NlinTS: 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) <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.

Version:	1.4.5
Depends:	Rcpp
Imports:	methods, timeSeries, Rdpack
LinkingTo:	Rcpp
Published:	2021-02-02
Author:	Youssef Hmamouche [aut, cre]
Maintainer:	Youssef Hmamouche <hmamoucheyussef at gmail.com>
License:	GPL-2 | GPL-3 [expanded from: GNU General Public License]
NeedsCompilation:	yes
SystemRequirements:	C++11
In views:	TimeSeries
CRAN checks:	NlinTS results

Documentation:

Reference manual:

NlinTS.pdf

Downloads:

Package source:	NlinTS_1.4.5.tar.gz
Windows binaries:	r-devel: NlinTS_1.4.5.zip, r-release: NlinTS_1.4.5.zip, r-oldrel: NlinTS_1.4.5.zip
macOS binaries:	r-release (arm64): NlinTS_1.4.5.tgz, r-oldrel (arm64): NlinTS_1.4.5.tgz, r-release (x86_64): NlinTS_1.4.5.tgz, r-oldrel (x86_64): NlinTS_1.4.5.tgz
Old sources:	NlinTS archive

Linking:

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