• Journal of the Korean Data and Information Science Society
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• v.8 no.1
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• pp.31-39
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• 1997

we shall propose some Bayes estimators and some generalized maximum likelihood estimators for reliability of a two-unit hot standby system with perfect switch based upon a complete sample of failure times observed from the exponential model and compare the peformances of the proposed estimators in terms of mean squared error.

• Communications for Statistical Applications and Methods
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• v.2 no.2
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• pp.52-62
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• 1995

Consider an estimation problem under squared error loss in a family of non-regular densities with both terminals of the support being decreasing functions of an unknown parameter. Using Karlin's(1958) technique, sufficient conditions are given for generalized Bayes estimators to be admissible for estimating an arbitrarily positive, monotone parametric function and then treat some examples which illustrate our results.

• International Journal of Reliability and Applications
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• v.11 no.1
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• pp.23-40
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• 2010

Recently, Zaindin and Sarhan (2009) introduced a new distribution named new generalized Weibull distribution. This paper deals with the problem of estimating the parameters of this distribution in the case where the data is grouped and censored. We use both the maximum likelihood and Bayes techniques. The results obtained are illustrated on a set of real data.

• Journal of the Korean Statistical Society
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• v.22 no.1
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• pp.55-69
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• 1993

Consider the problem of estimating an arbitrary continuous vector function under a weighted quadratic loss in the multiparameter exponential family with the density of the natural form. We first provide, using Blyth's (1951) method, a set of sufficient conditions for the admisibility of (possibly generalized Bayes) estimators and then treat some examples for normal, Poisson, and gamma distributions as applications of the main result.

• Journal of the Korean Data and Information Science Society
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• v.22 no.6
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• pp.1251-1256
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• 2011

Consider a p-variate ($p{\geq}4$) normal distribution with mean ${\theta}$ and identity covariance matrix. Using a simple property of noncentral chi square distribution, the generalized Bayes estimators dominating the Lindley estimator under quadratic loss are given based on the methods of Brown, Brewster and Zidek for estimating a normal variance. This result can be extended the cases where covariance matrix is completely unknown or ${\Sigma}={\sigma}^2I$ for an unknown scalar ${\sigma}^2$.

• Journal of the Korean Statistical Society
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• v.29 no.1
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• pp.95-108
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• 2000

Consider the oblique factor model X=Af＋$\varepsilon$, with defining relation $\Sigma$=Λ$\Phi$Λ'＋Ψ. This paper is concerned with suggesting an optimal Bayes criterion for determining the number of factors in the model, i.e. dimension of the vector f. The use of marginal likelihood as a method for calculating posterior probability of each model with given dimension is developed under a generalized conjugate prior. Then based on an appropriate loss function, a Bayes rule is developed by use of the posterior probabilities. It is shown that the approach is straightforward to specify distributionally and to imploement computationally, with output readily adopted for constructing required cirterion.

• Communications for Statistical Applications and Methods
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• v.29 no.5
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• pp.513-532
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• 2022

In this paper, the use of Bayes factors and the deviance information criterion for model selection are compared in a Bayesian accelerated life testing setup. In Bayesian accelerated life testing, the most used tool for model comparison is the deviance information criterion. An alternative and more formal approach is to use Bayes factors to compare models. However, Bayesian accelerated life testing models with more than one stressor often have mathematically intractable posterior distributions and Markov chain Monte Carlo methods are employed to obtain posterior samples to base inference on. The computation of the marginal likelihood is challenging when working with such complex models. In this paper, methods for approximating the marginal likelihood and the application thereof in the accelerated life testing paradigm are explored for dual-stress models. A simulation study is also included, where Bayes factors using the different approximation methods and the deviance information are compared.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.4
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• pp.805-812
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• 2009

In many intrusion detection applications, n-gram approach has been widely applied. However, n-gram approach has shown a few problems including unscalability and double counting of features. To address those problems, we applied n-gram augmented Naive Bayes with k-truncated suffix tree (k-TST) storage mechanism directly to classify intrusive sequences and compared performance with those of Naive Bayes and Support Vector Machines (SVM) with n-gram features by the experiments on host-based intrusion detection benchmark data sets. Experimental results on the University of New Mexico (UNM) benchmark data sets show that the n-gram augmented method, which solves the problem of independence violation that happens when n-gram features are directly applied to Naive Bayes (i.e. Naive Bayes with n-gram features), yields intrusion detectors with higher accuracy than those from Naive Bayes with n-gram features and shows comparable accuracy to those from SVM with n-gram features. For the scalable and efficient counting of n-gram features, we use k-truncated suffix tree mechanism for storing n-gram features. With the k-truncated suffix tree storage mechanism, we tested the performance of the classifiers up to 20-gram, which illustrates the scalability and accuracy of n-gram augmented Naive Bayes with k-truncated suffix tree storage mechanism.

• Communications for Statistical Applications and Methods
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• v.9 no.2
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• pp.515-520
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• 2002

In general, we use the hierarchical Poisson-gamma model for the Poisson data in generalized linear model. Time effect will be emphasized for the analysis of the observed data to be collected annually for the time period. An extended model with time effect for estimating the effect is proposed. In particularly, we discuss the Quasi likelihood function which is used to numerical approximation for the likelihood function of the parameter.

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1549-1555
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• 2014

Consider a p-variate normal distribution ($p-q{\geq}3$, q = rank($P_V$) with a projection matrix $P_V$). Using a simple property of noncentral chi square distribution, the generalized Bayes estimators dominating the James-Stein estimator shrinking towards projection vectors under quadratic loss are given based on the methods of Brown, Brewster and Zidek for estimating a normal variance. This result can be extended the cases where covariance matrix is completely unknown or ${\sum}={\sigma}^2I$ for an unknown scalar ${\sigma}^2$.