High-dimensional data monitoring using support machines

DOI10.1080/03610918.2019.1588312zbMath1497.62360OpenAlexW2927206695WikidataQ128107421 ScholiaQ128107421MaRDI QIDQ5082664

Edgard M. Maboudou-Tchao

Publication date: 21 June 2022

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

Full work available at URL: https://doi.org/10.1080/03610918.2019.1588312

zbMATH Keywords

tensorhigh-dimensional dataone-class classificationsmall sample size problemsupport tensor vector data description

Mathematics Subject Classification ID

Applications of statistics in engineering and industry; control charts (62P30)

Related Items (2)

Least-squares support tensor data description ⋮ Monitoring multivariate data with high missing rate by pooling univariate statistics

Uses Software

• UCI-ml

Cites Work

• Frequentist-Bayesian Monte Carlo test for mean vectors in high dimension
• Simultaneous monitoring of process mean vector and covariance matrix via penalized likelihood estimation
• Monitoring the covariance matrix with fewer observations than variables
• Tests for mean vectors in high dimension
• A kernel-distance-based multivariate control chart using support vector methods
• Kernel methods for changes detection in covariance matrices
• Kernel distance-based robust support vector methods and its application in developing a robust K-chart

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