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Multi-penalty linear, logistic and cox ridge regression, including estimation of the penalty parameters by efficient (repeated) cross-validation and marginal likelihood maximization. Multiple high-dimensional data types that require penalization are allowed, as well as unpenalized variables. Paired and preferential data types can be specified. See Van de Wiel et al. (2021), <doi:10.48550/arXiv.2005.09301>.
| Version: | 1.11 |
| Depends: | R (≥ 3.5.0), survival, pROC, methods, mgcv, snowfall |
| Published: | 2022-06-13 |
| Author: | Mark A. van de Wiel |
| Maintainer: | Mark A. van de Wiel <mark.vdwiel at amsterdamumc.nl> |
| License: | GPL (≥ 3) |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | multiridge results |
| Reference manual: | multiridge.pdf |
| Package source: | multiridge_1.11.tar.gz |
| Windows binaries: | r-devel: multiridge_1.11.zip, r-release: multiridge_1.11.zip, r-oldrel: multiridge_1.11.zip |
| macOS binaries: | r-release (arm64): multiridge_1.11.tgz, r-oldrel (arm64): multiridge_1.11.tgz, r-release (x86_64): multiridge_1.11.tgz, r-oldrel (x86_64): multiridge_1.11.tgz |
| Old sources: | multiridge archive |
| Reverse imports: | ecpc, squeezy |
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