统计与管理学院2016年学术报告第11期
【主 题】Sufficient Dimension Reduction on the Mean and Rate Functions of Recurrent Events
【报告人】 周宪
Macquarie University, NSW, Australia
【时 间】 2016年4月18日（星期一）16:00－17:00
【地 点】 上海财经大学统计与管理学院大楼1208室
【摘 要】 The counting process with a cox-type intensity function has been extensively applied to analyze recurrent event data, which assumes that the underlying counting process is a time-transformed Poisson process and that the covariates have multiplicative or additive effects on the mean and rate functions of the counting process. The existing statistical inference, however, often encounters difficulties due to high-dimensional covariates, such as in gene expression and single nucleotide polymoohism data that have revolutionized our understanding of cancer recurrence and other diseases. This talk introduces a technique of sufficient dimension reduction on the covariates for the mean and rate function of the number of event occurrences over time. A two-step procedure is proposed to estimate the model components: first a nonparametric estimator is proposed for the baseline, and then the basis of the central subspace and its dimension are estimated through a modified slicing inverse regression. An application is demonstrated on a set of chronic granulomatous disease (CGD) data.
【邀请人】 尤进红
