R/loglikcubecov.R

In CUB: A Class of Mixture Models for Ordinal Data

#' @title Log-likelihood function of a CUBE model with covariates
#' @aliases loglikcubecov
#' @description Compute the log-likelihood function of a CUBE model for ordinal responses,
#' with covariates for explaining all the three parameters.
#' @usage loglikcubecov(m, ordinal, Y, W, Z, bet, gama, alpha)
#' @param m Number of ordinal categories
#' @param ordinal  Vector of ordinal responses
#' @param Y Matrix of covariates for explaining the uncertainty component
#' @param W Matrix of covariates for explaining the feeling component
#' @param Z Matrix of covariates for explaining the overdispersion component
#' @param bet Vector of parameters for the uncertainty component, with length equal to 
#' NCOL(Y) + 1 to account for an intercept term (first entry of bet)
#' @param gama Vector of parameters for the feeling component, with length equal to 
#' NCOL(W) + 1 to account for an intercept term (first entry of gama)  
#' @param alpha Vector of parameters for the overdispersion component, with length equal to 
#' NCOL(Z) + 1 to account for an intercept term (first entry of alpha) 
#' @keywords internal



loglikcubecov <-
function(m,ordinal,Y,W,Z,bet,gama,alpha){
  
  
  if (is.factor(ordinal)){
    ordinal<-unclass(ordinal)
  }
  Y<-as.matrix(Y); W<-as.matrix(W); Z<-as.matrix(Z)
  paivett<-logis(Y,bet); csivett<-logis(W,gama); 
  phivett<-1/(-1+ 1/(logis(Z,alpha))) 
  probi<-paivett*(betabinomial(m,ordinal,csivett,phivett)-1/m)+1/m
  return(sum(log(probi)))
}