##### https://github.com/cran/statnet

Tip revision:

**9fd41f29ea177368cddd1f3c39b21b264c545d8b**authored by**Martina Morris**on**13 July 2015, 00:00 UTC****version 2015.6.2** Tip revision:

**9fd41f2** statnet-package.Rd

```
\name{statnet-package}
\alias{statnet-package}
\docType{package}
\title{
A Suite of Packages for the Statistical Modeling of Network Data
}
\description{
\pkg{statnet} is a suite of software packages for statistical network analysis.
The packages implement recent advances in network modeling based on
exponential-family random graph models (ERGM), as well as latent space
models and more traditional network methods. The components of the package
provide a comprehensive framework for ERGM-based network modeling: tools for
model estimation, for model evaluation, for model-based network simulation, and
for network visualization. This broad functionality is powered by a central
Markov chain Monte Carlo (MCMC) algorithm. The coding is optimized for speed
and robustness.
}
\details{
\pkg{statnet} packages are written in a combination of \R and
\code{C} It is usually used interactively from within the \R graphical
user interface via a command line. it can also be used in
non-interactive (or ``batch'') mode to allow longer or multiple tasks
to be processed without user interaction. The suite of packages are
available on the Comprehensive \R Archive Network (CRAN) at
\url{http://www.r-project.org/} and also on the \pkg{statnet} project
website at \url{http://statnet.org/}
The \pkg{statnet} suite of packages has the following components:
\itemize{
\item \pkg{ergm} is a collection of functions to fit, simulate from,
plot and evaluate exponential random graph models. The main
functions within the \pkg{ergm} package are
\code{\link[ergm]{ergm}}, a function to fit linear exponential
random graph models in which the probability of a graph is dependent
upon a vector of graph statistics specified by the user;
\code{simulate}, a function to simulate random graphs using an ERGM;
and \code{\link[ergm]{gof}}, a function to evaluate the goodness of
fit of an ERGM to the data. \pkg{ergm} contains many other functions
as well.
\item \pkg{tergm} is a collection of extentions to \pkg{ergm}
enabling it to fit models for dynamic networks.
\item \pkg{ergm.count} is an extension to \pkg{ergm} enabling it to
fit models for networks whose relations are counts.
\item \pkg{ergm.userterms} provides a template for implementing new
ERGM terms.
\item \pkg{sna} is a set of tools for traditional social network
analysis.
\item \pkg{degreenet} is a package for the statistical modeling of
degree distributions of networks. It includes power-law models such
as the Yule and Waring, as well as a range of alternative models
that have been proposed in the literature.
\item \pkg{latentnet} is a package to fit and evaluate latent position
and cluster models for statistical networks The probability of a tie
is expressed as a function of distances between these nodes in a
latent space as well as functions of observed dyadic level
covariates.
%% \item \pkg{netperm}: A package for permutation Models for relational
%% data. It provides simulation and inference tools for exponential
%% families of permutation models on relational structures.
\item \pkg{networksis} is a package to simulate bipartite graphs
with fixed marginals through sequential importance sampling.
\item \pkg{relevent} is a package providing tools to fit relational
event models.
\item \pkg{network} is a package to create, store, modify and plot
the data in network objects. The \code{\link[network]{network}}
object class, defined in the \pkg{network} package, can represent a
range of relational data types and it supports arbitrary vertex /
edge /graph attributes. Data stored as
\code{\link[network]{network}} objects can then be analyzed using
all of the component packages in the \pkg{statnet} suite.
\item \pkg{networkDynamic} extends \pkg{network} with functionality
to store information about about evolution of a network over time,
defining a \code{\link[networkDynamic]{networkDynamic}} object
class.
