Sequential change-point detection for skew normal distribution

IF 0.6 4区 数学 Q4 STATISTICS & PROBABILITY
Peiyao Wang, Wei Ning
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引用次数: 0

Abstract

Abstract In this article, we propose a modified max-cumulative sum (CUSUM) procedure for detecting changes in parameters of skew normal distribution. The corresponding false alarms frequency and the postchange detection delay are investigated. Asymptotic behaviors of detection delay and theoretical optimality of the detection procedure have been established. Simulations have been conducted to show the performance of the proposed method and compare it to the other existing methods including CUSUM. Real data are given to illustrate the detection procedure.
偏态正态分布的序列变化点检测
摘要本文提出了一种改进的最大累积和(CUSUM)方法来检测偏态正态分布参数的变化。研究了相应的虚警频率和后变检测延迟。建立了检测延迟的渐近行为和检测过程的理论最优性。通过仿真验证了所提方法的性能,并与包括CUSUM在内的其他现有方法进行了比较。给出了实际数据来说明检测过程。
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来源期刊
CiteScore
1.40
自引率
12.50%
发文量
20
期刊介绍: The purpose of Sequential Analysis is to contribute to theoretical and applied aspects of sequential methodologies in all areas of statistical science. Published papers highlight the development of new and important sequential approaches. Interdisciplinary articles that emphasize the methodology of practical value to applied researchers and statistical consultants are highly encouraged. Papers that cover contemporary areas of applications including animal abundance, bioequivalence, communication science, computer simulations, data mining, directional data, disease mapping, environmental sampling, genome, imaging, microarrays, networking, parallel processing, pest management, sonar detection, spatial statistics, tracking, and engineering are deemed especially important. Of particular value are expository review articles that critically synthesize broad-based statistical issues. Papers on case-studies are also considered. All papers are refereed.
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