einet: Effective Information and Causal Emergence

Methods and utilities for causal emergence. Used to explore and compute various information theory metrics for networks, such as effective information, effectiveness and causal emergence.

Version: 0.1.0
Depends: R (≥ 3.2.0)
Imports: assertthat, igraph, magrittr, shiny, entropy
Suggests: testthat, RColorBrewer, knitr, rmarkdown, bench
Published: 2020-04-23
Author: Travis Byrum [aut, cre], Anshuman Swain [aut], Brennan Klein [aut], William Fagan [aut]
Maintainer: Travis Byrum <tbyrum at terpmail.umd.edu>
BugReports: https://github.com/travisbyrum/einet/issues
License: MIT + file LICENSE
URL: https://github.com/travisbyrum/einet
NeedsCompilation: no
Materials: README
CRAN checks: einet results

Documentation:

Reference manual: einet.pdf
Vignettes: Introduction

Downloads:

Package source: einet_0.1.0.tar.gz
Windows binaries: r-devel: einet_0.1.0.zip, r-release: einet_0.1.0.zip, r-oldrel: einet_0.1.0.zip
macOS binaries: r-release (arm64): einet_0.1.0.tgz, r-release (x86_64): einet_0.1.0.tgz, r-oldrel: einet_0.1.0.tgz

Linking:

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