Bayesian Multiple Comparisons in Geometric Populations

• 발행기관: 한국자료분석학회
• 저자명: 조장식(Jang Sik Cho) 차영준(Young Joon Cha) 이재만(Jae Man Lee)
• 간행물 정보: 『Journal of The Korean Data Analysis Society (JKDAS)』Vol.8 No.3, 919~926쪽, 전체 8쪽
• 주제분류: 자연과학 > 통계학
• 파일형태: PDF
• 발행일자: 2006.06.30

영문 초록

In this paper, we consider the Bayesian multiple comparisons problem for K geometric populations to make inferences on the relationships among parameters based on observations. We introduce the configurations because there is a one to one correspondence between hypotheses and configurations. And we use Bayes factor when noninformative priors are applied for the parameters. But, since noninformative priors are typically improper, the priors are only up to arbitrary constants which affect the values of Bayes factors. Hence, we compute the fractional Bayes factor proposed by O Hagan(1995) to remove the arbitrariness by using a portion of the likelihood with a so-called the fraction b. Also we suggest the Bayesian procedure for multiple comparisons based on fractional Bayes factor by configuration notations. Finally, we give a numerical examples to illustrate our procedure.

목차

1. Introduction

2. Preliminaries

3. Bayesian Multiple Comparisons in Geometric Populations

4. Numerical Examples

References

키워드

Bayesian Multiple Comparison Configuration Fractional Bayes Factor Geometric Population Noninformative Priors Posterior Probability