A ROBUST BIPLOT

被引:11
作者
DAIGLE, G [1 ]
RIVEST, LP [1 ]
机构
[1] UNIV LAVAL, DEPT MATH & STAT, QUEBEC CITY G1K 7P4, QUEBEC, CANADA
来源
CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE | 1992年 / 20卷 / 03期
关键词
BIPLOT; HUBER ESTIMATORS; MULTIVARIATE M-ESTIMATORS; OUTLIERS; PRINCIPAL-COMPONENT ANALYSIS; PROCRUSTREE ROTATIONS; SINGULAR-VALUE DECOMPOSITION;
D O I
10.2307/3315312
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
This paper introduces a robust biplot which is related to multivariate M-estimates. The n x p data matrix is first considered as a sample of size n from some p-variate population, and robust M-estimates of the population location vector and scatter matrix are calculated. In the construction of the biplot, each row of the data matrix is assigned a weight determined in the preliminary robust estimation. In a robust biplot, one can plot the variables in order to represent characteristics of the robust variance-covariance matrix: the length of the vector representing a variable is proportional to its robust standard deviation, while the cosine of the angle between two variables is approximately equal to their robust correlation. The proposed biplot also permits a meaningful representation of the variables in a robust principal-component analysis. The discrepancies between least-squares and robust biplots are illustrated in an example.
引用
收藏
页码:241 / 255
页数:15
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