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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0 |
rolling source/ R- | g.ridge_1.0.tar.gz |
4.1 KiB |
1.0 |
rolling linux/jammy R-4.5 | g.ridge_1.0.tar.gz |
19.7 KiB |
1.0 |
latest source/ R- | g.ridge_1.0.tar.gz |
4.1 KiB |
1.0 |
latest linux/jammy R-4.5 | g.ridge_1.0.tar.gz |
19.7 KiB |
1.0 |
2026-04-23 source/ R- | g.ridge_1.0.tar.gz |
4.1 KiB |
1.0 |
2026-04-09 windows/windows R-4.5 | g.ridge_1.0.zip |
22.3 KiB |
1.0 |
2025-04-20 source/ R- | g.ridge_1.0.tar.gz |
4.1 KiB |