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arXiv · 2208.02942

sparsegl: An R Package for Estimating Sparse Group Lasso

Xiaoxuan Liang·Aaron Cohen·Anibal Solón Heinsfeld·Franco Pestilli·Daniel J. McDonald
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Abstract

The sparse group lasso is a high-dimensional regression technique that is useful for problems whose predictors have a naturally grouped structure and where sparsity is encouraged at both the group and individual predictor level. In this paper we discuss a new R package for computing such regularized models. The intention is to provide highly optimized solution routines enabling analysis of very large datasets, especially in the context of sparse design matrices.

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Xiaoxuan Liang, Aaron Cohen, Anibal Solón Heinsfeld, Franco Pestilli, Daniel J. McDonald. 2023-10-30. sparsegl: An R Package for Estimating Sparse Group Lasso. https://doi.org/10.18637/jss.v110.i06

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