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

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1.4.5 by Youssef Hmamouche, a year ago

Browse source code at

Authors: Youssef Hmamouche [aut, cre]

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