In nearly all papers on process control for time-dependent data, it is assumed that the underlying target process is stationary. In the present paper, the target process is modeled by a multivariate state-space model which may be non-stationary. Our aim is to monitor its mean behavior. The likelihood ratio method, the sequential probability ratio test and the Shiryaev–Roberts procedure are applied to derive control charts signaling a change from the supposed mean structure. These procedures depend on certain reference values which have to be chosen by the practitioners. The corresponding generalized approaches are considered as well, and generalized control charts are determined for state-space processes. These schemes do not have further design parameters. In an extensive simulation study, the behavior of the introduced schemes is compared with each other using various performance criteria like the average run length, the average delay, the probability of a successful detection, and the probability of a false detection.

中文翻译：

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监视非平稳过程

在几乎所有关于时间相关数据的过程控制的论文中，都假定基本目标过程是固定的。在本文中，目标过程由可能是非平稳的多元状态空间模型建模。我们的目的是监视其平均行为。应用似然比方法，顺序概率比检验和Shiryaev-Roberts程序来得出控制图，该控制图表明假定的均值结构发生了变化。这些程序取决于从业者必须选择的某些参考值。还考虑了相应的通用方法，并确定了状态空间过程的通用控制图。这些方案没有其他设计参数。在广泛的模拟研究中，