报告题目：A Bayesian approach to response optimization on data with multistratum structure.
报告人：Professor Po Yang
报告时间：2023年7月11日15:00-16:00
报告地点：文波楼四楼会议室
摘要：Multistratum design arises naturally in industrial experiments due to the inconvenient and impractical completely randomization. Most research has concentrated on finding optimal multistratum designs that have high efficiencies in parameter estimation. Accounting for the model uncertainty, we apply the Bayesian model averaging method and predictive approach to investigate the optimization problem for data with multi-stratum structure. With the posterior probabilities of models as weights, we consider the weighted average of the predictive densities of the response over all potential models. The goal of the optimization is to identify the values of the factors that result in a maximum probability of a response in a given range. The method is illustrated with two examples.
主讲人简介: 杨钋博士，加拿大曼尼托巴大学统计系教授，曾任教于芝加哥的德保罗大学。杨博士本科就读于河南大学数学系，在吉林大学获得数学硕士学位，在加拿大的萨斯喀彻温大学获得统计硕士学位，在麦克马斯特大学获得统计博士学位。现任统计系副系主任，主管研究生工作。研究方向是实验设计与数据分析，包括筛选设计、添加设计、区组设计、 裂区设计、超饱和设计、响应优化和贝叶斯方法。在《Statistica Sinica》 和 《Journal of Quality Technology》等国际知名期刊发表学术论文多篇，其研究一直受到加拿大囯家自然科学和工程研究基金的资助。
