Nothing
# a is the model returned from the mle functions
# Rtest and Stest are the design matrices of the test data
# currently, there is no offset
#
predict.copreg=function(object,Rtest,Stest,exposure=rep(1,nrow(Stest)),independence=FALSE,...){
a=object
x.pred<-as.vector(exp(Rtest%*%a$alpha))
lambda<-as.vector(exp(Stest%*%a$beta))*exposure
mu<-as.vector(exp(Rtest%*%a$alpha))
if (a$zt==TRUE){
y.pred<-lambda/(1-exp(-lambda))
}
if (a$zt==FALSE){
y.pred=lambda
}
l.pred.ifm<-NULL
if (independence==TRUE){
l.pred<-x.pred*y.pred
#l.pred.ifm<-epolicy_loss(mu,a$delta,lambda,a$theta.ifm,a$family0,a$zt)
}
else{
l.pred<-epolicy_loss(mu,a$delta,lambda,a$theta,a$family,zt=a$zt)}
return(list(x.pred=x.pred,y.pred=y.pred,l.pred=l.pred))
}
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