The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
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.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.