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:

Please use the canonical form https://CRAN.R-project.org/package=multiridge to link to this page.