dat <- msaenet.sim.gaussian(
n = 150, p = 500, rho = 0.6,
coef = rep(1, 5), snr = 2, p.train = 0.7,
seed = 1001
)
msaenet.fit <- msaenet(
dat$x.tr, dat$y.tr,
alphas = seq(0.2, 0.8, 0.2),
nsteps = 3L, seed = 1003
)
msaenet.nzv(msaenet.fit)
# coefficients of non-zero variables
coef(msaenet.fit)[msaenet.nzv(msaenet.fit)]
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