rFSA: Feasible Solution Algorithm for Finding Best Subsets and Interactions

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: 0.9.1
Imports: parallel, hashmap, methods, tibble
Suggests: testthat
Published: 2018-01-10
Author: Joshua Lambert [aut, cre], Liyu Gong [aut], Corrine Elliott [aut], Sarah Janse [ctb]
Maintainer: Joshua Lambert <joshua.lambert at uky.edu>
License: GPL-2
NeedsCompilation: no
Materials: README
CRAN checks: rFSA results


Reference manual: rFSA.pdf
Package source: rFSA_0.9.1.tar.gz
Windows binaries: r-prerel: rFSA_0.9.1.zip, r-release: rFSA_0.9.1.zip, r-oldrel: rFSA_0.9.1.zip
OS X binaries: r-prerel: rFSA_0.9.1.tgz, r-release: rFSA_0.9.1.tgz
Old sources: rFSA archive


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