permut <-
function(file, silt){
Y = file$Y
file = file
env <- environment()
r2_sim_CV_2 <- matrix(0,nrow = as.numeric(silt), ncol = 2)
corrY <- c()
#pb <- txtProgressBar(min = 1, max = silt, style = 3)
pCV <- function(x){
Y <- get("Y", envir=env)
file <- get("file", envir=env)
sid <- sample(length(Y),length(Y))
p1=pls::plsr(Y[sid]~X,data = file, ncomp = 2, validation = "CV",
method ="oscorespls")
q2r2=pls::R2(p1,estimate = "all")
corrY <- cor(Y[sid],Y)
#r2_cum <- cum(r2)
#r2_cum <- r2_cum[1:slt]
r2_sim_CV_2 <- cbind(t(as.data.frame(q2r2$val[5:6])),corrY)
}
output <- plyr::llply(1:silt,.fun= pCV,.progress = "text")
output = do.call(rbind,output)
}
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