Proposal of multivariate control chart using exponentially log-likelihood for detection of change in mean and variability

Yuma Ueno, Yasushi Nagata

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This study aims to detect various small changes in multivariate control charts. In previous studies, the MEWMA control chart was proposed as a detection of mean vector change, the MEWMC control chart was proposed as a detection of variance covariance matrix change, and the ELR control chart was proposed as a detection of the change of the mean vector and the variance covariance matrix. This study proposes two method using log-likelihood. The first method (MEWML control chart) uses the statistic obtained by directly weighting the log-likelihood. The second method (MEWMML control chart) uses obtained maximum likelihood estimate from log-likelihood using the maximum likelihood method. As a result of Monte Carlo simulations using the ARL evaluation index, the study shows that the MEWML control chart is useful for variance covariance matrix change, and the MEWMML control chart is the most useful for various patterns.

Original languageEnglish
Title of host publicationMathematical Methods and Computational Techniques in Science and Engineering II
EditorsNikos Bardis
PublisherAmerican Institute of Physics Inc.
ISBN (Electronic)9780735416987
DOIs
Publication statusPublished - 2018 Jul 27
Event2nd International Conference on Mathematical Methods and Computational Techniques in Science and Engineering - Cambridge, United Kingdom
Duration: 2018 Feb 162018 Feb 18

Publication series

NameAIP Conference Proceedings
Volume1982
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Other

Other2nd International Conference on Mathematical Methods and Computational Techniques in Science and Engineering
Country/TerritoryUnited Kingdom
CityCambridge
Period18/2/1618/2/18

ASJC Scopus subject areas

  • Physics and Astronomy(all)

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