Controlling correlated processes of Poisson counts
Controlling correlated processes of Poisson counts
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DOI：
10.1002/qre.875
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发表时间：
2007-10
影响因子：
2.3
通讯作者：
C. Weiß
中科院分区：
文献类型：
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作者：
C. Weiß
INARMA模型的类是非常适合建模的自相关结构的过程中产生的统计质量控制的上下文中的泊松边缘。在简要回顾了这个广泛的模型家族的基本原理和重要成员之后，我们集中讨论INAR（1）模型，它与质量控制特别相关。我们提出了四种方法来控制这样的计数过程，并比较它们的运行长度性能的模拟研究。结果表明，只有一些失控的情况下，可以有效地控制所讨论的控制方案。版权所有© 2007约翰威利父子有限公司。
The class of INARMA models is well suited to model the autocorrelation structure of processes with Poisson marginals arising in context of statistical quality control. After reviewing briefly the basic principles and important members of this broad family of models, we concentrate on the INAR(1) model, which is of particular relevance for quality control. We suggest four approaches to control such count processes, and compare their run length performance in a simulation study. Results show that only some of the out‐of‐control situations considered can be controlled effectively with the discussed control schemes. Copyright © 2007 John Wiley & Sons, Ltd.