報告承辦單位: 數學與統計學院
報告題目: Stopping time detection of wood panel compression: A functional time series approach
報告內容: 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.
報告人姓名: 桑培俊
報告人所在單位: 加拿大滑鐵盧大學
報告人職稱/職務及學術頭銜: 副教授
報告時間: 2024年7月5日上午10：00-11:00
報告地點: 理科樓A419
報告人簡介: 桑培俊，本科就讀于浙江大學，2018年在加拿大 Simon Fraser University取得博士學位， 隨后加入加拿大滑鐵盧大學擔任助理教授, 并于2024年7月晉升為副教授。在Biometrics, Statistica Sinica, Journal of Computational and Graphical Statistics等統計雜志發表多篇文章。主要研究方向是非參數回歸，函數型數據和實時數據，尤其是函數型數據分析回歸模型中的統計推斷問題以及實時函數型數據的回歸問題。目前擔任統計雜志The American Statistician 的副主編.