Objective Bayesian FDR

Here, we develop an objective Bayesian analysis for large-scale datasets. When Bayesian analysis is applied to large-scale datasets, the cut point that provides the posterior probability is usually determined following customs. In this work, we propose setting the cut point in an objective manner, w...

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Bibliographic Details
Published in:arXiv.org 2024-03
Main Author: Hayashi, Yoshiko
Format: Article
Language:English
Subjects:
Bayesian analysis
Conditional probability
Datasets
Online Access:Get full text
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Summary:Here, we develop an objective Bayesian analysis for large-scale datasets. When Bayesian analysis is applied to large-scale datasets, the cut point that provides the posterior probability is usually determined following customs. In this work, we propose setting the cut point in an objective manner, which is determined so as to match the posterior null number with the estimated true null number. The posterior probability obtained using an objective cut point is relatively similar to the real false discovery rate (FDR), which facilitates control of the FDR level.
ISSN:2331-8422