Cross-Validation for Linear and Ridge Regression Models R package cvLM version 2.0.0 Implements cross-validation methods for linear and ridge regression models. The package provides grid-based selection of the ridge penalty parameter using Singular Value Decomposition (SVD) and supports K-fold cross-validation, Leave-One-Out Cross-Validation (LOOCV), and Generalized Cross-Validation (GCV). Computations are implemented in C++ via 'RcppArmadillo' with optional parallelization using 'RcppParallel'. The methods are suitable for high-dimensional settings where the number of predictors exceeds the number of observations. Software Imports: stats, Rcpp (>= 1.0.13), RcppParallel (>= 5.1.8) LinkingTo: Rcpp, RcppArmadillo, RcppParallel Suggests: boot, RhpcBLASctl, testthat (>= 3.0.0) Philip Nye <phipnye@proton.me> Comprehensive R Archive Network (CRAN) Philip Nye [aut, cre] MIT + file LICENSE (https://CRAN.R-project.org/package=cvLM/LICENSE) 2026-02-03 application/tgz https://CRAN.R-project.org/package=cvLM doi:10.32614/CRAN.package.cvLM