An empirical Bayes derivation of best linear unbiased predictors

Rohana J. Karunamuni

International Journal of Mathematics and Mathematical Sciences, 2002, vol. 31, 1-12

Abstract:

Let ( Y 1 , θ 1 ) , … , ( Y n , θ n ) be independent real-valued random vectors with Y i , given θ i , is distributed according to a distribution depending only on θ i for i = 1 , … , n . In this paper, best linear unbiased predictors (BLUPs) of the θ i 's are investigated. We show that BLUPs of θ i 's do not exist in certain situations. Furthermore, we present a general empirical Bayes technique for deriving BLUPs.

Date: 2002
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jijmms:360869

DOI: 10.1155/S016117120211009X

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