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 |
| 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 + fileLICENSE |
| URL: | https://github.com/travisbyrum/einet |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | einet results |
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