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Frequentist Bayesian compound inference

  • Jinfeng Xu
  • , Ao Yuan*
  • *Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

In practice often either the Bayesian or frequentist method is used, although there are some combined uses of the two methods, a formal unified methodology of the two hasn’t been seen. Here we first give a brief review of the two methods and some combination of the two, then propose a procedure using both the frequentist likelihood and the Bayesian posterior loss in parameter estimation and hypothesis testing, as an attempt to unify the two methods. Basic properties of the proposed method are studied, and simulation studies are carried out to evaluate the performance of the method.
Original languageEnglish
Pages (from-to)9-26
JournalStatistics and Its Interface
Volume17
Issue number1
Online published27 Nov 2023
DOIs
Publication statusPublished - 2024

Funding

The authors are very grateful to the Co-editors Professor Ming-Hui Chen and Professor Yuedong Wang, an associate editor, and two reviewers for their very helpful and constructive comments. Xu’s work was supported in part by General Research Fund (17308820) of Hong Kong.

Research Keywords

  • Bayesian estimate
  • Compound inference
  • High order behavior
  • Maximum likelihood estimate

RGC Funding Information

  • RGC-funded

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