• The Korean Journal of Applied Statistics
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• v.11 no.2
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• pp.233-246
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• 1998

We made a sample design for next 5 years, based on the population as of 1995, for livestock statistics. In the sample design, we used the stratified one stage sampling method where the sample size depends on the prefixed coefficient of variation. In stratifying the population, we considered the complete linkage method, and decided the number of strata to be the one which yields the minimum sample size. We listed here some difficulties we had for the better sample design in the future.

• The Korean Journal of Applied Statistics
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• v.7 no.1
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• pp.131-140
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• 1994

In order to find the identification function from data and to apply the identification function for the pattern classification, we consider the existing problem of the number of patterns in such data. In this paper, a new criteria for the identification of Gaussaian mixture distribution could be established as a charateristic of the sample variance, which is a bootstrap estimate of the sample variance. We examine the properties and fittness of the criteria through a large scale of computer simulations.

• The Mathematical Education
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• v.45 no.3 s.114
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• pp.315-318
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• 2006

In this paper we present the simple updating formulas for a sum of product and a sum of cross product when a new value is added on or a specific value is eliminated from the original data. The sample variance and correlation for the new data set are derived by new computing formulas. Any statistic which is a function of the sum of product and a sum of cross product also can be updated by proposed method even though the original data is not available.

• Journal of the Korean Data and Information Science Society
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• v.27 no.1
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• pp.111-120
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• 2016

In usual, the discontinuous variance function was estimated nonparametrically using a kernel type estimator with data sets split by an estimated location of the change point. Kang et al. (2000) proposed the Gasser-$M{\ddot{u}}ller$ type kernel estimator of the discontinuous regression function using the adjusted observations of response variable by the estimated jump size of the change point in $M{\ddot{u}}ller$ (1992). The adjusted observations might be a random sample coming from a continuous regression function. In this paper, we estimate the variance function using the Nadaraya-Watson kernel type estimator using the adjusted squared residuals by the estimated location of the change point in the discontinuous variance function like Kang et al. (2000) did. The rate of convergence of integrated squared error of the proposed variance estimator is derived and numerical work demonstrates the improved performance of the method over the exist one with simulated examples.

• Journal of the Korean Data and Information Science Society
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• v.24 no.3
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• pp.477-485
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• 2013

In this paper, we consider the sample sizes required for each group in independent two sample test of normal populations when both the type I error and type II error probabilities are specified with sample sizes and variances being possibly different. We derived the sample sizes and the power of the tests, and implement them by web programing. The result is available over the world wide web. Further, we also provide the power calculations and have them available on the web.

• The Korean Journal of Applied Statistics
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• v.20 no.3
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• pp.605-618
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• 2007

Adaptive sampling design is the selection procedure which depends on observed values of the variable of interest. It is the method which could be applied to the rare and unapproachable population. Adaptive cluster sampling strategies are more efficient than simple random sampling on equivalent sample size. Adaptive sampling with new estimators through the Rao-blackwell method have lower variance than Horvitz-Thompson (HT) and Hansen-Hurwitz (HH). Also, to determine suitable sample size, it was used expected sample and the method finding appropriate sample size by changing initial sample size were studied.

• Proceedings of the Korean Association for Survey Research Conference
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• 2001.11a
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• pp.77-85
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• 2001

In this paper we study the calibration estimator and its variance estimator for the population total using a bootstrap method according to the levels of an auxiliary information having strong correlation with an interested variable in nonresponse situation. At this point, we find tire calibration estimator in case of auxiliary information for population and sample, and then we drive the bootstrap variance estimator of it. By simulation study we compare the efficiencies with the Taylor and Jackknife variance estimators.

• 한국데이터정보과학회:학술대회논문집
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• 2006.04a
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• pp.7-15
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• 2006

이번 연구의 목적은 평균 대신에 중앙값을 이용한 관리도를 제시하며 관리한계선을 결정하기 위하여 표본 중앙값에 대한 근사분포에서 bootstrap 방법을 이용한 분산을 추정하는 연구를 한다.

• Proceedings of the Korean Society for Quality Management Conference
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• 2006.04a
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• pp.523-532
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• 2006

• Journal of Korean Society of Transportation
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• v.9 no.2
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• pp.127-134
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• 1991

본 논문의 목적은 교통망 분석에 있어서 중요한 그러나 흔희 발생하지 않는 사건의 발생확률을 추정하는 방법론 개발에 있다. 예를 들어, 안정적(stable) 교통망에서 일시적인 혼잡현상이 발생할 확률을 씨뮬레이숀을 통해 추정하는 방법에 관한 것이다. 이 분야에서 활발한 연구([3], [12]) 가 있어 왔으나 개괄적(Heuristic) 방법에 제한되어 있었다. 본 논문은 위 문제에 대하여 포괄적(unified)이며 이론적인 방법론을 제시하였다. 이를 위해 대 분산이론(Large Deviation Theory)과 중요표본추출(Importance Sampling)기법이 이용되었으며 예로서 사용된 망은 두개의 구간이 이어진 교통망이다. 부수적으로 혼잡현상의 가장 대표적 형태를 구하는 방법이 제시되었다.