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
| Version | Repository | File | Size |
|---|---|---|---|
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 |