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Detecting changes in location using distribution-free control charts with big data

机译:使用具有大数据的无分布控制图来检测位置变化

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This paper proposes a simple distribution-free control chart for monitoring shifts in location when the process distribution is continuous but unknown. In particular, we are concerned with big data applications where there are sufficient in-control data that can be used to specify certain quantiles of interest which, in turn, are used to assess whether the new, incoming data to be monitored are in control. The distribution-free chart is shown to lose very little power against the Shewhart charts designed for normally distributed data. The proposed charts offer a practical and robust alternative to the classical Shewhart charts which assume normality, particularly when monitoring quantiles and the data distribution is skewed. The effect of the size of the reference sample is examined on the assumption that the quantiles are known. Conclusions and recommendations are offered.
机译:本文提出了一种简单的无分布控制图,用于在过程分布连续但未知的情况下监视位置变化。特别地,我们关注的是大数据应用程序,在这些应用程序中,有足够的控制中数据可用于指定特定的目标分位数,这些分位数又可用于评估要监视的新传入数据是否处于受控状态。与为正态分布数据设计的Shewhart图表相比,无分布图的损失很小。所提出的图表为假设具有正态性的经典Shewhart图表提供了一种实用且强大的替代方法,尤其是在监视分位数和数据分布倾斜时。在已知分位数的假设下检查参考样本大小的影响。提供结论和建议。

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