• The Korean Journal of Applied Statistics
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• v.16 no.2
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• pp.335-349
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• 2003

In this paper, we use Bayesian method for model selection of poisson vs. negative binomial distribution, and normal, double exponential vs. cauchy distribution. The fractional Bayes factor of O'Hagan (1995) was applied to Bayesian model selection under the assumption of noninformative improper priors for all parameters in the models. Through the analyses of real data and simulation data, we examine the usefulness of the fractional Bayes factor in comparison with intrinsic Bayes factors of Berger and Pericchi (1996, 1998).

• Journal of the Korean Data and Information Science Society
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• v.16 no.4
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• pp.861-870
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• 2005

The Bayesian model selection procedures for the shape parameter of gamma distribution are proposed in order to test that the failure rate of gamma distribution is constant, increasing or decreasing. The encompassing intrinsic Bayes factor by Beger and Pericchi (1996) based on Jeffreys prior for shape parameter is used to investigate the usefulness of the proposed Bayesian model selection procedures via both real data and pseudo data.

• Journal of the Korean Data and Information Science Society
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• v.11 no.2
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• pp.269-277
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• 2000

We propose the Bayesian testing for the equality of two log-normal population means. Specifically we use the intrinsic Bayes factors suggested by Berger and Perichi (1996, 1998) based on the noninformative priors for the parameters. In order to investigate the usefulness of the proposed Bayesian testing procedures, we compare it with classical tests via both real data analysis and simulation.

• Journal of the Korean Data and Information Science Society
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• v.12 no.1
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• pp.41-50
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• 2001

We propose the Bayesian testing for the equality of K-exponential populations means. Specially we use the intrinsic Bayesian factors suggested by Beregr and Perrichi (1996,1998) based on the noninformative priors for the parameters. And, we investigate the usefulness of the proposed Bayesian testing procedures via simulations.

• Journal of Korean Society of Transportation
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• v.31 no.6
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• pp.67-89
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• 2013

This study is to perform empirical analysis on observational before-after studies in Naive Method, Comparison Group(CG) Method and Empirical Bayes(EB) Method, and to compare with their results and to propose ways to apply to evaluation researches. For this purpose, the evaluation of road safety audit executed on Y$\breve{o}$ng-dong freeway in 2005 and 2006 was performed. As a result, all three methods have showed improved effects due to safety treatments. The safety effectiveness of Naive method is the largest, CG Method is the second and EB method is the last. The results of Naive method are overestimated due to the trend of reducing traffic accidents and those of CG method are affected by the external casual effects of comparison group. In the EB method, as "regression to the mean" phenomenon are controlled by reference group's accident model, it's result is relatively more accurate than that of other methods. In the conduct of evaluation studies, the analysts have to understand the pros and cons of each evaluation method. And after leading the survey on accident trends of related all sites, evaluation analysis is performed to be able to minimize bias.