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STOPES: Selection Threshold Optimized Empirically via Splitting
Implements variable selection procedures for low to moderate size generalized linear regressions models. It includes the STOPES functions for linear regression (Capanu M, Giurcanu M, Begg C, Gonen M, Optimized variable selection via repeated data splitting, Statistics in Medicine, 2020, 19(6):2167-2184) as well as subsampling based optimization methods for generalized linear regression models (Marinela Capanu, Mihai Giurcanu, Colin B Begg, Mithat Gonen, Subsampling based variable selection for generalized linear models).
Getting started
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Package details |
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| Author | Marinela Capanu [aut, cre], Mihai Giurcanu [aut, ctb], Colin Begg [aut], Mithat Gonen [aut] |
| Maintainer | Marinela Capanu <capanum@mskcc.org> |
| License | GPL-2 |
| Version | 0.2 |
| Package repository | View on CRAN |
| Installation |
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