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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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