The R package tseriesEntropy implements an entropy measure of
dependence based on the Bhattacharya-Hellinger-Matusita distance. It can
be used as a (nonlinear) autocorrelation/crosscorrelation function for
continuous and categorical time series. The package includes tests for
serial and cross dependence and nonlinearity based on it. Some routines
have a parallel version that can be used in a multicore/cluster
environment. The package makes use of S4 classes.
Giannerini S., Maasoumi E., Bee Dagum E., (2015), Entropy testing for nonlinear serial dependence in time series, Biometrika, 102(3), 661–675.
Giannerini S, Goracci G. (2023) Entropy-Based Tests for Complex Dependence in Economic and Financial Time Series with the R Package tseriesEntropy, Mathematics, 11(3):757.
Granger C. W. J., Maasoumi E., Racine J., (2004) A dependence metric for possibly nonlinear processes. Journal of Time Series Analysis, 25(5), 649–669.
You can install the stable version on CRAN:
install.packages('tseriesEntropy')You can install the development version of tseriesEntropy from GitHub with:
# install.packages("devtools")
devtools::install_github("sgiannerini/tseriesEntropy")This package is free and open source software, licensed under GPL.