Nonparametric control charts are used in process monitoring when there is insufficient information about the form of the underlying distribution. In this article, we propose a triple exponentially weighted moving average (TEWMA) control chart based on the sign statistic for monitoring the location parameter of an unknown continuous distribution. The run‐length characteristics of the proposed chart are evaluated performing Monte Carlo simulations. We also compare its statistical performance with existing nonparametric sign charts, such as the cumulative sum (CUSUM), exponentially weighted moving average (EWMA), generally weighted moving average (GWMA), and double exponentially weighted moving average (DEWMA) sign charts as well as the parametric TEWMA‐ $\overline{X}$ chart. The results show that the TEWMA sign chart is superior to its competitors, especially for small shifts. Moreover, two examples are given to demonstrate the application of the new scheme.

中文翻译：

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非参数三重指数加权移动平均符号控制图

当没有足够的关于基础分布形式的信息时，将非参数控制图用于过程监控。在本文中，我们基于符号统计量提出了一个三重指数加权移动平均（TEWMA）控制图，用于监视未知连续分布的位置参数。建议的图表的游程特征通过执行蒙特卡洛模拟进行评估。我们还将其统计性能与现有的非参数符号图进行比较，例如累计总和（CUSUM），指数加权移动平均值（EWMA），一般加权移动平均值（GWMA）和双指数加权移动平均值（DEWMA）符号图作为参数TEWMA-$\overline{X}$图表。结果表明，TEWMA标志图优于其竞争对手，尤其是对于小班次。此外，给出了两个例子来说明新方案的应用。