Models for Non Linear Causality Detection in Time Series

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) , and a non-linear version of it based on feed-forward neural networks. This package contains also an implementation of the Transfer Entropy , and the continuous Transfer Entropy using an approximation based on the k-nearest neighbors . 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.


Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.


1.3.9 by Youssef Hmamouche, 11 days ago

Browse source code at

Authors: Youssef Hmamouche [aut, cre] , Sylvain Barthelemy [cph]

Documentation:   PDF Manual  

Task views: Time Series Analysis

GNU General Public License license

Imports methods, timeSeries, Rdpack

Depends on Rcpp

Linking to Rcpp

System requirements: C++11

See at CRAN