• Communications for Statistical Applications and Methods
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• v.2 no.2
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• pp.221-226
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• 1995

본 연구는 붓스트랩에 의한 U-통계량의 분산추정방법을 제안하고, 추정량의 일치성을 증명하였다. 결과적으로 붓스트랩 추정량으로 표준화한 U-통계량의 값이 표준정규분포에 근사함을 보였다. 또한 실제적인 비모수검정에서 이를 응용하여 검정력과 특성을 연구하였다.

• The Korean Journal of Applied Statistics
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• v.12 no.1
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• pp.97-107
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• 1999

프로파일 분석은 반복측정 자료를 분석하는데 있어서 널리 사용되는 다변량 분석모형이다. 프로파일 분석에서는 처리 그룹간의 비교와 반응 프로파일의 평행성 검정을 위해서 4가지 검정통계량이 널리 사용되고 있다. 이들 검정통계량은 Wilks의 통계량($\Lambda$), Pillai's Trace 통계량(V), Hotelling-Lawley Trace 통계량(U), Roy's Maximum Root 통계량($\Theta$ )이다. 그 동안 이들 통계량들을 비교하기 위한 여러 연구가 있었지만 주로 일반적인 다변량 분산분석 모형에 근거한 비교였다. 본 논문에서는 자료가 반복측정 자료이고 우리의 관심이 프로파일 분석에 있을 때에 이 4가지 통계량의 비교에 초점을 맞추었다.

• The Korean Journal of Applied Statistics
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• v.32 no.6
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• pp.879-887
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• 2019

We construct a procedure to test the stochastic order of two samples of interval-valued data. We propose a test statistic that belongs to a U-statistic and derive its asymptotic distribution under the null hypothesis. We compare the performance of the newly proposed method with the existing one-sided bivariate Kolmogorov-Smirnov test using real data and simulated data.

• The Korean Journal of Applied Statistics
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• v.29 no.1
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• pp.75-83
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• 2016

We propose methodology to analyze the dynamic mechanisms of financial market contagion under market integration using a biological contagion analytical approach. We employ U-statistic to measure market integration, and a dynamic model based on an error correction mechanism (single equation error correction model) and latent factor model to examine market contagion. We also use quantile regression and Wald-Wolfowitz runs test to test market contagion. This methodology is designed to effectively handle heteroscedasticity and correlated errors. Our simulation results show that the single equation error correction model fits well with the linear regression model with a stationary predictor and correlated errors.

• Proceedings of the Korean Statistical Society Conference
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• 2005.05a
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• pp.245-250
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• 2005

보통 생태학 분야 등에 적용될 수 있는 적응집락추출계획(adaptive cluster sampling plan)을 수정하여, 표본의 크기 면에서 더 효율적인 Jumped 및 일반화 적응집락추출계획을 제안하였다. 이러한 계획 하에서 Hansen-Hurwitz(HH)와 Horvitz-Thompson (HT) 추정량으로 모수를 추정하였다. 제안한 새로운 계획들을 시뮬레이션을 통하여 기존의 계획과 비교하였다.

• The Korean Journal of Applied Statistics
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• v.15 no.1
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• pp.21-32
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• 2002

We searched out in the votes data of the State of Florida at presidential election 2000. We used a multivariate regression analysis. We got there were several outliers including Palm Beach County. It means that we should analyze the number of disqualified ballots which were double-punched as well as the votes, to insist the " Butterfly Ballot" made Palm Beach outlier.

• Journal of the Korean Statistical Society
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• v.4 no.1
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• pp.9-17
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• 1975

A, B 두 요인의 영향을 받고 있다고 생각되는 rc개 측정치가 있고 이것이 다음과 같이 $r\timesc$ 이차분류표로 정리되었다고 하자. 여기에서 $$y_{ij} = \mu + \alpha_i + \beta_j + \epsilon_{ij}$$ 와 같은 가법모형을 생각한다. 그리고 $\epsilon_{ij}$는 잔여항으로써 평균이 0, 분산이 $\sigma^2$인 정규분포를 한다고 가정하는 것이 보통이다. 또 이것은 모수모형인 경우 $E(y_{ij}) = \mu + \alpha_i + \beta_i, v(y_{ij}) = \sigma^2$임을 의미하는 것으로 생각된다. 그러나 자료에 따라서는 위에서와 같은 가법적 모형을 적용한다는 것이 적당하지 못한 경우가 있다.

• The Korean Journal of Applied Statistics
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• v.15 no.1
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• pp.45-55
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• 2002

The 2-level rotation design based on 3 rotation groups is discussed in view of Monthly Retail Trade Survey conducted by the Bureau of Census in U.S., and composite estimators for population characteristics are concerned. The generalized composite estimators and the recursive composite estimators are presented at 2-level rotation design with design gap and variance formulas for the composite estimators are provided. Also under the response variability related with covariance structure and correlation structure from repeated response, relative efficiencies of the composite estimators are compared.

• Journal of the Korean Data and Information Science Society
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• v.27 no.5
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• pp.1193-1201
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• 2016

In epidemiology or etiology, we are often interested in identifying areas of elevated risk, so called, hot spot or cluster. Many existing clustering methods only tend to a result if there exists any clustering pattern in study area. Recently, however, lots of newly introduced clustering methods can identify the location, size, and shape of clusters and test if the clusters are statistically significant as well. In this paper, one of most commonly used clustering methods, scan statistic, and its implementation SaTScan software, which is freely available, will be introduced. To exemplify the usage of SaTScan software, we used cancer data from the SEER program of National Cancer Institute of U.S.A.We aimed to help researchers and practitioners, who are interested in spatial cluster detection, using female lung cancer mortality data of the SEER program.

• Communications for Statistical Applications and Methods
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• v.19 no.3
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• pp.345-358
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• 2012

In a parametric sample selection model, the distribution assumption is critical to obtain consistent estimates. Conventionally, the normality assumption has been adopted for both error terms in selection and main equations of the model. The normality assumption, however, may excessively restrict the true underlying distribution of the model. This study introduces the $S_U$-normal distribution into the error distribution of a sample selection model. The $S_U$-normal distribution can accommodate a wide range of skewness and kurtosis compared to the normal distribution. It also includes the normal distribution as a limiting distribution. Moreover, the $S_U$-normal distribution can be easily extended to multivariate dimensions. We provide the log-likelihood function and expected value formula based on a bivariate $S_U$-normal distribution in a sample selection model. The results of simulations indicate the $S_U$-normal model outperforms the normal model for the consistency of estimators. As an empirical application, we provide the sample selection model for car ownership and a car expense relationship.