On shrinkage estimators improving the James-Stein estimator under balanced loss function

In this paper, we are interested in estimating a multivariate normal mean under the balanced loss function using the shrinkage estimators deduced from the Maximum Likelihood Estimator (MEE). First, we consider a class of estimators containing the James-Stein estimator, we then show that any estimato...

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Bibliographic Details
Published in:Pakistan journal of statistics and operation research 2021-07, Vol.17 (3), p.711-727
Main Authors: Hamdaoui, Abdenour, Terbeche, Mekki, Benkhaled, Abdelkader
Format: Article
Language:English
Subjects:
Maximum likelihood estimators
Minimax technique
Normal distribution
Random variables
Online Access:Get full text
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Summary:In this paper, we are interested in estimating a multivariate normal mean under the balanced loss function using the shrinkage estimators deduced from the Maximum Likelihood Estimator (MEE). First, we consider a class of estimators containing the James-Stein estimator, we then show that any estimator of this class dominates the MEE, consequently it is minimax. Secondly, we deal with shrinkage estimators which are not only minimax but also dominate the James-Stein estimator.
ISSN:1816-2711
2220-5810
DOI:10.18187/pjsor.vl7i3.3663