| probcubp0 | R Documentation |
Compute the probability distribution of a CUB model with covariates for the uncertainty component.
probcubp0(m,ordinal,Y,bet,csi)
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 |
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.
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, probcubpq, probcub0q
data(relgoods)
m<-10
naord<-which(is.na(relgoods$Physician))
nacov<-which(is.na(relgoods$Gender))
na<-union(naord,nacov)
ordinal<-relgoods$Physician[-na]
Y<-relgoods$Gender[-na]
bet<-c(-0.81,0.93); csi<-0.20
probi<-probcubp0(m,ordinal,Y,bet,csi)
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