Package: NlinTS
Type: Package
Title: Models for Non Linear Causality Detection in Time Series
Version: 1.4.2
Date: 2020-08-03
Authors@R: c(person("Youssef", "Hmamouche", role = c("aut", "cre"), email = "hmamoucheyussef@gmail.com"))
Maintainer: Youssef Hmamouche <hmamoucheyussef@gmail.com>
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) <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.
License: GNU General Public License
Depends: Rcpp
Imports: methods, timeSeries, Rdpack
RdMacros: Rdpack
LinkingTo: Rcpp
SystemRequirements: C++11
NeedsCompilation: yes
RoxygenNote: 7.1.0
Author: Youssef Hmamouche [aut, cre]
Packaged: 2020-08-03 12:16:40 UTC; youssef
Repository: CRAN
Date/Publication: 2020-08-03 15:10:03 UTC
Built: R 4.1.0; x86_64-w64-mingw32; 2020-08-05 23:43:54 UTC; windows
Archs: i386, x64
