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cvLM  

Cross-Validation for Linear & Ridge Regression Models
View on CRAN: Click here


Download and install cvLM package within the R console
Install from CRAN:
install.packages("cvLM")

Install from Github:
library("remotes")
install_github("cran/cvLM")

Install by package version:
library("remotes")
install_version("cvLM", "1.0.4")



Attach the package and use:
library("cvLM")
Maintained by
Philip Nye
[Scholar Profile | Author Map]
First Published: 2024-08-01
Latest Update: 2024-08-01
Description:
Efficient implementations of cross-validation techniques for linear and ridge regression models, leveraging 'C++' code with 'Rcpp', 'RcppParallel', and 'Eigen' libraries. It supports leave-one-out, generalized, and K-fold cross-validation methods, utilizing 'Eigen' matrices for high performance. Methodology references: Hastie, Tibshirani, and Friedman (2009) <doi:10.1007/978-0-387-84858-7>.
How to cite:
Philip Nye (2024). cvLM: Cross-Validation for Linear & Ridge Regression Models. R package version 1.0.4, https://cran.r-project.org/web/packages/cvLM. Accessed 03 May. 2025.
Previous versions and publish date:
No previous versions
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Complete documentation for cvLM
Functions, R codes and Examples using the cvLM R package
Full cvLM package functions and examples
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