报告题目：Inference for High Dimensional Proportional Hazards Model with Streaming Survival Data

报告人：韩东啸 副教授 南开大学统计与数据科学学院

报告时间：2026年1月9日 9:00-10:00

报告地点：腾讯会议：806-891-026

校内联系人：杜明月 [email protected]

报告摘要：We propose an online inference procedure for high dimensional streaming survival data based on the proportional hazards model. Specifically, we offer an online Lasso method for regression parameter estimation and establish the non-asymptotic error bounds of the corresponding Lasso estimators for the regression parameter vector. In addition, we study the pointwise inference for the regression parameters by utilizing a debiased Lasso approach. Furthermore, we conduct high dimensional group inference for the regression parameters based on quadratic forms of the Lasso estimators and the debiased Lasso idea. Extensive simulations are conducted to evaluate the finite sample performance of the proposed method. Applications to two real datasets are provided to demonstrate the practical utility of the proposed methodology.

报告人简介：韩东啸，南开大学统计与数据科学学院，副教授。主要研究方向为生存分析、高维统计推断、机器学习理论研究。在统计学国际顶尖期刊“JASA” 、机器学习顶级期刊“JMLR”、计量经济学顶级期刊“JOE” 等上发表论文十余篇。主持国家自然科学基金面上项目1项、国家自然科学基金青年项目1项。