probcubpq {FastCUB}

Probability distribution of a CUB model with covariates for both feeling and uncertainty

Description

Compute the probability distribution of a CUB model with covariates for both the feeling and the uncertainty components.

Usage

probcubpq(m,ordinal,Y,W,bet,gama)

Arguments

m

Number of ordinal categories

ordinal

Vector of ordinal responses

Y

Matrix of covariates for explaining the uncertainty component

W

Matrix of covariates for explaining the feeling component

bet

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

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 rating according to a CUB distribution with given covariates for both uncertainty and feeling, and specified coefficients vectors bet and gama, respectively.

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, probcub0q

Examples

data(relgoods)
m<-10
naord<-which(is.na(relgoods$Physician))
nacov<-which(is.na(relgoods$Gender))
na<-union(naord,nacov)
ordinal<-relgoods$Physician[-na]
W<-Y<-relgoods$Gender[-na]
gama<-c(-0.91,-0.7); bet<-c(-0.81,0.93)
probi<-probcubpq(m,ordinal,Y,W,bet,gama)