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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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Package details |
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| Author | Philip Nye [aut, cre] |
| Maintainer | Philip Nye <phipnye@proton.me> |
| License | MIT + file LICENSE |
| Version | 2.0.0 |
| URL | https://github.com/phipnye/CV-LM |
| Package repository | View on CRAN |
| Installation |
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