sglssnal: Sparse-Group Lasso via Semismooth Newton Augmented Lagrangian
Implements the sparse-group lasso method of Zhang et al.
(2020) <doi:10.1007/s10107-018-1329-6>. Unlike many widely available
methods based on first-order descent, this method uses second-order
information to solve the dual optimization problem via a semismooth
Newton method.
| Version: |
0.1.0 |
| Depends: |
R (≥ 4.4.0) |
| Imports: |
Matrix, Rcpp, RSpectra, methods, utils |
| LinkingTo: |
Rcpp, RcppArmadillo |
| Suggests: |
knitr, rmarkdown, spelling, testthat (≥ 3.0.0) |
| Published: |
2026-09-11 |
| DOI: |
10.32614/CRAN.package.sglssnal (may not be active yet) |
| Author: |
Robin Liu [aut, cre],
Yangjing Zhang [ctb] (Author of the original MATLAB SSNAL
implementation this package ports) |
| Maintainer: |
Robin Liu <robin28liu at gmail.com> |
| BugReports: |
https://github.com/roobnloo/sglssnal/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/roobnloo/sglssnal |
| NeedsCompilation: |
yes |
| Language: |
en-US |
| Citation: |
sglssnal citation info |
| Materials: |
NEWS |
| CRAN checks: |
sglssnal results |
Documentation:
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