NDLI: A Simple Density-Based Empirical Likelihood Ratio Test for Independence

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A Simple Density-Based Empirical Likelihood Ratio Test for Independence

Content Provider	Scilit
Author	Vexler, Albert Tsai, Wan-Min Hutson, Alan D.
Copyright Year	2014
Description	Journal: The American Statistician We develop a novel nonparametric likelihood ratio test for independence between two random variables using a technique that is free of the common constraints of defining a given set of specific dependence structures. Our methodology revolves around an exact density-based empirical likelihood ratio test statistic that approximates in a distribution-free fashion the corresponding most powerful parametric likelihood ratio test. We demonstrate that the proposed test is very powerful in detecting general structures of dependence between two random variables, including non-linear and/or random-effect dependence structures. An extensive Monte Carlo study confirms that the proposed test is superior to the classical nonparametric procedures across a variety of settings. The real-world applicability of the proposed test is illustrated using data from a study of biomarkers associated with myocardial infarction.
Related Links	http://europepmc.org/articles/pmc4191747?pdf=render https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4191747/pdf
Ending Page	169
Page Count	12
Starting Page	158
ISSN	00031305
e-ISSN	15372731
DOI	10.1080/00031305.2014.901922
Journal	The American Statistician
Issue Number	3
Volume Number	68
Language	English
Publisher	Informa UK Limited
Publisher Date	2014-07-03
Access Restriction	Open
Subject Keyword	Journal: The American Statistician Statistics and Probability Density-based Empirical Likelihood Empirical Likelihood Independence Test Nonlinear Dependence Nonparametric Test Random Effect
Content Type	Text
Resource Type	Article
Subject	Statistics and Probability Statistics, Probability and Uncertainty

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