On the Efficacy of State Space Reconstruction Methods in Determining Causality

DOI10.1137/130946344zbMath1370.37041OpenAlexW2152825328MaRDI QIDQ5250032

Tomáš Gedeon, Bree Cummins, Kelly Spendlove

Publication date: 15 May 2015

Published in: SIAM Journal on Applied Dynamical Systems (Search for Journal in Brave)

Full work available at URL: https://scholarworks.montana.edu/xmlui/handle/1/9349

zbMATH Keywords

filtrationcausalitychaotic attractorstate space reconstructionTakens' theoremdelay embeddingconvergent cross-mapping

Mathematics Subject Classification ID

Generic properties, structural stability of dynamical systems (37C20) Invariant manifolds for ordinary differential equations (34C45) Attractors of solutions to ordinary differential equations (34D45)

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Cites Work

• Detecting Causality in Complex Ecosystems
• State space reconstruction in the presence of noise
• An analytic approach to practical state space reconstruction
• Embedology
• Practical method for determining the minimum embedding dimension of a scalar time series
• State space reconstruction parameters in the analysis of chaotic time series - the role of the time window length
• Independent coordinates for strange attractors from mutual information
• Differential Topology
• Investigating Causal Relations by Econometric Models and Cross-spectral Methods
• Embedding theorems for non-uniformly sampled dynamical systems
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