Article
A Test of Symmetry Based on the Kernel Kullback-Leibler Information with Application to Base Deficit Data
Biometrics and Biostatistics International Journal
Document Type
Article
Publication Date
1-27-2016
DOI
10.15406/bbij.2016.03.00060
Disciplines
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.
Citation Information
Hani M. Samawi and Robert L. Vogel. "A Test of Symmetry Based on the Kernel Kullback-Leibler Information with Application to Base Deficit Data" Biometrics and Biostatistics International Journal Vol. 3 Iss. 2 (2016) p. 1 - 10 ISSN: 2378-315X Available at: http://works.bepress.com/robert_vogel/86/
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