“2020首师大青年统计论坛”系列报告

题目：Fault Classi_cation for High-dimensional Data Streams

报告人：项冬冬副教授（华东师范大学）

时间：2020年11月26日（周四）下午20:00-21:00

地点：线上腾讯会议（会议号：766 943 031）

Abstract : In various modern statistical process control applications that involve high-dimensional data streams (UDS), accurate fault diagnosis of out-of-control (OC) data streams is becoming crucial. The existing diagnostic approaches either focus on moderate dimensional processes or are unable to determine the shift direction accurately, especially when the signal-to-noise ratio is low. In this paper, we conduct a bold trial and consider the fault classification problem of UDS where determining the shift direction of the OC data streams is important to perform customized repairs. To this end, the problem is formulated into a three-classification multiple testing framework, and an efficient data-driven diagnostic procedure is developed to minimize the expected number of false positives while controlling the missed discovery rate at satisfactory level. The procedure is statistically optimal and computationally efficient, and improves the diagnostic effectiveness by taking into account directional information, which provides insights to guide further decisions. Numerical results show the superiority of the new procedure.

报告人简介：项冬冬,华东师范大学统计学院副教授，研究方向为统计过程控制和大规模多重检验，在JRSSB、Technometrics、Journal of Quality Technology、Statistica Sinica等杂志发表论文20余篇。

联系人：周洁、胡涛

举办单位：565net必赢客户端统计系、北京应用统计学会、交叉科学研究院

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