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Finding an unknown number of multivariate outliers

By Marco Riani, Anthony C. Atkinson and Andrea Cerioli

Abstract

We use the forward search to provide robust Mahalanobis distances to detect the presence of outliers in a sample of multivariate normal data. Theoretical results on order statistics and on estimation in truncated samples provide the distribution of our test statistic. We also introduce several new robust distances with associated distributional results. Comparisons of our procedure with tests using other robust Mahalanobis distances show the good size and high power of our procedure. We also provide a unification of results on correction factors for estimation from truncated samples

Topics: HA Statistics
Publisher: Wiley on behalf of the Royal Statistical Society
Year: 2009
DOI identifier: 10.1111/j.1467-9868.2008.00692.x
OAI identifier: oai:eprints.lse.ac.uk:30462
Provided by: LSE Research Online

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