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The stalactite plot for the detection of multivariate outliers

✍ Scribed by A. C. Atkinson; H.-M. Mulira


Book ID
104641389
Publisher
Springer US
Year
1993
Tongue
English
Weight
678 KB
Volume
3
Category
Article
ISSN
0960-3174

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✦ Synopsis


Detection of multiple outliers in multivariate data using Mahalanobis distances requires robust estimates of the means and covariance of the data. We obtain this by sequential construction of an outlier free subset of the data, starting from a small random subset. The stalactite plot provides a cogent summary of suspected outliers as the subset size increases. The dependence on subset size can be virtually removed by a simulation-based normalization. Combined with probability plots and resampling procedures, the stalactite plot, particularly in its normalized form, leads to identification of multivariate outliers, even in the presence of appreciable masking.


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