Could network analysis of horizontal visibility graphs be faithfully used to infer long-term memory properties in real-world time series?

DOI10.1016/J.CNSNS.2019.104908OpenAlexW2953857615WikidataQ127558877 ScholiaQ127558877MaRDI QIDQ2207085

Yu Huang, Qimin Deng, Zuntao Fu

Publication date: 22 October 2020

Published in: Communications in Nonlinear Science and Numerical Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cnsns.2019.104908

zbMATH Keywords

topological parameterslong-term memorynonlinear correlationshorizontal visibility graphshort-term correlation

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Small world graphs, complex networks (graph-theoretic aspects) (05C82)

Related Items (3)

Mapping time series into signed networks via horizontal visibility graph ⋮ Generalized Shannon-Fisher index: an effective method to quantify the instability of multivariate time series ⋮ Effective instability quantification for multivariate complex time series using reverse Shannon-Fisher index

Cites Work

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• From time series to complex networks: The visibility graph
• AN INTRODUCTION TO LONG-MEMORY TIME SERIES MODELS AND FRACTIONAL DIFFERENCING
• Complex network approach to fractional time series
• The largest eigenvalue of a graph: A survey
• Networks
• Detecting long-range correlations with detrended fluctuation analysis

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