NlinTS

Non Linear Time Series Analysis

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.

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Description file content

Package
NlinTS
Type
Package
Title
Non Linear Time Series Analysis
Version
1.3.7
Date
2019-01-22
Maintainer
Youssef Hmamouche
Description
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.
License
GNU General Public License
Depends
Rcpp
Imports
methods, timeSeries, Rdpack
RdMacros
Rdpack
LinkingTo
Rcpp
SystemRequirements
C++11
NeedsCompilation
yes
RoxygenNote
6.0.1
Packaged
2019-01-22 21:54:35 UTC; youssef
Author
Youssef Hmamouche [aut, cre], Sylvain Barthelemy [cph]
Repository
CRAN
Date/Publication
2019-01-22 22:30:03 UTC

install.packages('NlinTS')

1.3.7

a month ago

Youssef Hmamouche

GNU General Public License

Depends on

Rcpp

Imports

methods, timeSeries, Rdpack

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