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rFSA  

Feasible Solution Algorithm for Finding Best Subsets and Interactions
View on CRAN: Click here


Download and install rFSA package within the R console
Install from CRAN:
install.packages("rFSA")

Install from Github:
library("remotes")
install_github("cran/rFSA")

Install by package version:
library("remotes")
install_version("rFSA", "0.9.6")



Attach the package and use:
library("rFSA")
Maintained by
Joshua Lambert
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-10-18
Latest Update: 2020-06-10
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.
How to cite:
Joshua Lambert (2016). rFSA: Feasible Solution Algorithm for Finding Best Subsets and Interactions. R package version 0.9.6, https://cran.r-project.org/web/packages/rFSA. Accessed 15 Sep. 2026.
Previous versions and publish date:
(2026-07-09 06:47), 0.1.0 (2016-10-18 10:20), 0.9.1 (2018-01-10 15:25), 0.9 (2017-12-21 18:36)
Other packages that cited rFSA R package
View rFSA citation profile
Other R packages that rFSA depends, imports, suggests or enhances
Complete documentation for rFSA
Functions, R codes and Examples using the rFSA R package
Some associated functions: FSA . QICu.geeglm . adj.r.squared . apress . bdist . fitmodels . fitted.FSA . int.p.val . list.criterion . max_abs_resid . nextswap . pFSA . plot.FSA . predict.FSA . print.FSA . r.squared . rmse . summary.FSA . swaps . twFSA . which.max.na . which.min.na . 
Some associated R codes: FSA.R . criterion.R . fitmodels.R . fitted.FSA.R . pFSA.R . plot.FSA.R . predict.FSA.R . print.FSA.R . summary.FSA.R . support.R . twFSA.R .  Full rFSA package functions and examples
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