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2006•Journal of the Korean Data and Information Science SocietyRequires access

Bayesian Multiple Comparison of Bivariate Exponential Populations based on Fractional Bayes Factor

Jang-Sik Cho, Kil Ho Cho, Choi SeungBae

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Abstract

In this paper, we consider the Bayesian multiple comparisons problem for K bivariate exponential populations to make inferences on the relationships among the parameters based on observations. And we suggest the Bayesian procedure based on fractional Bayes factor when noninformative priors are applied for the parameters. Also, we give a numerical examples to illustrate our procedure.

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What this paper is about

In this paper, we consider the Bayesian multiple comparisons problem for K bivariate exponential populations to make inferences on the relationships among the parameters based on observations. And we suggest the Bayesian procedure based on fractional Bayes factor when noninformative priors are applied for the parameters. Also, we give a numerical examples to illustrate our procedure.

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Available abstract

In this paper, we consider the Bayesian multiple comparisons problem for K bivariate exponential populations to make inferences on the relationships among the parameters based on observations. And we suggest the Bayesian procedure based on fractional Bayes factor when noninformative priors are applied for the parameters. Also, we give a numerical examples to illustrate our procedure.

Key concepts: Bivariate analysis, Prior probability, Mathematics, Bayesian probability, Bayes factor, Bayes' theorem, Statistics, Bayes' rule

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