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rFSA: Feasible Solution Algorithm for Finding Best Subsets andInteractions

Assists in statistical model building to find optimal and semi-optimal higher order interactions and best subsets. Uses the lm(), glm(), and other R functions to fit models generated from a feasible solution algorithm. Discussed in Subset Selection in Regression, A Miller (2002). Applied and explained for least median of squares in Hawkins (1993) <doi:10.1016/0167-9473(93)90246-P>. The feasible solution algorithm comes up with model forms of a specific type that can have fixed variables, higher order interactions and their lower order terms.

Version:0.9.6
Imports:parallel, methods,tibble,rPref,tidyr,hash
Published:2020-06-10
DOI:10.32614/CRAN.package.rFSA
Author:Joshua Lambert [aut, cre], Liyu Gong [aut], Corrine Elliott [aut], Sarah Janse [ctb]
Maintainer:Joshua Lambert <joshua.lambert at uc.edu>
License:GPL-2
NeedsCompilation:no
Materials:README
CRAN checks:rFSA results

Documentation:

Reference manual:rFSA.html ,rFSA.pdf

Downloads:

Package source: rFSA_0.9.6.tar.gz
Windows binaries: r-devel:rFSA_0.9.6.zip, r-release:rFSA_0.9.6.zip, r-oldrel:rFSA_0.9.6.zip
macOS binaries: r-release (arm64):rFSA_0.9.6.tgz, r-oldrel (arm64):rFSA_0.9.6.tgz, r-release (x86_64):rFSA_0.9.6.tgz, r-oldrel (x86_64):rFSA_0.9.6.tgz
Old sources: rFSA archive

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=rFSAto link to this page.


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