The Superiorities of Bayes Linear Minimum Risk Estimation in Linear Model

Abstract

In this article, the Bayes linear minimum risk estimator (BLMRE) of parameters is derived in linear model. The superiorities of the BLMRE over ordinary least square estimator (LSE) is studied in terms of the mean square error matrix (MSEM) criterion and Pitman closeness (PC) criterion.

Keywords:

• Bayes linear minimum risk estimator
• Least square estimator
• Linear model
• Mean square error matrix criterion
• Pitman closeness criterion

Mathematics Subject Classification 2000:

• Primary 62C10
• Secondary 62J05

Acknowledgments

The project is supported by the Doctoral Program Foundation of the Institute of High Education and Knowledge Innovation Program of the Chinese Academy of Sciences (Grant No. KJCX3-SYW-S02). The authors wish to thank the referees for their helpful suggestions and comments.