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-4.5-noble)multiridge_1.11.tar.gz(r-4.4-noble)
multiridge_1.11.tgz(r-4.4-emscripten)multiridge_1.11.tgz(r-4.3-emscripten)
multiridge.pdf |multiridge.html✨
multiridge/json (API)

Peer review:

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

20 exports 0.61 score 10 dependencies 2 dependents 1 scripts 175 downloads

Last updated 2 years agofrom:95dbb68884. Checks:OK: 2. Indexed: yes.

Exports:augmentbetasoutcreateXblockscreateXXblocksCVfoldsCVscoredoubleCVfastCV2IWLSCoxridgeIWLSridgemgcv_lambdamlikCVoptLambdasoptLambdas_mgcvoptLambdas_mgcvWrapoptLambdasWrappredictIWLSScoringsetupParallelSigmaFromBlocks

Dependencies:latticeMatrixmgcvnlmeplyrpROCRcppsnowsnowfallsurvival