• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.710-714
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• 2006

지역빈도해석기법은 수문학적으로 성질이 유사한 지점을 하나의 군으로 구성한 자료를 이용해서 빈도해석을 하는 기법으로, 지점빈도해석이 가질 수 있는 단점들을 보완하기 위한 방안의 하나로 기대되고 있다. 본 논문은, 지역빈도해석기법을 적용하기 위한 단계중의 하나인 군집해석에 사용되는 변수들을 보다 효율적으로 선택하기 위한 연구로서, 다변량 분석방법인 주성분분석과 요인분석, 그리고, 변수선택을 위한 Procrustes Analysis를 통해서 보다 효율적으로 변수를 선택하는 방법을 제안하기 위한 연구이다.

• Journal of Korean Society of Environmental Engineers
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• v.38 no.2
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• pp.71-78
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• 2016

The study of water environment system in Changnyeong-Haman weir section using a statistical analysis has been conducted. Statistical analyses used in this study were the correlation analysis, the principal components, and the factor analysis. The purpose of the study is to establish better understanding of relationships between water quality factors in the Changnyeong-Haman weir section which can provide useful information to manage Nakdong river. According to correlation analyses on COD and TOC, it revealed that the value of correlation coefficient was 0.844. Furthermore, the results from the principal component analysis categorized the water quality factors into three factor groups, the first principal factor group included COD, TOC, BOD, pH, water temperature (WT). And, it was observed that the concentration of cyanobacteria in the water body decreased, while the concentrations of the diatoms and the green algae increased after the events of rainfall.

• Journal of Bio-Environment Control
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• v.17 no.2
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• pp.124-131
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• 2008

To investigate main air temperature factors correlated to difference of fruit characteristics according to cultivating areas, fruit and air temperature characteristics of eight cultivating areas of 'Fuyu' persimmon were analyzed by principle components and multiple regression analysis. The first principal components extracted from 16 air temperature factors was annual mean temperature, mean temperature during October, annual mean minimum extreme temperature, mean temperature during growing period, and so forth. The second principal components was mean temperature during May and June and so forth. And cumulative contribution was 91.4%. The five of eight cultivating area had clearly the difference of main factors or the correlated direction among cultivating areas. In multiple regression analysis between the extracted main factors and fruit characteristics, fruit hight were highly correlated with mean temperature during growing period ($X_8$) and cumulative temperature ($X_6$), and the regression equation was $Y=150.55-5.375X_8+ 0.014X_6(r^2=0.843)$. Also this regression equation was affected by mean minimum temperature during growing period, cumulative temperature, and mean temperature during August. Fruit diameter was negatively correlated with mean temperature during growing period, flesh browning rate and Hunter a value of peel color were positively correlated with mean minimum temperature during growing period and annual minimum air temperature, respectively.

• Journal of Wetlands Research
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• v.21 no.3
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• pp.215-223
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• 2019

In this study, we analyzed the water quality characteristics of major tributaries of Nakdong River through statistical analysis such as correlation analysis, principal component and factor analysis, and cluster analysis. Organic matter and nutrients are highly correlated, and are high in spring and autumn, and seasonal water quality management is required. Principal component and factor analysis showed that 82% of total variance could be explained by 4 principal components such as organic matter, nutrients, nature, and weather. BOD, COD, TOC, and TP items were analyzed as major influencing factors. As a result of the cluster analysis, the four clusters were classified according to seasonal organic matter and nutrient pollution. Kumho River watershed showed high pollution characteristics in all seasons. Therefore, effective management of water quality in tributary streams requires measures in consideration of spatio-temporal characteristics and multivariate statistical techniques may be useful in water quality management and policy formulation.

• Journal of Navigation and Port Research
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• v.30 no.1 s.107
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• pp.35-43
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• 2006

This study suggests strategies to prevent traffic accidents by utilizing impact factors per each cluster and the typical patterns of 81 cities based on the statistical analysis of the data concerning the TCI which was developed from the partnership of the Traffic Safety Authority and the Green Traffic Movement Corporation in 2002 and 2003. The Principal Component Analysis and Cluster Analysis on impact factors and TCI result in 4 components and 4 clusters. Also as the results of Stepwise Multiple Regression Analysis examining the relationship between impact factors and TCI, R2 values of these models show high to all clusters. According to the results, we suggest strategies to prevent traffic accidents per cluster concretely and it is necessary to analyze how effective the invested facilities are in reducing traffic accidents in the future.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.1
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• pp.173-185
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• 2015

