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Nonparametric Test of Symmetry Based on Overlapping Coefficient
Journal of Applied Statistics (2011)
  • Hani M. Samawi, Georgia Southern University
  • Amal Helu, University of Jordan
  • Robert L. Vogel, Georgia Southern University
In this paper, we introduce a new nonparametric 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.
  • test of symmetry,
  • power of the test,
  • bootstrap method,
  • Matusita's measure,
  • Morisita's measure,
  • overlap coefficients,
  • Weitzman's measure,
  • kernel density estimation
Publication Date
Citation Information
Hani M. Samawi, Amal Helu and Robert L. Vogel. "Nonparametric Test of Symmetry Based on Overlapping Coefficient" Journal of Applied Statistics (2011)
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