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.
| Version: |
0.9.6 |
| Imports: |
parallel, methods, tibble, rPref, tidyr, hash |
| Published: |
2020-06-10 |
| DOI: |
10.32614/CRAN.package.rFSA |
| Author: |
Joshua Lambert [aut, cre],
Liyu Gong [aut],
Corrine Elliott [aut],
Sarah Janse [ctb] |
| Maintainer: |
Joshua Lambert <joshua.lambert at uc.edu> |
| License: |
GPL-2 |
| NeedsCompilation: |
no |
| Materials: |
README |
| CRAN checks: |
rFSA results |
Documentation:
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