Kernel methods for changes detection in covariance matrices

DOI10.1080/03610918.2017.1322701OpenAlexW2608431721MaRDI QIDQ5084948

Edgard M. Maboudou-Tchao

Publication date: 29 June 2022

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

Full work available at URL: https://doi.org/10.1080/03610918.2017.1322701

zbMATH Keywords

Mercer kernelone-class classificationmatrix variatessupport matricesmatrix outlier detectionpower-Euclidean kernel

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30)

Related Items (2)

High-dimensional data monitoring using support machines ⋮ Least-squares support tensor data description

Uses Software

• glasso

Cites Work

• Unnamed Item
• Sparse inverse covariance estimation with the graphical lasso
• Simultaneous monitoring of process mean vector and covariance matrix via penalized likelihood estimation
• Monitoring the covariance matrix with fewer observations than variables
• Estimating the Support of a High-Dimensional Distribution
• A kernel-distance-based multivariate control chart using support vector methods
• Kernel distance-based robust support vector methods and its application in developing a robust K-chart

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