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. The algorithm is applicable to a broad class of convex loss functions. Convergence of the algorithm is established (see reference). 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. Development version is on github, please report package issues on github.

Version: 1.3.0
Depends: R (≥ 3.0.0), Matrix, foreach, doParallel
Imports: methods, stats, utils
LinkingTo: Rcpp, RcppProgress, RcppArmadillo, BH
Published: 2016-09-28
Author: Martin Vincent
Maintainer: Martin Vincent <martin.vincent.dk at gmail.com>
BugReports: https://github.com/vincent-dk/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/vincent-dk/sglOptim
NeedsCompilation: yes
Citation: sglOptim citation info
Materials: NEWS
CRAN checks: sglOptim results

Downloads:

Reference manual: sglOptim.pdf
Package source: sglOptim_1.3.0.tar.gz
Windows binaries: r-devel: sglOptim_1.3.0.zip, r-release: sglOptim_1.3.0.zip, r-oldrel: sglOptim_1.3.0.zip
OS X Mavericks binaries: r-release: sglOptim_1.3.0.tgz, r-oldrel: sglOptim_1.3.0.tgz
Old sources: sglOptim archive

Reverse dependencies:

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

Linking:

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