An interpretable framework for inferring nonlinear multivariate Granger causality based on self-explaining neural networks.
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Updated
Apr 5, 2023 - Python
An interpretable framework for inferring nonlinear multivariate Granger causality based on self-explaining neural networks.
The asympPDC Package is a MATLAB and Octave package for Partial Directed Coherence (PDC) and Directed Transfer Function (DTF) estimation with asymptotic statistics, allied functions and routines for Granger Causality Test and results pretty plotting.
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This repository contains the Matlab code for implementing the bootstrap panel Granger causality procedure proposed by Kónya (Kónya, L. Exports and growth: Granger causality analysis on OECD countries with a panel data approach. Economic Modelling, 23(6), 978-992, 2006), which is based on the seemingly unrelated regressions (SUR) systems and the …
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