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 |
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-release: sglOptim_1.3.8.zip, r-oldrel: sglOptim_1.3.8.zip |
macOS binaries: | r-release: sglOptim_1.3.8.tgz, r-oldrel: sglOptim_1.3.8.tgz |
Old sources: | sglOptim archive |
Reverse depends: | msgl |
Reverse linking to: | msgl |
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