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.
Version: |
1.0 |
Published: |
2023-12-07 |
Author: |
Takeshi Emura [aut, cre],
Szu-Peng Yang [ctb] |
Maintainer: |
Takeshi Emura <takeshiemura at gmail.com> |
License: |
GPL-2 |
NeedsCompilation: |
no |
CRAN checks: |
g.ridge results |
Documentation:
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