Generalized Ridge Regression for Linear Models
Description
Ridge regression due to Hoerl and Kennard (1970) and generalized ridge regression due to Yang and Emura (2017) 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.