Online non-parametric changepoint detection with application to monitoring operational performance of network devices
Online non-parametric changepoint detection with application to monitoring operational performance of network devices
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DOI：
10.1016/j.csda.2022.107551
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发表时间：
2022-07
期刊：
影响因子：
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通讯作者：
Edward P. Austin;Gaetano Romano;I. Eckley;P. Fearnhead
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文献类型：
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作者：
Edward P. Austin;Gaetano Romano;I. Eckley;P. Fearnhead
受电信应用中计算约束较少的启发，引入了一种新的非参数算法NUNC来执行数据分布变化的在线检测。考虑了两个变体：第一个是NUNC Local，检测滑动窗口内的更改。相反，NUNC Global将当前数据窗口与迄今为止看到的所有历史信息进行比较，并利用有效的更新步骤，以便不需要存储这些历史信息。为了探索这两种算法的特性，对真实数据集和模拟数据集进行了分析。此外，本文还给出了控制虚警率的测试阈值选择的理论结果，该结果可应用于其他二值分割变化检测设置。
Motivated by a telecommunications application where there are few computational constraints, a novel nonparametric algorithm, NUNC, is introduced to perform an online detection for changes in the distribution of data. Two variants are considered: the first, NUNC Local, detects changes within a sliding window. Conversely, NUNC Global, compares the current window of data to all of the historic information seen so far and makes use of an efficient update step so that this historic information does not need to be stored. To explore the properties of both algorithms, both real and simulated datasets are analysed. Furthermore, a theoretical result for the choice of test threshold to control the false alarm rate is presented, a result that could be applied in other binary segmentation change detection settings.