The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Granger Causality and Transfer Entropy Are Equivalent for Gaussian Variables
Open accessAbstract
Granger causality is a statistical notion of causal influence based on prediction via vector autoregression. Developed originally in the field of econometrics, it has since found application in a broader arena, particularly in neuroscience. More recently transfer entropy, an information-theoretic measure of time-directed information transfer between jointly dependent processes, has gained traction in a similarly wide field. While it has been recognized that the two concepts must be related, the exact relationship has until now not been formally described. Here we show that for Gaussian variables, Granger causality and transfer entropy are entirely equivalent, thus bridging autoregressive and information-theoretic approaches to data-driven causal inference.
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Citations
Cites
Investigating causal relations by econometric models and cross-spectral methods
Granger, C. W. J. (1969) · Econometrica · doi:10.2307/1912791 · Cited by 22,989
Causality: Models, Reasoning, and Inference
Pearl, J. (2009) · doi:10.1017/cbo9780511803161 · Cited by 11,653
Cited by
Granger causality analysis in neuroscience and neuroimaging
Seth, A. K., Barrett, A. B., & Barnett, L. (2015) · The Journal of Neuroscience · doi:10.1523/jneurosci.4399-14.2015 · Cited by 928
Self-citationAnalysing connectivity with Granger causality and dynamic causal modelling
Friston, K., Moran, R., & Seth, A. K. (2013) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2012.11.010 · Cited by 684
Self-citationCausal network reconstruction from time series: From theoretical assumptions to practical estimation
Runge, J. (2018) · Chaos: An Interdisciplinary Journal of Nonlinear Science · doi:10.1063/1.5025050 · Cited by 422
Unraveling the cause-effect relation between time series
Liang, X. S. (2014) · Physical Review E · doi:10.1103/physreve.90.052150 · Cited by 409
Practical Measures of Integrated Information for Time-Series Data
Barrett, A. B., & Seth, A. K. (2011) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1001052 · Cited by 225
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Metadata
- Authors
- Barnett, L., Barrett, A. B., & Seth, A. K.
- Venue
- Physical Review Letters
- Publisher
- American Physical Society (APS)
- Published
- 2009-12-04
- Volume
- 103
- Issue
- 23
- Pages
- 238701-238701
- ISSN
- 0031-9007 (ISSN-L)
- 1079-7114
- OpenAlex
- W2079656335
- Cited by
- 1,139
- References
- 2
- FWCI
- 48.08
- Type
- journal article
- Language
- en
- Open access
- green
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- Barnett, L., Barrett, A. B., & Seth, A. K. (2009). Granger Causality and Transfer Entropy Are Equivalent for Gaussian Variables. Physical Review Letters. https://doi.org/10.1103/physrevlett.103.238701
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