sglOptim: Generic Sparse Group Lasso Solver

Fast generic solver for sparse group lasso optimization problems. The loss (objective) function must be defined in a C++ module. The optimization problem is solved using a coordinate gradient descent algorithm. Convergence of the algorithm is established (see reference) and the algorithm is applicable to a broad class of loss functions. Use of parallel computing for cross validation and subsampling is supported through the 'foreach' and 'doParallel' packages. Development version is on GitHub, please report package issues on GitHub.

Version: 1.3.6
Depends: R (≥ 3.2.4), Matrix, foreach, doParallel
Imports: methods, stats, tools, utils
LinkingTo: Rcpp, RcppProgress, RcppArmadillo, BH
Suggests: knitr, rmarkdown
Published: 2017-04-02
Author: Martin Vincent
Maintainer: Martin Vincent < at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Citation: sglOptim citation info
Materials: NEWS
CRAN checks: sglOptim results


Reference manual: sglOptim.pdf
Vignettes: Quick Start
Package source: sglOptim_1.3.6.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X El Capitan binaries: r-release: sglOptim_1.3.6.tgz
OS X Mavericks binaries: r-oldrel: sglOptim_1.3.6.tgz
Old sources: sglOptim archive

Reverse dependencies:

Reverse depends: lsgl, msgl
Reverse linking to: lsgl, msgl


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