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.
