Nothing
plotdhglm <-
function (OUTPUT,type="mean",random=NULL) {
random=NULL
par(mfrow=c(2,2))
if (type=="mean") {
mu<-OUTPUT[7][[1]]
StudentResidual<-OUTPUT[1][[1]]
}
if (type=="phi") {
mu<-OUTPUT[4][[1]]
StudentResidual<-OUTPUT[3][[1]]
}
if (type=="lambda") {
mu<-OUTPUT[6][[1]]
StudentResidual<-OUTPUT[5][[1]]
}
if (type=="v") {
mu<-OUTPUT[24][[1]]
StudentResidual<-OUTPUT[5][[1]]
}
x<-mu
y<-StudentResidual
fit<- supsmu(x,y)
plot(x, y, main="Residuals vs Fitted", xlab="scaled fitted values", ylab="Studentized Residual", cex=0.5) #plot data point
lines(fit$x, fit$y) #plot smooth spline fit
y<-abs(StudentResidual)
fit<- supsmu(x,y)
plot(x, y, main="|Residuals| vs Fitted",xlab="scaled fitted values", ylab="|Studentized Residual|", cex=0.5) #plot data point
lines(fit$x, fit$y) #plot smooth spline fit
qqnorm(StudentResidual,main="Normal Probability Plot"); qqline(StudentResidual) # Normal probability plot
hist(StudentResidual)
}
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