sparsegl: An R Package for Estimating Sparse Group Lasso

• DOI: 10.18637/jss.v110.i06
• Publication Date: 2024-08-29T02:26:25Z
• Authors: Xiaoxuan Liang; Aaron Cohen; Anibal Sólon Hein...; Franco Pestilli; Daniel J. McDonald
• Keywords: Methodology (stat.ME); FOS: Computer and information sciences; Statistics; 0101 mathematics; 01 natural sciences; Statistics - Methodology; HA1-4737

18 pages, 9 figures, 1 table<br/>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.<br/>