报告题目：Variable selection for generalized linear models with interval-censored failure time data
报 告 人：胡涛 教授 首都师范大学
报告时间：2022年9月21日 星期三13:30-14:30
报告地点：腾讯会议：496457998
校内联系人：赵世舜 zhaoss@jlu.edu.cn
报告摘要：Variable selection is often needed in many fields and has been discussed by many authors in various situations. This is especially the case under linear models and when one observes complete data. Among others, one common situation where variable selection is required is to identify important risk factors from a large number of covariates. In this paper, we consider the problem when one observes interval-censored failure time data arising from generalized linear models, for which there does not seem to exist an established method. To address this, we propose a penalized least squares method with the use of an unbiased transformation and the oracle property of the method is established along with the asymptotic normality of the resulting estimators of regression parameters. Simulation studies were conducted and demonstrated that the proposed method performed well for practical situations. In addition, the method was applied to a motivating example about children’s mortality data of Nigeria.
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、应用统计。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。
