Abstract

Dynamic data detection is one of the main concerns in the statistical process control (SPC) field. Here we focus on monitoring parametric multivariate dynamic data streams using the ARMAX-GARCH model, which reflects both the influence of exogenous variables on the mean vector and the heterogeneity of the covariance matrix. A quasi maximum likelihood estimator is used to estimate the parameter vector of a dynamic process, and a top-r control scheme is proposed to monitor the parameters of multi-dimensional data streams. Finally, a real-data example of monitoring landslide illustrates the superiorities of the proposed scheme.

中文翻译：

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使用 ARMAX-GARCH 模型检测参数多元动态数据流的变化

摘要

动态数据检测是统计过程控制（SPC）领域的主要关注点之一。这里我们重点关注使用ARMAX-GARCH模型监测参数多元动态数据流，该模型既反映了外生变量对均值向量的影响，也反映了协方差矩阵的异质性。使用准最大似然估计器估计动态过程的参数向量，并提出了top -r控制方案来监控多维数据流的参数。最后，通过监测滑坡的真实数据示例说明了该方案的优越性。