陈晓林副教授学术报告和讨论会

发布时间:2018年12月14日 作者:王洪   消息来源:    阅读次数:[]

报告题目:Joint feature screening for ultra-high-dimensional sparse additive hazards model by the sparsity-restricted pseudo-score estimator

报告人:陈晓林副教授(曲阜师范大学)
时间:2018年12月18日(星期二)上午9:00-11:00
地点:数学院145小报告厅

摘要:Due to the coexistence of ultra-high dimensionality and right censoring, it is very challenging to develop feature screening procedure for ultra-high-dimensional survival data. In this paper, we propose a joint screening approach for the sparse additive hazards model with ultra-high-dimensional features. Our proposed screening is based on a sparsity-restricted pseudo-score estimator which could be obtained effectively through the iterative hard-thresholding algorithm. We establish the sure screening property of the proposed procedure theoretically under rather mild assumptions. Extensive simulation studies verify its improvements over the main existing screening approaches for ultra-high-dimensional survival data. Finally, the proposed screening method is illustrated by dataset from a breast cancer study.

讨论会主持人:陈晓林副教授(曲阜师范大学)
时间:2018年12月18日(星期二)下午15:00-17:00
地点:数学院659办公室
讨论主题:高维变量选择和超高维变量筛选若干前沿问题

报告人简介:陈晓林,2012年于中国科学院数学与系统科学研究院获博士学位,现为曲阜师范大学统计学院副教授。研究方向主要为生存分析、高维数据分析、缺失数据的统计推断等。迄今,已在《Computational Statistics and Data Analysis》、《Annals of the Institute of Statistical Mathematics》、《Lifetime Data Analysis》等国际统计学期刊发表学术论文15篇,主持和参与国家自然科学基金、国家社会科学基金、山东省自然科学基金10余项。



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