# Generate Data
set.seed(10)
n <- 200
beta <- c(1,1,rep(0,8))
X <- mvtnorm::rmvnorm(n,sigma=diag(1,10))
eps <- rnorm(n)
Y <- (X%*%beta)**3+eps
# \donttest{
res = SIR_threshold_bootstrap(Y,X,H=10,n_lambda=300,thresholding="hard", n_replications=30,k=2)
# Estimated index versus Y
plot(res,choice="estim_ind")
# Model size
plot(res,choice="size")
# Selected variables
plot(res,choice="selec_var")
# Coefficients of b
plot(res,choice="coefs_b")
# Optimal lambdas
plot(res,choice="lambdas_replic")
# }
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