Methodological analysis demonstrates superior efficiency and robustness of a novel Mahalanobis distance estimator in non-normal populations, highlighting improved hypothesis testing accuracy.
We give a novel estimator of Mahalanobis distance D 2 between two non-normal populations. We show that it is enormously more efficient and robust than the traditional estimator based on least squares estimators. We give a test statistic for testing that D 2=0 and study its power and robustness properties.
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Tiku et al. (2009) studied this question.
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