威尼斯欢迎你welcome建院40周年系列活动之学术讲座第36期
威尼斯欢迎你welcome统计学系列 Seminar 第72期
主题: Sieve Maximum Likelihood Regression Analysis of Dependent Current Status Data
主讲人: 胡涛教授
主持人：王国长
会议工具：腾讯会议 (ID: 302 256 639)
会议时间：2020年11月10日上午09:00-10:00
摘要
Current status data occur in contexts including demographic studies and tumorigenicity experiments. In such cases, each subject is observed only once and the failure time of interest is either left- or right-censored (Kalbfleisch & Prentice, 2002). Many methods have been developed for the analysis of such data (Huang,1996; Sun, 2006), most of which assume that the failure time and the observation time are independent completely or given covariates. In this paper, we present a sieve maximum likelihood approach for current status data when independence does not hold. A copula model and monotone I-splines are used and the asymptotic properties of the resulting estimators are established. In particular, the estimated regression parameters are shown to be semiparametrically efficient. An illustrative example is provided.
主讲人简介
胡涛，现任首都师范大学数学科学学院教授，博士生导师。研究方向：生存分析、风能数据分析。2009年毕业于北京师范大学数学科学学院，获概率论与数理统计专业博士学位。美国University of Missouri 统计系博士后。2009年3月至2012年12月先后在新加坡国立大学统计与应用概率系、南洋理工大学数学与物理学院任Research Assistant 和Research Fellow。在Journal of the American Statistical Association、Biometrika、Renewable Energy、Energy Conversion and Management、《中国科学：数学》等国内外学术刊物上发表学术论文多篇，主持自然科学基金2项。
