Nothing
"crossval"<- function(x,y,theta.fit,theta.predict,...,ngroup=n){
call <- match.call()
x <- as.matrix(x)
n <- length(y)
ngroup <- trunc(ngroup)
if( ngroup < 2){
stop ("ngroup should be greater than or equal to 2")
}
if(ngroup > n){
stop ("ngroup should be less than or equal to the number of observations")
}
if(ngroup==n) {groups <- 1:n; leave.out <- 1}
if(ngroup<n){
leave.out <- trunc(n/ngroup);
o <- sample(1:n)
groups <- vector("list",ngroup)
for(j in 1:(ngroup-1)){
jj <- (1+(j-1)*leave.out)
groups[[j]] <- (o[jj:(jj+leave.out-1)])
}
groups[[ngroup]] <- o[(1+(ngroup-1)*leave.out):n]
}
u <- vector("list",ngroup)
cv.fit <- rep(NA,n)
for(j in 1:ngroup){
u <- theta.fit(x[-groups[[j]], ],y[-groups[[j]]],...)
cv.fit[groups[[j]]] <- theta.predict(u,x[groups[[j]],])
}
if(leave.out==1) groups <- NULL
return(list(cv.fit=cv.fit,
ngroup=ngroup,
leave.out=leave.out,
groups=groups,
call=call))
}
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