Band Width Selection for High Dimensional Covariance Matrix Estimation
报 告 人:: 陈松蹊
报告地点:: 数学与统计学院四楼报告厅
报告时间:: 2017年11月06日星期一14:00-15:00

 The banding estimator of Bickel and Levina (2008a) and its tapering version of Cai, Zhang and Zhou (2010) are important high dimensional covariance estimators. Both estimators require a band width parameter. We propose a band width selector for the banding estimator by minimizing an empirical  estimate of the expected squared Frobenius norms of the estimation error matrix.

  The ratio consistency of the band width selector is established.  We provide a lower bound for  the coverage probability of  the underlying  band width being contained in an interval around the band width estimate.  Extensions to the band width selection for the tapering estimator and threshold level selection for the thresholding covariance estimator are made.  Numerical simulations and a case study on sonar spectrum data are conducted to demonstrate the proposed approaches.

发 布 人:科研助理 发布时间: 2017-11-03
陈松蹊, 北京大学教授,光华管理学院商务统计与经济计量系主任。美国爱荷华州立大学统计学终身教授。2008-2009年任国际华人统计学会理事会成员,2008年获得 Iowa State University教员杰出研究奖,2009年当选为数理统计学会(IMS)资深会员及美国统计学会(ASA)会士。入选 2008年度首批海外高层次人才“千人计划”。迄今已在国际权威学术杂志发表论文近60篇。因在数理统计学领域的杰出贡献, 他是国际统计学学术组织数理统计学会(Institute of Mathematical Statistics) 资深会员及美国统计学会会士, 国际华人统计学会理事,及国际统计学最权威的学术刊物The Annals of Statistics(统计年鉴) 副主编。