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On the Run Length of a State-Space Control Chart for Multivariate Autocorrelated Data

机译:多元自相关数据的状态空间控制图的游程长度

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The literature on statistical process control (SPC) describes the negative effects of autocorrelation in terms of the increase in false alarms. This has been treated by the individual modeling of each series or the application of VAR models. In the former case, the analysis of the cross correlation structure between the variables is altered. In the latter, if the cross correlation is not strong, the filtering process may modify the weakest relations. In order to improve these aspects, state-space models have been introduced in multivariate statistical process control (MSPC). This article presents a proposal for building a control chart for innovations, estimating its average run length to highlight its advantages over the VAR approach mentioned above.
机译:统计过程控制(SPC)的文献描述了虚假警报增加带来的自相关的负面影响。每个系列的单独建模或VAR模型的应用已解决了这一问题。在前一种情况下,变量之间的互相关结构的分析被更改。在后者中,如果互相关性不强,则滤波过程可能会修改最弱的关系。为了改进这些方面,在多元统计过程控制(MSPC)中引入了状态空间模型。本文提出了一个构建创新控制图的建议,估算其平均运行时间以突出其相对于上述VAR方法的优势。

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