cv: Cross-Validating Regression Models
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".
| Version: |
2.0.3 |
| Depends: |
R (≥ 3.5.0), doParallel |
| Imports: |
car, foreach, glmmTMB, graphics, grDevices, gtools, insight, lattice, lme4, MASS, methods, nlme, parallel, stats, utils |
| Suggests: |
boot, carData, dplyr, effects, ISLR2, knitr, latticeExtra, leaps, Metrics, microbenchmark, nnet, rmarkdown, spelling, testthat |
| Published: |
2024-09-22 |
| DOI: |
10.32614/CRAN.package.cv |
| Author: |
John Fox  [aut],
Georges Monette [aut, cre] |
| Maintainer: |
Georges Monette <georges+cv at yorku.ca> |
| BugReports: |
https://github.com/gmonette/cv/issues |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: |
https://gmonette.github.io/cv/,
https://CRAN.R-project.org/package=cv |
| NeedsCompilation: |
no |
| Language: |
en-US |
| Materials: |
README NEWS |
| CRAN checks: |
cv results |
Documentation:
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