A test of independence based on a generalized correlation function

Authors:
Murali Rao;Sohan Seth;Jianwu Xu;Yunmei Chen;Hemant Tagare;José C. Príncipe
Affiliations:
Department of Mathematics, University of Florida, Gainesville, FL 32611, USA;Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL 32611, USA;Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL 32611, USA;Department of Mathematics, University of Florida, Gainesville, FL 32611, USA;Department of Mathematics, University of Florida, Gainesville, FL 32611, USA;Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL 32611, USA
Venue:
Signal Processing
Year:
2011

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Abstract

In this paper, we propose a novel test of independence based on the concept of correntropy. We explore correntropy from a statistical perspective and discuss its properties in the context of testing independence. We introduce the novel concept of parametric correntropy and design a test of independence based on it. We further discuss how the proposed test relaxes the assumption of Gaussianity. Finally, we discuss some computational issues related to the proposed method and compare it with state-of-the-art techniques.