Power studies of multivariate two-sample tests of comparison
Loading...
Date
2007
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
University of the Western Cape
Abstract
The multivariate two-sample tests provide a means to test the match between two multivariate distributions. Although many tests exist in the literature, relatively little is known about the relative power of these procedures. The studies reported in the thesis contrasts the effectiveness, in terms of power, of seven such tests with a Monte Carlo study. The relative power of the tests was investigated against location, scale, and correlation alternatives. Samples were drawn from bivariate exponential, normal and uniform populations. Results from the power studies show that there is no single test which is the most powerful in all situations. The use of particular test statistics is recommended for specific alternatives. A possible supplementary non-parametric graphical procedure, such as the Depth-Depth plot, can be recommended for diagnosing possible differences between the multivariate samples, if the null hypothesis is rejected. As an example of the utility of the procedures for real data, the multivariate two-sample tests were applied to photometric data of twenty galactic globular clusters. The results from the analyses support the recommendations associĀated with specific test statistics.
Description
>Magister Scientiae - MSc
Keywords
Permutation method, Non-parametric test, Euclidean distance, Multivariate two-sample test, Nearest neighbour tests