• Journal of the Korean Data and Information Science Society
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• v.21 no.2
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• pp.297-308
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• 2010

This article deals with the problem of testing mean when the coefficient of variation in normal distribution is known. We propose Bayesian hypothesis testing procedures for the normal mean under the noninformative prior. 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 hypothesis testing procedures based on the fractional Bayes factor and the intrinsic Bayes factor under the reference prior. Specially, we develop intrinsic priors which give asymptotically same Bayes factor with the intrinsic Bayes factor under the reference prior. Simulation study and a real data example are provided.

• Journal of the Korean Statistical Society
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• v.29 no.4
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• pp.395-405
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• 2000

This article addresses the Bayesian hypothesis testing for the comparison of two exponential mans. Conventional Bayes factors with improper non-informative priors are into well defined. The fractional Byes factor(FBF) of O'Hagan(1995) is used to overcome such as difficulty. we derive proper intrinsic priors, whose Bayes factors are asymptotically equivalent to the corresponding FBFs. We demonstrate our results with three examples.

• Journal of the Korean Data and Information Science Society
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• v.18 no.3
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• pp.833-845
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• 2007

When X and Y have independent exponential distributions, we develop a Bayesian testing procedure for the ratio of two quantiles under reference prior. The noninformative prior such as reference prior is usually improper which yields a calibration problem that makes the Bayes factor to be defined up to a multiplicative constant. So we develop a Bayesian testing procedure based on fractional Bayes factor and intrinsic Bayes factor. We show that the posterior density under the reference prior is proper and propose the Bayesian testing procedure for the ratio of two quantiles using fractional Bayes factor and intrinsic Bayes factor. Simulation study and a real data example are provided.

• Journal of the Korean Data and Information Science Society
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• v.19 no.2
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• pp.621-634
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• 2008

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.

• Journal of the Korean Data and Information Science Society
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• v.19 no.3
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• pp.995-1006
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• 2008

This article deals with the one-sided hypothesis testing problem in inverse Gaussian distribution. We propose Bayesian hypothesis testing procedures for the one-sided hypotheses of the shape parameter under the noninformative prior. 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 hypothesis testing procedures based on the fractional Bayes factor, the median intrinsic Bayes factor and the encompassing intrinsic Bayes factor under the reference prior. Simulation study and a real data example are provided.

• Journal of the Korean Data and Information Science Society
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• v.18 no.4
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• pp.1191-1203
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• 2007

In this paper, we consider the hypothesis testing for the homogeneity of the shape parameters in the gamma distributions. The noninformative priors such as Jeffreys# prior or reference prior are 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 testing procedure for the homogeneity of the shape parameters based on the fractional Bayes factor and the intrinsic Bayes factor under the reference prior. Simulation study and a real data example are provided.

• Journal of the Korean Data and Information Science Society
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• v.28 no.1
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• pp.217-225
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• 2017

This article deals with the problem of multiple hypothesis testing for the shape parameter in the generalized exponential distribution. We propose Bayesian hypothesis testing procedures for multiple hypotheses of the shape parameter with the noninformative prior. The Bayes factor with the noninformative prior is not well defined. The reason is that the most of the noninformative prior can be improper. Therefore we study the default Bayesian multiple hypothesis testing methods using the fractional and intrinsic Bayes factors with the reference priors. Simulation study is performed and an example is given.

• The Korean Journal of Applied Statistics
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• v.16 no.1
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• pp.141-150
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• 2003

This paper presents the multiple testing method of an autoregressive parameter in stationary AR(1) model using the usual Bayes factor. As prior distributions of parameters in each model, uniform prior and noninformative improper priors are assumed. Posterior probabilities through the usual Bayes factors are used for the model selection. Finally, to check whether these theoretical results are correct, simulated data and real data are analyzed.

• Journal of the Korean Data and Information Science Society
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• v.19 no.4
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• pp.1477-1489
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• 2008

This article deals with the problem of testing whether the effect size in paired study exists. We propose Bayesian hypothesis testing procedures for the effect size in paired study under the noninformative prior. 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 hypothesis testing procedures based on the fractional Bayes factor and the intrinsic Bayes factor under the reference prior. Simulation study and a real data example are provided.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.17 no.4
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• pp.70-75
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• 2009

According to the aviation statistics, tail strike incidents and accidents are cyclic. Although many tail strikes occurred during takeoff, these are less than during landing cases. Many cases are related on human factors. In my opinion it is possible to analyze the causes of takeoff tail strikes to some extent. There are major casual factors of tail strike during takeoff such as; (1) Mis-trimmed horizontal stabilizer (2) premature rotation prior to $V_R$ (3) Excessive pitch up rate during rotation (4) Improper use of the flight director. Among these causes improper use of flight director is excluded in this paper because it is recommended that pilot should use flight director after airborne. So I analyzed the other three causes as following. Firstly, because mis-trimmed stabilizer is related to center of gravity(CG), the relationship between stabilizer and CG is reviewed. Secondly, concerned premature rotation prior to $V_R$ I reviewed the background of rotation speed($V_R$) establishment and analyzed theoretically what speed leads to tail strikes. Thirdly, concerning excessive pitch up rate during rotation I analyzed what excessive pitch up rate can decrease ground clearance while using FDR data.