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Main Author: Maruyama, Yuzo
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2603.00553
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author Maruyama, Yuzo
author_facet Maruyama, Yuzo
contents This paper is a follow-up to Maruyama and Strawderman (2006, Journal of Statistical Planning and Inference), which identified a new class of generalized Bayes estimators with a particularly simple form for estimating a normal variance under entropy loss. Although their previous work established the Bayesianity of these estimators, it did not provide a closed-form result for their minimaxity. In this paper, we revisit the problem and establish a definitive closed-form minimaxity result for this class of simple Bayes estimators.
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publishDate 2026
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spellingShingle Minimax Simple Bayes Estimators of a Normal Variance
Maruyama, Yuzo
Statistics Theory
This paper is a follow-up to Maruyama and Strawderman (2006, Journal of Statistical Planning and Inference), which identified a new class of generalized Bayes estimators with a particularly simple form for estimating a normal variance under entropy loss. Although their previous work established the Bayesianity of these estimators, it did not provide a closed-form result for their minimaxity. In this paper, we revisit the problem and establish a definitive closed-form minimaxity result for this class of simple Bayes estimators.
title Minimax Simple Bayes Estimators of a Normal Variance
topic Statistics Theory
url https://arxiv.org/abs/2603.00553