A nonparametric test of symmetry based on the overlapping coefficient

Abstract

In this paper, we introduce a new nonparametric test of symmetry based on the empirical overlap coefficient using kernel density estimation. Our investigation reveals that the new test is more powerful than the runs test of symmetry proposed by McWilliams [31]. Intensive simulation is conducted to examine the power of the proposed test. Data from a level I Trauma center are used to illustrate the procedures developed in this paper.

Keywords:

• test of symmetry
• power of the test
• bootstrap method
• Matusita's measure
• Morisita's measure
• overlap coefficients
• Weitzman's measure
• kernel density estimation

AMS Subject Classification :

• 62G10

Acknowledgements

This project is fully supported by the Catalyst grant 2009 at Georgia Southern University. The authors are sincerely grateful to reviewers and the associate editor for their valuable comments which helped improving the paper.