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