|
Title
|
|
|
|
A robust hotelling test
| |
|
Author
|
|
|
|
| |
|
Abstract
|
|
|
|
| Hotelling's T-2 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 [9] instead of the classical mean and covariance matrix. Recently, a fast algorithm was constructed to compute the MCD [10]. 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 T-2 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 T-2 are investigated through simulation. |
| |
|
Language
|
|
|
|
English
| |
|
Source (journal)
|
|
|
|
Metrika : Zeitschrift für theoretische und angewandte Statistik. - Heidelberg, 1958, currens
| |
|
Source (book)
|
|
|
|
International Conference on Robust Statistics, JUL 23-27, 2001, VORAU, AUSTRIA
| |
|
Publication
|
|
|
|
Heidelberg
:
2002
| |
|
ISSN
|
|
|
|
0026-1335
[print]
1435-926X
[online]
| |
|
Volume/pages
|
|
|
|
55
:1-2
(2002)
, p. 125-138
| |
|
ISI
|
|
|
|
000175702200012
| |
|
Full text (Publisher's DOI)
|
|
|
|
| |
|
Full text (publisher's version - intranet only)
|
|
|
|
| |
|