cvLM

Cross-Validation for Linear and Ridge Regression Models

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.

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