时 间：2024年11月08日 14:00 - 15:00
地 点：普陀校区理科大楼A614
报告人：郁文 复旦大学教授
主持人：项冬冬 华东师范大学教授
摘 要：
Doubly truncated data are found in astronomy, econometrics, and survival analysis literature. They arise when each observation is confined to an interval, that is, only those which fall within their respective intervals are observed along with the intervals. Unlike the one-sided truncation that can be handled by counting process-based approach, doubly truncated data are much more difficult to handle. In their analysis of an astronomical dataset, Efron and Petrosian (1999) proposed some nonparametric methods for doubly truncated data. Motivated by their approach, as well as by the work of Bhattacharya et al. (1983) for right truncated data, we propose a general method for estimating the regression parameter when the dependent variable is subject to the double truncation. It extends the Mann–Whitney-type rank estimator and can be computed easily by existing software packages. Weighted rank estimation is also considered for improving estimation efficiency. We show that the resulting estimators are consistent and asymptotically normal. Resampling schemes are proposed with large sample justification for approximating the limiting distributions. Some discussion on variable selection is provided. The quasar data in Efron and Petrosian (1999) and an AIDS incubation data are analyzed by the new method. Simulation results show that the proposed method works well.
报告人简介：
郁文，复旦大学管理学院统计与数据科学系教授、博士生导师，主要从事生存分析、半参数模型、两阶段抽样设计、经验似然等方向的研究，在JRSSB、JASA、中国科学等国内外学术期刊以及NeurIPS等国际会议上发表学术论文三十余篇，主持国家自然科学基金面上项目、青年项目以及教育部博士点基金等研究工作。