Robust Hotelling's Statistic for Test A Hypothesis of Mean Multivariate Population Based on RMCD | ||
| basrah journal of science | ||
| Article 17, Volume 34, Issue 3, December 2016, Pages 182-195 PDF (0 K) | ||
| Authors | ||
| Abdullah A. Ameen; Mohand N. Abdul - Seid | ||
| Abstract | ||
| Hotelling’s statistic is an important to test a hypothesis about the mean of a multivariate normal population with location and scale parameters (with the proposition that the scale parameter is unknown positive definite matrix ) . However, hypothesis test based on this statistic can be adversely affected by outliers. In this paper, an alternative technique is proposed based on a statistic which uses the reweighted minimum covariance determinant (RMCD) estimators instead of the classical mean vector and covariance matrix . A simulation technique has been used as a technique to make a comparison between the classical and the proposed statistic by generating the data that have a contaminated multivariate normal distribution from one side and from two sides . The results have shown that, the proposed robust statistic is almost better than the classical statistic depending on the rates of type I error and the power test. | ||
| Keywords | ||
| Hotelling; Minimum Covariance Determinant; Robustness; One; Sample Hypothesis Test | ||
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