Document Type
Article
Publication Date
1-27-2016
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): 1-10.
doi: 10.15406/bbij.2016.03.00060
https://digitalcommons.georgiasouthern.edu/biostat-facpubs/144
Comments
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