报告题目【On Parsimonious and Flexible Modeling of Multivariate Failure Time Data】
时间: 2019年4月26日（星期五）14：00
地点:旗山校区 理工北楼601报告厅
主讲: 香港大学副教授，徐锦峰
主办: 数学与信息学院
参加对象：感兴趣的老师和学生
报告人简介：徐锦峰，香港大学统计及精算学系副教授。1999年本科毕业于中国科技大学数学与应用数学专业，2005年博士毕业于哥伦比亚大学统计学专业。
摘要: The frailty or random effects approach has been commonly used to model correlated failure time data. With the unobserved heterogeneity characterized by the random effects, it directly models the dependency and yields easy interpretation for the estimated model. In practice, however, it is often subjective and difficult to specify the distribution of the random effects. Furthermore, the (nonparametric) maximum likelihood estimation may involve numerical computation for intractable multiple integrals. To avoid these difficulties, we propose a new approach, using the idea of homogeneity pursuit, which is computationally convenient and theoretically justified by its asymptotic properties. Simulation studies and a real data application are also provided to illustrate the utility of our proposal.