题 目：A new measure for testing independence  

时 间：2015年6月9日（周二）14:00-14:50

地 点：6号楼415教室

主讲人：殷向荣教授

主办单位：数学与统计学院  

Abstract:                                            

We introduce a new measure for testing independence between two random vectors. Our measure differs from that of distance covariance, by using expected conditional difference of characteristic functions. We propose one empirical version by slicing on one of the random vectors. We show that this particular version is equivalent to DISCO(Rizzo and Szêkely, 2010).This empirical measure is based on certain Euclidean distance.Its properties, asymptotic and applications in testing independence are discussed. Implementation and Monte Carlo results are also presented.                  

主讲人简介

Professor, Department of Statistics, The University of Georgia, International Chinese Statistical Association (ICSA). IMS membership. ASA membership. Associate Editor: Journal of Nonparametric Statistics,2011–.Associate Editor: Statistics and Probability Letters.Published Papers on Journal, such as Journal of American Statistical Association,Biometrics,Statistica Sincia. ect.                          

Research Interests: Dimension reduction in regression analysis; Regression graphics and data visualization; Classification and discriminant analysis; Pattern recognition such as face and expression recognition; Data analysis for experimental designs; Microarray data analysis; Data mining, and variable selections; Time series data analysis; Application of multivariate methods in biology, climate, etc.; Fast computing algorithms.