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OPTIMAL AND ROBUST DETECTION OF MULTIVARIATE OUTLIERS FOR ELLIPTICALLY CONTOURED DISTRIBUTION
作者姓名:WANG  Xueren  PAN  Jianxin
作者单位:Institute of Applied Statistics,Yunnan University,Kunming 650091,China
摘    要:The outlier problem for a multivariate elliptically contoured distribu-tion's random sample with mean slippage is defined and the likelihood ratio test ofthe null hypothesis,in which there are no outliers,versus the alternative hypothesis,in which some outliers are present,is derived.We show that the testing problemis invariant under a group of affine transformations and obtain the maximal in-variance which is equivalent to the likelihood ratio testing statistic.Furthermore,the non-null and null density distribution functions of the likelihood ratio testingstatistic are derived.We find that the null density distribution function of thetesting statistic is robust and the density distribution function is a monotonicallikelihood ratio function of the maximal invariance.Therefore,the likelihood ratiotest is a uniformly most powerful invariant test among the group of affine transfor-mations.In the last section,we give an example of detecting multivariate outliersin elliptically contoured distribution.


OPTIMAL AND ROBUST DETECTION OF MULTIVARIATE OUTLIERS FOR ELLIPTICALLY CONTOURED DISTRIBUTION
WANG Xueren PAN Jianxin.OPTIMAL AND ROBUST DETECTION OF MULTIVARIATE OUTLIERS FOR ELLIPTICALLY CONTOURED DISTRIBUTION[J].Journal of Systems Science and Complexity,1992(2).
Authors:WANG Xueren PAN Jianxin
Abstract:The outlier problem for a multivariate elliptically contoured distribu-tion's random sample with mean slippage is defined and the likelihood ratio test ofthe null hypothesis,in which there are no outliers,versus the alternative hypothesis,in which some outliers are present,is derived.We show that the testing problemis invariant under a group of affine transformations and obtain the maximal in-variance which is equivalent to the likelihood ratio testing statistic.Furthermore,the non-null and null density distribution functions of the likelihood ratio testingstatistic are derived.We find that the null density distribution function of thetesting statistic is robust and the density distribution function is a monotonicallikelihood ratio function of the maximal invariance.Therefore,the likelihood ratiotest is a uniformly most powerful invariant test among the group of affine transfor-mations.In the last section,we give an example of detecting multivariate outliersin elliptically contoured distribution.
Keywords:Outliers  elliptically contoured distributions  likelihood ratio criteria  uniformly most powerful invariant test
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