IMVCFDR {newIMVC} | R Documentation |
Integrated Mean Variance Correlation Based FDR Control
Description
This function is used for FDR control with integrated mean variance correlation
Usage
IMVCFDR(y, x, K, NN = 3, numboot, timeboot, true_signal, null_method, alpha)
Arguments
y |
is the response vector |
x |
is the covariate matrix |
K |
is the number of quantile levels |
NN |
is the number of B spline basis, default is 3 |
numboot |
is the size of bootstrap samples |
timeboot |
is the number of bootstrap times for computing standard deviation of the IMVC |
true_signal |
is the true active set |
null_method |
is the estimation method for proportion of true null hypotheses. Choices are "lfdr", "mean", "hist" or "convest" |
alpha |
is the nominal FDR level |
Value
A list of FDP, power and selected variables
Examples
require("mvtnorm")
n=200
p=20
pho1=0.5
mean_x=rep(0,p)
sigma_x=matrix(NA,nrow = p,ncol = p)
for (i in 1:p) {
for (j in 1:p) {
sigma_x[i,j]=pho1^(abs(i-j))
}
}
x=rmvnorm(n, mean = mean_x, sigma = sigma_x,method = "chol")
x1=x[,1]
x2=x[,2]
x3=x[,3]
y=2*x1+2*x2+2*x3+rnorm(n)
IMVCFDR(y,x,K=5,numboot=100,timeboot=20,true_signal=c(1,2,3),null_method="hist",alpha=0.2)
[Package newIMVC version 0.1.0 Index]