A Frequentist Analysis of a Class of Ridge Regression Estimators
将六种新提出的岭回归估计量归为一类，基于频率学派视角而非模拟分析，论证其中经验贝叶斯最大似然估计量优于其他五种。
Abstract We discuss ridge regression estimators as a class, showing how six recently proposed estimators can thus be viewed, and give reasons for preferring one of these (empirical Bayes maximum likelihood estimator) to the other five. Results are based on analysis rather than simulations and on a frequentist rather than Bayesian viewpoint.