An algorithm for arbitrary-order cumulant tensor calculation in a sliding window of data streams

DOI10.2478/AMCS-2019-0015zbMath1454.62257arXiv1701.06446OpenAlexW2964231157MaRDI QIDQ2314540

Krzysztof Domino, Piotr Gawron

Publication date: 29 July 2019

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

Full work available at URL: https://arxiv.org/abs/1701.06446

zbMATH Keywords

data streaminghigh-order cumulantsnon-normally distributed datatime-series statistics

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Estimation in multivariate analysis (62H12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Statistical aspects of big data and data science (62R07)

Related Items (2)

Multivariate cumulants in outlier detection for financial data analysis ⋮ CumulantsUpdates.jl

Uses Software

• Julia
• CuBICA
• SymmetricTensors.jl
• Cumulants.jl
• Cummulants.jl

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• Monte Carlo approximate tensor moment simulations
• Julia: A Fresh Approach to Numerical Computing
• Knowledge Discovery from Data Streams
• Efficient Computation of Higher-Order Cumulant Tensors
• High-Resolution Direction Finding From Higher Order Statistics: The$2rm q$-MUSIC Algorithm
• Consumption-Based Asset Pricing with Higher Cumulants
• CuBICA: Independent Component Analysis by Simultaneous Third- and Fourth-Order Cumulant Diagonalization

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