Random projections and Hotelling’s T2 statistics for change detection in high-dimensional data streams

DOI10.2478/amcs-2013-0034zbMath1282.93064OpenAlexW1988380277MaRDI QIDQ2872879

Ewa Skubalska-Rafajłowicz

Publication date: 16 January 2014

Published in: International Journal of Applied Mathematics and Computer Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.2478/amcs-2013-0034

zbMATH Keywords

dimensionality reductionchange detectionrandom projectionsprocess monitoringmultidimensional control charts

Mathematics Subject Classification ID

Control/observation systems involving computers (process control, etc.) (93C83) System structure simplification (93B11) Stochastic systems in control theory (general) (93E03)

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Cites Work

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• The random projection method in goodness of fit for functional data
• The Johnson-Lindenstrauss lemma and the sphericity of some graphs
• Principal component analysis.
• Multivariate control charts based on a projection approach
• An algorithmic theory of learning: Robust concepts and random projection
• Approximate nearest neighbors and the fast Johnson-Lindenstrauss transform
• Statistical Distributions
• Extensions of Lipschitz mappings into a Hilbert space
• On variants of the Johnson–Lindenstrauss lemma
• Nearest-neighbor-preserving embeddings
• Random Projection RBF Nets for Multidimensional Density Estimation
• On the Performance of Clustering in Hilbert Spaces
• The Generalization of Student's Ratio
• An elementary proof of a theorem of Johnson and Lindenstrauss
• Nonlinear Estimators and Tail Bounds for Dimension Reduction in l 1 Using Cauchy Random Projections
• Some Theorems on Distribution Functions