logscore {CUB} | R Documentation |
Logarithmic score
Description
Compute the logarithmic score of a CUB model with covariates both for the uncertainty and the feeling parameters.
Usage
logscore(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, with length NCOL(Y)+1
to account for an intercept term (first entry of |
gama |
Vector of parameters for the feeling component, with length NCOL(W)+1
to account for an intercept term (first entry of |
Details
No missing value should be present neither
for ordinal
nor for covariate matrices: thus, deletion or imputation procedures should be
preliminarily run.
References
Tutz, G. (2012). Regression for Categorical Data, Cambridge University Press, Cambridge
Examples
data(relgoods)
m<-10
naord<-which(is.na(relgoods$Walking))
nacovpai<-which(is.na(relgoods$Gender))
nacovcsi<-which(is.na(relgoods$Smoking))
na<-union(naord,union(nacovpai,nacovcsi))
ordinal<-relgoods$Walking[-na]
Y<-relgoods$Gender[-na]
W<-relgoods$Smoking[-na]
bet<-c(-0.45,-0.48)
gama<-c(-0.55,-0.43)
logscore(m,ordinal,Y=Y,W=W,bet,gama)