• Communications for Statistical Applications and Methods
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• 제7권2호
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• pp.403-414
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• 2000

A diagnostic tool for testing homogeneity for random effects is proposed in unbalanced linear mixed model based on score statistic. The finite sample behavior of the test statistic is examined using Monte Carlo experiments examine the chi-square approximation of the test statistic under the null hypothesis.

• 한국전자통신학회논문지
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• 제9권8호
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• pp.883-888
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• 2014

시뮬레이션은 현대의 복잡한 환경에서 효율적인 의사 결정을 위한 도구로서 폭넓게 사용되고 있다. 하지만, 대부분은 결과의 분석 보다는 시뮬레이션 모델의 개발 및 수행에 중점을 두고 있다. 본 논문에서는 시뮬레이션 모델링은 물론 결과의 분석도 중요하고 체계적으로 진행되어야 한다는 점을 강조하고, 이를 위하여 통계분석과 다양한 데이터 조작 및 그래픽 기능을 가진 R을 사용하여 이윤 최적화 시뮬레이션에 대한 모델링과 결과 데이터의 조작 및 다양한 그래픽을 사용한 분석 작업을 수행하여 유용성을 입증하였다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.455-457
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• 2003

Diverse researches are working moving objects. The most important activities in a moving object database system are query and analysis of spatio -temporal data providing decision-making and problem solving support. Traditional spatial database query language and tools are inappropriate of the real world entities. This paper presents a spatio-temporal query and analysis tool with visual environment. It provides effective, interactive and user-friendly as well as statistic analysis. The moving objects database system stores plentiful moving objects data and performs spatio-temporal and nonspatio-temporal queries.

• Communications for Statistical Applications and Methods
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• 제25권4호
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• pp.373-383
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• 2018

The spatial scan statistic is a widely used method to detect spatial clusters. The method imposes a large number of scanning windows with pre-defined shapes and varying sizes on the entire study region. The likelihood ratio test statistic comparing inside versus outside each window is then calculated and the window with the maximum value of test statistic becomes the most likely cluster. The results of cluster detection respond sensitively to the shape and the maximum size of scanning windows. The shape of scanning window has been extensively studied; however, there has been relatively little attention on the maximum scanning window size (MSWS) or maximum reported cluster size (MRCS). The Gini coefficient has recently been proposed by Han et al. (International Journal of Health Geographics, 15, 27, 2016) as a powerful tool to determine the optimal value of MRCS for the Poisson-based spatial scan statistic. In this paper, we apply the Gini coefficient to normal-based spatial scan statistics. Through a simulation study, we evaluate the performance of the proposed method. We illustrate the method using a real data example of female colorectal cancer incidence rates in South Korea for the year 2009.

• 응용통계연구
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• 제31권6호
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• pp.811-823
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• 2018

호텔링 $T^2$ 통계량에 근거한 다변량 관리도는 공정의 이상상태를 식별하는 통계적 공정관리의 강력한 도구 중 하나이다. 다수의 품질 특성치를 동시에 모니터링하는데 사용된다. $T^2$ 관리도를 통해 이상신호가 탐지된다는 것은 평균 벡터의 변화가 있다는 것을 의미하게 된다. 그러나, 이러한 다변량 통계량의 신호는 이상신호에 대한 원인을 식별하기 어렵게 한다. 이 논문에서는 $T^2$ 통계량을 서로 독립인 항으로 분해한 Mason, Young, Tracy (MYT) 분해에 기반한 원인 식별 방법들을 살펴본다. 또한, R 소프트웨어를 사용하여 사례분석을 하고, 모의실험을 통해 각 절차의 성능을 비교 평가해보고자 한다.

• 한국실내디자인학회논문집
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• 제16권2호
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• pp.314-321
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• 2007

The statistical method of human sensibility ergonomics is widely used for analyzing interior design because it has standard processes and it can help to get quantifiable results. However applying this method demands repeated intense work and great time and effort is required. In this study, a tool applying Web and virtual reality techniques for statistical human sensibility ergonomic interior design analysis is proposed and the key parts of the tool including database and interface are implemented. The database contains the sensibility adjective table and the physical interior design factor table for analyzing the relationship between human sense and physical design factors. Interface of the tool is implemented using Web technologies, so testers can evaluate interior design samples via standard Web browsers. The 3D control which is an important component of the interface is also implemented. Employing the suggested tool can reduce effort and time for evaluating human sense in Interior design field.

