set.seed(123) #
n=300 #
x=rbinom(n, 2, 0.2) #
y=rnorm(n, mean=0, sd=1) #
z=cbind(rbinom(n, 1, 0.3), rnorm(n, mean=2, sd=2)) #
taus=c( 0.25, 0.5, 0.75) #
# - run the proposed QRank approach #
QRank(gene=y, snp=x, cov=z, tau=taus) #
# - output #
#Composite.pvalue: #
#[1] 0.2241873 #
#Quantile.specific.pvalue: #
# 0.25 0.5 0.75 #
#0.5452044 0.1821452 0.5938421 #
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