报告题目：The Sparse Estimation for Interval-Censored Data With Broken Adaptive Ridge Regression

报告人：赵慧教授（中南财经政法大学）

报告时间：2022年6月28日上午9:00-11:00

报告地点：腾讯会议ID： 478-773-399 密码：551286

报告摘要：

Variable selection has been discussed under many contexts and especially, a large literature has been established for the analysis of right-censored failure time data. In this talk, we discuss the simultaneous estimation and variable selection for Cox model and then extend the proposed procedure to the partly linear additive Cox model, where the number of covariates may diverge with the sample size, and In particular, we propose a broken adaptive ridge (BAR) regression procedure that combines the strengths of the quadratic regularization and the adaptive weighted ridge shrinkage. In the method, Bernstein polynomials are used to approximate the involved nonlinear functions. Under some weak regularity conditions, we establish both the oracle property and the grouping effect of the proposed BAR procedure. Some extensive simulation and application studies are also provided.

报告人简介：

赵慧，中南财经政法大学统计与数学学院教授，博士生导师。2005年博士毕业于北京大学数学科学学院，之后在中科院系统所和美国密苏里大学做博士后。早年主要研究图模型和因果推断问题，近年来研究兴趣主要在生存分析、纵向数据分析、高维统计等领域。主持国家自然科学基金三项及若干项其他科研项目，在JASA，Biometrics， Scandinavian Journal of Statistics，Journal of Multivariate Analysis，Statistics in Medicine等期刊发表科研论文五十余篇