Minimaxity of a preliminary test estimator for the mean of normal distribution
type: Item
instance of: scholarly article
title: Minimaxity of a preliminary test estimator for the mean of normal distribution
zbMATH Open document ID: 0584.62038
DOI: 10.1007/BF02481111
author: Yasushi Nagata
author: Taichi Inaba
published in: Annals of the Institute of Statistical Mathematics
publication date: 1985-01-01T00:00:00Z
review text: The problem is to estimate the mean of the normal distribution under the situation where there is vague information that the mean might be equal to zero. A minimax property of the preliminary test estimator obtained by the use of AIC (Akaike information criterion) procedure is proved under a loss function based on the Kullback-Leibler information measure.
Mathematics Subject Classification ID: 62F10
Mathematics Subject Classification ID: 62B10
zbMATH DE Number: 3936197
zbMATH Keywords: mean of the normal distribution
zbMATH Keywords: minimax property
zbMATH Keywords: preliminary test estimator
zbMATH Keywords: AIC
zbMATH Keywords: Akaike information criterion
zbMATH Keywords: loss function
zbMATH Keywords: Kullback- Leibler information measure
MaRDI profile type: Publication
cites work: Estimation procedures based on preliminary test, shrinkage technique and information criterion
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cites work: Q3672893
cites work: The Admissibility of a Preliminary Test Estimator When the Loss Incorporates a Complexity Cost
cites work: Admissibility of some preliminary test estimators for the mean of normal distribution
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full work available at URL: https://doi.org/10.1007/bf02481111
OpenAlex ID: W1969531907
description: scientific article; zbMATH DE number 3936197