Simulation study of direct causality measures in multivariate time series

DOI10.3390/E15072635zbMath1336.62153OpenAlexW2152112426MaRDI QIDQ280447

F. Blanchet-Sadri, M. Dambrine

Publication date: 10 May 2016

Published in: Entropy (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.3390/e15072635

zbMATH Keywords

information measuresmultivariate time seriesdirect Granger causality

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Measures of association (correlation, canonical correlation, etc.) (62H20)

Related Items (8)

A novel Granger causality method based on HSIC-Lasso for revealing nonlinear relationship between multivariate time series ⋮ A Fast Method for Detecting Interdependence between Time Series and Its Directionality ⋮ Evaluation of connectivity estimates using spiking neuronal network models ⋮ Assessing directionality and strength of coupling through symbolic analysis: an application to epilepsy patients ⋮ On the relationship between oil and gold before and after financial crisis: linear, nonlinear and time-varying causality testing ⋮ Measuring information transfer by dispersion transfer entropy ⋮ Shortcomings of Transfer Entropy and Partial Transfer Entropy: Extending Them to Escape the Curse of Dimensionality ⋮ Detecting direct causality in multivariate time series: a comparative study

Cites Work

• Unnamed Item
• Graphical modelling of multivariate time series
• A new method of the description of the information flow in the brain structures
• Comparison of linear signal processing techniques to infer directed interactions in multivariate neural systems
• Estimating the dimension of a model
• Partial directed coherence: a new concept in neural structure determination
• Coarse-grained entropy rates for characterization of complex time series
• Linear and nonlinear causality between signals: methods, examples and neurophysiological applications
• Short and long run causality measures: theory and inference
• DETECTION OF DIRECT CAUSAL EFFECTS AND APPLICATION TO EPILEPTIC ELECTROENCEPHALOGRAM ANALYSIS
• Investigating Causal Relations by Econometric Models and Cross-spectral Methods
• A robust method for detecting interdependences: Application to intracranially recorded EEG
• A distribution free plotting position
• A new look at the statistical model identification

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