VARIANCE TESTING WITH SIMPLICIAL DATA DEPTH

A method is developed and studied for testing equality of variances based on simplicial data depth and Mood\u27s nonparametric test in the case of two samples. A method for calculating univariate simplicial data depth using a rank transformation is introduced. Type I error rates and power curves are compared for three existing tests for equality of variances and the data depth test using data simulated from the nonnal distribution and 5 nonnormal distributions. In addition, a new method of aligning two samples with unequal location parameters is proposed. This method shows significant improvement over aligning by either the median or mean in controlling Type I error rates of skewed distributions