Cross-validation methods of regression models that exploit features of various modeling functions to improve speed. Some of the methods implemented in the package are novel, as described in the package vignettes; for general introductions to cross-validation, see, for example, Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani (2021, ISBN 978-1-0716-1417-4, Secs. 5.1, 5.3), "An Introduction to Statistical Learning with Applications in R, Second Edition", and Trevor Hastie, Robert Tibshirani, and Jerome Friedman (2009, ISBN 978-0-387-84857-0, Sec. 7.10), "The Elements of Statistical Learning, Second Edition".
Package details |
|
---|---|
Author | John Fox [aut] (<https://orcid.org/0000-0002-1196-8012>), Georges Monette [aut, cre] |
Maintainer | Georges Monette <georges+cv@yorku.ca> |
License | GPL (>= 2) |
Version | 2.0.3 |
URL | https://gmonette.github.io/cv/ https://CRAN.R-project.org/package=cv |
Package repository | View on CRAN |
Installation |
Install the latest version of this package by entering the following in R:
|
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.