报 告 人：张久军 教授

报告题目：Distribution-free joint change-point detection of location and scale – a comprehensive reviewand some new results

报告时间：2025年4月19日（周六）下午2点

报告地点：静远楼1506学术报告厅

主办单位：数学与统计学院、数学研究院、科学技术研究院

报告人简介：

       张久军，辽宁大学数学与统计学院教授，博士研究生导师，统计与数据科学系主任。辽宁大学“双带头人”教师党支部书记，美国明尼苏达大学访问者，辽宁省“百千万人才工程”百人层次人选，辽宁省普通本科教学名师，辽宁大学本科优秀主讲教师。兼任中国现场统计研究会多元统计分析分会理事，中国现场统计学会生存分析分会理事，辽宁省数学会理事。近年来，主持、参与国家自然科学基金，辽宁省自然科学基金十余项，发表论文50余篇。

报告摘要：

        Traditional process monitoring schemes often assume knowledge of process distributions. However, in the real world, where distribution information is rarely available, this necessitates the use of distribution-free schemes. Lepage and Cucconi statistics are commonly employed to construct nonparametric control schemes for jointly monitoring location and scale parameters. The change-point design (CPD) approach is frequently utilized for constructing monitoring schemes, as it does not require as many in-control (IC) reference sample observations compared to traditional Phase-II schemes. This paper investigates two new joint location-scale CPD schemes by integrating other Lepage-type statistics into the exponentially weighted moving average (EWMA) scheme. The study also compares these new schemes with existing Lepage and Cucconi-type CPD schemes. Simulation results are promising and support the application of these schemes in industrial contexts. Finally, real-world data is used to illustrate the effectiveness of the various schemes.