Journal of the Korean Data and Information Science Society
- Volume 19 Issue 2
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- Pages.621-634
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- 2008
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- 1598-9402(pISSN)
Bayesian Model Selection for Inverse Gaussian Populations with Heterogeneity
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Kang, Sang-Gil
(Department of Computer & Data Information, Sangji University) ;
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Kim, Dal-Ho
(Department of Statistics, Kyungpook National University) ;
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Lee, Woo-Dong
(Department of Asset Management, Daegu Haany University)
- Published : 2008.04.30
Abstract
This paper addresses the problem of testing whether the means in several inverse Gaussian populations with heterogeneity are equal. The analysis of reciprocals for the equality of inverse Gaussian means needs the assumption of equal scale parameters. We propose Bayesian model selection procedures for testing equality of the inverse Gaussian means under the noninformative prior without the assumption of equal scale parameters. The noninformative prior is usually improper which yields a calibration problem that makes the Bayes factor to be defined up to a multiplicative constant. So we propose the objective Bayesian model selection procedures based on the fractional Bayes factor and the intrinsic Bayes factor under the reference prior. Simulation study and real data analysis are provided.
Keywords
- Equality of the Inverse Gaussian Means;
- Fractional Bayes Factor;
- Intrinsic Bayes Factor;
- Reference Prior