This study aims to investigate the characteristics and types of car accidents and establish a prediction model by analyzing 456 car accidents having occurred in the 11 tunnels in Busan, through statistical analysis techniques. The results of this study can be summarized as below. As a result of analyzing the characteristics of car accidents, it was found that 64.9% of all the car accidents took place in the tunnels between 08:00 and 18:00, which was higher than 45.8 to 46.1% of the car accidents in common roads. As a result of analyzing the types of car accidents, the car-to-car accident type was the majority, and the sole-car accident type in the tunnels was relatively high, compared to that in common roads. Besides, people at the age between 21 and 40 were most involved in car accidents, and in the vehicle type of the first party to car accidents, trucks showed a high proportion, and in the cloud cover, rainy days or cloudy days showed a high proportion unlike clear days. As a result of analyzing the principal components of car accident influence factors, it was found that the first principal components were road, tunnel structure and traffic flow-related factors, the second principal components lighting facility and road structure-related factors, the third principal factors stand-by and lighting facility-related factors, the fourth principal components human and time series-related factors, the fifth principal components human-related factors, the sixth principal components vehicle and traffic flow-related factors, and the seventh principal components meteorological factors. As a result of classifying car accident spots, there were 5 optimized groups classified, and as a result of analyzing each group based on Quantification Theory Type I, it was found that the first group showed low explanation power for the prediction model, while the fourth group showed a middle explanation power and the second, third and fifth groups showed high explanation power for the prediction model. Out of all the items(principal components) over 0.2(a weak correlation) in the partial correlation coefficient absolute value of the prediction model, this study analyzed variables including road environment variables. As a result, main examination items were summarized as proper traffic flow processing, cross-section composition(the width of a road), tunnel structure(the length of a tunnel), the lineal of a road, ventilation facilities and lighting facilities.

• Journal of the Korean Society for Railway
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• v.17 no.5
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• pp.381-389
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• 2014

This research focuses on the current trend of 'Sharing Transportation' to clarify the regional factors having a decisive effect on the use of Car Sharing. To accomplish this, the current research is built a Database of the regional characteristics of Car Sharing spots based on railway stations in Seoul and performed an analysis of the primary regional factors affecting Car Sharing usage. As a result, we found conclusive factors affecting the use of Car Sharing. This research can be utilized for establishing strategies and effective measures to support the use of Car Sharing and sustainable development with respect to issues of motorization.

• Journal of Korean Society of Environmental Engineers
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• v.39 no.11
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• pp.641-649
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• 2017

In the study, the water quality of the Imjin River basin with pollutants of changing characteristics it was determined through statistical analysis, correlation analysis, principle component and factor analysis, and cluster analysis. Among all analyzed data points, the average water quality concentration at the Sincheon 3 site shows high levels of BOD 13.4 mg/L, COD 19.9 mg/L, T-N 11.145 mg/L, T-P 0.336 mg/L, TOC 14.2 mg/L, indicating that Sincheon basin requires intersive water quality management out of the entire drainage basin. The correlational analysis of comprehensive water quality data shows statistically significant correlation between COD, TOC, BOD, T-N water quality factors, as well as finding of high correlation between organic and nutrients. The principal component analysis show that 2 main components being extracted at 81.221% from the measuring station's entire data, while seasonal data show 3 main components being extracted at 96.241%. Factor analysis of the entire data set and the seasonal data identify BOD, COD, T-N, T-P, TOC as the common factors influencing water quality. The spatial and temporal cluster analysis showed 4 groups and 3 groups, respectively, according to seasonal characteristics and land use. By analysing the water quality factors for the Imjin River basins over an 8 year period, with consideration to the spatial and temporal characteristics, this study will become the fundamental analytic data that will help understand the future changes of water quality in the Imjin River basin.

• The Korean Journal of Financial Management
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• v.15 no.1
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• pp.329-350
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• 1998

이 논문에서는 자산의 수익률과 공통요인이 시간가변적 변동성을 갖는 경우의 APT를 검증하고자 시도하였다. 이를 위하여 1980년 1월부터 1995년 12월까지의 17개업종별 포트폴리오 수익률로부터 주성분분석에 의하여 4개의 공통요인을 추출하였다. (이중 첫 번째 요인은 동일가중 시장수익률과 거의 1에 가까운 상관성을 갖고 있으므로, 추출된 첫 번째 요인 대신에 시장수익률을 사용하였다.) 17개 업종별 포트폴리오에 대한 ARCH모형을 추정한 결과, 12개 포트폴리오의 수익률이 조건부 이분산성을 보이고 있다. 또 네 개의 공통요인 중 시장수익률을 포함한 3개의 요인은 뚜렷한 조건부 이분산성을 보이고 있다. 따라서 요인위험--즉, 공통요인에 대한 개별자산의 민감도$({\beta}_{ij})$--은, 개별자산과 공통요인의 상관계수가 일정하다고 가정하여, ARCH모형에 의해 측정된 자산 및 공통요인의 시간가변 표준편차로부터 계산되었다. 이와 같이 계산된 요인위험에 대하여 어느 정도의 위험프리미엄이 주어지고 있는가는 일반화 적률법(GMM)에 의하여 추정하였다. 그 결과, APT의 추정에 사용된 4개의 공통요인 중 시장수익률을 포함한 3개의 요인에 대하여 유의한 위험프리미엄이 추정되었다.

• The Korean Journal of Applied Statistics
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• v.23 no.5
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• pp.967-975
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• 2010

Since the least squares estimation is not appropriate when multicollinearity exists among the regressors of the linear regression model, the principal components regression is used to deal with the multicollinearity problem. This article suggests a new procedure for the selection of suitable principal components. The procedure is based on the condition index instead of the eigenvalue. The principal components corresponding to the indices are removed from the model if any condition indices are larger than the upper limit of the cutoff value. On the other hand, the corresponding principal components are included if any condition indices are smaller than the lower limit. The forward inclusion method is employed to select proper principal components if any condition indices are between the upper limit and the lower limit. The limits are obtained from the linear model which is constructed on the basis of the conjoint analysis. The procedure is evaluated by Monte Carlo simulation in terms of the mean square error of estimator. The simulation results indicate that the proposed procedure is superior to the existing methods.