MULTIplex NEtworks with Shared Structure
person(given = "Peter W.",
family = "MacDonald",
role = c("aut", "cre"),
email = "pwmacdon@umich.edu",
comment = c(ORCID = "0000-0001-7024-7242"))
Model fitting and simulation for Gaussian and logistic inner
product MultiNeSS models for multiplex networks. The package implements
a convex fitting algorithm with fully adaptive parameter tuning,
including options for edge cross-validation. For more details see
MacDonald et al. (2020).
Peter W. MacDonald [aut, cre] (<https://orcid.org/0000-0001-7024-7242>)

Analysis and Mining of Multilayer Social Networks
Functions for the creation/generation and analysis of multilayer social networks.

Matteo Magnani, Mikael Dubik (lart and glouvain functions). The package uses functions from dlib, Eigen, Spectra and eclat libraries, whose code has been included in our source package.

Matteo Magnani, Davide Vega, Mikael Dubik (glouvain). The package uses functions from eclat (www.borgelt.net/eclat.html), for association rule mining, Eigen (eigen.tuxfamily.org) and spectra (https://spectralib.org), for matrix manipulation, Infomap (www.mapequation.org), for the Infomap community detection method, and Howard Hinnant's date and time library (https://github.com/HowardHinnant/date). The code from this libraries has been included in our source package.

igraph (>= 1.0.1), Rcpp (>= 0.12.11), methods, RColorBrewer

igraph (>= 1.0.1), Rcpp (>= 1.0.1), methods, RColorBrewer

Matteo Magnani, Davide Vega, Mikael Dubik (glouvain). The package uses functions from eclat (www.borgelt.net/eclat.html), for association rule mining, Eigen (eigen.tuxfamily.org) and spectra (https://spectralib.org), for matrix manipulation, Infomap (www.mapequation.org), for the Infomap community detection method, and Howard Hinnant's date and time library (https://github.com/HowardHinnant/date). The code from these libraries has been included in our source package.
the current version of the library has been developed as part of
the European Union's Horizon 2020 research and innovation
programme under grant agreement No. 727040 (Virt-EU).