Xiaofeng Shao
University of Illinois at Urbana-Champaign, USA
Title: Martingale difference divergence and its applications to contemporary statistics
Biography
Biography: Xiaofeng Shao
Abstract
Martingale difference divergence is a metric that quantifies the conditional mean dependence of a random vector Y given another random vector X and it can be viewed as an extension of distance covariance, which characterizes the dependence and has recently much attention in the literature. We shall present applications of martingale difference divergence and its variant to several contemporary statistical problems: high dimensional variable screening, dependence testing and dimension reduction for multivariate time series.