A Control Chart for On-line Monitoring High-dimensional Process Covariance Matrices with Individual Observations

报告题目:A Control Chart for On-line Monitoring High-dimensional Process Covariance Matrices with Individual Observations

 报  告  人:李忠华    副教授

 报告时间:2017年11月10日(星期五)下午16:00

 报告地点:数学学院205室


 报告摘要:

In this talk, we propose a new control chart that integrates a powerful high-dimensional covariance matrix test with the exponentially weighted moving average (EWMA) procedure for monitoring high-dimensional variability with individual observations. Monte-Carlo simulation results show that the new chart, with its powerful inherited properties, provides satisfactory performance in various cases, especially for covariance shifts that involve diagonal components. The application of the proposed method is illustrated with a real data example from a white-wine production process.


 报告人介绍:

李忠华,南开大学统计研究院副教授,美国北卡罗莱纳大学教堂山分校、美国明尼苏达大学、新加坡国立大学、香港科技大学、香港城市大学访问学者。研究方向为统计质量控制、变点、质量工程、高维统计等。合作出版专著1本,发表SCI学术论文30余篇,包括Technometrics、Journal of Quality Technology等。现任中国现场统计研究会高维数据统计分会理事、北京大数据协会理事、天津市现场统计研究会理事、美国Mathematical Reviews评论员等。