Package: einet 1.1.0

Travis Byrum

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.

Authors:Travis Byrum [aut, cre], Anshuman Swain [aut], Brennan Klein [aut], William Fagan [aut]

einet_1.1.0.tar.gz
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einet.pdf |einet.html✨
einet/json (API)
NEWS

# Install 'einet' in R:
install.packages('einet', repos = c('https://travisbyrum.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/travisbyrum/einet/issues

Datasets:
  • karate - Zachary's karate club

On CRAN:

Conda:

4.26 score 3 stars 12 scripts 164 downloads 4 exports 38 dependencies

Last updated 3 years agofrom:c6922be9e0. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 09 2025
R-4.5-winOKMar 09 2025
R-4.5-macOKMar 09 2025
R-4.5-linuxOKMar 09 2025
R-4.4-winOKMar 09 2025
R-4.4-macOKMar 09 2025
R-4.4-linuxOKMar 09 2025
R-4.3-winOKMar 09 2025
R-4.3-macOKMar 09 2025

Exports:%>%causal_emergenceeffective_informationrun_example

Dependencies:assertthatbase64encbslibcachemclicommonmarkcpp11crayondigestentropyfastmapfontawesomefsgluehtmltoolshttpuvigraphjquerylibjsonlitelaterlatticelifecyclemagrittrMatrixmemoisemimepkgconfigpromisesR6rappdirsRcpprlangsassshinysourcetoolsvctrswithrxtable

Introduction

Rendered fromIntroduction.Rmdusingknitr::rmarkdownon Mar 09 2025.

Last update: 2020-05-17
Started: 2020-03-30