James-Stein Estimation from an Alternative Perspective

Abstract

In the comparison of estimators, the typical viewpoint of mean squared error has been challenged by C. R. Rao. In this article we propose a method of selecting estimators in normal populations based on their regions of preference. These regions of preference are a natural consequence of Rao's emphasis on Pitman nearness. We apply the method in the case of estimation of the mean of a bivariate normal through the James-Stein class.

Key Words:

• Adaptive estimator
• Pitman nearness
• Mean squared error