Nothing
OrdinaryBoot1 <- function(x, type, p, b, parallel = FALSE) {
if ( is.vector(x) ) stop( 'Multivariate time series only.' )
if ( !all( is.finite(x) ) ) stop( 'Missing or infitive values.' )
if ( !is.numeric(x) ) stop( "'x' must be numeric." )
n <- dim(x)[1]
MaxLag <- n - 2
boot <- function(x, j) {
ind <- Rfast2::Sample.int(n, n, replace = TRUE )
xStar <- x[ind, ]
Vrm <- mADCV(xStar, j, unbiased = FALSE, output = FALSE)
sum(Vrm^2)
}
test <- function(j) {
kern <- kernelFun(type, j/p)
if ( abs(kern) < 1e-16 ) {
d <- numeric(b)
} else d <- (n - j) * kern^2 * replicate(b, boot(x, j) )
d
}
if ( parallel ) {
oop <- options(warn = -1)
on.exit( options(oop) )
requireNamespace("doParallel", quietly = TRUE, warn.conflicts = FALSE)
closeAllConnections()
cl <- makeCluster(detectCores())
registerDoParallel(cl)
clusterSetRNGStream(cl = cl, iseed = 9182)
i <- 1:MaxLag
fe_call <- as.call( c( list( as.name("foreach"), i = i, .combine = "+",
.export = c("kernelFun", "mADCV", "boot", "Sample.int"), .packages = c("Rfast2", "dcov") ) ) )
fe <- eval(fe_call)
res <- fe %dopar% test(i)
stopCluster(cl)
} else res <- rowSums( sapply( 1:MaxLag, function(i) test(i) ) )
res
}
# OrdinaryBoot1 <- function(x,type,p,b,parallel=FALSE){
# if(is.vector(x))stop('Multivariate time series only')
# if(!all(is.finite(x))) stop('Missing or infitive values')
# if (!is.numeric(x)) stop("'x' must be numeric")
# n <- as.integer(NROW(x))
# q <- as.integer(NCOL(x))
# MaxLag <- n-2
# test <- function(j){
# kern <- kernelFun(type,j/p)
# if (kern==0){
# d=rep(0,b)
# } else {
# boot = function(x,j){
# ind <- sample(1:n,replace=T)
# xStar <- x[ind,]
# Vrm <- mADCV(xStar,j,unbiased=FALSE,output=FALSE)
# res <- (n-j)*kern^2*sum(Vrm^2)
# return(res)
# }
# d=replicate(b,boot(x,j))
# }
# d
# }
# if(parallel==TRUE){
# closeAllConnections()
# cl <- makeCluster(detectCores())
# registerDoParallel(cl)
# clusterSetRNGStream(cl = cl, iseed = 9182)
# i <- seq_len(MaxLag)
# fe_call <- as.call(c(list (as.name("foreach"), i = i,.combine="+",.export=c("kernelFun","mADCV","dcov")) ))
# fe <- eval(fe_call)
# res <- fe %dopar% test(i)
# stopCluster(cl)
# }
# else {
# res <- rowSums(sapply(1:MaxLag,function(i) test(i)))
# }
# return(res)
# }
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