Nothing
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>.
Getting started
Browse package contents
Package details |
|
|---|---|
| Author | Marc 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) |
| Maintainer | Marc Hofmann <marc.hofmann@gmail.com> |
| License | GPL (>= 3) |
| Version | 0.5-2 |
| URL | https://github.com/marc-hofmann/lmSubsets.R |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
|
Try the lmSubsets package in your browser
Any scripts or data that you put into this service are public.
