Finding an unknown number of multivariate outliers

Marco Riani, Anthony C. Atkinson and Andrea Cerioli

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

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.

JEL-codes: C1 (search for similar items in EconPapers)
Date: 2009
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (50)

Published in Journal of the Royal Statistical Society. Series B: Statistical Methodology, 2009, 71(2), pp. 447-466. ISSN: 1369-7412

Downloads: (external link)
http://eprints.lse.ac.uk/30462/ Open access version. (application/pdf)

Related works:
Journal Article: Finding an unknown number of multivariate outliers (2009)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ehl:lserod:30462

Access Statistics for this paper

More papers in LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library LSE Library Portugal Street London, WC2A 2HD, U.K.. Contact information at EDIRC.
Bibliographic data for series maintained by LSERO Manager ().