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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), <arXiv:2005.09301>.

Versions across snapshots

VersionRepositoryFileSize
1.11 rolling linux/jammy R-4.5 multiridge_1.11.tar.gz 188.2 KiB
1.11 rolling linux/noble R-4.5 multiridge_1.11.tar.gz 188.2 KiB
1.11 rolling source/ R- multiridge_1.11.tar.gz 52.2 KiB
1.11 latest linux/jammy R-4.5 multiridge_1.11.tar.gz 188.2 KiB
1.11 latest linux/noble R-4.5 multiridge_1.11.tar.gz 188.2 KiB
1.11 latest source/ R- multiridge_1.11.tar.gz 52.2 KiB
1.11 2026-04-26 source/ R- multiridge_1.11.tar.gz 52.2 KiB
1.11 2026-04-23 source/ R- multiridge_1.11.tar.gz 52.2 KiB
1.11 2026-04-09 windows/windows R-4.5 multiridge_1.11.zip 191.3 KiB
1.11 2025-04-20 source/ R- multiridge_1.11.tar.gz 52.2 KiB

Dependencies (latest)

Depends