A Markov Chain Model for the Multivariate Exponentially Weighted Moving Averages Control Chart
作者:
GeorgeC. Runger,
SharadS. Prabhu,
期刊:
Journal of the American Statistical Association
(Taylor Available online 1996)
卷期:
Volume 91,
issue 436
页码: 1701-1706
ISSN:0162-1459
年代: 1996
DOI:10.1080/01621459.1996.10476741
出版商: Taylor & Francis Group
关键词: Average run length;Exponentially weighted moving averages;Multivariate control chart;Statistical process control
数据来源: Taylor
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 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.
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