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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.

Versions across snapshots

VersionRepositoryFileSize
0.9.6 rolling linux/jammy R-4.5 rFSA_0.9.6.tar.gz 93.8 KiB
0.9.6 rolling linux/noble R-4.5 rFSA_0.9.6.tar.gz 93.6 KiB
0.9.6 rolling source/ R- rFSA_0.9.6.tar.gz 19.2 KiB
0.9.6 latest linux/jammy R-4.5 rFSA_0.9.6.tar.gz 93.8 KiB
0.9.6 latest linux/noble R-4.5 rFSA_0.9.6.tar.gz 93.6 KiB
0.9.6 latest source/ R- rFSA_0.9.6.tar.gz 19.2 KiB
0.9.6 2026-04-26 source/ R- rFSA_0.9.6.tar.gz 19.2 KiB
0.9.6 2026-04-23 source/ R- rFSA_0.9.6.tar.gz 19.2 KiB
0.9.6 2026-04-09 windows/windows R-4.5 rFSA_0.9.6.zip 96.5 KiB
0.9.6 2025-04-20 source/ R- rFSA_0.9.6.tar.gz 19.2 KiB

Dependencies (latest)

Imports