报告题目：Variable Selection for Generalized Odds Rate Mixture Cure Models with Interval-Censored Failure Time Data
报 告 人：胡涛 教授 首都师范大学
报告时间：2021年10月28日 上午 11:00-12:00
报告地点：腾讯会议 ID：875 622 657
或点击链接直接加入会议：https://meeting.tencent.com/dm/af8zcvkUahv0
校内联系人：赵世舜 zhaoss@jlu.edu.cn
报告摘要：Variable selection for failure time data with a cured fraction has been discussed by many authors but most of existing methods apply only to right-censored failure time data. In this paper, we consider variable selection when one faces interval-censored failure time data arising from a general class of generalized odds rate mixture cure models, and we propose a penalized variable selection method by maximizing a derived penalized likelihood function. In the method, the sieve approach is employed to approximate the unknown function, and it is implemented using a novel penalized expectation–maximization (EM) algorithm. Also the asymptotic properties of the proposed estimators of regression parameters, including the oracle property, are obtained. Furthermore, a simulation study is conducted to assess the finite sample performance of the proposed method, and the results indicate that it works well in practice. Finally, the approach is applied to a set of real data on childhood mortality taken from the Nigeria Demographic and Health Survey.
报告人简介：胡涛，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。在国内外学术刊物Journal of the American Statistical Association、Biometrika、Renewable Energy、Energy Conversion and Management、中国科学：数学等上发表学术论文多篇。
