probcub0q {CUB}

Probability distribution of a CUB model with covariates for the feeling component

Description

Compute the probability distribution of a CUB model with covariates for the feeling component.

Usage

probcub0q(m,ordinal,W,pai,gama)

Arguments

m

Number of ordinal categories

ordinal

Vector of ordinal responses

W

Matrix of covariates for explaining the feeling component NCOL(Y)+1 to include an intercept term in the model (first entry)

pai

Uncertainty parameter

gama

Vector of parameters for the feeling component, whose length equals NCOL(W)+1 to include an intercept term in the model (first entry)

Value

A vector of the same length as ordinal, whose i-th component is the probability of the i-th observation according to a CUB distribution with the corresponding values of the covariates for the feeling component and coefficients specified in gama.

References

Piccolo D. (2006). Observed Information Matrix for MUB Models, Quaderni di Statistica, 8, 33–78
Piccolo D. and D'Elia A. (2008). A new approach for modelling consumers' preferences, Food Quality and Preference, 18, 247–259
Iannario M. and Piccolo D. (2012). CUB models: Statistical methods and empirical evidence, in: Kenett R. S. and Salini S. (eds.), Modern Analysis of Customer Surveys: with applications using R, J. Wiley and Sons, Chichester, 231–258

See Also

bitgama, probcub00, probcubp0, probcubpq

Examples

data(relgoods)
m<-10
naord<-which(is.na(relgoods$Physician))
nacov<-which(is.na(relgoods$Gender))
na<-union(naord,nacov)
ordinal<-relgoods$Physician[-na]
W<-relgoods$Gender[-na]
pai<-0.44; gama<-c(-0.91,-0.7)
pr<-probcub0q(m,ordinal,W,pai,gama)