摘要：Confidence sets are of key importance in high-dimensional statistical inference. Under case-control study, a popular response-selective sampling design in medical study or econometrics, we consider the confidence intervals and statistical tests for single or low-dimensional parameters in high-dimensional logistic regression model. The asymptotic properties of the resulting estimators are established under mild regularity conditions. Furthermore, statistical tests for testing more general and complex hypotheses of the high-dimensional parameters are studied. The general testing procedures are proved to be asymptotically exact and has satisfactory power. Numerical studies including extensive simulations and a real data example confirm that the proposed method performs well in practical settings.

 

报告人简介：云南大学数学与统计学院教授，博士生导师，院长。“国家杰出青年科学基金”获得者，教育部“长江学者特聘教授”，教育部“新世纪优秀人才支持计划”入选者，国家百千万人才工程暨有突出贡献中青年专家，享受国务院政府特殊津贴。国际统计学会推选会员，国际数理统计学会会士（IMS Fellow）。云南省科技领军人才，云南省高等学校教学名师。现兼任教育部高等学校统计学类教学指导委员会委员、中国统计学会常务理事、中国现场统计研究会副理事长、中国现场统计研究会资源与环境统计分会副理事长、中国现场统计研究会高维数据统计分会副理事长；Statistics and Its Interface、Communications in Mathematics and Statistics 等10余个杂志的编委或副主编。研究方向包括：生物统计、贝叶斯统计、统计诊断、缺失数据分析、高维数据分析、生存数据分析等，在JASA、Annals of Statistics、Biometrika、Journal of Econometrics、JMLR等学术期刊发表论文190余篇；出版学术专著5部、译著2部、教材1部。

 

 

 

 

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