SDA_M {sdafilter}

Symmetrized Data Aggregation

Description

This is the core function for the paper posted in arXiv preprint arXiv:2002.11992

Usage

SDA_M(dat, alpha, Omega, nonsparse = FALSE, stable = TRUE)

Arguments

dat

a n by p data matrix

alpha

the FDR level

Omega

the inverse covariance matrix; if missing, it will be estimated by the glasso package

nonsparse

if TRUE, the covariance matrix will be estimated by the POET package

stable

if TRUE, the sample will be randomly splitted B=10 times for stability performance; otherwise, only single sample splitting is used.

Value

the indices of the hypotheses rejected

Examples

n = 50
p = 100
dat = matrix(rnorm(n*p), nrow=n)
mu = rep(0, p)
mu[1:as.integer(0.1*p)]=0.3
dat = dat+rep(1, n)%*%t(mu)
alpha = 0.2
out = SDA_M(dat, alpha, diag(p))
print(out)