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Article
A More Efficient Nonparametric Test of Symmetry Based on Overlapping Coefficient
Biometrics & Biostatistics International Journal
  • Hani Samawi, Georgia Southern University
  • Robert L. Vogel, Georgia Southern University
Document Type
Article
Publication Date
1-1-2014
Disciplines
Abstract
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.
Citation Information
Hani Samawi and Robert L. Vogel. "A More Efficient Nonparametric Test of Symmetry Based on Overlapping Coefficient" Biometrics & Biostatistics International Journal Vol. 1 Iss. 3 (2014)
Available at: http://works.bepress.com/robert_vogel/69/