IMPROVING ON THE MLE OF A POSITIVE NORMAL MEAN

We study the problem of estimating the mean of a univariate normal population when the mean is known to be non-negative and loss is squared error. The MLE is superior to the UMVUE, but it is known that the MLE is itself inadmissible. A long unsolved problem is to find an explicit estimator which dom...

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Bibliographic Details
Published in:Statistica Sinica 1996-01, Vol.6 (1), p.259-274
Main Authors: Shao, Peter Yi-Shi, Strawderman, William E.
Format: Article
Language:English
Subjects:
Bayes estimators
Continuous functions
Estimators
Maximum likelihood estimation
Minimax
Online Access:Get full text
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Summary:We study the problem of estimating the mean of a univariate normal population when the mean is known to be non-negative and loss is squared error. The MLE is superior to the UMVUE, but it is known that the MLE is itself inadmissible. A long unsolved problem is to find an explicit estimator which dominates the MLE. This paper is devoted to producing a class of such estimators. We believe, but have not proved, that some members of our class are admissible.
ISSN:1017-0405
1996-8507