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

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Description

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

Usage

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probcubp0(m, ordinal, Y, bet, csi)

Arguments

m

Number of ordinal categories

ordinal

Vector of ordinal responses

Y

Matrix of covariates for explaining the uncertainty 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)

csi

Feeling parameter

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 model with the corresponding values of the covariates for the uncertainty component and coefficients for the covariates specified in bet

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, probcubpq, probcub0q

Examples

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data(relgoods)
m<-10
ordinal<-relgoods[,29]
gender<-relgoods[,2]
nona<-na.omit(cbind(ordinal,gender))
ordinalnew<-nona[,1]
Y<-nona[,2]
bet<-c(-0.81,  0.93)
csi<-0.20
probi<-probcubp0(m,ordinalnew,Y,bet,csi)

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