loglikcuben: Log-likelihood function of CUBE models for ordinal data

In CUB: A Class of Mixture Models for Ordinal Data

Description

Compute the log-likelihood function of a CUBE model without covariates for ordinal responses, possibly with different vectors of parameters for each observation.

Usage

loglikcuben(m, ordinal, assepai, assecsi, assephi)

Arguments

m	Number of ordinal categories
ordinal	Vector of ordinal responses
assepai	Vector of uncertainty parameters for the given observations (with the same length as ordinal)
assecsi	Vector of feeling parameters for the given observations (with the same length as ordinal)
assephi	Vector of overdispersion parameters for the given observations (with the same length as ordinal)

See Also

loglikCUBE

Examples

m<-8
n0<-230;  n1<-270
bet<-c(-1.5,1.2)
gama<-c(0.5,-1.2)
alpha<-c(-1.2,-0.5)
pai0<-1/(1+exp(-bet[1])); csi0<-1/(1+exp(-gama[1])); phi0<-exp(alpha[1])
ordinal0<-simcube(n0,m,pai0,csi0,phi0)
pai1<-1/(1+exp(-sum(bet))); csi1<-1/(1+exp(-sum(gama))); phi1<-exp(sum(alpha))
ordinal1<-simcube(n1,m,pai1,csi1,phi1)
ordinal<-c(ordinal0,ordinal1)
assepai<-c(rep(pai0,n0),rep(pai1,n1))
assecsi<-c(rep(csi0,n0),rep(csi1,n1))
assephi<-c(rep(phi0,n0),rep(phi1,n1))
lli<-loglikcuben(m,ordinal,assepai,assecsi,assephi)

CUB documentation built on March 31, 2020, 5:14 p.m.