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Public Health

Georgia Southern University

Kernel Density estimation

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Full-Text Articles in Physical Sciences and Mathematics

A Test Of Symmetry Based On The Kernel Kullback-Leibler Information With Application To Base Deficit Data, Hani M. Samawi, Robert L. Vogel Jan 2016

A Test Of Symmetry Based On The Kernel Kullback-Leibler Information With Application To Base Deficit Data, Hani M. Samawi, Robert L. Vogel

Biostatistics Faculty Publications

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.


A More Efficient Nonparametric Test Of Symmetry Based On Overlapping Coefficient, Hani M. Samawi, Robert L. Vogel Dec 2014

A More Efficient Nonparametric Test Of Symmetry Based On Overlapping Coefficient, Hani M. Samawi, Robert L. Vogel

Biostatistics Faculty Publications

In this paper we provide a more efficient nonparametric test of symmetry based on the empirical overlap coefficient using kernel density estimation applied to an extreme order statistics, namely extreme ranked set sampling. Our simulation investigation reveals that our proposed test of symmetry is at least as powerful as currently available tests of symmetry. Intensive simulation is conducted to examine the power of the proposed test. An illustration is provided using cardiac output and body weight of neonates in a neonatal intensive care unit.