Nonlinear parametric model for Granger causality of time series
Disordered Systems and Neural Networks
2009-11-11 v1 Statistical Mechanics
Machine Learning
Medical Physics
Quantitative Methods
Abstract
We generalize a previously proposed approach for nonlinear Granger causality of time series, based on radial basis function. The proposed model is not constrained to be additive in variables from the two time series and can approximate any function of these variables, still being suitable to evaluate causality. Usefulness of this measure of causality is shown in a physiological example and in the study of the feed-back loop in a model of excitatory and inhibitory neurons.
Keywords
Cite
@article{arxiv.cond-mat/0602183,
title = {Nonlinear parametric model for Granger causality of time series},
author = {Daniele Marinazzo and Mario Pellicoro and Sebastiano Stramaglia},
journal= {arXiv preprint arXiv:cond-mat/0602183},
year = {2009}
}
Comments
4 pages 5 figures