• Proceedings of the Korean Reliability Society Conference
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• 2000.11a
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• pp.373-373
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• 2000

Bum-in procedures are developed far limited failure populations in which defective products fail soon after they are put in operation and non-defective ones never fail during the technological life of the products. The situation where products are produced from a production process with variable fraction defective is considered. Bum-in schemes guaranteeing pre-specified outgoing quality of products are derived using the mixed binomial prior distribution for the number of defectives in a batch.

• Journal of the Korean Statistical Society
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• v.24 no.2
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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.

• Communications for Statistical Applications and Methods
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• v.5 no.1
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• pp.145-153
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• 1998

In this paper, a hierarchical Bayesian analysis of a bivariate exponential model is discussed using Gibbs sampler. Parameters and reliability estimators are obtained. A numerical study is provided.

• Smart Structures and Systems
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• v.11 no.1
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• pp.103-122
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• 2013

It is essential to update the model with reflecting observation or inspection data for reliability estimation of existing structures. Authors proposed updated reliability analysis by using Particle Filter. We discuss how to apply the proposed method through numerical examples on reinforced concrete structures after verification of the method with hypothetical linear Gaussian problem. Reinforced concrete structures in a marine environment deteriorate with time due to chloride-induced corrosion of reinforcing bars. In the case of existing structures, it is essential to monitor the current condition such as chloride-induced corrosion and to reflect it to rational maintenance with consideration of the uncertainty. In this context, updated reliability estimation of a structure provides useful information for the rational decision. Accuracy estimation is also one of the important issues when Monte Carlo approach such as Particle Filter is adopted. Especially Particle Filter approach has a problem known as degeneracy. Effective sample size is introduced to predict the covariance of variance of limit state exceeding probabilities calculated by Particle Filter. Its validity is shown by the numerical experiments.

• The Korean Journal of Applied Statistics
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• v.12 no.2
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• pp.405-414
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• 1999

양쪽중단(doubly censored)된 지수분포에서 모수와 신뢰도함수를 계층적 베이지안(hierarchical Bayesian)방법을 이용하여 추정하였다. 베이즈 계산은 깁스표본기법(Gibbs sampler)을 이용하고 또한 완전조건부 분포(full conditional distribution)의 정량화 상수를 모르는 경우에는 적합기각방법(adaptive rejection sampling)을 이용하였다. 그리고 실제자료를 이용하여 분석을 하였다.

• Communications for Statistical Applications and Methods
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• v.2 no.2
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• pp.43-51
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• 1995

For the stress-strengh function, hierarchical Bayes estimations considered under squared error loss and entropy loss. In particular, the desired marginal postrior densities ate obtained via Gibbs sampler, an iterative Monte Carlo method, and Normal approximation (by Delta method). A simulation is presented.

• The KIPS Transactions:PartD
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• v.9D no.3
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• pp.389-398
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• 2002

Software reliability growth models are used in testing stages of software development to model the error content and time intervals between software failures. This paper presents a stochastic model for the software failure phenomenon based on a nonhomogeneous Poisson process(NHPP) and performs Bayesian inference using prior information. The failure process is analyzed to develop a suitable mean value function for the NHPP ; expressions are given for several performance measure. Actual software failure data are compared with several model on the constant reflecting the quality of testing. The performance measures and parametric inferences of the suggested models using Rayleigh distribution and Laplace distribution are discussed. The results of the suggested models are applied to real software failure data and compared with Goel model. Tools of parameter point inference and 95% credible intereval was used method of Gibbs sampling. In this paper, model selection using the sum of the squared errors was employed. The numerical example by NTDS data was illustrated.

• The Journal of Korean Association of Computer Education
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• v.9 no.6
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• pp.11-18
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• 2006

The purpose of this paper is to draw problems from analyzing "General Computer" questions of Career Searching Section in the College Scholastic Ability Test in 2005 and 2006 and to offer some suggestions about them. For the qualitative research, this paper analyzed content validity. For the quantitative research, this paper analyzed item difficulty and item discrimination by using Bayesian 1.0 based on 2-parameter item response model and this paper analyzed item reliability and distracters by using Testan 1.0. By analyzing "General Computer" questions, this paper would like to improve the quality of items and estimate item difficulty. Therefore, "General Computer" questions could be suggested as materials for developing reliable and discriminative questions.

• Communications for Statistical Applications and Methods
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• v.14 no.2
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• pp.389-399
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• 2007

In this paper, Bayes estimates for the parameters k, c and reliability function of the Burr type XII model based on a type II censored samples under asymmetric loss functions viz., LINEX and SQUAREX loss functions are obtained. An approximation based on the Laplace approximation method (Tierney and Kadane, 1986) is used for obtaining the Bayes estimators of the parameters and reliability function. In order to compare the Bayes estimators under squared error loss, LINEX and SQUAREX loss functions respectively and the maximum likelihood estimator of the parameters and reliability function, Monte Carlo simulations are used.

• Nuclear Engineering and Technology
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• v.15 no.1
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• pp.41-49
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• 1983

A computer code, BERD (Bayesian Estimation of Reliability Data), has been developed and tested in order to update the data for the reliability analysis of safety related systems in a specific nuclear power plant. The code has been used to derive the plant-specific data for reliability analysis of the auxiliary feedwater system of a pressurized water reactor. The prior information for components selected was taken from the U.S. Reactor Safety Study, WASH-1400, and the operating experiences from published licensee event reports. The results show that the updated data are well fitted to log-normal distribution curves and the error factors are reduced significantly.