• Magazine of korean Tunnelling and Underground Space Association
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• v.4 no.4
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• pp.86-94
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• 2002

• Bulletin of the Korean Chemical Society
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• v.17 no.2
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• pp.120-123
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• 1996

• Communications for Statistical Applications and Methods
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• v.14 no.1
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• pp.195-203
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• 2007

In this paper we propose support vector quantile regression (SVQR) for randomly right censored data. The proposed procedure basically utilizes iterative method based on the empirical distribution functions of the censored times and the sample quantiles of the observed variables, and applies support vector regression for the estimation of the quantile function. Experimental results we then presented to indicate the performance of the proposed procedure.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.395-398
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• 2005

Genetic association case-control studies using DNA pools are efficient ways of detecting association between a marker allele and disease status. DNA pooling is an efficient screening method for locating susceptibility genes associated with the disease. However, DNA pooling is efficient only when allele frequency estimation is done precisely and accurately. Through the evaluation of empirical type I errors and empirical powers by simulation, we will evaluate the methods that correct for preferential amplification of nucleotides when estimating the allele frequency of single-nucleotide polymorphisms.

• Journal of Korean Society for Quality Management
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• v.23 no.3
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• pp.45-56
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• 1995

The method of lot by lot quality protection for sampling inspection by variables is widely used in quality control. In case of sampling inspection being done repeatedly, one can use the information from the previous sampling inspection to improve current estimates. This article shows that empirical Bayes estimator is superior to the usual sample mean in repeated sampling inspection by variables.

• Proceedings of the Korean Statistical Society Conference
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• 2003.05a
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• pp.191-197
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• 2003

This paper considers the independence test for two stationary infinite order autoregressive processes. For a test, we follow the empirical process method devised by Hoeffding (1948) and Blum, Kiefer and Rosenblatt (1961), and construct the Cram${\acute{e}}$r-von Mises type test statistics based on the least squares residuals. It is shown that the proposed test statistics behave asymptotically the same as those based on true errors.

• Communications for Statistical Applications and Methods
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• v.8 no.1
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• pp.219-227
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• 2001

Another approach (multi-parameter measurement method) of interlaboratory studies of test methods is presented. When the unrestricted normal likelihood for the fixed latent variable model is unbounded, we propose a me쇙 of restricting the parameter space by formulating realistic alternative hypothesis under which the likelihood is bounded. A simulation study verified the claim of conservatism of level of significance based on assumptions about central chi-square distributed test statistics and on Bonferroni approximations. We showed a randomization approach that furnished empirical significance levels would be better than a Bonferroni adjustment.

• Journal of the Korea Society for Simulation
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• v.10 no.2
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• pp.25-32
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• 2001

The Multiple Recursive Generator(MRG) has been considered by many scholars as a very good random number generator. For the long period md excellent statistical properties, the method of the combination with random number generators is used. In this paper, we thought the two-combined MRGs. Using the frequency and serial test, and runs test, we studied the importance of the initial seeds likewise other random number generators.

• Journal of the Korean Data and Information Science Society
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• v.17 no.1
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• pp.221-231
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• 2006

A chi-squared test of multivariate normality is suggested which is oriented for detecting deviations from elliptical symmetry. We derive the limiting distribution of the test statistic via a central limit theorem on empirical processes. A simulation study is conducted to study the accuracy of the limiting distribution in finite samples. Finally, we compare the power of our method with those of other popular tests of multivariate normality under a non-normal distribution.

• Journal of the Korean Data and Information Science Society
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• v.24 no.4
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• pp.885-893
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• 2013

This paper considers Bayes estimations of the small area means under Fay-Herriot model with measurement errors. We provide empirical Bayes predictors of small area means with the corresponding jackknifed mean squared prediction errors. Also we obtain hierarchical Bayes predictors and the corresponding posterior standard deviations using Gibbs sampling. Numerical studies are provided to illustrate our methods and compare their eciencies.