MATEC Web Conf.
Volume 71, 2016The International Conference on Computing and Precision Engineering (ICCPE 2015)
|Number of page(s)||4|
|Section||Computer and Information Design and Analysis Technologies|
|Published online||02 August 2016|
Generalized Correlation Coefficient Based on Log Likelihood Ratio Test Statistic
Department of Informatics and Biomedical Engineering, Asia University, Taichung 41354, Taiwan, ROC
Graduate Institute of Educational Information and Measurement, National Taichung University of Education, Taichung 40306, Taiwan
a Corresponding author: email@example.com
In this paper, I point out that both Joe’s and Ding’s strength statistics can only be used for testing the pair-wise independence, and I propose a novel G-square based strength statistic, called Liu’s generalized correlation coefficient, it can be used to detect and compare the strength of not only the pair-wise independence but also the mutual independence of any multivariate variables. Furthermore, I proved that only Liu’s generalized correlation coefficient is strictly increasing on its number of variables, it is more sensitive and useful than Cramer’s V coefficient, in other words, Liu generalized correlation coefficient is not only the G-square based strength statistic, but also an improved statistic for detecting and comparing the strengths of deferent associations of any two or more sets of multivariate variables, moreover, this new strength statistic can also be tested by G2.
© The Authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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