讲座信息

讲座信息

您当前的位置: 讲座信息
20171215 张春明:On Condition Number Constrained Estimation of Precision Matrix
时间:2017-12-05

题目:On Condition Number Constrained Estimation of Precision Matrix

主讲:张春

时间:20171215 14:00-15:00

地点:明德主楼 1030会议室

 

摘要:“Estimation of large precision matrices is fundamental to high-dimensional inference. We will discuss the estimation of the precision matrix by imposing a bound on the condition number of the estimate, which effectively ensures well-conditioning. Specifically, we propose a correlation-based estimator, constrained with both the condition number and the L1 penalty, yielding a precision matrix estimator with theoretically guaranteed rate of convergence. This result further enables us to demonstrate that incorporating the L1 penalty is necessary for achieving consistency of the resulting estimator in typical high-dimensional settings, while inconsistency will occur when the L1 penalty is absent. An algorithm is developed to implement the proposed method, which reveals the satisfactory performance in simulation studies. An application of the method to a call center data is illustrated.” 

 

简介:张春明1990数理统计专业本科毕业于南开大学,1993计算数学专业硕士毕业于中国科学院,2000年统计专业博士毕业于美国北卡莱罗纳大学教堂山分校。之后她任美国威斯康星大学麦迪逊分校统计系的助理教授(2000-2005),副教授2005-2010和正教授2010-至今)。担任以下刊物的副主编Annals of Statistics (2007-2009), Journal of the American Statistical Association (2011-), and Journal of Statistics Planning and Inference (2012-). 她是国际数理统计学会会士fellow),美国统计学会会士fellow)。2015年担任美国统计协会非参数统计分会的程序主席。她的研究兴趣包括 高维复杂数据统计建模与推断非参数与半参数统计建模与推断大规模多元联合统计推断及其应用于脑科学研究及神经影像数据分析、生物信息、医学、计量经济学及金融