• The Korean Journal of Applied Statistics
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• v.28 no.1
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• pp.49-60
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• 2015

Various kinds of ordination methods such as correspondence analysis and canonical correspondence analysis are used in community ecology to visualize relationships among species, sites, and environmental variables. Ter Braak (1986), Jackson and Somers (1991), Parmer (1993), compared the ordination methods using eigenvalue and distance graph. However, these methods did not show the relationship between population and biplot because they are only based on surveyed data. In this paper, a method that measures the extent to show population information to biplot was introduced to compare ordination methods objectively.

• The Korean Journal of Applied Statistics
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• v.24 no.3
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• pp.559-566
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• 2011

Biplot is a useful graphical method to explore simultaneously rows and columns of two-way data matrix. In particular, canonical correlation biplot is a method for investigating two sets of variables and observations in canonical correlation analysis graphically. For more than three sets of variables, we can apply the generalized canonical correlation biplot in generalized canonical correlation analysis which is an expansion of the canonical correlation analysis. On the other hand, we consider the set of covariate variables which is affecting the linearly two sets of variables. In this case, if we apply the generalized canonical correlation biplot, we cannot clearly interpret the other two sets of variables due to the effect of the set of covariate variables. Therefor, in this paper, we will apply the partial canonical correlation analysis of Rao (1969) removing the linear effect of the set of covariate variables on two sets of variables. We will suggest the partial canonical correlation biplot for inpreting the partial canonical correlation analysis graphically.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.9
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• pp.1878-1883
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• 2012

Generally, in the underwater target recognition, feature vectors are extracted from the target signal utilizing spatial information according to target shape/material characteristics. And, various signal processing techniques have been studied to extract feature vectors which is less sensitive to the location of the receiver. In this paper, we analyzed the characteristics of synthesized underwater objects using canonical correlation analysis method which is relatively less sensitive to the location of receiver. Canonical correlation analysis is applied to two consecutive backscattered sonar returns at different aspect angles to analyze the correlation characteristics in multi-aspect environment.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.4D
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• pp.569-577
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• 2008

The purpose of this study is focused on the development of compound classification process by mixing multitemporal data and annexing a specific image enhancement technique with a specific image classification algorithm, to gain more accurate land information from satellite imagery. That is, this study suggests the classification process using canonical correlation classification technique after principal component analysis for the mixed multitemporal data. The result of this proposed classification process is compared with the canonical correlation classification result of one date images, multitemporal imagery and a mixed image after principal component analysis for one date images. The satellite images which are used are the Landsat 5 TM images acquired on July 26, 1994 and September 1, 1996. Ground truth data for accuracy assessment is obtained from topographic map and aerial photograph, and all of the study area is used for accuracy assessment. The proposed compound classification process showed superior efficiency to appling canonical correlation classification technique for only one date image in classification accuracy by 8.2%. Especially, it was valid in classifying mixed urban area correctly. Conclusively, to improve the classification accuracy when extracting land cover information using Landsat TM image, appling canonical correlation classification technique after principal component analysis for multitemporal imagery is very useful.

• The Korean Journal of Applied Statistics
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• v.28 no.3
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• pp.485-494
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• 2015

Canonical correspondence analysis is an ordination method used to visualize the relationships among sites, species and environmental variables. However, projection results are fluctuations if the samples slightly change and consistent interpretation on ecological similarity among species tends to be difficult. We use the bootstrap methods for canonical correspondence analysis to solve this problem. The bootstrap method results show that the variations of coordinate points are inversely proportional to the number of observations and coverage rates with bootstrap confidence interval approximates to nominal probabilities.

• Journal of Korean Society of Transportation
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• v.20 no.7
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• pp.5-13
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• 2002

