Paper Publications

DOI number:10.1109/ACCESS.2016.2622358

Journal:IEEE Access

Funded by:the National Natural Science Foundation of China under Project 61271380, Project U1501251, and Proje

Key Words:Contaminated Gaussian model (CGM), correlation coefficient, Gini correlation (GC), Pearson's product moment correlation coefficient (PPMCC).

Abstract:This paper establishes the asymptotic closed forms of the expectation and variance of the Gini correlation (GC) under a particular type of bivariate contaminated Gaussian model emulating a frequently encountered scenario in statistical signal processing. Monte Carlo simulation results verify the correctness of the theoretical results established in this paper. In order to gain further insight into GC, we also compare GC to Pearson’s product moment correlation coefficient, Kendall’s tau, and Spearman’s rho by means of root mean squared error. The newly explored theoretical and simulational findings not only deepen the understanding of the rather new GC, but also shed new light on the topic of correlation theory, which is widely applied in statistical signal processing

Co-author:SHUN LIU,YUN ZHANG,JIANBIN XIONG

First Author:RUBAO MA

Indexed by:Journal paper

Correspondence Author:WEICHAO XU

Volume:4

Page Number:Asymptotic Mean and Variance of Gini Correlation Under Contaminated Gaussian Model

Translation or Not:no

Included Journals:SCI