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December, 1984 Detection of Multivariate Outliers in Elliptically Symmetric Distributions
Bimal Kumar Sinha
Ann. Statist. 12(4): 1558-1565 (December, 1984). DOI: 10.1214/aos/1176346813

Abstract

An extension of Ferguson's (Fourth Berkeley Symposium on Probability and Mathematical Statistics, 1961, Volume 1) univariate normal results and Schwager and Margolin's (1982) multivariate normal results for detection of outliers is made to the multivariate elliptically symmetric case with mean slippage. The main result can be viewed as a robustness property of the use of Mardia's multivariate kurtosis statistic as a locally optimum test statistic to detect outliers against nonnormal multivariate distributions.

Citation

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Bimal Kumar Sinha. "Detection of Multivariate Outliers in Elliptically Symmetric Distributions." Ann. Statist. 12 (4) 1558 - 1565, December, 1984. https://doi.org/10.1214/aos/1176346813

Information

Published: December, 1984
First available in Project Euclid: 12 April 2007

zbMATH: 0554.62043
MathSciNet: MR760709
Digital Object Identifier: 10.1214/aos/1176346813

Subjects:
Primary: 62A05
Secondary: 62E15, 62H10, 62H15

Rights: Copyright © 1984 Institute of Mathematical Statistics

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Vol.12 • No. 4 • December, 1984
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