Large data series: modeling the usual to identify the unusual.

DOI10.1016/S0167-9473(99)00079-1zbMath1110.62303OpenAlexW2024025648MaRDI QIDQ1566632

N. Delaunay

Publication date: 4 June 2000

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0167-9473(99)00079-1

zbMATH Keywords

Principal componentsSegmentationLocal modelsFeature extractionData reductionNonlinear dynamical model

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Linear inference, regression (62J99)

Related Items (2)

APPLIED REGRESSION ANALYSIS BIBLIOGRAPHY UPDATE 2000–2001 ⋮ Sampling streaming data with replacement

Uses Software

• longmemo

Cites Work

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• Algorithms and Randomness
• Algorithmic Complexity and Randomness: Recent Developments
• Model-Based Gaussian and Non-Gaussian Clustering

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