고도의 산업화성장에 따라 도시의 기능이 지역간의 완전분리가 아닌 경제적 사회적 상호 연관성이 점점 증가하고 그 내용도 복잡하고 다양해짐에 따라 이에 대한 체계적인 분석이 필요하게 되었으며, 그에 대한 연구 또한 활발히 진행되고 있다. 그러나 기존에 연구에서 제시하고 있는 각 지역단위별로 취업자수에 대한 고용자수 비율 또는 출근통행의 유출량에 대한 유입량 비율 등의 단순지표를 이용한 지역간의 경제적 의존성을 설명하는 데는 한계가 있다고 할 수 있다. 따라서 본 연구는 지역간의 경제적 연관관계 즉 경제적 의존성을 복합적이고 표준화 할 수 있는 계량치로 추정하기 위해 두 변수 집합간의 연관성을 추정하는데 매우 유용한 분석기법인 정준상관분석 기법을 이용하여 추정하고자 하였다. 이에 수도권 72개존의 출근통행자료을 이용하여 지역간의 경제적 의존성을 측정하였으며, 각 존들로 구성된 지역간의 정준상관계수 및 각 존들의 정준가 중계수를 통해 통계적으로 정산되어진 표준화된 계수를 산출하였다. 그 결과 대존의 경우 경기도와 인천시는 각각 0.9753. 0.2968 정도의 서울에 대한 경제적 의존정도를 보이는 것으로 나타나 서울에 대한 경기도의 경제적 의존성이 높은 것으로 나타났으며, 산출된 정준가중계수를 살펴보면 분당구와 서울시의 중구는 서울에 대한 경기도의 경제적 의존성에 가장 높은 영향을 미친 것으로 나타났으며, 또한 중존에 해당되는 인천의 3개 권역, 경기의 16개 권역의 서울 5개 권역에 대한 경제적 의존성도 분석되었다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.16 no.1
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• pp.75-84
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• 1998

To achieve more accurate information from satellite image data, a research on a technique for mixed pixel ex-traction has been produced. The mixed pixels with only two land covers have been experimented. By analyzing canonical vector in canonical correlation classification, the mixed pixels have been classified. The ratio of the two canonical weighted values-the elements of canonical vector have been used as a threshold to discriminate mixed pixels. In case of the classification for the mixed pixels of bridge and water class in TM data before or after the 1st of September, the threshold for the optimal classification of the mixed pixels is 4.0. That is, if the ratio of the two canonical weighted values is less than 4.0, the pixel is a mixed pixel. Also, using the distribution of canonical weighted values, the constitution percentages of land covers within one mixed pixel can be approximately deducted. The accuracy of mixed pixel extraction for experimental area is 90％ and quite acceptable. Conclusively, a technique for mixed pixel extraction by canonical vector analysis is effective.

• Communications for Statistical Applications and Methods
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• v.19 no.1
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• pp.97-105
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• 2012

The generalized canonical correlation biplot is a 2-dimensional plot to graphically investigate the relationship between more than three sets of variables and the relationship between observations and variables. Recently, Choi and Choi (2010) investigated the relationship physique, physical fitness and basic skill factors of Korea Tennis Association(KTA) players of using this biplot; however we consider the set of covariate variables affecting the linearly on two sets of variables. In this case, if we apply the generalized canonical correlation biplot, we cannot clearly interpret the other two sets of variables due to the effect of the set of covariate variables. Moreover, Yeom and Choi (2011) provided partial canonical correlation analysis that removed the linear effect of the set of covariate variables on two sets of variables. In addition, Procrustes analysis is a useful tool for comparing shape between configurations. In this study, we will investigate the relationship between physical fitness and basic skill factors of KTA players of using a partial canonical correlation biplot and Procrustes analysis. We compare shapes and shape variabilities for the generalized, partial and simple canonical correlation biplots.

• 한국데이터정보과학회:학술대회논문집
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• 2006.11a
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• pp.113-117
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• 2006

우리는 다양한 자료에서 유의미한 정보를 파악하기 위한 방법으로 다변량 분석 방법 중에서 정준판별분석, 로지스틱, 다층퍼셉트론 그리고 의사결정나무를 사용자 편의를 극대화하고 사용이 간단한 비주얼 베이직 6.0을 이용하여 개발하였다.

• The Journal of Engineering Geology
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• v.15 no.4 s.42
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• pp.463-473
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• 2005

Because of using the same rating ranges for every rock types the RMR or the Q-system could not usually consider local geological characteristics They also could not present sufficiently the engineering anisotropy of rocks. The canonical correlation analysis was carried out with 3 kinds of face mapping data obtained from granite, sedimentary rock and phyllite in order to clarify a discrepancy between rock types. According to analysis results, as a type of rocks changes, RM factors have different influences on the total rating of RMR.