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Main Authors: Okudo, Michiko, Yano, Keisuke
Format: Preprint
Published: 2023
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Online Access:https://arxiv.org/abs/2312.09586
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author Okudo, Michiko
Yano, Keisuke
author_facet Okudo, Michiko
Yano, Keisuke
contents Bayesian statistics has two common measures of central tendency of a posterior distribution: posterior means and Maximum A Posteriori (MAP) estimates. In this paper, we discuss a connection between MAP estimates and posterior means. We derive an asymptotic condition for a pair of prior densities under which the posterior mean based on one prior coincides with the MAP estimate based on the other prior. A sufficient condition for the existence of this prior pair relates to $α$-flatness of the statistical model in information geometry. We also construct a matching prior pair using $α$-parallel priors. Our result elucidates an interesting connection between regularization in generalized linear regression models and posterior expectation.
format Preprint
id arxiv_https___arxiv_org_abs_2312_09586
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Matching prior pairs connecting Maximum A Posteriori estimation and posterior expectation
Okudo, Michiko
Yano, Keisuke
Statistics Theory
Bayesian statistics has two common measures of central tendency of a posterior distribution: posterior means and Maximum A Posteriori (MAP) estimates. In this paper, we discuss a connection between MAP estimates and posterior means. We derive an asymptotic condition for a pair of prior densities under which the posterior mean based on one prior coincides with the MAP estimate based on the other prior. A sufficient condition for the existence of this prior pair relates to $α$-flatness of the statistical model in information geometry. We also construct a matching prior pair using $α$-parallel priors. Our result elucidates an interesting connection between regularization in generalized linear regression models and posterior expectation.
title Matching prior pairs connecting Maximum A Posteriori estimation and posterior expectation
topic Statistics Theory
url https://arxiv.org/abs/2312.09586