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
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rFSA_0.9.6.tgz(r-4.4-any)rFSA_0.9.6.tgz(r-4.3-any)
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rFSA.pdf |rFSA.html✨
rFSA/json (API)

Peer review:

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

On CRAN:

algorithmfsainteractionmodelsparallelstatisticalstatisticssubset

19 exports 7 stars 1.40 score 29 dependencies 20 scripts 189 downloads

Last updated 3 years agofrom:b0986bb253. Checks:OK: 7. Indexed: yes.

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

Dependencies:clicpp11dplyrfansigenericsgluehashigraphlatticelazyevallifecyclemagrittrMatrixpillarpkgconfigpurrrR6RcppRcppParallelrlangrPrefstringistringrtibbletidyrtidyselectutf8vctrswithr