RTransferEntropy: Measuring Information Flow Between Time Series with Shannon and Renyi Transfer Entropy

Measuring information flow between time series with Shannon and Rényi transfer entropy. See also Dimpfl and Peter (2013) <doi:10.1515/snde-2012-0044> and Dimpfl and Peter (2014) <doi:10.1016/j.intfin.2014.03.004> for theory and applications to financial time series. Additional references can be found in the theory part of the vignette.

Version: 0.2.7
Depends: R (≥ 3.1.2)
Imports: future, future.apply, Rcpp
LinkingTo: Rcpp
Suggests: data.table, ggplot2, gridExtra, knitr, quantmod, rmarkdown, testthat, vars, xts, zoo
Published: 2018-09-21
Author: Simon Behrendt [aut, cre], David Zimmermann [aut], Thomas Dimpfl [aut], Franziska Peter [aut]
Maintainer: Simon Behrendt <simon.behrendt at zu.de>
BugReports: https://github.com/BZPaper/RTransferEntropy/issues
License: GPL-3
URL: https://github.com/BZPaper/RTransferEntropy
NeedsCompilation: yes
Materials: README
In views: TimeSeries
CRAN checks: RTransferEntropy results

Downloads:

Reference manual: RTransferEntropy.pdf
Vignettes: RTransferEntropy
Package source: RTransferEntropy_0.2.7.tar.gz
Windows binaries: r-devel: RTransferEntropy_0.2.7.zip, r-release: RTransferEntropy_0.2.7.zip, r-oldrel: RTransferEntropy_0.2.7.zip
OS X binaries: r-release: RTransferEntropy_0.2.7.tgz, r-oldrel: RTransferEntropy_0.2.7.tgz
Old sources: RTransferEntropy archive

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