c(person("Derek", "Corcoran", email = "derek.corcoran.barrios@gmail.com",
role = c("aut", "cre"), comment = c(ORCID = "0000-0002-0248-6230")), person("M. Isidora", "Ávila-Thieme", email = "msavila@uc.cl",
role = c("aut"), comment = c(ORCID = "0000-0003-0772-4717")), person("Fernanda S.", "Valdovinos", role = c("aut")), person("Sergio A.", "Navarrete", role = c("aut")),
person("Pablo A.", "Marquet", role = c("aut"), comment = c(ORCID = "0000-0001-6369-9339")), person("Erik", "Kusch", email = "erik.kusch@bio.au.dk",
role = c("aut"), comment = c(ORCID = "0000-0002-4984-7646")))
broom, doParallel, dplyr, foreach, ggplot2, igraph, magrittr,
network, scales, sna, stats, tidyr, MASS, parallel, purrr,
methods
Derek Corcoran [aut, cre] (<https://orcid.org/0000-0002-0248-6230>),
M. Isidora Ávila-Thieme [aut] (<https://orcid.org/0000-0003-0772-4717>),
Fernanda S. Valdovinos [aut],
Sergio A. Navarrete [aut],
Pablo A. Marquet [aut] (<https://orcid.org/0000-0001-6369-9339>),
Erik Kusch [aut] (<https://orcid.org/0000-0002-4984-7646>)

Extinction Simulation in Ecological Networks
Simulates the extinction of species in ecological networks and it analyzes
its cascading effects, described in Dunne et al. (2002) <doi:10.1073/pnas.192407699>.

c(person("Fridolin", "Linder", email = "fridolin.linder@gmail.com",
role = c("aut", "cre")),
person("Bruce", "Desmarais", role = "ctb"))
This is an R implementation of the netinf algorithm (Gomez Rodriguez, Leskovec, and Krause, 2010)<doi:10.1145/1835804.1835933>. Given a set of events that spread between a set of nodes the algorithm infers the most likely stable diffusion network that is underlying the diffusion process.
Rcpp (>= 0.12.5), assertthat, checkmate, ggplot2, ggrepel,
stats
testthat, knitr, rmarkdown, pander, igraph, utils
Fridolin Linder [aut, cre],
Bruce Desmarais [ctb]

testthat, knitr, rmarkdown, pander, igraph, utils, dplyr

Regression Model on Network-Linked Data with Statistical
Inference
Linear regression model with nonparametric network effects on network-linked observations. The model is proposed by Le and Li (2020) <arXiv:2007.00803> and is assumed on observations that are connected by a network or similar relational data structure. The model does not assume that the relational data or network structure to be precisely observed; thus, the method is provably robust to a certain level of perturbation of the network structure. The package contains the estimation and inference function for the model.
Matrix, stats, methods, randnet, RSpectra