• The Journal of Engineering Geology
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• v.23 no.4
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• pp.353-361
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• 2013

To analyze the distribution of earthquake-induced strain data in rock masses, statistical analysis was performed on four-directional strain data obtained from a ground movement monitoring system installed in Korea. Strain data related to the 2011 Tohoku-oki earthquake and two aftershocks of >M7.0 in 2011 were used in x-MR control chart analysis, a type of univariate statistical analysis that can detect an abnormal distribution. The analysis revealed different dispersion times for each measurement orientation. In a more comprehensive analysis, the strain data were re-evaluated using multivariate statistical analysis (MSA) considering correlations among the various data from the different measurement orientations. $T_2$ and Q-statistics, based on principal component analysis, were used to analyze the time-series strain data in real-time. The procedures were performed with 99.9%, 99.0%, and 95.0% control limits. It is possible to use the MSA data to successfully detect an abnormal distribution caused by earthquakes because the dispersion time using the 99.9% control limit is concurrent with or earlier than that from the x-MR analysis. In addition, the dispersion using the 99.0% and 95.0% control limits detected an abnormal distribution in advance. This finding indicates the potential use of MSA for recognizing abnormal distributions of strain data.

• The Korean Journal of Applied Statistics
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• v.30 no.4
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• pp.567-578
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• 2017

Grouped multivariate data can be tested for differences between two or more groups using multivariate analysis of variance (MANOVA). However, this method cannot be used if several assumptions of MANOVA are violated. In this case, multidimensional scaling (MDS) and analysis of distance (AOD) can be applied to grouped dissimilarities based on the various distances. A permutation test is a non-parametric method that can also be used to test differences between groups. MDS is used to calculate the coordinates of observations from dissimilarities and AOD is useful for finding group structure using the coordinates. In particular, AOD is mathematically associated with MANOVA if using the Euclidean distance when computing dissimilarities. In this paper, we study the between and within group structure by applying MDS and AOD to the grouped dissimilarities. In addition, we propose a new test statistic using the group structure for the permutation test. Finally, we investigate the relationship between AOD and MANOVA from dissimilarities based on the Euclidean distance.

• Journal of Korean Society of Environmental Engineers
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• v.37 no.3
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• pp.137-144
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• 2015

The purpose of this study is to develop an warning system to detect real-time water quality abnormality using a multivariate statistical approach. In this study, we applied principal component analysis among multivariate data analyses which was used for the correlation between water quality parameters considering the real-time algorithm to determine abnormality in water quality. We applied our approach to real field data and showed the utilization of algorithm for the real-time monitoring to find water quality abnormality. In addition, our approach with Korea Meterological Adminstration database identified heavy rain data due to climate change is one of the most important factors to explain water quality abnormality.

• The Korean Journal of Applied Statistics
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• v.26 no.5
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• pp.747-758
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• 2013

The covariance matrix is important in multivariate statistical analysis and a sample covariance matrix is used as an estimator of the covariance matrix. High dimensional data has a larger dimension than the sample size; therefore, the sample covariance matrix may not be suitable since it is known to perform poorly and event not invertible. A number of covariance matrix estimators have been recently proposed with three different approaches of shrinkage, thresholding, and modified Cholesky decomposition. We compare the performance of these newly proposed estimators in various situations.

• Journal of the Ergonomics Society of Korea
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• v.25 no.1
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• pp.27-33
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• 2006

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.237-240
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• 2017

지구온난화로 인해 세계 곳곳에서 기온상승이 관측되고 있으며, 이는 전지구적 기후시스템의 변화를 보여주는 대표적인 예이다. 온도를 비롯한 강수량, 풍속, 증발량 등의 기상학적, 수문학적 인자들이 각각 서로에게 영향을 주고 받으며 복잡하게 변화할 것이고, 그 변화폭도 점점 커질 것이다. 증발에 영향을 미치는 인자들은 크게 세 가지로 나뉘는데, 태양복사에너지, 온도, 바람, 기압, 습도와 같은 기상학적인자, 증발표면의 특성인자 그리고 수질인자로 분류할 수 있다. 증발에 영향을 주는 인자들은 예전부터 알려져 있지만 이들 간의 복잡한 상호작용에 대해 정확히 이해하기는 쉽지 않다. 본 연구에서는 댐유역의 증발량에 영향을 미치는 기상인자 파악을 위해 2008부터 2016년까지 관측된 낙동강수계 내 안동댐과 남강댐의 기상자료(기온, 강수량, 풍속, 상대습도, 기압, 일사량, 일조시간, 전운량)를 이용한 변화를 분석하였으며, 다변량 통계기법인요인분석을 통해 증발량과 상관성이 높은 인자들을 분류하였다. 안동댐과 남강댐 공통적으로 증발량과 기온, 기압이 같은 요인으로 분류되고 높은 상관성을 보였으며, 강수량, 일조시간, 일사량, 전운량이 같은 요인으로 분류되었다. 국내의 증발량 측정지점에 대한 추가적인 분석과 영향인자를 이용한 다변량회귀식과 인공신경망 통해 증발량 미측정 지점의 증발량 산정이 가능할 것으로 판단된다.

• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1201-1212
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• 2016

Value at Risk (VaR) for market risk management is a favorite method used by financial companies; however, there are some problems that cannot be explained for the amount of loss when a specific investment fails. Conditional Tail Expectation (CTE) is an alternative risk measure defined as the conditional expectation exceeded VaR. Multivariate loss rates are transformed into a univariate distribution in real financial markets in order to obtain CTE for some portfolio as well as to estimate CTE. We propose multivariate CTEs using multivariate quantile vectors. A relationship among multivariate CTEs is also derived by extending univariate CTEs. Multivariate CTEs are obtained from bivariate and trivariate normal distributions; in addition, relationships among multivariate CTEs are also explored. We then discuss the extensibility to high dimension as well as illustrate some examples. Multivariate CTEs (using variance-covariance matrix and multivariate quantile vector) are found to have smaller values than CTEs transformed to univariate. Therefore, it can be concluded that the proposed multivariate CTEs provides smaller estimates that represent less risk than others and that a drastic investment using this CTE is also possible when a diversified investment strategy includes many companies in a portfolio.

• The Korean Journal of Applied Statistics
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• v.26 no.6
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• pp.903-913
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• 2013

Social network services generate a considerable amount of social data every day on personal feelings or thoughts. This social data provides changing patterns of information production and consumption but are also a tool that reflects social phenomenon. We analyze negative emotional words from daily blogs to detect the change in blooger sentiment using multivariate control charts. We used the all the blogs produced between 1 January 2008 and 31 December 2009. Hotelling's T-square control chart control chart is commonly used to monitor multivariate quality characteristics; however, it assumes that quality characteristics follow multivariate normal distribution. The performance of a multivariate control chart is affected by this assumption; consequently, we introduce the support vector data description and its extension (K-control chart) suggested by Sun and Tsung (2003) and they are applied to detect the chage in blogger sentiment.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.359-359
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• 2020

현재 우리나라의 가뭄감시 정보는 기상학적/농업적/수문학적 가뭄이 별도의 지수로 개발되어 다양한 형태의 정보를 생산·제공되고 있다. 각각의 가뭄 지수들 기준 및 특성에 따라 분석되고 있기 때문에 가뭄전문가의 입장에서는 매우 정밀한 가뭄정보를 제공받는 장점이 있는 반면에, 일반 국민들이 가뭄 정보를 받아들이고 이해하는데 어려움이 있어 이를 한눈에 알아볼 수 있는 통합가뭄지도가 필요하며, 통합가뭄도를 제작하기 위해서는 통합가뭄지수가 개발되어야 한다. 본 연구에서는 원격탐사자료를 활용하여 농업적 가뭄지수인 Agricultural Dry Condition Index (ADCI)와 수문학적 가뭄지수인 Water Budget-based Drought Index (WBDI)를 개발하였으며, 기상학적 가뭄지수인 Standardized Precipitation Index (SPI)를 포함하여 기상-농업-수문학적 가뭄지수를 결합한 통합가뭄지수를 산정하였다. 다양한 가뭄지수를 활용하여 개발되었기 때문에 다변량 통계 모형 중 선형 모형인 Principal Component Analysis (PCA)기법과 비선형 모형인 Kernel Entropy PCA, Kernel PCA를 적용하였다. 또한 과거 가뭄사상을 활용하여 산정된 통합가뭄지수 검증을 위해 과거 가뭄사상에 대한 가뭄 발생시기, 심도, 쇠퇴패턴이 양상 평가 및 Intentionally Biased Bootstrap Resampling (IBBR)을 활용한 지수별 민감도 분석을 통해 통합가뭄지수 적용성 평가를 진행하였다.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2012.10a
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• pp.353-354
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• 2012