Quantile correlation-based variable selection

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:唐年胜
:2021-08-04 10:28
:厦大海韵园实验楼105报告厅

报告人:唐年胜(云南大学)

 间:2021813日下午15:00

 点:厦大韵园实验楼105报告厅

内容摘要:

This talk is concerned with identifying important features in high dimensional data analysis, especially when there are complex relationships among predictors. Without any specification of an actual model, we first introduce a multiple testing procedure based on the quantile correlationto select important predictors in high dimensionality. The quantile-correlation statistic is able to capture a wide range of dependence.A stepwise procedure is studied for further identifying important variables. Moreover, a sure independent  screening based on the quantile correlation is developed in handling ultrahigh dimensional data. It is computationally efficient and easy to implement. We establish the theoretical properties under mild conditions. Numerical studies including simulation studies and real data analysis contain supporting evidence that the proposal performs reasonably well in practical settings.

个人简介:

唐年胜,云南大学数学与统计学院二级教授、院长。主持从事生物统计、贝叶斯统计、缺失数据分析、高维数据分析、机器学习等研究。国家杰出青年科学基金获得者,教育部长江学者特聘教授,国家百千万人才工程入选者,国家有突出贡献中青年专家,享受国务院政府特殊津贴,教育部新世纪优秀人才支持计划入选者,国际数理统计学会会士,国际统计学会推选会员,云南省高等学校教学名师。教育部高等学校统计学类专业教学指导委员会委员,国家自然科学基金委第八届数学天元基金学术领导小组成员。