Variable sampling interval EWMA chart for multivariate coefficient of variation

Heba N. Ayyoub, Michael B. C. Khoo, Sajal Saha and Ming Ha Lee

Communications in Statistics - Theory and Methods, 2022, vol. 51, issue 14, 4617-4637

Abstract: A control chart for monitoring the multivariate coefficient of variation (MCV) is used when the focus is on monitoring the ratio of relative multivariate variability to the mean of a multivariate process. The MCV chart is useful in process monitoring when practitioners are not interested in the consistency of the mean vector or covariance matrix. This study proposes a one-sided upward variable sampling interval (VSI) exponentially weighted moving average (EWMA) chart to detect increasing shifts in MCV squared (γ2) and shows the derivation of formulae to evaluate the performance of the VSI EWMA-γ2 chart by using the Markov chain approach. Comparative investigations show that the proposed chart outperforms existing MCV charts in detecting shifts in process MCV. A numerical example that uses real data reveals that the proposed chart performs well in actual applications.

Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2020.1818100 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:lstaxx:v:51:y:2022:i:14:p:4617-4637

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/lsta20

DOI: 10.1080/03610926.2020.1818100

Access Statistics for this article

Communications in Statistics - Theory and Methods is currently edited by Debbie Iscoe

More articles in Communications in Statistics - Theory and Methods from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().