nonlinear Granger causality

ROLE OF MODEL NONLINEARITY FOR GRANGER CAUSALITY BASED COUPLING ESTIMATION FOR PATHOLOGICAL TREMOR

Estimating coupling between systems of different nature is an urgent field of nonlinear dynamics method application. This work aims to compare classical linear Granger approach and its nonlinear analogues based on analysis of ethalon dynamical systems and neurophysiological data. The results achieved show nonlinear approach to be more sensitive, and so it is able to detect significant coupling, when linear one fails.

SELECTING TIME SCALES FOR EMPIRICAL MODEL CONSTRUCTION

The task is considered of taking into account the multiple time scales of original time series, with these time series being used for Granger causality estimation. It is proposed to use the combination of prediction length and lag, different in value, that could be fruitful for comparatively short times series, e. g. of medical-biological nature. The automated methods are constructed to select lag and prediction length values. The proposed approach is tested on a set of examples – ethalon systems.