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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 |
| DOI: | 10.32614/CRAN.package.einet |
| 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 |
| Reference manual: | einet.pdf |
| Vignettes: |
Introduction |
| 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-oldrel (arm64): einet_0.1.0.tgz, r-release (x86_64): einet_0.1.0.tgz, r-oldrel (x86_64): einet_0.1.0.tgz |
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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.