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.

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Description file content

Package
rFSA
Type
Package
Title
Feasible Solution Algorithm for Finding Best Subsets and Interactions
Version
0.9.1
Date
2017-12-21
Description
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) . 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.
License
GPL-2
LazyData
TRUE
Imports
parallel, hashmap, methods, tibble
RoxygenNote
6.0.1
Suggests
testthat
NeedsCompilation
no
Packaged
2018-01-10 14:20:01 UTC; josh
Author
Joshua Lambert [aut, cre], Liyu Gong [aut], Corrine Elliott [aut], Sarah Janse [ctb]
Maintainer
Joshua Lambert
Repository
CRAN
Date/Publication
2018-01-10 14:25:55 UTC

install.packages('rFSA')

0.9.1

8 months ago

Joshua Lambert

GPL-2

Imports

parallel, hashmap, methods, tibble

Suggests

testthat

Discussions