A Bayesian Stochastic Approximation Method
报 告 人:: 徐进
报告地点:: 数学与统计学院四楼会议室
报告时间:: 2017年07月05日星期三14:00-15:00

Motivated by the goal of improving the efficiency of small sample design, we propose a novel Bayesian stochastic approximation method to estimate the root of a regression function. The method feature adap- tive local modelling and non-recursive iteration. Strong consistency of the Bayes estimator is obtained. Simulation studies show that our met- hod is superior in finite-sample performance to Robbins-Monro type procedures. Extensions to searching for extreme and a version of gen- eralized multivariate quantile are presented.

发 布 人:科研助理 发布时间: 2017-06-30
徐进,华东师范大学统计学院教授。1999年华东师范大学统计系本科。2004年美国鲍林格林大学(Bowling Green State University)统计学博士,2004-2005年加利福尼亚大学河边分校博士后。主要研究方向:临床试验, 序贯设计,多元分析。