A Markov chain model for the multivariate exponentially weighted moving averages control chart

• 成果类型: Article
• 署名作者: Runger, GC; Prabhu, SS
• 署名单位: SAS Institute Inc
• 刊物名称: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
• ISSN/ISSBN: 0162-1459
• DOI: 10.2307/2291599
• 发表日期: 1996
• 页码: 1701-1706
• 关键词: run-length; integral-equation; control schemes

摘要

A Markov chain approximation is used to determine the run length performance of a multivariate statistical process control chart. The Markov chain approach is widely used in the analysis of univariate control charts, and we extend the advantages of this type of analysis to a multivariate exponentially weighted moving averages control chart. The analysis can be applied whenever the multivariate control statistic can be modeled as a Markov chain and the run length performance depends on the off-target mean only through the noncentrality parameter.