• Journal of the Korean Statistical Society
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• 제28권4호
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• pp.503-513
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• 1999

The Bayes factor for the identification of stationary ARM(p,q) models is exactly computed using the Monte Carlo method. As priors are used the uniform prior for (\ulcorner,\ulcorner) in its stationarity-invertibility region, the Jefferys prior and the reference prior that are noninformative improper for ($\mu$,$\sigma$\ulcorner).

• Journal of the Korean Data and Information Science Society
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• 제17권2호
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• pp.559-568
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• 2006

In this paper, we develop the noninformative priors for the linear mixed models when the parameter of interest is the ratio of variance components. We developed the first and second order matching priors. We reveal that the one-at-a-time reference prior satisfies the second order matching criterion. It turns out that the two group reference prior satisfies a first order matching criterion, but Jeffreys' prior is not first order matching prior. Some simulation study is performed.

• 한국산업정보학회:학술대회논문집
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• 한국산업정보학회 1999년도 춘계학술대회 발표논문집
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• pp.191-197
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• 1999

In this paper, we develop noninformative priors that are used for estimating the reliability of stress-strength system under the Burr-type X distribution. A class of priors is found by matching the coverage probabilities of one-sided Bayesian credible interval with the corresponding frequentist coverage probabilities. It turns out that the reference prior is a first order matching prior. The propriety of posterior under matching prior is provided. The frequentist coverage probabilities are given for small samples.

• Journal of the Korean Data and Information Science Society
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• 제27권3호
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• pp.835-844
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• 2016

We develop the testing procedures about the homogeneity of the shape parameters of several inverse Gaussian distributions in our paper. We propose default Bayesian testing procedures for the shape parameters under the reference priors. The Bayes factor based on the proper priors gives the successful results for Bayesian hypothesis testing. For the case of the lack of information, the noninformative priors such as Jereys' prior or the reference prior can be used. Jereys' prior or the reference prior involves the undefined constants in the computation of the Bayes factors. Therefore under the reference priors, we develop the Bayesian testing procedures with the intrinsic Bayes factors and the fractional Bayes factor. Simulation study for the performance of the developed testing procedures is given, and an example for illustration is given.

• Journal of the Korean Data and Information Science Society
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• 제21권6호
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• pp.1327-1335
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• 2010

In this paper, we want to develop objective priors for the common location parameter in two half-t distributions with unequal scale parameters. The half-t distribution is a non-regular class of distribution. One can not develop the reference prior by using the algorithm of Berger of Bernardo (1989). Specially, we derive the reference priors and prove the propriety of joint posterior distribution under the developed priors. Through the simulation study, we show that the proposed reference prior matches the target coverage probabilities in a frequentist sense.

• Journal of the Korean Data and Information Science Society
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• 제28권1호
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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.

• 응용통계연구
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• 제16권1호
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• pp.141-150
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• 2003

본 논문은 베이즈인자(Bayes factor)를 이용하여 정상(stationary) AR(1)모형의 자기회귀계수에 대해 다중검정하는 방법을 제시한다. 모수들에 대한 사전분포로는 무정보 사전분포(noninformative prior distribution)를 가정한다. 이러한 경우에 통상적으로 사용되는 베이즈인자를 근사없이 정확히 계산하여 각 모형에 대한 사후확률(posterior probability)을 얻는다. 최종적으로 모의실험 자료 및 실제 자료에 적용하여 이론의 결과가 잘 부합되는지를 검토한다.

• Journal of the Korean Data and Information Science Society
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• 제11권2호
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• pp.269-277
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• 2000

독립이면서 로그정규분포를 따르는 두 모집단의 평균 차이에 대한 검정으로 Berger와 Pericchi(1996, 1998)가 제안한 내재적 베이즈 요인(intrinsic Bayes factor)을 이용한 베이지안 방법을 제안한다. 이 때 모수에 대한 사전분포로는 무정보적 사전분포(noninformative prior)를 사용한다. 제안한 검정 방법의 유용성을 알아보기 위해 실제 자료의 분석과 모의실험을 이용하여 고전적인 검정 방범과 그 결과를 비교한다.

• 한국데이터정보과학회:학술대회논문집
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• 한국데이터정보과학회 2005년도 춘계학술대회
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• pp.135-144
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• 2005

In this paper, we develop the noninformative priors for the exponential models when the parameter of interest is the difference of two means. We develop the first and second order matching priors. We reveal that the second order matching priors do not exist. It turns out that Jeffreys' prior does not satisfy a first order matching criterion. The Bayesian credible intervals based on the first order matching meet the frequentist target coverage probabilities much better than the frequentist intervals of Jeffreys' prior.

• Journal of the Korean Data and Information Science Society
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• 제16권4호
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• pp.1067-1078
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• 2005

In this paper, we develop the noninformative priors for the exponential models when the parameter of interest is the difference of two means. We develop the first and second order matching priors. We reveal that the second order matching priors do not exist. It turns out that Jeffreys' prior does not satisfy the first order matching criterion. The Bayesian credible intervals based on the first order matching meet the frequentist target coverage probabilities much better than the frequentist intervals of Jeffreys' prior.