Nothing
boot.henv <- function(X, Y, u, B) {
XX <- as.factor(X)
a <- dim(Y)
n <- a[1]
r <- a[2]
p <- nlevels(XX)
if(u < 0 | u > r){
stop("u should be an interger between 0 and r")
}
ncumx <- c()
for (i in 1:p) {
ncumx[i] <- length(which(XX == as.numeric(levels(XX)[i])))
}
ncum <- cumsum(ncumx)
ng <- diff(c(0, ncum))
sortx <- sort(X, index.return = T)
Xs <- sortx$x
ind <- sortx$ix
fit <- henv(X, Y, u, asy = F, fit = T)
Yfit <- fit$Yfit
res <- Y - Yfit
boothenv <- function(i) {
res.boot <- matrix(rep(0, n * r), ncol = r)
for (j in 1:p) {
if (j > 1) {
res.boot[ind[(ncum[j - 1] + 1):ncum[j]], ] <- as.matrix(res[sample(ind[(ncum[j - 1] + 1)
:ncum[j]], ng[j], replace = T), ], ncol = r)
}
else {
res.boot[ind[1:ncum[1]], ] <- as.matrix(res[sample(ind[1:ncum[1]], ng[1], replace = T), ], ncol = r)
}
}
Y.boot <- Yfit + res.boot
return(c(henv(X, Y.boot, u, asy = F)$beta))
}
bootbeta <- lapply(1:B, function(i) boothenv(i))
bootbeta <- matrix(unlist(bootbeta), nrow = B, byrow = TRUE)
bootse <- matrix(apply(bootbeta, 2, stats::sd), nrow = r)
return(bootse)
}
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