• 한국산업융합학회 논문집
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• 제24권3호
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• pp.307-313
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• 2021

In this study, the comparative analysis, among the design standard value of distribution power, the calculated value from the measurement data of strand and the empirical data of the distribution line itself, have been performed for the elastic coefficients and linear expansion coefficients of distribution line conductors. The empirical values of elastic coefficients were lower about 10.6%(892kgf/mm²) than those of the design standard value of the distribution power and there were a little difference between the empirical values of linear expansion coefficients and the design standard value of the distribution power. From the above results, it could be concluded that the empirical values of conductor characteristics should be used in the dip design and installation of distribution line.

• 응용통계연구
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• 제30권4호
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• pp.579-590
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• 2017

다변량 자료의 분포함수를 알고 있거나 추정할 수 있으면 다변량 경험분포함수를 정의할 수 있다. 이변량인 경우에는 계단그림과 분위그림을 사용하여 경험분포함수를 시각화할 수 있는데, 본 연구에서는 다변량인 경우에 경험분포함수를 정사각형에 표현할 수 있는 다변량 경험분포그림을 제안하였다. 여러 종류의 다변량 정규분포와 특정한 분포에 대하여 경험분포그림을 작성하고 특징을 살펴보니, 다양한 분산공분산행렬을 포함된 분포함수에 따라 경험분포그림이 민감하게 반응하는 것을 탐색하였다. 이를 바탕으로 경험분포함수를 구할 때 가정한 다변량 분포함수의 적합도 검정방법을 제안하였다. 대표적인 다섯 종류의 적합도 검정방법을 사용하고, 다양한 분포함수들에 대하여 각각의 검정통계량 기각역을 구하였다. 본 연구에서 얻은 기각역은 문헌에서 구할 수 있는 기각역과 큰 차이가 없음을 발견하였다. 그러므로 본 연구에서 제안한 적합도 검정방법을 문헌에서 제시한 기각역으로 쉽게 사용할 수 있는 장점이 있다.

• 대한수학회지
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• 제36권5호
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• pp.923-943
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• 1999

In this paper we consider functionals of the empirical age distribution of supercritical Bellman-Harris processes. Let f : R+ longrightarrow R be a measurable function that integrates to zero with respect to the stable age distribution in a supercritical Bellman-Harris process with no extinction. We present sufficient conditions for the asymptotic normality of the mean of f with respect to the empirical age distribution at time t.

• 한국해양공학회:학술대회논문집
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• 한국해양공학회 2006년 창립20주년기념 정기학술대회 및 국제워크샵
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• pp.367-372
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• 2006

If the sea is narrowband, the Rayleigh distribution introduced by Longuet-Higgins can be used for the individual wave height distribution. However the Rayleigh distribution over-predicts the probability of high waves. Longuet-Higgins introduced alternative form of the Rayleigh distribution with an empirical constant. The wave height distribution can be fitted well by one parameter Rayleigh distribution with a proper choice of the empirical constant. The empirical constant is the ratio of the significant wave height based the time domain analysis and the spectral analysis. Here we examine wave data which contain extreme waves. Once again we confirmed that extreme wave height distribution can be modelled well by a modified Rayleigh distribution.

• Journal of the Korean Statistical Society
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• 제33권4호
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• pp.353-365
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• 2004

In this paper, we define the weighted U-empirical process for simple linear model and show the weak convergence to a Gaussian process under some conditions. Then we illustrate the usage of our result with examples. In the appendix, we derive the variance of the weighted U-empirical distribution function.

• Communications for Statistical Applications and Methods
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• 제3권3호
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• pp.215-223
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• 1996

By using Tukey's generalized lambda distribution, appoximate posterior density is derived under the Bayes-empirical Bayes model. The sensitivity of posterior distribution to the hyperprior distribution is examined by using Tukey's generalized lambda distriburion which approximate many well-knmown distributions. Based upon Monte Varlo simulation studies it can be said that posterior distribution is sensitive to the cariance of the prior distribution and to the symmetry of the hyperprior distribution. Also posterior distribution is approximately obtained by using the following methods : Lindley method, Laplace method and Gibbs sampler method.

• Journal of the Korean Data and Information Science Society
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• 제15권3호
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• pp.625-632
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• 2004

We consider the empirical Bayes confidence intervals that attain a specified level of EB coverage for the scale parameter in the Burr distribution under type II censoring data. Also, we compare the coverage probabilities and the expected confidence interval lengths for these confidence intervals through simulation study.

• 한국데이터정보과학회:학술대회논문집
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• 한국데이터정보과학회 2002년도 춘계학술대회
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• pp.51-73
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• 2002

Empirical likelihood ratio method is a new technique in nonparametric inference developed by A. Owen (1988, 2001). Sometimes empirical likelihood has difficulties to define itself. As such a case in point, we discuss the way to define a modified empirical likelihood for the location of symmetry using well-known points of symmetry as a side conditions. The side condition of symmetry is defined through a finite subset of the infinite set of constraints. The modified empirical likelihood under symmetry studied in this paper is to construct a constrained parameter space $\theta+$ of distributions imposing known symmetry as side information. We show that the usual asymptotic theory (Wilks theorem) still hold for the empirical likelihood ratio on the constrained parameter space and the asymptotic distribution of the empirical NPMLE of difference of two symmetric points is obtained.

• Journal of the Korean Data and Information Science Society
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• 제25권1호
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• pp.237-244
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• 2014

It is known that the dierence in the length between two location parameters of two random variables is equivalent to the difference in the area between two cumulative distribution functions. In this paper, we suggest two applications by using the difference of distribution functions. The first is that the difference of expectations of a certain function of two continuous random variables such as the differences of two kth moments and two moment generating functions could be defined by using the difference between two univariate distribution functions. The other is that the difference in the volume between two empirical bivariate distribution functions is derived. If their covariance is estimated to be zero, the difference in the volume between two empirical bivariate distribution functions could be defined as the difference in two certain areas.

• Journal of the Korean Data and Information Science Society
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• 제27권5호
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• pp.1399-1412
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• 2016

We compare many normality tests consisting of different sources of information extracted from the given data: Anderson-Darling test, Kolmogorov-Smirnov test, Cramervon Mises test, Shapiro-Wilk test, Shaprio-Francia test, Lilliefors, Jarque-Bera test, D'Agostino' D, Doornik-Hansen test, Energy test and Martinzez-Iglewicz test. For the purpose of comparison, those tests are applied to the various types of data generated from skewed distribution, unsymmetric distribution, and distribution with different length of support. We then summarize comparison results in terms of two things: type I error control and power. The selection of the best test depends on the shape of the distribution of the data, implying that there is no test which is the most powerful for all distributions.