• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2010년도 추계학술대회
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• pp.27-33
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• 2010

The paper proposes the guidelines of application and interpretation for quality and reliability methodologies using deductive or inductive reasoning. The research also reviews Bayesian quality and reliability tools by deductive prior function and inductive posterior function.

• 응용통계연구
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• 제13권1호
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• pp.189-196
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• 2000

포아송 분포에서 일반적으로 공액 사전 분포를 이용하여 사후확률의 수학적 계산이 간편하도록 한다. 그러나 모수 집합의 제한적 조건 때문에 비공액 사전 분포를 이용할 수 도 있다. 비공액 사전분포의 사용은 사후분포의 형태가 일상적인 분포집합의 형태를 갖지 않으므로 모형의 가정에 따라서 복잡한 구조를 갖을 수 도 있다. 특히 포아송-로그정규분포 모형에서의 모수 추정문제를 몬테 칼로방법을 이용하여 추정하고자 할 때 필요한 완전한 조건부 분포의 형태는 잘 알려진 분포의 형태를 갖지 않는다. 본 논문에서는 계층적 구조를 갖는 포아송-로그정규분포 모형에 대하여 고찰하고 추정에 있어서 잠재적 변수를 활용하여 필요한 난수발생이 쉽도록 하는 방법에 대하여 알아보았다.

• Journal of the Korean Statistical Society
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• 제25권4호
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• pp.577-588
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• 1996

The Bayes factor provides a possible hierarchical Bayesian approach for studying the change point problems. A hypothesis for testing change versus no change is considered using predictive distributions. When the underlying distribution is in one-parameter exponential family with conjugate priors, Bayes factors are investigated to the hypothesis above. Finally one example is provided .

• Communications for Statistical Applications and Methods
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• 제8권1호
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• pp.87-96
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• 2001

We consider the empirical Bayes estimation problems with the binomial and normal components when the prior distributions are unknown but are assumed to be in certain families. There may be the families of all distributions on the parameter space or subfamilies such as the parametric families of conjugate priors. We treat both cases and establish the asymptotic optimality for the corresponding decision procedures.

• 한국콘텐츠학회논문지
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• 제20권6호
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• pp.1-8
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• 2020

빅데이터 분석에서 텍스트 데이터의 활용이 증가하고 있다. 따라서 텍스트 데이터의 분석 기법에 관한 많은 연구가 이루어지고 있다. 본 논문에서는 텍스트 데이터로부터 추출된 키워드 데이터의 분석을 위하여 공액사전분포 기반의 베이지안 학습 방법이 연구된다. 베이지안 통계학은 기존의 데이터에 새로운 데이터가 추가될 때마다 모수를 갱신하는 데이터 학습을 제공하기 때문에 시간에 따라 대용량의 데이터가 생성 및 추가되는 빅데이터 환경에서 효율적인 방법을 제공한다. 제안 방법의 성능과 적용 가능성을 보이기 위하여 실제 특허 빅데이터를 전처리하여 구축된 정형화된 키워드 데이터를 분석하는 사례연구를 수행한다.

• Journal of applied mathematics & informatics
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• 제6권2호
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• pp.589-598
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• 1999

Classification errors are included in sampling -with -re-placement model where items are sampled from a Bernoulli process. Bayesian imperfect inspection model is considered. In addition con-jugate prior and predctive densities for imperfect inspection model are obtained.

• Journal of the Korean Statistical Society
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• 제24권2호
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• pp.313-335
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• 1995

Suppose that we have $k(k \geq 2)$ populations (or systems), say $\pi_1, \cdots, \pi_k$, to be tested. Under the type-II censored testing without replacement we consider the problem of estimating the unknown parameters of interests and the reliability for a given time t for each population. Also we compare the perfomances of the proposed Bayes estimators with another estiamtors under the Jeffrey-type noninformative prior distribution.

• 한국항해학회지
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• 제17권1호
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• pp.91-98
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• 1993

This paper presents a class of Bayes estimation of component steady-state availability . Throughout this paper, we will denote the mean time between failure and the mean time between repair by MTBF and MTBR respectively. In section 2 , we investigated Bayes estimation of the steady-state availability for noninformative prior density function and in section 3, we compute Bayes estimation for conjugate prior density function.

• 대한안전경영과학회지
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• 제13권1호
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• pp.195-202
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• 2011

The study interprets each of three classification models based on Bath-Tub Failure Rate (BTFR), Extreme Value Distribution (EVD) and Conjugate Bayesian Distribution (CBD). The classification model based on BTFR is analyzed by three failure patterns of decreasing, constant, or increasing which utilize systematic management strategies for reliability of time. Distribution model based on BTFR is identified using individual factors for each of three corresponding cases. First, in case of using shape parameter, the distribution based on BTFR is analyzed with a factor of component or part number. In case of using scale parameter, the distribution model based on BTFR is analyzed with a factor of time precision. Meanwhile, in case of using location parameter, the distribution model based on BTFR is analyzed with a factor of guarantee time. The classification model based on EVD is assorted into long-tailed distribution, medium-tailed distribution, and short-tailed distribution by the length of right-tail in distribution, and depended on asymptotic reliability property which signifies skewness and kurtosis of distribution curve. Furthermore, the classification model based on CBD is relied upon conjugate distribution relations between prior function, likelihood function and posterior function for dimension reduction and easy tractability under the occasion of Bayesian posterior updating.

• 대한기계학회논문집B
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• 제28권9호
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• pp.1124-1132
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• 2004

The inverse problem of determining unknown inlet temperature in thermally developing, hydrodynamically developed two phase laminar flow in a parallel plate duct is considered. The inlet temperature profile is determined by measuring temperature in the flow field. No prior information is needed for the functional form of the inlet temperature profile. The inverse convection problem is solved by minimizing the objective function with regularization method. The conjugate gradient method as iterative method and the Tikhonov regularization method are employed. The effects of the functional form of inlet temperature, the number of measurement points and the measurement errors are investigated. The accuracy and efficiency of these two methods are compared and discussed.