| probcub0q | R Documentation |
Compute the probability distribution of a CUB model with covariates for the feeling component.
probcub0q(m,ordinal,W,pai,gama)
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) |
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.
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
bitgama, probcub00, probcubp0,
probcubpq
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)
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