Large sample asymptotic properties of the double k-class estimators in linear regression models
研究了双k类估计量在预测均方误差上优于普通最小二乘和Stein规则估计量的条件，推导了非正态等情形下的渐近偏差和均方误差，并通过模拟比较了三种估计量的表现。
This paper provides guidance in choosing k1 andk2 of the double k-class (KK) estimator such that it will improve upon both the ordinary least squares (OLS) and Stein-rule (SR) estimators in predictive mean squared error (PMSE). Asymptotic bias and mean squared error (MSE) results are derived for nonnormal and other cases. A simulation compares the KK estimator with the OLS and SR estimators.