# R/varcovgecub.R In CUB: A Class of Mixture Models for Ordinal Data

#### Documented in varcovgecub

```#' @title Variance-covariance matrix of a CUB model without covariates
#' @description Compute the variance-covariance matrix of parameter estimates of a CUB model without covariates.
#' @aliases varcovgecub
#' @usage varcovgecub(ordinal,Y,W,X,bet,gama,omega,shelter)
#' @param ordinal Vector of ordinal responses
#' @param Y Matrix of selected covariates to explain the uncertainty component (default: no covariate is included
#' in the model)
#' @param W Y Matrix of selected covariates to explain the feeling component (default: no covariate is included
#' in the model)
#' @param X Matrix of selected covariates to explain the shelter component (default: no covariate is included
#' in the model)
#' @param bet Parameter vector for the Uncertainty component
#' @param gama Parameter vector for the Feeling component
#' @param omega Parameter vector for the shelter component
#' @param shelter Cateogry corresponding to the shelter effect
#' @details The function checks if the variance-covariance matrix is positive-definite: if not,
#' it returns a warning message and produces a matrix with NA entries.
#' @keywords internal

varcovgecub<-function(ordinal,Y,W,X,bet,gama,omega,shelter){

Y<-as.matrix(Y);W<-as.matrix(W);  X<-as.matrix(X);
if (ncol(W)==1){
W<-as.numeric(W)
}
if (ncol(Y)==1){
Y<-as.numeric(Y)
}
if (ncol(X)==1){
X<-as.numeric(X)
}

probi<-probgecub(ordinal,Y,W,X,bet,gama,omega,shelter);
vvi<-1/probi; dicotom<-ifelse(ordinal==shelter,1,0)

#   Y=as.matrix(Y)
#   W=as.matrix(W)
#   X=as.matrix(X)
paii<-logis(Y,bet);
csii<-logis(W,gama); deltai<-logis(X,omega);
m<-length(levels(factor(ordinal,ordered=TRUE)))

bierrei<-bitgama(m,ordinal,W,gama);
YY<-cbind(1,Y);
WW<-cbind(1,W); XX<-cbind(1,X);
np<-NCOL(YY)+NCOL(WW)+NCOL(XX);
#  /* vettori (n,1)  utili per deriv...prime*/
mconi<-m-ordinal-(m-1)*csii;

#  /* deriv.prime/prob_i */
vettAA<-paii*(1-paii)*(1-deltai)*(bierrei-1/m)*vvi
AA <- Hadprod(YY,vettAA)  ###   n x p+1
#AA=YY.*paii.*(1-paii).*(1-deltai).*(bierrei-1/m).*vvi;
vettBB<-paii*(1-deltai)*mconi*bierrei*vvi;
vettCC<-deltai*(dicotom-probi)*vvi
# CC=XX.*deltai.*(dicotom-probi).*vvi;

# /* utili per deriv.seconde/prob_i*/
dconi<- paii*(1-paii)*(1-2*paii)*(1-deltai)*(bierrei-1/m)*vvi;
#dconi=paii.*(1-paii).*(1-2*paii).*(1-deltai).*(bierrei-1/m).*vvi;
gconi<- paii*(1-deltai)*bierrei*(mconi^2-(m-1)*csii)*(1-csii)*vvi;
#   gconi=paii.*(1-deltai).*bierrei.*(mconi^2-(m-1)*csii.*(1-csii)).*vvi;
lconi <- deltai*(1-2*deltai)*(dicotom-probi)*vvi;
#   lconi=deltai.*(1-2*deltai).*(dicotom-probi).*vvi;
econi <- paii*(1-paii)*(1-deltai)*(bierrei)*mconi*vvi;
#   econi=paii.*(1-paii).*(1-deltai).*bierrei.*mconi.*vvi;
fconi<- (-paii)*(1-paii)*deltai*(1-deltai)*(bierrei-1/m)*vvi;
#   fconi=-paii.*(1-paii).*deltai.*(1-deltai).*(bierrei-1/m).*vvi;
hconi<-(-paii)*deltai*(1-deltai)*bierrei*mconi*vvi;#   hconi=-paii.*deltai.*(1-deltai).*bierrei.*mconi.*vvi;
#/* Observed information matrix (gi??? con il segno meno) */

inf32<-t(CC)%*%BB-t(XX)%*%Hadprod(WW,hconi);          #/* (s+1,q+1) */  @...prima era: BB'CC @

inf12<-t(inf21);  inf13<-t(inf31);  inf23<-t(inf32);

matinf<-rbind(cbind(inf11,inf12,inf13),cbind(inf21,inf22,inf23),cbind(inf31,inf32,inf33));  # Information matrix

if(any(is.na(matinf))==TRUE){
warning("ATTENTION: NAs produced")
varmat<-matrix(NA,nrow=np,ncol=np)
} else {
if(det(matinf)<=0){
warning("ATTENTION: Variance-covariance matrix NOT positive definite")
varmat<-matrix(NA,nrow=np,ncol=np)
} else {
varmat<-solve(matinf)
}
}

#
# if(det(matinf)<=0){
#   notpd=1;
#   cat("=======================================================================","\n")
#   cat("Variance-covariance matrix NOT positive definite","\n")
#   cat("=======================================================================","\n")
# } else {
#   notpd=0;
#   varmat=solve(matinf);
# }
return(varmat)

}
```

## Try the CUB package in your browser

Any scripts or data that you put into this service are public.

CUB documentation built on Feb. 9, 2018, 6:14 a.m.