• Communications for Statistical Applications and Methods
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• 제17권1호
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• pp.117-126
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• 2010

Clinical researchers often analyze survival data as binary outcomes using the logistic regression method. This paper examines the information loss resulting from analyzing survival time as binary outcomes. We first demonstrate that, under the proportional hazard assumption, this binary discretization does result in a significant information loss. Second, when fitting a logistic model to survival time data, researchers inadvertently use the maximal statistic. We implement a numerical study to examine the properties of the reference distribution for this statistic, finally, we show that the logistic regression method can still be a useful tool for analyzing survival data in particular when the proportional hazard assumption is questionable.

• 품질경영학회지
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• 제26권1호
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• pp.108-125
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• 1998

The EWMA(Exponentially Weighted Moving Average) has recently received a great deal of attention in the quality control literature as a process monitoring tool on the shop floor of manufacturing industires, since it is easy to plot, to interpret, and its control limits are easy to obtain. Most a, pp.ications of the EWMA for process monitoring have concentrated on the problem of detecting shifts of a process mean and a process standard deviation with ARL(Average Run Length) properties. But there may be the necessity of controlling linearity on product quality such as the correlation coefficient to the process operator. Control managers may want to protect the increase of a process correlation coefficient value, such as 0, between two variables of interest. However, there are few studies concerned on this part. Therefore, we propose EWMA models for a process correlation coefficient using two transformed statistics, T-statistic and (Fisher's) Z-statistic. We also present some results of simulation by SAS/IML and compare two models.

• 대한토목학회논문집
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• 제29권2B호
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• pp.163-171
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• 2009

수문시계열 분석과 예측을 위하여 통상적으로 기존의 선형적인 모형들을 이용하여 왔다. 그러나 최근 자연현상이나 수문시계열의 패턴 그리고 변동성에 비선형구조가 존재하고 있다는 것이 입증되고 있다. 따라서 기존의 선형적인 방법들에 의한 시계열분석이나 예측은 비선형 시스템에 대해서 적절하지 않을 것이다. 최근, 시계열의 비선형성 구조를 판단하기 위해 카오스 이론을 토대로 한 상관적분으로부터 BDS(Brock-Dechert-Scheinkman) 통계 기법이 유도되었다. BDS 통계는 시스템의 비선형구조와 무작위성 구조를 구별하는데 매우 효과적으로 이용되어 오고 있다. 또한 DVS(Deterministic Versus Stochastic) 알고리즘은 카오스와 추계학적 시스템을 구별하고 예측하는데 주로 이용되어 왔다. 그러나 본 연구에서는 DVS 알고리즘에 의해 시계열의 비선형성을 판별할 수 있음을 보이고자 한다. 따라서 본 연구에서는 추계학적 시계열과 수문학적 시계열들의 비선형성을 검사하고자 한다. ARMA 모형과 TAR(Threshold autoregressive) 모형으로부터로 발생시킨 추계학적 시계열, 미국 유타주 GSL 체적자료, 미국 플로리다 주 St. Johns 강 Cocoa 지점의 유출량 자료, 소양강 댐 일 유입량 자료 등의 수문시계열에 대해 비선형성 분석을 수행하고 그 결과를 비교하였다. 분석결과 BDS 통계가 선형 및 비선형 시계열을 구분하는데 매우 강력한 도구임을 보였고, DVS 알고리즘 또한 시계열의 비선형성을 구별하는데 효과적으로 이용될 수 있음을 보였다.

• Smart Structures and Systems
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• 제14권3호
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• pp.377-395
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• 2014

Vibration-based fault detection and condition monitoring of rotating machinery, using statistical process control (SPC) combined with statistical pattern recognition methodology, has been widely investigated by many researchers. In particular, the discrete wavelet transform (DWT) is considered as a powerful tool for feature extraction in detecting fault on rotating machinery. Although DWT significantly reduces the dimensionality of the data, the number of retained wavelet features can still be significantly large. Then, the use of standard multivariate SPC techniques is not advised, because the sample covariance matrix is likely to be singular, so that the common multivariate statistics cannot be calculated. Even though many feature-based SPC methods have been introduced to tackle this deficiency, most methods require a parametric distributional assumption that restricts their feasibility to specific problems of process control, and thus limit their application. This study proposes a nonparametric multivariate control chart method, based on multiscale wavelet scalogram (MWS) features, that overcomes the limitation posed by the parametric assumption in existing SPC methods. The presented approach takes advantage of multi-resolution analysis using DWT, and obtains MWS features with significantly low dimensionality. We calculate Hotelling's $T^2$-type monitoring statistic using MWS, which has enough damage-discrimination ability. A bootstrap approach is used to determine the upper control limit of the monitoring statistic, without any distributional assumption. Numerical simulations demonstrate the performance of the proposed control charting method, under various damage-level scenarios for a bearing system.