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A Robust Test for Location Parameters in Multivariate Data
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 Title & Authors
A Robust Test for Location Parameters in Multivariate Data
So, Sun-Ha; Lee, Dong-Hee; Jung, Byoung-Cheo;
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This work propose a robust test for location parameters in multivariate data based on MVE and MCD with the affine equivariance and the high-breakdown properties. We consider the hypothesis testing satisfying high efficiency and high test power simultaneously to bring in the one-step reweighting procedure upon high-breakdown estimators, which generally suffer from the low efficiency and, as a result, usually used only in the exploratory analysis. Monte Carlo study shows that the suggested method retains nominal significance levels and higher testing power without regard to various population distributions than a Hotelling`s test. In an example, a data set containing known outliers does not make an influence toward our proposal, while it renders a Hotelling`s useless.
High-breakdown estimation;minimum covariance determinant;minimum volume ellipsoid;outliers;reweighting;spatial median;
 Cited by
붓스트랩을 활용한 최적 절사공간중위수 추정량,이동희;정병철;

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