lmSubsets: Exact Variable-Subset Selection in Linear Regression

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) <doi:10.18637/jss.v093.i03>.

Package details

AuthorMarc Hofmann [aut, cre], Cristian Gatu [aut], Erricos J. Kontoghiorghes [aut], Ana Colubi [aut], Achim Zeileis [aut] (<https://orcid.org/0000-0003-0918-3766>), 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)
MaintainerMarc Hofmann <marc.hofmann@gmail.com>
LicenseGPL (>= 3)
URL https://github.com/marc-hofmann/lmSubsets.R
Package repositoryView on CRAN
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lmSubsets documentation built on Feb. 8, 2021, 1:06 a.m.