时 间：2026年4月20 日（周一）16：00-17：00
地 点：普陀校区理科大楼A1514室
报告人：孙建国 南方科技大学讲席教授
主持人：於州 华东师范大学教授
摘 要:
In this talk, we will discuss regression analysis of interval-censored failure time data when there exist random change points with the focus on variable selection. Such data can occur in, for example, clinical trials where the risk of a disease may dramatically change when some biological indexes of the human body exceed certain thresholds. For the problem, we will first present a class of linear transformation change point models and develop a sieve maximum likelihood estimation procedure. Then a penalized method will be proposed for simultaneous estimation and variable selection, and the asymptotic properties of the proposed method are established. A simulation study is conducted and indicates that the proposed methods work well in practical situations. The approaches are applied to a set of real data from a breast cancer study.
报告人简介：
孙建国教授现任南方科技大学讲席教授，长期致力于生物统计、基因数据分析、复杂数据建模方法及其在临床医学与社会科学领域的交叉应用研究。他在《Journal of the American Statistical Association (JASA)》《Journal of the Royal Statistical Society: Series B (JRSSB)》《Biometrika》《Annals of Statistics》《Biometrics》《Statistica Sinica》及《Statistics in Medicine》等国际顶级统计期刊发表论文300余篇，并出版统计学著作4部。他是美国统计学会（ASA）Fellow、国际数理统计学会（IMS）Fellow及国际统计学会（ISI）Elected Member。曾 担 任 美 国 统 计 学 会 生 存 分 析 分 会 主 席（ASA Lifetime Data Science Section）、国际泛华统计协会（ICSA）主席等多个重要学术组织职务。目前或曾经担 任 包 括 《JASA 》《Statistics in Medicine 》《 Lifetime Data Analysis 》《The International Journal of Biostatistics》《Computational Statistics & Data Analysis》等国际顶级统计期刊副主编，现在担任《Statistics in Biosciences》主编。