A Robust Hotelling Test View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2003

AUTHORS

G. Willems , G. Pison , P. J. Rousseeuw , S. Van Aelst

ABSTRACT

Hotelling’s T2 statistic is an important tool for inference about the center of a multivariate normal population. However, hypothesis tests and confidence intervals based on this statistic can be adversely affected by outliers. Therefore, we construct an alternative inference technique based on a statistic which uses the highly robust MCD estimator (Rousseeuw, 1984) instead of the classical mean and covariance matrix. Recently, a fast algorithm was constructed to compute the MCD (Rousseeuw and Van Driessen, 1999). In our test statistic we use the reweighted MCD, which has a higher efficiency. The distribution of this new statistic differs from the classical one. Therefore, the key problem is to find a good approximation for this distribution. Similarly to the classical T2 distribution, we obtain a multiple of a certain F-distribution. A Monte Carlo study shows that this distribution is an accurate approximation of the true distribution. Finally, the power and the robustness of the one-sample test based on our robust T2 are investigated through simulation. More... »

PAGES

417-431

Book

TITLE

Developments in Robust Statistics

ISBN

978-3-642-63241-9
978-3-642-57338-5

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-57338-5_36

DOI

http://dx.doi.org/10.1007/978-3-642-57338-5_36

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1042142954


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