Abstract

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.

Original languageEnglish (US)
Pages (from-to)1701-1706
Number of pages6
JournalJournal of the American Statistical Association
Volume91
Issue number436
StatePublished - Dec 1996

Fingerprint

Exponentially Weighted Moving Average Control Chart
Markov Chain Model
Run Length
Control Charts
Markov chain
Multivariate Statistical Process Control
Markov Chain Approximation
Noncentrality Parameter
Univariate
Statistic
Target
Control charts
Markov chain model
Exponentially weighted moving average

Keywords

  • Average run length
  • Exponentially weighted moving averages
  • Multivariate control chart
  • Statistical process control

ASJC Scopus subject areas

  • Mathematics(all)
  • Statistics and Probability

Cite this

A Markov chain model for the multivariate exponentially weighted moving averages control chart. / Runger, George; Prabhu, Sharad S.

In: Journal of the American Statistical Association, Vol. 91, No. 436, 12.1996, p. 1701-1706.

Research output: Contribution to journalArticle

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