Unbiased estimation of the MSE matrices of improved estimators in linear regression
by
Anoop Chaturvedi
Department of Statistics, University of Allahabad, Allahabad
Coauthors: Alan T.K.Wan (Department of Management Sciences, City University of Hong Kong, Hong Kong), Guohua Zou (Institute of System Sciences, Chinese Academy of Sciences, China)

Stein-rule and other improved estimators have scarcely been used in empirical work. One major reason is that it is not easy to obtain precision measures for these estimators. In this paper, we derive unbiased estimators for both the mean squared error (MSE) and the scaled MSE matrices of a class of Stein-type estimators. Our derivation provides the basis for measuring the estimators’ precision and constructing confidence bands. Comparisons are made between these MSE estimators and the least squares covariance estimator. For illustration, the methodology is applied to data on energy consumption.

Date received: November 13, 2002

Copyright © 2002 by the author(s). The author(s) of this document and the organizers of the conference have granted their consent to include this abstract in Atlas Conferences Inc. Document # cakd-09.