A Heuristic Method for Determining Admissibility of Estimators--With Applications

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Statistics Papers
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estimation
admissibility
(nonlinear) differential inequalities
generalized Bayes estimators
estimation location parameters
estimating Poisson means
estimating the largest mean
estimating a normal variance (mean unknown).
Statistics and Probability
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Brown, Lawrence D
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Questions of admissibility of statistical estimators are reduced to considerations involving differential inequalities. The coefficients of these inequalities involve moments of the underlying distributions; and so are, in principle, not difficult to derive. The methods are "heuristic" because it is necessary to verify on an ad-hoc basis that error terms are small. Some conditions on the structure of the problem are given which we believe will guarantee that these error terms are small. Several different statistical estimation problems are discussed. Each problem is transformed (if necessary) so as to meet the above mentioned structure conditions. Then the heuristic method is applied in order to generate conjectures concerning the admissibility of certain generalized Bayes procedures in these problems.

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1979
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The Annals of Statistics
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At the time of publication, author Lawrence Brown was affiliated with Rutgers University. Currently, he is a faculty member at the Statistics Department at the University of Pennsylvania.
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