报告题目: Category-AdaptiveVariableScreeningforUltra-highDimension-alHeterogeneousCategoricalData

报告人：唐年胜

时间：2019年12月11日 14:30—15:30

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报告摘要

The populations of interest in modern studies are very often heterogeneous. The population heterogeneity, the qualitative nature of the outcome variable and the high dimensionality of the predictors pose significant challenge in statistical analysis. In this article, we introduce a category-adaptive screening procedure with high-dimensional heterogeneous data, which is to detect category-specific important covariates. The proposal is a model-free approach without any specification of a regression model and an adaptive procedure in the sense that the set of active variables is allowed to vary across different categories, thus making it mo-re flexible to accommodate heterogeneity.
         For response-selective sampling data, another main discovery of this paper is that  the proposed method works directly without any modification. Under mild regularity conditions, the newly procedure is shown to possess the sure screening and ranking consistency properties. Simulation studies contain supportive evidence  that the proposed method performs well under various settings and it is effective to extract category-specific information. Applications are illustrated with two real data sets.

 

专家简介

唐年胜，云南大学数学与统计学院教授，博士生导师，院长。主要从事统计诊断、非线性模型、生物医学统计研究。获省部级二等奖5项、三等奖2项。曾获“云南大学伍达观教育基金优秀教师奖（杰出类）”。2003年获霍英东教育基金会第九届高等院校青年教师奖（教学类三等）。2004年获云南省科学技术奖（自然科学类三等）；2007年入选教育部“新世纪优秀人才支持计划”；2008年入选“云南省中青年学术技术带头人后备人才”。