统计学系系列讲座之240期

时间：2016年11月11日（星期五）上午8:30—9:30

地点：史带楼801室

主持人：张新生教授复旦大学管理学院统计学系

主题：A New Nested Cholesky Decomposition and Estimation for the Covariance Matrix of Bivariate Longitudinal Data

主讲人：薛留根教授北京工业大学

个人简介：薛留根教授现任北京工业大学统计学系系主任，博士生导师。中国数学会概率统计学会常务理事，中国现场统计研究会理事及生存分析分会副理事长等。主持完成和在研的国家和省部级科研项目13项。出版著作8部（独著6部），其中3部专著。在《Journal of the American Statistical Association》、《Journal of the Royal Statistical Society，Series B》、《The Annals of Statistics》、《Biometrika》等国内外学术期刊上发表学术论文200余篇，被SCI他引200余次，其中2篇属高被引论文。曾获教育部自然科学二等奖1项。

摘要：We propose a nested modified Cholesky decomposition for modeling the covariance structure in multivariate longitudinal data analysis. The entries of this decomposition have simple structures and can be interpreted as the generalized moving average coefficient matrices and innovation covariance matrices. We model the elements of these matrices by a class of unconstrained linear models, and develop a Fisher scoring algorithm to compute the maximum likelihood estimator of the regression parameters. The consistency and asymptotic normality of the estimators are established. Furthermore, we employ the smoothly clipped absolute deviation (SCAD) penalty to select the relevant variables in the models. The resulting SCAD estimators are shown to be asymptotically normal and have the oracle property. Some simulations are conducted to examine the finite sample performance of the proposed method. A real dataset is analyzed for illustration.

统计学系

2016-11-7