Title: Inference of Causal Links Between a Network and an External
person("Luke", "Johnston", , "lwjohnst@gmail.com", role = c("aut", "cre", "cph"),
person("Clemens", "Wittenbecher", , "Clemens.Wittenbecher@dife.de", role = "aut",
person("Fabian", "Eichelmann", , "Fabian.Eichelmann@dife.de", role = "ctb"),
person("Helena", "Zacharias", , "helena.zacharias@helmholtz-muenchen.de", role = "ctb"),
person("Daniel", "Ibsen", , "dbi@ph.au.dk", role = "ctb",
Description: 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.
Imports: checkmate, dplyr, ids, igraph, lifecycle, magrittr, pcalg,
ppcor, purrr, rlang (>= 0.4.6), stats, tibble, tidyselect,
Suggests: broom, furrr, knitr, rmarkdown, spelling, testthat (>= 2.1.0)
Author: Luke Johnston [aut, cre, cph] (<https://orcid.org/0000-0003-4169-2616>),

Title: Network-Based Discriminant Analysis Subject to Multi-Label
Description: Implementation of discriminant analysis with network structures in predictors accommodated to do classification and prediction.
Packaged: 2022-01-18 08:40:34 UTC; Li-Pang Chen

Packaged: 2022-05-27 02:48:38 UTC; Li-Pang Chen

Title: Network Data for McFarland's SNA R labs
Author: Mike Nowak <michael.nowak@gmail.com>, Sean J Westwood
Description: This package contains all data needed for Dan McFarland's

Packaged: 2010-06-24 03:03:31 UTC; Administrator

Authors@R: c(person("Sosa", "Sebastian", email = "s.sosa@live.fr", role = c("aut", "cre")))
Description: Social network analysis has become an essential tool in the study of complex systems. 'NetExplorer' allows to visualize and explore complex systems. It is based on 'd3js' library that brings 1) Graphical user interface;  2) Circular, linear, multilayer and force Layout; 3) Network live exploration and 4) SVG exportation.

Title: Network Applications to Facial Communication Data
Description: Functions to analyze and visualize communication data,
based on network theory and resampling methods.
Primarily targeted at datasets of facial expressions coded with the Facial Action Coding System.
Ekman, P., Friesen, W. V., & Hager, J. C. (2002). "Facial action coding system - investigator's guide" <https://www.paulekman.com/facial-action-coding-system/>.
Imports: parallel, doParallel, igraph, ggplot2, ggraph, picante, rlang,
Maintainer: Alan V. Rincon <avrincon1@gmail.com>