Title

Multivariate Exponentially Weighted Moving Covariance Matrix

Keywords

Average run length; Average run length bias; Regression adjustment

Abstract

Multivariate exponentially weighted moving average (MEWMA) charts are among the best control charts for detecting small changes in any direction. The well-known MEWMA is directed at changes in the mean vector. But changes can occur in either the location or the variability of the correlated multivariate quality characteristics, calling for parallel methodologies for detecting changes in the covariance matrix. This article discusses an exponentially weighted moving covariance matrix for monitoring the stability of the covariance matrix of a process. Used together with the location MEWMA, this chart provides a way to satisfy Shewhart's dictum that proper process control monitor both mean and variability. We show that the chart is competitive, generally outperforming current control charts for the covariance matrix. © 2008 American Statistical Association and the American Society for Quality.

Publication Date

5-1-2008

Publication Title

Technometrics

Volume

50

Issue

2

Number of Pages

155-166

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1198/004017008000000163

Socpus ID

46749103696 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/46749103696

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