Title : ( Power comparison of independence test for Farlie-Gumbel-Morgenstern family )
Authors: Mohammad Amini , Hadi Jabbari Nooghabi , Gholam Reza Mohtashami Borzadaran , M. Azadbakhsh ,
Full TextAbstract
Developing test for independence of random variables X and Y against the alternative has an important role in statistical inference. citet*{Kochar1987} proposed a class of tests in view of citet*{Block} model and compared the powers for sample sizes n=8,12 . In this paper, we evaluate citet*{Kochar1987} 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 citet*{Guven} based on the asymptotic distribution of the test statistics.
Keywords
, Negative and Positive quadrant dependence, Farlie-Gambel-Morgenstern distribution, U-Statistics
@article{paperid:1015803,
author = {Amini, Mohammad and Jabbari Nooghabi, Hadi and Mohtashami Borzadaran, Gholam Reza and M. Azadbakhsh},
title = {Power comparison of independence test for Farlie-Gumbel-Morgenstern family},
journal = {Communications of the Korean statistical society},
year = {2010},
volume = {17},
number = {3},
month = {June},
issn = {1225-9500},
keywords = {Negative and Positive quadrant dependence; Farlie-Gambel-Morgenstern distribution; U-Statistics},
}
%0 Journal Article
%T Power comparison of independence test for Farlie-Gumbel-Morgenstern family
%A Amini, Mohammad
%A Jabbari Nooghabi, Hadi
%A Mohtashami Borzadaran, Gholam Reza
%A M. Azadbakhsh
%J Communications of the Korean statistical society
%@ 1225-9500
%D 2010
