Package: rFSA 0.9.6

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.

Authors:Joshua Lambert [aut, cre], Liyu Gong [aut], Corrine Elliott [aut], Sarah Janse [ctb]

rFSA_0.9.6.tar.gz
rFSA_0.9.6.zip(r-4.7)rFSA_0.9.6.zip(r-4.6)rFSA_0.9.6.zip(r-4.5)
rFSA_0.9.6.tgz(r-4.6-any)rFSA_0.9.6.tgz(r-4.5-any)
rFSA_0.9.6.tar.gz(r-4.7-any)rFSA_0.9.6.tar.gz(r-4.6-any)
rFSA_0.9.6.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
rFSA/json (API)

# Install 'rFSA' in R:
install.packages('rFSA', repos = c('https://joshuawlambert.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/joshuawlambert/rfsa/issues

On CRAN:

Conda:

algorithmfsainteractionmodelsparallelstatisticalstatisticssubset

4.26 score 7 stars 26 scripts 242 downloads 19 exports 28 dependencies

Last updated from:b0986bb253. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK125
source / vignettesOK210
linux-release-x86_64OK133
macos-release-arm64OK160
macos-oldrel-arm64OK194
windows-develOK98
windows-releaseOK100
windows-oldrelOK83
wasm-releaseOK99

Exports:adj.r.squaredapressbdistfitmodelsFSAglmFSAint.p.vallist.criterionlmFSAmax_abs_residnextswappFSAQICu.geeglmr.squaredrmseswapstwFSAwhich.max.nawhich.min.na

Dependencies:clicpp11dplyrgenericsgluehashigraphlatticelazyevallifecyclemagrittrMatrixpillarpkgconfigpurrrR6RcppRcppParallelrlangrPrefstringistringrtibbletidyrtidyselectutf8vctrswithr