einet: Effective Information and Causal Emergence (original) (raw)
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 |
| BugReports: | https://github.com/travisbyrum/einet/issues |
| License: | MIT + file |
| URL: | https://github.com/travisbyrum/einet |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | einet results |
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