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A new nonparametric monitoring of data streams for changes in location and scale via Cucconi statistic
Journal of Nonparametric Statistics ( IF 1.2 ) Pub Date : 2019-06-19 , DOI: 10.1080/10485252.2019.1632307
Dongdong Xiang 1 , Shulin Gao 1 , Wendong Li 2 , Xiaolong Pu 1 , Wen Dou 3
Affiliation  

ABSTRACT Many distribution-free control charts have been proposed for jointly monitoring location and scale parameters of a continuous distribution when their in-control (IC) status are unknown in advance. Unfortunately, most existing methods require relatively large amount of historical observations to estimate the IC parameters or to activate the control chart, and batch observations to construct the charting statistic. When such assumptions are invalid, they may not be reliable for online monitoring. In this paper, we propose a novel distribution-free control chart for joint monitoring of location and scale parameters with extremely small IC sample size. The proposed control chart integrates the Cucconi test into the framework of change-point detection and exponentially weighted moving average strategy. It requires no prior knowledge of the underlying distribution, and is very robust in start-up situations. Comprehensive numerical results show that the proposed chart is superior to its competitors.

中文翻译:

通过 Cucconi 统计对数据流的位置和规模变化进行新的非参数监控

摘要 已经提出了许多无分布控制图来联合监测连续分布的位置和尺度参数,当它们的控制(IC)状态事先未知时。不幸的是,大多数现有方法需要相对大量的历史观察来估计 IC 参数或激活控制图,并需要批量观察来构建图表统计量。当这些假设无效时,它们对于在线监控可能不可靠。在本文中,我们提出了一种新颖的无分布控制图,用于以极小的 IC 样本量联合监测位置和尺度参数。所提出的控制图将 Cucconi 测试集成到变化点检测和指数加权移动平均策略的框架中。它不需要潜在分布的先验知识,并且在启动情况下非常强大。综合数值结果表明,所提出的图表优于其竞争对手。
更新日期:2019-06-19
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