Detection of nonlinearity and chaoticity in time series using the transportation distance function

DOI10.1016/S0375-9601(02)01083-6zbMath0999.62507OpenAlexW2147556416MaRDI QIDQ1612855

Sukanta Basu, Efi Foufoula-Georgiou

Publication date: 4 September 2002

Published in: Physics Letters. A (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0375-9601(02)01083-6

zbMATH Keywords

competition seriestwo-step framework

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Time series analysis of dynamical systems (37M10)

Related Items (4)

Correntropy as a novel measure for nonlinearity tests ⋮ Estimating intermittency exponent in neutrally stratified atmospheric surface layer flows: A robust framework based on magnitude cumulant and surrogate analyses ⋮ Detecting nonlinearity in short and noisy time series using the permutation entropy ⋮ Revisiting multifractality of TCP traffic using multifractal detrended fluctuation analysis

Uses Software

• TISEAN

Cites Work

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• Measuring the distance between time series
• Testing for nonlinearity in time series: the method of surrogate data
• Testing for nonlinearity using redundancies: Quantitative and qualitative aspects
• Surrogate time series.
• On the detection of determinism in a time series
• Coarse-grained entropy rates for characterization of complex time series
• Practical implementation of nonlinear time series methods: The <scp>TISEAN</scp> package
• Pathological tremors: Deterministic chaos or nonlinear stochastic oscillators?

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