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multiridge: Fast Cross-Validation for Multi-Penalty Ridge Regression

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
DOI: 10.32614/CRAN.package.multiridge
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

Documentation:

Reference manual: multiridge.pdf

Downloads:

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 dependencies:

Reverse imports: ecpc, squeezy

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.