Principal component analysis-based control charts using support vector machines for multivariate non-normal distributions

DOI10.1080/03610918.2018.1506032OpenAlexW2914783956WikidataQ128423426 ScholiaQ128423426MaRDI QIDQ5086321

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Publication date: 5 July 2022

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2018.1506032

zbMATH Keywords

bootstrapprincipal component analysissupport vector machinemultivariate control charts

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (1)

Monitoring multivariate data with high missing rate by pooling univariate statistics

Cites Work

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• Bootstrap methods for standard errors, confidence intervals, and other measures of statistical accuracy
• Principal component analysis: a review and recent developments
• Robust principal component analysis?
• Multivariate CUSUM Quality-Control Procedures
• Multivariate Generalizations of Cumulative Sum Quality-Control Schemes
• Control Procedures for Residuals Associated with Principal Component Analysis
• A Multivariate Exponentially Weighted Moving Average Control Chart
• A kernel-distance-based multivariate control chart using support vector methods
• THE CONTROL CHART FOR INDIVIDUAL OBSERVATIONS FROM A MULTIVARIATE NON-NORMAL DISTRIBUTION

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