R/rplotCV.R

In musto101/wilcox_R: What the package does (short line)

rplotCV <-
function(x,y,fr=NA,varfun=pbvar,est=tmean,xout=FALSE,outfun=out,eout=FALSE,corfun=pbvar,...){
#
# Estimate prediction error based on
# a running interval smoother in conjunction with
# a leave-one-out cross validation method
#
#  varfun is the measure of variation used on the predicted Y values.
#  est is the measure of location used by the running interval smoother.
#  The estimate is returned in VAR.Y.HAT
#
m=elimna(cbind(x,y))
if(eout){
flag<-outfun(m,plotit=FALSE)$keep
m=m[flag,]
}
x=as.matrix(x)
p=ncol(x)
p1=p+1
x=as.matrix(m[,1:p])
y=m[,p1]
vals=NA
if(is.na(fr)){
if(p==1)fr=.8
if(p>1)fr=1
}
if(xout){
keepit<-outfun(x,plotit=FALSE,...)$keep
x<-x[keepit,]
y<-y[keepit]
}
x=as.matrix(x)
for(i in 1:nrow(x)){
if(p==1)vals[i]=runhat(x[-i,],y[-i],fr=fr,est=est,pts=x[i,],...)
if(p>1)vals[i]=rung3hat(x[-i,],y[-i],fr=fr,pts=t(as.matrix(x[i,])))$rmd
}
dif=y-vals
ans=varfun(elimna(dif))
list(VAR.Y.HAT=ans)
}