# Computes the rejection frequencies of the LRT
rm(list=ls())
library(parallel)
library(normalregMix)
library(subgroupLRT)
setwd("~/Dropbox/yoichi/ProR/subgroupLRT/experiments_ya")
nrep <- 10
# nobset <- c(100,200)
nobset <- c(100)
nnob <- length(nobset)
DGPset <- c(1:1)
m <- 2
mubeta <- matrix(c(1,2,1,2), nrow=2, ncol=2) # one-component model in effect
gammatrue <- c(0.3, -0.7)
gammavec = as.matrix(gammatrue, nrow=2)
sigma <- c(0.5, 0.5)
# rejfreq5all <- matrix(0, nrow=length(DGPset), ncol=3*nnob)
# rejfreq1all <- matrix(0, nrow=length(DGPset), ncol=3*nnob)
for (DGP in DGPset)
{
for (inob in 1:nnob)
{
time_start <- proc.time()
nob <- nobset[inob]
set.seed(123456)
x.all <- matrix(rnorm(nob*nrep), nrow = nob) - 1 # corresponds to Z in the paper
v.all <- matrix(rnorm(nob*nrep), nrow = nob) + 1 # corresponds to X in the paper
y.all <- matrix(double(nob*nrep), nrow = nob)
for (j in 1:nrep) {
v1 <- cbind(1, v.all[, j])
v1gamma <- v1 %*% gammavec
alpha1 <- exp(v1gamma) / (1 + exp(v1gamma))
alpha <- cbind(alpha1, 1 - alpha1)
ii <- apply(alpha, 1, function(x) {sample(m, 1, replace = TRUE, x)})
x1 <- cbind(1, x.all[, j])
x1mubeta <- rowSums(x1 * t(mubeta[, ii]))
y.all[, j] <- rnorm(n = nob, mean = mubeta, sd=sigma[ii])
}
# lrtout <- parLapply(cl,1:nrep, function(j) regmixLRT_homo(y=y.all[,j],
# x=x.all[,j], m=m, crit.method="boot", parallel=0) )
# pvalsum <- sapply(lrtout,"[[","pvals")
# # print(pvalsum)
# rejfreq10 <- 100*mean(pvalsum < 0.10)
# rejfreq5 <- 100*mean(pvalsum < 0.05)
# rejfreq1 <- 100*mean(pvalsum < 0.01)
# # rejfreq5all[DGP,(3*inob-2):(3*inob)] <- rejfreq5
# # rejfreq1all[DGP,(3*inob-2):(3*inob)] <- rejfreq1
#
# time_end <- proc.time()
# runtime <- time_end - time_start
#
# print("DGP, nob, nrep")
# print(c(DGP, nob, nrep))
# print(runtime)
# print("rejfreq10, rejfreq5, rejfreq1")
# print(c(rejfreq10, rejfreq5, rejfreq1))
# rm(list=c("y.all", "x.all"))
# save.image(file = outfilename)
} # end of inob loop
} # end of DGP loop
# return(list(outall=outall,runtime=runtime))
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