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tseriesEntropy: Entropy Based Analysis and Tests for Time Series

Implements an Entropy measure of dependence based on the Bhattacharya-Hellinger-Matusita distance. 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.

Version: 0.7-2
Depends: R (≥ 2.14.0)
Imports: cubature, methods, parallel, stats, graphics, ks
Suggests: knitr, rmarkdown
Published: 2023-08-09
Author: Simone Giannerini ORCID iD [aut, cre]
Maintainer: Simone Giannerini <simone.giannerini at unibo.it>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Citation: tseriesEntropy citation info
Materials: README NEWS
In views: TimeSeries
CRAN checks: tseriesEntropy results

Documentation:

Reference manual: tseriesEntropy.pdf

Downloads:

Package source: tseriesEntropy_0.7-2.tar.gz
Windows binaries: r-devel: tseriesEntropy_0.7-2.zip, r-release: tseriesEntropy_0.7-2.zip, r-oldrel: tseriesEntropy_0.7-2.zip
macOS binaries: r-release (arm64): tseriesEntropy_0.7-2.tgz, r-oldrel (arm64): tseriesEntropy_0.7-2.tgz, r-release (x86_64): tseriesEntropy_0.7-2.tgz, r-oldrel (x86_64): tseriesEntropy_0.7-2.tgz
Old sources: tseriesEntropy archive

Linking:

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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.
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