报告人：陈建伟（美国圣地亚哥州立大学）

时 间：2023年8月4日10:00

地 点：厦门大学海韵园实验楼105报告厅

内容摘要:

This talk introduces Probit model in non-parametric space and Probit model in semi-parametric space, and focuses on the estimation method of the model. Spline approximation is carried out for the non-parametric part of the model, and the posterior probability of each parameter of the model is calculated by using Bayesian method after expanding the spline function. Numerical simulation is carried out by MCMC to verify the estimation effect of the model. The results show that the method has good fitting effect and high accuracy. An empirical analysis of the proposed model is performed, using regression spline and Bayesian method to estimate the parameters of the model.

个人简介：

陈建伟：美国圣地亚哥州立大学数学与统计系终身教授，博士生导师。主要从事应用统计学，管理科学，可靠性分析、大数据科学等交叉领域的研究工作。在非参数统计，微分方程动态系统，运筹学，质量检验等领域取得成果。先后在The Annals of Statistics, Journal of the American Statistics Association, Journal of the Royal Statistical Society等学术期刊发表论文100多篇，先后主持美国NSF, NSA和NlH研究项目。

联系人：周达