The MVGC multivariate Granger causality toolbox: A new approach to Granger-causal inference. The MVGC Matlab© Toolbox approach to G-causal inference is based on multiple equivalent representations of a VAR model by (i) regression parameters, (ii) the autocovariance sequence and (iii) the cross-power spectral density of the underlying process. It features a variety of algorithms for moving between these representations, enabling selection of the most suitable algorithms with regard to computational efficiency and numerical accuracy.
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References in zbMATH (referenced in 5 articles )
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- Malekpour, Sheida; Sethares, William A.: Conditional Granger causality and partitioned Granger causality: differences and similarities (2015)
- Seth, Anil K.; Barrett, Adam B.; Barnett, Lionel: Causal density and integrated information as measures of conscious level (2011)