A Test of Symmetry Based on the Kernel Kullback-Leibler Information with Application to Base Deficit Data

Authors

Hani M. Samawi, Georgia Southern UniversityFollow
Robert L. Vogel, Georgia Southern UniversityFollow

Document Type

Article

Publication Date

2016

Publication Title

Biometrics and Biostatistics International Journal

DOI

10.15406/bbij.2016.03.00060

ISSN

2378-315X

Abstract

The assumption of the symmetry of the underlying distribution is important to many statistical inference and modeling procedures. This paper provides a test of symmetry using kernel density estimation and the Kullback-Leibler information. Based on simulation studies, the new test procedure outperforms other tests of symmetry found in the literature, including the Runs Test of Symmetry. We illustrate our new procedure using real data.

Recommended Citation

Samawi, Hani M., Robert L. Vogel. 2016. "A Test of Symmetry Based on the Kernel Kullback-Leibler Information with Application to Base Deficit Data." Biometrics and Biostatistics International Journal, 3 (2). doi: 10.15406/bbij.2016.03.00060
https://digitalcommons.georgiasouthern.edu/biostat-facpubs/219