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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국자료분석학회 Journal of The Korean Data Analysis Society Journal of The Korean Data Analysis Society 제7권 제6호
- 발행연도
- 2005.1
- 수록면
- 1,935 - 1,943 (9page)
이용수
초록· 키워드
오류제보하기
Kim(2000) proposed two meaningful decompositions of the squared Mahalanobis distance to uncover the sources of outlyingness for multivariate observations. The decompo- sition is useful for identifying some component variables dominating the Mahalanobis distance. In this article we considered the distributions for components of the decompo- sitions and we showed that each component follows a normal distribution and the random vector consisting of two components is a multivariate normal distribution. We may detect outliers using the cut-off values. We proposed a graphical tool for detecting multivariate outliers through one-sheet figure. It is a very useful result to analyze the outlyingness for high dimensional data. Two illustrative examples are given.
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등록된 정보가 없습니다.
참고문헌 (6)
참고문헌 신청
/ 1972 / Multivariate Analysis
/ 1972 / residuals and outlier detection with multiresponse data : 81 ~ 124
/ 1987 / A new graphical method for detecting single and multiple outliers in univariate and multivariate data : 153 ~ 162
/ 1990 / Journal of the American Statistical Association : 633 ~ 651
/ 2000 / Multivariate outliers and decompositions of Mahalanobis distance 29 : 1511 ~ 1526
/ 1972 / residuals and outlier detection with multiresponse data : 81 ~ 124
/ 1987 / A new graphical method for detecting single and multiple outliers in univariate and multivariate data : 153 ~ 162
/ 1990 / Journal of the American Statistical Association : 633 ~ 651
/ 2000 / Multivariate outliers and decompositions of Mahalanobis distance 29 : 1511 ~ 1526
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