Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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Power Comparison of Independence Test for the Farlie-Gumbel-Morgenstern Family

  • Amini, M. (Department of Statistics, Ordered and Spatial Data Center of Excellence, Ferdowsi University of Mashhad) ;
  • Jabbari, H. (Department of Statistics, Ordered and Spatial Data Center of Excellence, Ferdowsi University of Mashhad) ;
  • Mohtashami Borzadaran, G.R. (Department of Statistics, Ordered and Spatial Data Center of Excellence, Ferdowsi University of Mashhad) ;
  • Azadbakhsh, M. (Department of Mathematics, University of Damghan)
  • Received : 20100100
  • Accepted : 20100500
  • Published : 2010.07.31
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Abstract

Developing a test for independence of random variables X and Y against the alternative has an important role in statistical inference. Kochar and Gupta (1987) proposed a class of tests in view of Block and Basu (1974) model and compared the powers for sample sizes n = 8, 12. In this paper, we evaluate Kochar and Gupta (1987) class of tests for testing independence against quadrant dependence in absolutely continuous bivariate Farlie-Gambel-Morgenstern distribution, via a simulation study for sample sizes n = 6, 8, 10, 12, 16 and 20. Furthermore, we compare the power of the tests with that proposed by G$\ddot{u}$uven and Kotz (2008) based on the asymptotic distribution of the test statistics.

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References

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  1. Aspects of Dependence in Generalized Farlie-Gumbel-Morgenstern Distributions vol.40, pp.8, 2011, https://doi.org/10.1080/03610918.2011.568149