Nothing
"plot.glmmNPML" <-
function(x,plot.opt=15, noformat= FALSE, ...){
k<-length(x$masses)
if (k==1){stop("No graphical output for k=1")}
if (!noformat){
if (plot.opt==0){
stop("Specify plot.opt >0")
} else if (plot.opt %in% c(1,2,4,8)){
par(mfrow=c(1,1))
} else if (plot.opt %in% c(3,5,6,9,10,12)){
par(mfrow=c(2,1),cex=0.5,cex.axis=1.5,cex.lab=1.5)
} else {
par(mfrow=c(2,2),cex=0.5,cex.axis=1.1,cex.lab=1.1)
}
}
if (plot.opt%%2==1){#Disparities
plot(0:x$EMiter,x$Misc$Disparity.trend, col=1,type="l",xlab='EM iterations',ylab='-2logL')
}
if (plot.opt %%4 %in% c(2,3) ){# EM Trajectories
R<- x$Misc$res; ylim<- x$Misc$ylim; followmass<-x$Misc$EMTraj
plot(0:x$EMiter,followmass[,1],col=1,type='l',ylim=ylim,ylab='mass points',xlab='EM iterations')
for (i in 1:k){
lines(0:x$EMiter, followmass[,i],col=i)
if (x$Misc$mform=="1"){points(rep(x$EMiter,length(R)),R)}
}
}
if (plot.opt %%8 %in% c(4,5,6,7) ){# EBP vs true values
#class.col<- masspoint.classifier(x)
class.col<- post(x, level="lower")$classif
plot(x$y[1:length(x$weights)], predict(x,type="response"), xlab="true response", ylab="Emp. Bayes Pred." ,col=class.col)
abline(0,1)
}
if (plot.opt >7){ #wik
if (is.infinite(abs(max(x$Misc$res)))){
cat("Infinite values: Posterior probability plot not applicable for this object."); return()
}
pmax<-max(x$post.prob)
plot(x$Misc$res, x$post.prob[,1],col=1,type="p",ylim=c(0,pmax),ylab="post.prob", xlab="Residuals")
for (i in 2:k) {
points(x$Misc$res, x$post.prob[,i],col=i,pch=i,type="p")
}
}
invisible(x)
}
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