报告人: 栗家量 (National University of Singapore)
时 间: 2018年5月14日 15:00---16:00
地 点: 理科楼 LD202
摘 要:A two-stage procedure for simultaneously detecting multiple thresholds and achieving model selection in the segmented accelerated failure time (AFT) model is developed in this paper. In the first stage, we formulate the threshold problem as a group model selection problem so that a concave 2-norm group selection method can be applied. In the second stage, the thresholds are finalized via a refining method. We establish the strong consistency of the threshold estimates and regression coefficient estimates under some mild technical conditions. The proposed procedure performs satisfactorily in our simulation studies. Its real world applicability is demonstrated via analyzing a follicular lymphoma data.
报告人简介: 栗家量教授就职于新加坡国立大学，主要研究领域为非参数统计、函数型数据分析、高维统计推断等，已发表包含Journal of the Royal Statistical Society Series B, Annals of Statistics, Journal of the American Statistical Association等顶级期刊在内的论文60余篇，目前担任Biometrics, Lifetime Data Analysis等国际权威期刊的Associate Editor。