Inference of Causal Links Between a Network and an External Variable [R package NetCoupler version 0.1.1]

NetCoupler: Inference of Causal Links Between a Network and an External Variable

The 'NetCoupler' algorithm identifies potential direct effects of correlated, high-dimensional variables formed as a network with an external variable. The external variable may act as the dependent/response variable or as an independent/predictor variable to the network.

Version: 0.1.1

Depends: R (≥ 3.5.0)

Imports: checkmate, dplyr, ids, igraph, lifecycle, magrittr, pcalg, ppcor, purrr, rlang (≥ 0.4.6), stats, tibble, tidyselect, utils, tidygraph

Suggests: broom, furrr, knitr, rmarkdown, spelling, testthat (≥ 2.1.0)

Published: 2025年05月20日

DOI: 10.32614/CRAN.package.NetCoupler

Author: Luke Johnston ORCID iD [aut, cre, cph], Clemens Wittenbecher ORCID iD [aut, cph], Fabian Eichelmann [ctb], Helena Zacharias [ctb], Daniel Ibsen ORCID iD [ctb]

Maintainer: Luke Johnston <lwjohnst at gmail.com>

BugReports: https://github.com/NetCoupler/NetCoupler/issues

License: MIT + file LICENSE

URL: https://github.com/NetCoupler/NetCoupler, https://netcoupler.github.io/NetCoupler/

NeedsCompilation: no

Language: en-US

Materials: README, NEWS

CRAN checks: NetCoupler results