This is based on the paper:
"Heavy Lasso: sparse penalized regression under heavy-tailed noise via data-augmented soft-thresholding."
Install the package using:
devtools::install_github('tienmt/heavylasso')
library(heavylasso)
# simulate data
n <- 100; p <- 10
X <- matrix(rnorm(n * p), n, p)
beta_true <- c(1, -1, rep(0, p - 2))
y <- X %*% beta_true + rt(n, df = 3) # heavy-tailed noise
fit <- heavylasso(X, y, lambda = 0.1)
print(fit$coefficients)
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