NetCoupler: Inference of Causal Links Between a Network and an External Variable (original) (raw)
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:
0.1.0
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:
2022-04-08
DOI:
10.32614/CRAN.package.NetCoupler
Author:
Luke Johnston 
[aut, cre, cph], Clemens Wittenbecher [aut], Fabian Eichelmann [ctb], Helena Zacharias [ctb], Daniel Ibsen [ctb]
Maintainer:
Luke Johnston
BugReports:
https://github.com/NetCoupler/NetCoupler/issues
License:
MIT + file
URL:
https://github.com/NetCoupler/NetCoupler
NeedsCompilation:
no
Language:
en-US
Materials:
CRAN checks: