International Journal of Mathematics and Mathematical Sciences
Volume 31 (2002), Issue 12, Pages 703-714
An empirical Bayes derivation of best linear unbiased predictors
Department of Mathematical and Statistical Sciences, University of Alberta, Alberta, Edmonton T6G 2G1, Canada
Received 8 October 2001
Copyright © 2002 Rohana J. Karunamuni. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Let be independent real-valued random vectors with , given , is distributed according to a distribution depending only on for . In this paper, best linear unbiased predictors (BLUPs) of the 's are investigated. We show that BLUPs of 's do not exist in certain situations. Furthermore, we present a general empirical Bayes technique for deriving BLUPs.