Multivariate EWMA control chart based on a variable selection using AIC for multivariate statistical process monitoring

Kazuya Nishimura, Shun Matsuura, Hideo Suzuki

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

In multivariate statistical process control, when a process shift occurs, not all variables but a few variables may shift from the in-control state. This paper proposes a multivariate EWMA control chart based on a variable selection using AIC.

Original languageEnglish
Pages (from-to)7-13
Number of pages7
JournalStatistics and Probability Letters
Volume104
DOIs
Publication statusPublished - 2015 Sep 1

Keywords

  • Akaike information criterion
  • Exponentially weighted moving average
  • Multivariate control chart
  • Multivariate statistical process control
  • Variable selection

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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