[aut],
Martin Moene [cph] (for the GSL Lite library),
Microsoft Corporation [cph] (for the GSL Lite library),
Free Software Foundation, Inc. [cph] (for snippets from the GNU ISO C++
Library)Exact and approximation algorithms for variable-subset selection in ordinary linear regression models. Either compute all submodels with the lowest residual sum of squares, or determine the single-best submodel according to a pre-determined statistical criterion. Hofmann et al. (2020) <10.18637/jss.v093.i03>.
| Version: | 0.5-1 |
| Depends: | R (≥ 3.4.0) |
| Imports: | stats, graphics, utils |
| Published: | 2020-05-23 |
| Author: | Marc Hofmann [aut, cre],
Cristian Gatu [aut],
Erricos J. Kontoghiorghes [aut],
Ana Colubi [aut],
Achim Zeileis
[aut],
Martin Moene [cph] (for the GSL Lite library),
Microsoft Corporation [cph] (for the GSL Lite library),
Free Software Foundation, Inc. [cph] (for snippets from the GNU ISO C++
Library) |
| Maintainer: | Marc Hofmann <marc.hofmann at gmail.com> |
| License: | GPL (≥ 3) |
| URL: | https://github.com/marc-hofmann/lmSubsets.R |
| NeedsCompilation: | yes |
| SystemRequirements: | C++11 |
| Citation: | lmSubsets citation info |
| CRAN checks: | lmSubsets results |
| Reference manual: | lmSubsets.pdf |
| Vignettes: |
lmSubsets: Exact Variable-Subset Selection in Linear Regression for R |
| Package source: | lmSubsets_0.5-1.tar.gz |
| Windows binaries: | r-devel: lmSubsets_0.5-1.zip, r-release: lmSubsets_0.5-1.zip, r-oldrel: lmSubsets_0.5-1.zip |
| macOS binaries: | r-release: lmSubsets_0.5-1.tgz, r-oldrel: lmSubsets_0.5-1.tgz |
| Old sources: | lmSubsets archive |
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