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A robust hotelling test
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| Abstract |
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| 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. | | |
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English
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Metrika. - Wien | |
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International Conference on Robust Statistics, JUL 23-27, 2001, VORAU, AUSTRIA | |
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Wien : 2002
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0026-1335
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55:1-2(2002), p. 125-138
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000175702200012
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