Induced Smoothed Lasso

📦 Installation

You can install the development version of islasso from GitHub:

# install.packages("devtools")
# devtools::install_github("gianluca-sottile/islasso")
install.packages("islasso", repos = c('https://gianluca-sottile.r-universe.dev', 'https://cloud.r-project.org'))

Once installed, load the package:

library(islasso)

🔍 Description

islasso implements the Induced Smoothed Lasso, a robust and interpretable approach for hypothesis testing in high-dimensional linear and generalized linear models.

Key features include:

Efficient Fortran backend for fast computation
Support for Gaussian, Binomial, Poisson, and Gamma families
Smoothed penalization for stable inference
Automatic selection of active variables
Visualization tools powered by ggplot2

🚀 Quick Example

set.seed(123)
sim <- simulXy(n = 100, p = 20, family = "gaussian")
mod <- islasso(y ~ ., data = sim$data)
summary(mod)
plot(mod)

📚 Documentation

📘 Function reference: ?islasso
📄 Vignette: vignette("islasso-intro")
🌐 Website: https://gianluca-sottile.github.io/islasso

📖 References

Cilluffo G, Sottile G, La Grutta S, Muggeo V (2020). The Induced Smoothed lasso: A practical framework for hypothesis testing in high dimensional regression. Statistical Methods in Medical Research_, 29(3), 765-777. doi:10.1177/0962280219842890

🤝 Contributing

Feel free to open issues, suggest improvements, or submit pull requests.
Bug reports and feature requests are welcome!