Objective priors for common correlation coefficient in bivariate normal populations

Sang Gil Kang, Woo Dong Lee, Yongku Kim

Research output: Contribution to journalArticlepeer-review

Abstract

Various objective priors have been defined for the common correlation coefficient concerning several bivariate normal populations. In this paper, the proposed approach relies on the asymptotic matching of coverage probabilities corresponding to Bayesian credible intervals considering the corresponding frequentist ones. In the present paper, we focus on several matching criteria including quantile matching, distribution function matching, highest posterior density matching, and matching via inversion of test statistics. In addition, we consider reference priors for different groups of ordering. The proposed methods are investigated and compared between each other in terms of a frequentist coverage probability and then, they are illustrated through a simulation study and two real data examples.

Original languageEnglish
Pages (from-to)2124-2143
Number of pages20
JournalCommunications in Statistics - Theory and Methods
Volume52
Issue number7
DOIs
StatePublished - 2023

Keywords

  • Bayesian inference
  • common correlation coefficient
  • matching prior
  • reference prior

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