A nonparametric test of symmetry based on the overlapping coefficient

Hani M. Samawi; Amal Helu; Robert L. Vogel

doi:10.1080/02664761003692365

A nonparametric test of symmetry based on the overlapping coefficient

Hani M. Samawi, Amal Helu, Robert L. Vogel

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Abstract

In this paper,we introduce a newnonparametric 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.

Original language	English
Pages (from-to)	885-898
Number of pages	14
Journal	Journal of Applied Statistics
Volume	38
Issue number	5
DOIs	https://doi.org/10.1080/02664761003692365
State	Published - May 2011

Keywords

Bootstrap method
Kernel density estimation
Matusita's measure
Morisita's measure
Overlap coefficients;Weitzman's measure
Power of the test
Test of symmetry

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10.1080/02664761003692365

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KW - Kernel density estimation

KW - Matusita's measure

KW - Morisita's measure

KW - Overlap coefficients;Weitzman's measure

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KW - Test of symmetry

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JF - Journal of Applied Statistics

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A nonparametric test of symmetry based on the overlapping coefficient

Abstract

Keywords

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