DOI码：10.1109/ACCESS.2016.2622358

发表刊物：IEEE Access

项目来源：the National Natural Science Foundation of China under Project 61271380, Project U1501251, and Proje

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

摘要：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

合写作者：刘舜,章云,熊建斌

第一作者：马如豹

论文类型：期刊论文

通讯作者：徐维超

卷号：4

页面范围：Asymptotic Mean and Variance of Gini Correlation Under Contaminated Gaussian Model

是否译文：否

收录刊物：SCI