p = 200
n = 100
beta = c(1,3,3)
s = 0.15
signal.r = 0.08
non.zero = floor(p * s)
seed = 2
alpha = c(rep(signal.r,non.zero),rep(0,p-non.zero))
dat = generate_data(seed, n = n, p = p, beta = beta,alpha = alpha)
cov = dat$Z
X = dat$X
Y = dat$Y
Goeman_perm(Y, X, cov = cov,model="gaussian", n.perm=1000)
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