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: 1.3.8
Depends: R (≥ 3.2.4), Matrix, foreach, doParallel
Imports: methods, stats, tools, utils
LinkingTo: Rcpp, RcppProgress, RcppArmadillo, BH
Suggests: knitr, rmarkdown
Published: 2019-05-07
Author: Martin Vincent [aut], Niels Richard Hansen [ctb, cre]
Maintainer: Niels Richard Hansen <niels.r.hansen at math.ku.dk>
BugReports: https://github.com/nielsrhansen/sglOptim/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://dx.doi.org/10.1016/j.csda.2013.06.004, https://github.com/nielsrhansen/sglOptim
NeedsCompilation: yes
Citation: sglOptim citation info
Materials: NEWS
CRAN checks: sglOptim results

Downloads:

Reference manual: sglOptim.pdf
Vignettes: Readme
sglOptim structure and usage
Package source: sglOptim_1.3.8.tar.gz
Windows binaries: r-devel: sglOptim_1.3.8.zip, r-devel-gcc8: sglOptim_1.3.8.zip, r-release: sglOptim_1.3.8.zip, r-oldrel: sglOptim_1.3.8.zip
OS X binaries: r-release: sglOptim_1.3.8.tgz, r-oldrel: sglOptim_1.3.8.tgz
Old sources: sglOptim archive

Reverse dependencies:

Reverse depends: msgl
Reverse linking to: msgl

Linking:

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