Multi-purpose open-end monitoring procedures for multivariate observations based on the empirical distribution function

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2023-03-06 DOI:10.1111/jtsa.12683

Mark Holmes, Ivan Kojadinovic, Alex Verhoijsen

引用次数: 0

Abstract

We propose non-parametric open-end sequential testing procedures that can detect all types of changes in the contemporary distribution function of possibly multivariate observations. Their asymptotic properties are theoretically investigated under stationarity and under alternatives to stationarity. Monte Carlo experiments reveal their good finite-sample behavior in the case of continuous univariate, bivariate and trivariate observations. A short data example concludes the work.

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基于经验分布函数的多变量观测的多用途开放式监测程序

我们提出了非参数开放式序列检验程序，该程序可以检测可能的多变量观测的当代分布函数的所有类型的变化。从理论上研究了它们在平稳性和可替代平稳性下的渐近性质。蒙特卡罗实验揭示了在连续单变量、二变量和三变量观测的情况下，它们良好的有限样本行为。一个简短的数据示例结束了这项工作。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.