• 한국통계학회:학술대회논문집
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• 한국통계학회 2003년도 추계 학술발표회 논문집
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• pp.15-19
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• 2003

In this paper, we develop the Jeffreys' prior, reference priors and the probability matching priors for the intraclass correlation coefficient of a symmetric normal distribution. We next verify propriety of posterior distributions under those noninformative priors. We examine whether reference priors satisfy the probability matching criterion.

• Journal of the Korean Data and Information Science Society
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• 제28권4호
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• pp.875-888
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• 2017

The Rayleigh distribution has been commonly used in life time testing studies of the probability of surviving until mission time. We focus on a reliability function of the Rayleigh distribution and deal with prior distribution on R(t). This paper is an effort to obtain Bayes estimators of rayleigh distribution with three different prior distribution on the reliability function; a noninformative prior, uniform prior and inverse gamma prior. We have found the Bayes estimator and predictive density function of a future observation y with each prior distribution. We compare the performance of the Bayes estimators under different sample size and in simulation study. We also derive the most plausible region, prediction intervals for a future observation.

• Journal of the Korean Data and Information Science Society
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• 제17권4호
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• pp.1329-1341
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• 2006

When X and Y have independent gamma distributions, we consider the testing problem for two gamma means. We propose a solution based on a Bayesian model selection procedure to this problem in which no subjective input is considered. The reference prior is derived. Using the derived reference prior, we compute the fractional Bayes factor and the intrinsic Bayes factors. The posterior probability of each model is used as a model selection tool. Simulation study and a real data example are provided.

• Journal of the Korean Statistical Society
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• 제32권4호
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• pp.411-423
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• 2003

In this paper we develop a method for calculating a probability that a particular generalized variance is the smallest of all the K multivariate normal generalized variances. The method gives a way of comparing K multivariate populations in terms of their dispersion or spread, because the generalized variance is a scalar measure of the overall multivariate scatter. Fully parametric frequentist approach for the probability is intractable and thus a Bayesian method is pursued using a variant of weighted Monte Carlo (WMC) sampling based approach. Necessary theory involved in the method and computation is provided.

• Journal of the Korean Data and Information Science Society
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• 제13권2호
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• pp.217-226
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• 2002

In this paper, we derive noninformative priors for the ratio of failure rates in exponential model. A class of priors is found by matching the coverage probabilities of one-sided Baysian credible interval with the corresponding frequentist coverage probabilities. And we prove that the noninformative prior matches the alternative coverage probabilities and is a HPD matching prior up to the second order. Finally, we provide simulated freqentist coverage probabilities under the derived noninformative prior for small samples.

• Journal of the Korean Data and Information Science Society
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• 제26권1호
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• pp.243-253
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• 2015

In this paper, we develop the noninformative priors for the common shape parameter of several inverse Gaussian distributions. Specially, we want to develop noninformative priors which satisfy certain objective criterion. The probability matching priors and reference priors of the common shape parameter will be developed. It turns out that the second order matching prior does not exist. The reference priors satisfy the first order matching criterion, but Jeffrey's prior is not the first order matching prior. We showed that the proposed reference prior matches the target coverage probabilities in a frequentist sense through simulation study, and an example based on real data is given.

• 한국신뢰성학회지:신뢰성응용연구
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• 제17권3호
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• pp.188-196
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• 2017

Purpose: The purpose of this research is to determine optimal replacement age using non-informative prior information and Bayesian method. Methods: We propose a novel approach using Bayesian method to determine the optimal replacement age in block replacement policy by defining the prior probability with data on failure time and repair time. The Marcov Chain Monte Carlo simulation is used to investigate the asymptotic distribution of posterior parameters. Results: An optimal replacement age of block replacement policy is determined which minimizes cost and nonoperating time when no information on prior distribution of parameters is given. Conclusion: We find the posterior distribution of parameters when lack of information on prior distribution, so that the optimal replacement age which minimizes the total cost and maximizes the total values is determined.

• 지구물리와물리탐사
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• 제10권4호
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• pp.293-298
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• 2007

암반등급 평가를 위한 물리탐사 자료의 복합해석에 관한 새로운 방안을 제시하고자 한다. 본 연구에서는 시추공이 없는 지점에서의 암반등급을 추정하기 위해 직접적으로 RQD (Rock Quality Designation)값을 지정하는 방식을 이용하지 않는다. 대신 시추공 자료를 보완하는 탄성파 속도와 전기비저항 탐사 결과를 복합하여 특정 RQD 값의 확률적 분포를 추정한다. 우선 시추공에서 확보한 RQD 값에 대해 지구통계학적 지시자 크리깅을 수행하고, 탄성파 속도와 전기비저항 자료에 대해서는 보조 자료를 활용한 지시자 크리깅을 수행하여 각각에 대한 확률분포를 구성하였다. 이러한 확률 분포들에 대해 permanence ratio 법칙에 근거한 자료 통합을 수행하였다. 이와 같이 확률적으로 획득된 암반등급 평가 결과는 다양하게 이용될 수 있는데, 본 논문에서는 실제와 다르게 등급 평가가 이루어질 수 있는 가능성에 대한 활용 방안도 함께 제안하였으며, 이는 대상 구간에 대한 의사결정 시스템에 이용될 수 있음을 제시하였다.

• Journal of the Korean Statistical Society
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• 제29권1호
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• pp.17-27
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• 2000

In this paper, we develop noninformative priors that are used for estimating the reliability of stress-strength system under the Burr-type X model. 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 as well as the Jeffreys prior are the second order matching prior. The propriety of posterior under the noninformative priors is proved. The frequentist coverage probabilities are investigated for samll samples via simulation study.

• 응용통계연구
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• 제15권2호
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• pp.405-414
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• 2002

반복이 같은 이원배치 혼합효과 분산분석모형에서 무정보 사전분포를 이용하여 오차분산을 추정하는 문제를 생각하고자 한다. 먼저 무정보 사전분포로 제프리스사전분포, 준거 사전분포 그리고 확률일치 사전분포를 유도하고 이들 각각의 사전분포들에 대하여 주변사후분포를 제시하였다. 끝으로 실제 자료를 근거로 오차분산의 주변사후밀도함수에 대한 그래프와 오차분산에 대한 신용구간들을 구하고 이 구간들을 비교한다.