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cv: An R Package for Cross-Validating Regression Models

Дата публикации: 15-06-2026 00:00:00

We describe the cv package, which implements cross-validation for standard R regression models through a uniform and simple to use generic function. Methods for the cv() function are provided for many commonly employed classes of statistical models, including mixed-effects models, and it is straightforward to extend the cv package by writing methods for additional classes of models. The cv() function can also cross-validate complex model-selection procedures, such as those that include variable transformations, predictor selection, and selection among competing models. The cv() function generally supports parallel computations, and the supplied methods for linear and generalized linear models take advantage of computational efficiencies.

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Abstract

We describe the cv package, which implements cross-validation for standard R regression models through a uniform and simple to use generic function. Methods for the cv() function are provided for many commonly employed classes of statistical models, including mixed-effects models, and it is straightforward to extend the cv package by writing methods for additional classes of models. The cv() function can also cross-validate complex model-selection procedures, such as those that include variable transformations, predictor selection, and selection among competing models. The cv() function generally supports parallel computations, and the supplied methods for linear and generalized linear models take advantage of computational efficiencies.

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