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cvLM: Cross-Validation for Linear & Ridge Regression Models

Efficient implementations of cross-validation techniques for linear and ridge regression models, leveraging 'C++' code with 'Rcpp', 'RcppParallel', and 'Eigen' libraries. It supports leave-one-out, generalized, and K-fold cross-validation methods, utilizing 'Eigen' matrices for high performance. Methodology references: Hastie, Tibshirani, and Friedman (2009) <doi:10.1007/978-0-387-84858-7>.

Version: 1.0.4
Imports: stats, Rcpp (≥ 1.0.13), RcppParallel (≥ 5.1.8)
LinkingTo: Rcpp, RcppParallel, RcppEigen
Published: 2024-08-01
DOI: 10.32614/CRAN.package.cvLM
Author: Philip Nye [aut, cre]
Maintainer: Philip Nye <phipnye at proton.me>
License: MIT + file LICENSE
NeedsCompilation: yes
SystemRequirements: GNU make
Materials: README
CRAN checks: cvLM results

Documentation:

Reference manual: cvLM.pdf

Downloads:

Package source: cvLM_1.0.4.tar.gz
Windows binaries: r-devel: cvLM_1.0.4.zip, r-release: cvLM_1.0.4.zip, r-oldrel: cvLM_1.0.4.zip
macOS binaries: r-release (arm64): cvLM_1.0.4.tgz, r-oldrel (arm64): cvLM_1.0.4.tgz, r-release (x86_64): cvLM_1.0.4.tgz, r-oldrel (x86_64): cvLM_1.0.4.tgz

Linking:

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

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.