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中山大学 王学钦教授:Strong independence screening for ultra-high dimensional survival data

([西财新闻] 发布于 :2017-04-19 )

光华讲坛——社会名流与企业家论坛第4460期


  题:Strong independence screening for ultra-high dimensional survival data          

主讲人:中山大学 王学钦教授

主持人:林华珍 教授

  间:20170420日(星期四)下午4:00-5:00

  点:弘远楼402B

主办单位:统计研究中心  统计学院   科研处

主讲人简介

王学钦,中山大学数学学院和中山医学院双聘教授,博士生导师,中山大学统计学科带头人,中山大学华南统计科学研究中心执行主任,国家优秀青年基金获得者,教育部新世纪人才,教育部统计专业教指委委员。研究领域为非参多元统计学、统计学习、和精准医学。

 

内容提要:

Ranking by marginal utility provides an efficient way to reduce the data from ultra-high dimension to portable size. In order to handle the complex big data in great variability, the statistic that can measure the nonlinear relationship between response and marginal predictor were extensively discussed recently. Comparing to the regression analysis, it is more challenging when the response is the survival time with possible censoring. We propose a novel method to measure the marginal dependency between survival time and predictors. A screening criteria is presented to determine an active set to include important predictors and exclude unimportant predictors. It is shown that the proposed procedure enjoys good statistical properties. Its performance in finite sample size is evaluated via simulations and illustrated by a real data analysis.

 

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