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 |
Author: |
Luke Johnston
[aut, cre, cph],
Clemens Wittenbecher
[aut],
Fabian Eichelmann [ctb],
Helena Zacharias [ctb],
Daniel Ibsen
[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 |
NeedsCompilation: |
no |
Language: |
en-US |
Materials: |
README NEWS |
CRAN checks: |
NetCoupler results |