• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.10 no.2
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• pp.41-47
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• 2006

The Renewal process and the Non-homogeneous Poisson process (NHPP) process are probably the most popular models for describing the failure pattern of repairable systems. But both these models are based on too restrictive assumptions on the effect of the repair action. For these reasons, several authors have recently proposed point process models which incorporate both renewal type behavior and time trend. One of these models is the Modulated Power Law Process (MPLP). The Modulated Power Law Process is a suitable model for describing the failure pattern of repairable systems when both renewal-type behavior and time trend are present. In this paper we propose Bayes estimation of the next failure time after the system has experienced some failures, that is, Mean Time Between Failure for the MPLP model. Numerical examples illustrate the estimation procedure.

• Journal of KSNVE
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• v.6 no.3
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• pp.305-315
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• 1996

Present paper aims at the correlation of modal characteristics of folding fin between test and analysis using an optimization theory. Folding fin is composed of a movable fin, a base fin, and many functional components related to the folding mechanism. Joint parts of folding fin in FEM are initially modeled as rigid elements resulting some difference between test and analysis in modal characteristics. Therefore, some equivalent springs representing joint parts are introduced to improve the FEM model. The springs were set as design variables, while the frequency difference between test and analysis was set as the object function. Bayesian procedure was ujsed for the minimization.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.11
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• pp.103-111
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• 2002

In this study, the natural flaws in welding parts are classified using the signal pattern classification method. The storage digital oscilloscope including FFT function and enveloped waveform generator is used and the signal pattern recognition procedure is made up the digital signal processing, feature extraction, feature selection and classifier design. It is composed with and discussed using the distance classifier that is based on euclidean distance the empirical Bayesian classifier. feature extraction is performed using the class-mean scatter criteria. The signal pattern classification method is applied to the signal pattern recognition of natural flaws.

• Communications for Statistical Applications and Methods
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• v.24 no.5
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• pp.457-480
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• 2017

We develop a random partition procedure based on a Dirichlet process prior with Laplace distribution. Gibbs sampling of a Laplace mixture of linear mixed regressions with a Dirichlet process is implemented as a random partition model when the number of clusters is unknown. Our approach provides simultaneous partitioning and parameter estimation with the computation of classification probabilities, unlike its counterparts. A full Gibbs-sampling algorithm is developed for an efficient Markov chain Monte Carlo posterior computation. The proposed method is illustrated with simulated data and one real data of the energy efficiency of Tsanas and Xifara (Energy and Buildings, 49, 560-567, 2012).

• Communications for Statistical Applications and Methods
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• v.7 no.2
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• pp.541-548
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• 2000

Various statistical methods for assessment of equivalence in average bioavailabilities have been developed under the assumption that the intra-subject variabilities for the test and reference formulations are the same. Without the assumption, assessing the equivalence in average bioavailabilites does not imply that the two formulations are therapeutically equivalent and exchangeable. The most commonly used test procedure for equality of variabilites in 2$\times$2 crossover experiment is the so called Pitman-Morgan's adjusted F test based on the model without carryover effects (Chow and Liu(1992)). In this paper, a Bayesian method based on the Intrinsic Bayes Factor is proposed, which can be applied to the model with carryover effects.

• The Korean Journal of Applied Statistics
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• v.2 no.2
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• pp.27-35
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• 1989

This article deals with statistical inference on Interleukin-2 titer of which the clinical applications to cancer immunotherapy and some immunodeficiency diseases have been widely tried. A Linear model and the Bayesian approach are used to explain the bioassay which performs the measurements of IL-2 activity from an patient and an inference procedure including confidence intervals for the IL-2 titer of the patient through comparision with the Standard IL-2 is suggested and a real case of example is illustrated.

• Journal of the Korean Data and Information Science Society
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• v.18 no.2
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• pp.553-560
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• 2007

In this paper, we consider two components system which lifetimes have Freund's bivariate exponential model with equal failure rates. We propose Bayesian multiple comparisons procedure for the failure rates of I Freund's bivariate exponential populations based on Dirichlet process priors(DPP). The family of DPP is applied in the form of baseline prior and likelihood combination to provide the comparisons. Computation of the posterior probabilities of all possible hypotheses are carried out through Markov Chain Monte Carlo(MCMC) method, namely, Gibbs sampling, due to the intractability of analytic evaluation. The whole process of multiple comparisons problem for the failure rates of bivariate exponential populations is illustrated through a numerical example.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.304-309
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• 2003

In this study, natural flaws in welding parts are classified using the signal pattern classification method. The storage digital oscilloscope including FFT function and enveloped waveform generator is used and the signal pattern recognition procedure is made up the digital signal processing, feature extraction, feature selection and classifier design. It is composed with and discussed using the distance classifier that is based on euclidean distance the empirical Bayesian classifier. Feature extraction is performed using the class-mean scatter criteria. The signal pattern classification method is applied to the signal pattern recognition of natural flaws.

• Journal of Korean Society for Quality Management
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• v.8 no.2
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• pp.15-22
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• 1980

This paper deals with the problem of determining a minimum cost sampling inspection plan for a single destructive testing by attribute. The cost for inspection lot is constructed by following three cost factors: (1) cost of inspection, (2) cost of accepted defective, (3) cost of rejected lot Using Hald's Bayesian approach in a single non-destructive testing, procedure's for finding the minimum cost single destructive sampling inspection plan by attribute are given. Assuming the uniform distribution as a prior-distribution and using numerical analysis by computer, a minimum cost single destructive sampling inspection plan by attribute for several lot sizes, unit cost, destructive testing cost, and salvage cost is given.

• Journal of the Korean Data and Information Science Society
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• v.28 no.6
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• pp.1557-1564
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• 2017

We take genomic sequences of high-dimensional low sample size (HDLSS) without ordering of response categories into account. When constructing an appropriate test statistics in this model, the classical multivariate analysis of variance (MANOVA) approach might not be useful owing to very large number of parameters and very small sample size. For these reasons, we present a pseudo marginal model based upon the Gini-Simpson index estimated via Bayesian approach. In view of small sample size, we consider the permutation distribution by every possible n! (equally likely) permutation of the joined sample observations across G groups of (sizes $n_1,{\ldots}n_G$). We simulate data and apply false discovery rate (FDR) and positive false discovery rate (pFDR) with associated proposed test statistics to the data. And we also analyze real SARS data and compute FDR and pFDR. FDR and pFDR procedure along with the associated test statistics for each gene control the FDR and pFDR respectively at any level ${\alpha}$ for the set of p-values by using the exact conditional permutation theory.