Communications for Statistical Applications and Methods, Volume (23), No (3), Year (2016-5) , Pages (215-230)

Title : ( Comparing the empirical powers of several independence tests in generalized FGM family )

Authors: Mansoor zargar , Hadi Jabbari Nooghabi , Mohammad Amini ,

Citation: BibTeX | EndNote

The powers of some tests for independence hypothesis against positive (negative) quadrant dependence in generalized Farlie-Gumbel-Morgenstern distribution are compared graphically by simulation. Some of these tests are usual linear rank tests of independence. Two other possible rank tests of independence are locally most powerful rank test and a powerful nonparametric test based on the Cramér-von Mises statistic. We also evaluate the empirical power of the class of distribution-free tests proposed by Kochar and Gupta (1987) based on the asymptotic distribution of a U-statistic and the test statistic proposed by Güven and Kotz (2008) in generalized Farlie-Gumbel-Morgenstern distribution. Tests of independence are also compared for sample sizes n = 20, 30, 50, empirically. Finally, we apply two examples to illustrate the results.

Keywords

, Generalized Farlie-Gumbel-Morgenstern (FGM) distribution, positive and negative quadrant dependence, rank tests, tests of independence,
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@article{paperid:1056761,
author = {Zargar, Mansoor and Jabbari Nooghabi, Hadi and Amini, Mohammad},
title = {Comparing the empirical powers of several independence tests in generalized FGM family},
journal = {Communications for Statistical Applications and Methods},
year = {2016},
volume = {23},
number = {3},
month = {May},
issn = {2287-7843},
pages = {215--230},
numpages = {15},
keywords = {Generalized Farlie-Gumbel-Morgenstern (FGM) distribution; positive and negative quadrant dependence; rank tests; tests of independence; U-statistic},
}

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%0 Journal Article
%T Comparing the empirical powers of several independence tests in generalized FGM family
%A Zargar, Mansoor
%A Jabbari Nooghabi, Hadi
%A Amini, Mohammad
%J Communications for Statistical Applications and Methods
%@ 2287-7843
%D 2016

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