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

DOI10.1016/J.SPL.2015.05.003zbMath1396.62288OpenAlexW847212691MaRDI QIDQ491685

Shun Matsuura, Kazuya Nishimura, Hideo Suzuki

Publication date: 19 August 2015

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.spl.2015.05.003

zbMATH Keywords

Akaike information criterionvariable selectionmultivariate statistical process controlexponentially weighted moving averagemultivariate control chart

Mathematics Subject Classification ID

Applications of statistics in engineering and industry; control charts (62P30) Statistical aspects of information-theoretic topics (62B10)

Related Items (1)

Adaptive multivariate EWMA charts for monitoring sparse mean shifts based on parameter optimization design

Cites Work

• Simultaneous monitoring of process mean vector and covariance matrix via penalized likelihood estimation
• Multivariate Statistical Process Control Using LASSO
• Principal Variables
• A Multivariate Exponentially Weighted Moving Average Control Chart

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