报告承办单位: 数学与统计学院

报告题目: Stopping time detection of wood panel compression: A functional time series approach

报告内容: We consider determining the optimal stopping time for the glue curing of wood panels in an automatic process environment. Using the near-infrared spectroscopy technology to monitor the manufacturing process ensures substantial savings in energy and time. We collect a time-series of curves from a near-infrared spectrum probe consisting of 72 spectra and aim to detect an optimal stopping time. We propose an estimation procedure to determine the optimal stopping time of wood panel compression and the estimation uncertainty associated with the estimated stopping time. Our method first divides the entire data set into a training sample and a testing sample, then iteratively computes integrated squared forecast errors based on the testing sample. We then apply a structural break detection method with one breakpoint to determine an estimated optimal stopping time from a univariate time-series of the integrated squared forecast errors. We also investigate the finite sample performance of the proposed method via a series of simulation studies.

报告人姓名: 桑培俊

报告人所在单位: 加拿大滑铁卢大学

报告人职称/职务及学术头衔: 副教授

报告时间: 2024年7月5日上午10：00-11:00

报告地点: 理科楼A419

报告人简介: 桑培俊，本科就读于浙江大学，2018年在加拿大 Simon Fraser University取得博士学位， 随后加入加拿大滑铁卢大学担任助理教授, 并于2024年7月晋升为副教授。在Biometrics, Statistica Sinica, Journal of Computational and Graphical Statistics等统计杂志发表多篇文章。主要研究方向是非参数回归，函数型数据和实时数据，尤其是函数型数据分析回归模型中的统计推断问题以及实时函数型数据的回归问题。目前担任统计杂志The American Statistician 的副主编.