probcub0q: 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)

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.

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)

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

Examples

Run this code

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)