• The Korean Journal of Applied Statistics
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• v.17 no.1
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• pp.49-60
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• 2004

In this paper, when the observations are distributed as inverse gaussian, we developed the noninformative priors for ratio of the parameters of inverse gaussian distribution. We developed the first order matching prior and proved that the second order matching prior does not exist. It turns out that one-at-a-time reference prior satisfies a first order matching criterion. Some simulation study is performed.

• 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.

• The Korean Journal of Applied Statistics
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• v.14 no.2
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• pp.449-462
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• 2001

베이지안 다중 검정방법(multiple hypothesis test)은 여러 통계모형에서 성공적인 결과를 주는 것으로 알려져있다. 일반적으로, 베이지안 가설검정은 고려중인 모형에 대한 사후확률을 계산하여 가장 높은 확률은 갖는 모형을 선택하기 때문에 귀무가설의 기각여부에만 관심을 가지는 고전적인 분산분석 검정과는 달리 좀 더 구체적인 모형을 선택할 수 있는 장점이 있다. 이 논문에서는 독립이면서 로그정규분포를 따르는 K($\geq$3)개 모집단의 모수에 대한 가설 검정방법으로 O’Hagan(1995)이 제안한 부분 베이즈 요인을 이용한 베이지안 방법을 제안한다. 이 때 모수에 대한 사전분포로는 무정보적 사전분포를 사용한다. 제안한 검정 방법의 유용성을 알아보기 위하여 실제 자료의 분석과 모의 실험을 이용하여 고전적인 검정방법과 그 결과를 비교한다.

• Communications for Statistical Applications and Methods
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• v.5 no.2
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• pp.431-437
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• 1998

본 논문의 목적은 계층적 베이즈 일반화 선형모형을 이용하여 경시적 자료를 분석하는 것이다. 구체적으로 계층적 베이즈 변량효과 모형을 소개하고 무정보적 사전분포 하에서 사후분포가 진(proper)인지에 대한 충분조건을 찾는다 또한, 깁스(Gibbs) 표본자를 사용하여 제안된 계층적 베이즈 절차의 수행에 관해 논의한다. 현실자료를 사용하여 제안된 계층적 베이즈 분석을 예시하고, 이에 대응하는 경험적 베이즈 분석과 비교한다.

• Journal of the Korean Data and Information Science Society
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• v.24 no.4
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• pp.689-699
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• 2013

This paper studies the partial credibility application method by assuming the empirical prior or noninformative prior informations in auto insurnace business where intensive rating segmentation is expanded because of premium competition. Expanding of rating factor segmetation brings the increase of pricing cells, as a result, the number of cells for partial credibility application will increase correspondingly. This study is trying to suggest more accurate estimation method by considering the Bayesian framework. By using empirically well-known or noninformative information, inducing the proper posterior distribution and applying the Bayes estimate which is minimizing the error loss into the credibility method, we will show the advantage of Bayesian inference by comparison with current approaches. The comparison is implemented with square root rule which is a widely accepted method in insurance business. The convergence level towarding to the true risk will be compared among various approaches. This study introduces the alternative way of redcuing the error to the auto insurance business fields in need of various methods because of more segmentations.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2009.05a
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• pp.107-113
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• 2009

This paper deals with noninformative priors for such as Jeffres' prior, reference prior and probability matching prior for scale parameter of exponential distribution when the data are collected in multiple step stress accelerated life tests. We find the noninformative priors for this model and show that the reference prior satisfies first order matching criterion. Using artificial data, we perform Bayesian analysis for proposed priors.

• Proceedings of the Korean Statistical Society Conference
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• 2002.11a
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• pp.159-162
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• 2002

일반적으로 p-값은 귀무가설에 의하여 주어지는 통계적 모형과 현재 관측치 사이의 호환성의 측도로써 가장 널리 쓰이는 개념중의 하나로 간주될 수 있다. 이 연구에서는 고전통계학에서의 고전적 p-값에 대응하는 베이즈 관점에서의 베이즈 p-값을 제안하고 그 성질에 대하여 고찰한다.

• Journal of the Korean Data and Information Science Society
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• v.13 no.1
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• pp.67-77
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• 2002

We propose the Bayesian testing for the equality of K-exponential populations means with Type-II censored data. Specially we use the fractional Bayesian factors suggested by O'Hagan (1995) based on the noninformative priors for the parameters. And, we investigate the usefulness of the proposed Bayesian testing procedures via both real data analysis and simulations and compare the classical likelihood ratio(LR) test with the proposed Bayesian test.

• 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 the Korean Data and Information Science Society
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• v.12 no.1
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• pp.51-59
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• 2001

We propose the Bayesian testing for the equality of two Lognormal population means. Specially we use the fractional Bayesian factors suggested by O'Hagan (1995) 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 simulations.