probcubpq function

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

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

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)

Returns

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.

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)

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