Mark S. Handcock <handcock@ucla.edu>, David R. Hunter
<dhunter@stat.psu.edu>, Carter T. Butts <buttsc@uci.edu>,
Steven M. Goodreau <goodreau@u.washington.edu>, Pavel N.
Krivitsky <krivitsky@stat.psu.edu> Martina Morris
<morrism@u.washington.edu>

A template package to demonstrate the use of user-specified statistics for use in "ergm" models as part of the "statnet" suite of packages.

User-specified Terms for the statnet Suite of Packages
c(
person("Mark S.", "Handcock", role=c("aut"), email="handcock@stat.ucla.edu"),
person("David R.", "Hunter", role=c("aut"), email="dhunter@stat.psu.edu"),
person("Carter T.", "Butts", role=c("aut"), email="buttsc@uci.edu"),
person("Steven M.", "Goodreau", role=c("aut"), email="goodreau@u.washington.edu"),
person("Pavel N.", "Krivitsky", role=c("aut","cre"), email="pavel@uow.edu.au", comment=c(ORCID="0000-0002-9101-3362")),
person("Martina", "Morris", role=c("aut"), email="morrism@u.washington.edu"))
A template package to demonstrate the use of user-specified statistics for use in 'ergm' models as part of the Statnet suite of packages.
Mark S. Handcock [aut],
David R. Hunter [aut],
Carter T. Butts [aut],
Steven M. Goodreau [aut],
Pavel N. Krivitsky [aut, cre] (<https://orcid.org/0000-0002-9101-3362>),
Martina Morris [aut]

c(person("Amal", "Agarwal", role = c("aut", "cre"),
email = "amalag.19@gmail.com"),
person("Kevin H.", "Lee", role = "aut"),
person("Lingzhou", "Xue", role = c("aut", "ths")),
person("Anna Yinqi", "Zhang", role = "com"))
Implements clustering and estimates parameters in Exponential-Family Random Graph Models (ERGMs) for static undirected and directed networks, developed in Vu et. al. (2013) <https://projecteuclid.org/euclid.aoas/1372338477>.
Rcpp (>= 1.0.1), MASS, lda, quadprog, igraph, viridis
Amal Agarwal [aut, cre],
Kevin H. Lee [aut],
Lingzhou Xue [aut, ths],
Anna Yinqi Zhang [com]

Local Health Department network data set
Data for use with the Sage Introduction to Exponential
Random Graph Modeling text by Jenine K. Harris.  Network data
set consists of 1283 local health departments and the
communication links among them along with several attributes.