Models for Non Linear Causality Detection in Time Series
The Granger causality test
Augmented Dickey_Fuller test
Continuous entropy
Discrete Entropy
Continuous Mutual Information
Discrete multivariate Mutual Information
Discrete bivariate Mutual Information
A non linear Granger causality test
Models for non-linear causality detection in time series.
Continuous Transfer Entropy
Discrete Transfer Entropy
Artificial Neural Network VAR (Vector Auto-Regressive) model using a M...
Models for non-linear time series analysis and causality detection. The main functionalities of this package consist of an implementation of the classical causality test (C.W.J.Granger 1980) <doi:10.1016/0165-1889(80)90069-X>, and a non-linear version of it based on feed-forward neural networks. This package contains also an implementation of the Transfer Entropy <doi:10.1103/PhysRevLett.85.461>, and the continuous Transfer Entropy using an approximation based on the k-nearest neighbors <doi:10.1103/PhysRevE.69.066138>. There are also some other useful tools, like the VARNN (Vector Auto-Regressive Neural Network) prediction model, the Augmented test of stationarity, and the discrete and continuous entropy and mutual information.