.96 * W .\n But be careful that parameters are highly correlated because incidence of disability is highly correlated to incidence of recovery.\n It might be better to visualize the covariance matrix. See the page 'Matrix of variance-covariance of one-step probabilities' and its graphs.\n"); fprintf(ficlog, "Parameters, Wald tests and Wald-based confidence intervals\n W is simply the result of the division of the parameter by the square root of covariance of the parameter.\n And Wald-based confidence intervals plus and minus 1.96 * W \n It might be better to visualize the covariance matrix. See the page 'Matrix of variance-covariance of one-step probabilities' and its graphs.\n"); - fprintf(fichtm, "\n

Parameters, Wald tests and Wald-based confidence intervals\n
W is simply the result of the division of the parameter by the square root of covariance of the parameter.\n
And Wald-based confidence intervals plus and minus 1.96 * W \n
It might be better to visualize the covariance matrix. See the page 'Matrix of variance-covariance of one-step probabilities' and its graphs.\n
"); + fprintf(fichtm, "\n

The Wald test results are output only if the maximimzation of the Likelihood is performed (mle=1)\n
Parameters, Wald tests and Wald-based confidence intervals\n
W is simply the result of the division of the parameter by the square root of covariance of the parameter.\n
And Wald-based confidence intervals plus and minus 1.96 * W \n
It might be better to visualize the covariance matrix. See the page 'Matrix of variance-covariance of one-step probabilities and its graphs'.\n
",optionfilehtmcov); fprintf(fichtm,"\n"); fprintf(fichtm, "\n"); if(nagesqr==1){ @@ -12587,14 +12665,14 @@ Please run with mle=-1 to get a correct fprintf(fichtm, "",i,k); for(j=1; j <=ncovmodel; j++){ wald=p[jk]/sqrt(matcov[jk][jk]); - printf("%12.7f(%12.7f) sqrt(W)=%8.3f CI=[%12.7f ; %12.7f] ",p[jk],sqrt(matcov[jk][jk]), p[jk]/sqrt(matcov[jk][jk]), p[jk]-1.96*sqrt(matcov[jk][jk]),p[jk]+1.96*sqrt(matcov[jk][jk])); - fprintf(ficlog,"%12.7f(%12.7f) sqrt(W)=%8.3f CI=[%12.7f ; %12.7f] ",p[jk],sqrt(matcov[jk][jk]), p[jk]/sqrt(matcov[jk][jk]), p[jk]-1.96*sqrt(matcov[jk][jk]),p[jk]+1.96*sqrt(matcov[jk][jk])); + printf("%12.7f(%12.7f) W=%8.3f CI=[%12.7f ; %12.7f] ",p[jk],sqrt(matcov[jk][jk]), p[jk]/sqrt(matcov[jk][jk]), p[jk]-1.96*sqrt(matcov[jk][jk]),p[jk]+1.96*sqrt(matcov[jk][jk])); + fprintf(ficlog,"%12.7f(%12.7f) W=%8.3f CI=[%12.7f ; %12.7f] ",p[jk],sqrt(matcov[jk][jk]), p[jk]/sqrt(matcov[jk][jk]), p[jk]-1.96*sqrt(matcov[jk][jk]),p[jk]+1.96*sqrt(matcov[jk][jk])); if(fabs(wald) > 1.96){ fprintf(fichtm, "", p[jk]-1.96*sqrt(matcov[jk][jk]),p[jk]+1.96*sqrt(matcov[jk][jk])); jk++; }
Model=1+ age%1d%1d%12.7f
(%12.7f)
",p[jk],sqrt(matcov[jk][jk])); }else{ fprintf(fichtm, "		%12.7f (%12.7f)
",p[jk],sqrt(matcov[jk][jk])); } - fprintf(fichtm,"sqrt(W)=%8.3f
",wald); + fprintf(fichtm,"W=%8.3f
",wald); fprintf(fichtm,"[%12.7f;%12.7f]