Package: g.ridge 1.0

Takeshi Emura

g.ridge: Generalized Ridge Regression for Linear Models

Ridge regression due to Hoerl and Kennard (1970)<doi:10.1080/00401706.1970.10488634> and generalized ridge regression due to Yang and Emura (2017)<doi:10.1080/03610918.2016.1193195> with optimized tuning parameters. These ridge regression estimators (the HK estimator and the YE estimator) are computed by minimizing the cross-validated mean squared errors. Both the ridge and generalized ridge estimators are applicable for high-dimensional regressors (p>n), where p is the number of regressors, and n is the sample size.

Authors:Takeshi Emura [aut, cre], Szu-Peng Yang [ctb]

g.ridge_1.0.tar.gz
g.ridge_1.0.tar.gz(r-4.5-noble)g.ridge_1.0.tar.gz(r-4.4-noble)
g.ridge_1.0.tgz(r-4.4-emscripten)g.ridge_1.0.tgz(r-4.3-emscripten)
g.ridge.pdf |g.ridge.html✨
g.ridge/json (API)

# Install 'g.ridge' in R:
install.packages('g.ridge', repos = 'https://cloud.r-project.org')

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 219 downloads 3 exports 0 dependencies

Last updated 1 years agofrom:f91de599e3. Checks:3 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 31 2025
R-4.5-linuxOKMar 31 2025
R-4.4-linuxOKMar 31 2025

Exports:g.ridgeGCVX.mat

Dependencies:

Citation

To cite package ‘g.ridge’ in publications use:

Emura T (2023). g.ridge: Generalized Ridge Regression for Linear Models. R package version 1.0, https://CRAN.R-project.org/package=g.ridge.

Corresponding BibTeX entry: 

  @Manual{,
    title = {g.ridge: Generalized Ridge Regression for Linear Models},
    author = {Takeshi Emura},
    year = {2023},
    note = {R package version 1.0},
    url = {https://CRAN.R-project.org/package=g.ridge},
  }