Minimax Simple Bayes Estimators of a Normal Variance
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arXiv
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| Format: | Preprint |
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2026
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| _version_ | 1866914361188024320 |
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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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_00553 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| 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 |