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Unmasking Multiple Outliers in Multivariate Data
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 Title & Authors
Unmasking Multiple Outliers in Multivariate Data
Yoo Jong-Young;
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We proposed a procedure for detecting of multiple outliers in multivariate data. Rousseeuw and van Zomeren (1990) have suggested the robust distance by using the Resampling Algorithm. But are based on the assumption that X is in the general position.(X is said to be in the general position when every subsample of size p+1 has rank p) From the practical points of view, this is clearly unrealistic. In this paper, we proposed a computing method for approximating MVE, which is not subject to these problems. The procedure is easy to compute, and works well even if subsample is singular or nearly singular matrix.
Mahalanobis distances;Minimum volume ellipsoid;Masking effects;Swamping effects;Resampling algorithm;
 Cited by
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