好色视频 学术报告[2025] 079号

(高水平大学建设系列报告1101号)

报告题目: When Tukey meets Chauvenet: a new boxplot criterion for outlier detection

报告人：林红梅 副教授（上海对外经贸大学）

报告时间：2025年8月29日上午10:00-11:00

报告地点：汇星楼514  

报告内容：The box-and-whisker plot, introduced by Tukey（1977）, is one of the most popular graphical methods in descriptive statistics. On the other hand, however, Tukey's boxplot is free of sample size, yielding the so-called ``one-size-fits-all" fences for outlier detection. Although improvements on the sample size adjusted boxplots do exist in the literature, most of them are either not easy to implement or lack justification. As another common rule for outlier detection, Chauvenet's criterion uses the sample mean and standard derivation to perform the test, but it is often sensitive to the included outliers and hence is not robust. In this paper, by combining Tukey's boxplot and Chauvenet's criterion, we introduce a new boxplot, namely the Chauvenet-type boxplot, with the fence coefficient determined by an exact control of the outside rate per observation. Our new outlier criterion not only maintains the simplicity of the boxplot from a practical perspective, but also serves as a robust Chauvenet's criterion. Simulation study and a real data analysis on the civil service pay adjustment in Hong Kong demonstrate that the Chauvenet-type boxplot performs extremely well regardless of the sample size, and can therefore be highly recommended for practical use to replace both Tukey's boxplot and Chauvenet's criterion.

报告人简历：林红梅，上海对外经贸大学统计与信息好色视频 副教授，博士研究生导师。博士毕业于华东师范大学统计学专业，并曾作为联合培养博士赴美国加州大学圣巴巴拉分校深造，作为高级研究学者赴美国加州大学河滨分校访问交流，多次赴香港浸会大学、香港中文大学进行学术交流与访问。主要研究方向包括非参半参数回归分析、函数型数据分析、分布式统计方法等领域。在国内外统计学一流杂志《Statistica Sinica》、《Journal of Computational and Graphical Statistics》在内的期刊发表论文20余篇，主持国家自然科学基金青年基金项目、面上项目各1项，主持上海市自然科学基金项目面上项目1项，主持教育部重点实验室开放课题项目1项，主持上海市重点课程项目。2022年入选上海市“曙光计划”项目并荣获“曙光学者”称号， 2023年入选上海市“东方英才”青年人才项目。现担任中国现场统计研究会理事、中国现场统计研究会教育统计与管理分会副理事长。

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报告邀请人：周彦

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2025年8月26日