Package: multiridge 1.11

Mark A. van de Wiel

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>.

Authors:Mark A. van de Wiel

multiridge_1.11.tar.gz
multiridge_1.11.tar.gz(r-4.7-any)multiridge_1.11.tar.gz(r-4.6-any)
multiridge_1.11.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
multiridge/json (API)

# Install 'multiridge' in R:
install.packages('multiridge', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.70 score 2 scripts 256 downloads 20 exports 9 dependencies

Last updated from:95dbb68884. Checks:4 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK141
source / vignettesOK236
linux-release-x86_64OK123
wasm-releaseOK101

Exports:augmentbetasoutcreateXblockscreateXXblocksCVfoldsCVscoredoubleCVfastCV2IWLSCoxridgeIWLSridgemgcv_lambdamlikCVoptLambdasoptLambdas_mgcvoptLambdas_mgcvWrapoptLambdasWrappredictIWLSScoringsetupParallelSigmaFromBlocks

Dependencies:latticeMatrixmgcvnlmepROCRcppsnowsnowfallsurvival