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学术讲座【Efficient Feature Screening for Ultrahigh-dimensional Varying Coefficient Models】

时间:2017-05-24浏览:526设置

时间:2017年5月29日(星期一)9:30 -10:30

地点:旗山校山理工北楼601报告厅

主讲:ASSISTANT PROFESSOR  DEPT. OF STATISTICS & APPLIED PROBABILITY NATIONAL UNIVERSITY OF SINGAPORE 陈欣 

主办:数学与计算机科学学院、福建省分析数学及应用重点实验室、数学研究中心

专家简介:陈欣,本科毕业于南开大学数学专业,博士毕业于明尼苏达大学统计学专业,现就职于新加坡国立大学统计与应用概率系,主持3项NSU项目,已在统计学TOP杂志“The Annals of Statistics”、“Biometrika”等发表多篇论文。

报告摘要:Feature screening in ultrahigh-dimensional varying coefficient models is a crucial statistical problem in economics, genomics and etc. Existing methods suffer in the cases of multiple index variables and group predictor variables.Moreover, current methods can not handle nonlinear varying coefficient models which is possible in reality. To deal with those scenarios efficiently in real life, we develop a screening procedure for ultrahigh-dimensional varying coefficient models utilizing conditional distance covariance (CDC). Extensive simulation studies and two real economic data examples have shown the effectiveness and the flexibility of our proposed methods.

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