• Communications for Statistical Applications and Methods
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• v.8 no.2
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• pp.427-434
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• 2001

In this paper, we consider the nonparametric Bayesian approach to the multiple comparisons problem for I Poisson populations using Dirichlet process priors. We describe Gibbs sampling algorithm for calculating posterior probabilities for the hypotheses and calculate posterior probabilities for the hypotheses using Markov chain Monte Carlo. Also we provide a numerical example to illustrate the developed numerical technique.

• Communications for Statistical Applications and Methods
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• v.4 no.2
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• pp.435-444
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• 1997

The objective of this study is to investigate the problem of goodness of fit testing based on nonparametric function estimation techniques for the random censorship model. The small and large sample properties of the proposed test, $E_{mn}$, were investigated and it is shown that under the proportional hazard model $E_{mn}$ has higher power compared to the powers of the Kolmogorov -Smirnov, Kuiper, Cramer-von Mises, and analogue of the Cramer-von Mises type test statistic.

• The Korean Journal of Applied Statistics
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• v.6 no.1
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• pp.173-181
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• 1993

Nonparametric empirical Bayes estimation of a distribution function with respect to dirichlet process prior is considered when sample sizes are varying from component to component. Zehnwirth's estimate of $\alpha$(R) is modified to be used in our empirical Bayes problem with non-identical components.

• Communications for Statistical Applications and Methods
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• v.4 no.1
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• pp.177-183
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• 1997

A data-adaptive order selection procedure is proposed for local polynomial nonparametric regression. For each given polynomial order, bias and variance are estimated and the adaptive polynomial order that has the smallest estimated mean squared error is selected locally at each location point. To estimate mean squared error, empirical bias estimate of Ruppert (1995) and local polynomial variance estimate of Ruppert, Wand, Wand, Holst and Hossjer (1995) are used. Since the proposed method does not require fitting polynomial model of order higher than the model order, it is simpler than the order selection method proposed by Fan and Gijbels (1995b).

• Journal of the Korean Data and Information Science Society
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• v.18 no.4
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• pp.1145-1155
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• 2007

In this paper, we consider the permutation tests for the multivariate data under the two-sample problem setting. We review some testing procedures, which are parametric and nonparametric and compare them with the permutation ones. Then we consider to try to apply the permutation tests to the multivariate data having the continuous and discrete components together by choosing some suitable combining function through the partial testing. Finally we discuss more aspects for the permutation tests as concluding remarks.

• Journal of Korean Society for Quality Management
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• v.25 no.1
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• pp.173-181
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• 1997

A modified periodic inspection policy is examined. It is troublesome to know the life distribution and burdensome to compute an optimum planned inspection time numerically as well. A nonparametric a, pp.oximation is used so that equations for the optimum inspection time are expressed as closed forms. To show that the a, pp.oximation can be used in practice, simulations are conducted in the case of Weibull failure times.

• Journal of Korean Society for Quality Management
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• v.23 no.2
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• pp.91-102
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• 1995

For two independent random variables X and Y, the functional R=Pr[X>Y] is of practical importance in reliability. X can be interpreted as the strength of a component subjected to a stress Y, and R is the component's reliability. In this paper nonparametric approach to estimation of R based on censored observations in the strength variables is analyzed and compared by simulations in the moderate sample sizes.

• Journal of the Korean Data and Information Science Society
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• v.12 no.1
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• pp.135-142
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• 2001

A multivariate statistic based on interdirection is proposed for detecting dependence among many vectors. The asymptotic distribution of the proposed statistic is derived under the null hypothesis of independence. Also we find the asymptotic distribution under the alternatives contiguous to the null hypothesis, which is needed for later use of computing relative efficiencies.

• Communications of the Korean Mathematical Society
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• v.19 no.2
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• pp.345-354
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• 2004

Boente and Fraiman [2] studied robust nonparametric estimators for regression or autoregression problems when the observations exhibit serial dependence. They established strong consistency of two families of M-type robust equivariant estimators for $\phi$-mixing processes. In this paper we extend their results to weaker $\alpha$$alpha$-mixing processes.

• Bulletin of the Korean Mathematical Society
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• v.57 no.1
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• pp.51-68
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• 2020

In this paper, the author considers the nonparametric regression model with negatively orthant dependent random variables. The wavelet procedures are developed to estimate the regression function. For the wavelet estimator of unknown function g(·), the almost sure consistency is derived and the complete consistency is established under the mild conditions. Our results generalize and improve some known ones for independent random variables and dependent random variables.