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

Kazuya Nishimura, Shun Matsuura, Hideo Suzuki

研究成果: Article

7 引用 (Scopus)

抄録

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.

元の言語English
ページ(範囲)7-13
ページ数7
ジャーナルStatistics and Probability Letters
104
DOI
出版物ステータスPublished - 2015 9 1

Fingerprint

EWMA Chart
Process Monitoring
Control Charts
Variable Selection
Multivariate Statistical Process Control
Control charts
Process monitoring
Exponentially weighted moving average
Variable selection

ASJC Scopus subject areas

  • Statistics, Probability and Uncertainty
  • Statistics and Probability

これを引用

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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.",
keywords = "Akaike information criterion, Exponentially weighted moving average, Multivariate control chart, Multivariate statistical process control, Variable selection",
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AU - Matsuura, Shun

AU - Suzuki, Hideo

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KW - Exponentially weighted moving average

KW - Multivariate control chart

KW - Multivariate statistical process control

KW - Variable selection

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