An optimization method for change-point monitoring in finite samples sequence

IF 1.2 4区 数学 Q2 STATISTICS & PROBABILITY Statistics Pub Date : 2023-09-03 DOI:10.1080/02331888.2023.2258249
Dong Han, Fugee Tsung, Jinguo Xian
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Abstract

AbstractThis article proposes a method of optimizing control chart (sequential test) to detect an abnormal change in a sequence of finite or even small samples with the unknown change-point and the unknown post-change probability distribution. We not only introduced a performance measure for a given charting statistic to evaluate the detection effect of a control chart, but also constructed an optimal control chart under the measure. The effect of optimization method was illustrated by numerical simulations of three optimized Shewhart, CUSUM and EWMA control charts, and a real data example.Keywords: Optimization of control chartchange-point detectionfinite samplesMSC 2010 Subject Classifications: Primary 62L10secondary 62L15 AcknowledgmentsWe sincerely thank the two reviewers for their precious comments on the manuscript.Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work is supported by RGC Competitive Earmarked Research Grants and National Natural Science Foundation of China (11531001).
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有限样本序列变点监测的优化方法
摘要本文提出了一种优化控制图(序列检验)的方法,用于检测具有未知变化点和未知变化后概率分布的有限甚至小样本序列的异常变化。引入了给定图表统计量的性能度量来评价控制图的检测效果,并在此度量下构造了最优控制图。通过优化后的Shewhart控制图、CUSUM控制图和EWMA控制图的数值仿真,以及一个实际数据算例,说明了优化方法的效果。关键词:控制图优化变点检测有限样本msc 2010主题分类:初级62l10次级62L15致谢我们衷心感谢两位审稿人对稿件的宝贵意见。披露声明作者未报告潜在的利益冲突。项目资助:中国国家自然科学基金(11531001)。
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来源期刊
Statistics
Statistics 数学-统计学与概率论
CiteScore
1.00
自引率
0.00%
发文量
59
审稿时长
12 months
期刊介绍: Statistics publishes papers developing and analysing new methods for any active field of statistics, motivated by real-life problems. Papers submitted for consideration should provide interesting and novel contributions to statistical theory and its applications with rigorous mathematical results and proofs. Moreover, numerical simulations and application to real data sets can improve the quality of papers, and should be included where appropriate. Statistics does not publish papers which represent mere application of existing procedures to case studies, and papers are required to contain methodological or theoretical innovation. Topics of interest include, for example, nonparametric statistics, time series, analysis of topological or functional data. Furthermore the journal also welcomes submissions in the field of theoretical econometrics and its links to mathematical statistics.
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