\item \pkg{ndtv}: (Network Dynamic Temporal Visualization): Exports dynamic network data from networkDynamic objects as animated movies or other representations of relational structure and node attributes that change over time.
\item \pkg{EpiModel}: Tools for building, solving, and plotting mathematical models of infectious disease, including stochastic models of disease on dynamic networks with demographic processes.
}
\pkg{statnet} is a metapackage, depending on all of the above
packages, so that they can be installed together.
Each of these components is described in detail in the references
below. Loading the \pkg{statnet} package into \R automatically
loads them all. Each package has associated help files and internal
documentation that is supported by the information on the Statnet
Project website (\url{http://statnet.org/}). A tutorial, support
mailing list, references and links to further resources are provided
there.
When publishing results obtained using this package the original
authors are to be cited as described in
\code{citation("statnet")}. In addition, please cite the specific
package that you use.
We have invested a lot of time and effort in creating the
\code{statnet} suite of packages for use by other researchers.
lease cite it in all papers where it is used.
}
\author{
Mark S. Handcock \email{handcock@stat.washington.edu},\cr
David R. Hunter \email{dhunter@stat.psu.edu},\cr
Carter T. Butts \email{buttsc@uci.edu},\cr
Steven M. Goodreau \email{goodreau@u.washington.edu},\cr
Pavel N. Krivitsky \email{pavel@cmu.edu}, and\cr
Martina Morris \email{morrism@u.washington.edu}
Maintainer: Pavel N. Krivitsky \email{krivitsky@stat.psu.edu}
}
\references{
Admiraal R, Handcock MS (2007).
{\pkg{networksis}: Simulate bipartite graphs with fixed
marginals through sequential importance sampling}.
Statnet Project, Seattle, WA.
Version 1, \url{http://statnet.org}.
Bender-deMoll S, Morris M, Moody J (2008).
{Prototype Packages for Managing and Animating Longitudinal
Network Data: \pkg{dynamicnetwork} and \pkg{rSoNIA}.}
{Journal of Statistical Software}, {24} (7).
\url{http://www.jstatsoft.org/v24/i07/}.
Besag, J., 1974, Spatial interaction and the statistical analysis
of lattice systems (with discussion), Journal of the Royal Statistical
Society, B, 36, 192-236.
Carter T. Butts (2014).
{\pkg{sna}: Tools for Social Network Analysis. R package}
version 2.3-2. \url{http://CRAN.R-project.org/package=sna}
Butts C (2015).
{\pkg{network}: Classes for Relational Data}.
The Statnet Project (\url{http://www.statnet.org}). R package version 1.12.0,
\url{CRAN.R-project.org/package=network}.
Butts CT (2008).
{\pkg{network}: {A} Package for Managing Relational Data in \R.}
{Journal of Statistical Software}, {24} (2).
\url{http://www.jstatsoft.org/v24/i02/}.
Frank, O., and Strauss, D.(1986). Markov graphs. Journal of the American
Statistical Association, 81, 832-842.
Goodreau SM, Handcock MS, Hunter DR, Butts CT, Morris M (2008a).
{A \pkg{statnet} Tutorial.}
{Journal of Statistical Software}, {24} (8).
\url{http://www.jstatsoft.org/v24/i08/}.
Goodreau SM, Kitts J, Morris M (2008{{b}}).
{Birds of a Feather, or Friend of a Friend? Using Exponential
Random Graph Models to Investigate Adolescent Social Networks.}
{Demography}, {45}, in press.
Handcock, M. S. (2003)
\emph{Assessing Degeneracy in Statistical Models of Social Networks},
Working Paper \#39,
Center for Statistics and the Social Sciences,
University of Washington.
\url{www.csss.washington.edu/Papers/wp39.pdf}
Handcock MS (2003{{b}}).
{\pkg{degreenet}: Models for Skewed Count Distributions Relevant
to Networks}.
Statnet Project, Seattle, WA.
Version 1. Project homepage at \url{http://statnet.org},
URL: \url{http://CRAN.R-project.org/package=degreenet}.
Handcock MS, Hunter DR, Butts CT, Goodreau SM, Morris M (2003{{a}}).
{\pkg{ergm}: {A} Package to Fit, Simulate and Diagnose
Exponential-Family Models for Networks}.
Statnet Project, Seattle, WA.
Version 2. Project homepage at \url{http://statnet.org},
URL: \url{http://CRAN.R-project.org/package=ergm}.
Handcock MS, Hunter DR, Butts CT, Goodreau SM, Morris M (2003{{b}}).
{\pkg{statnet}: Software tools for the Statistical Modeling of
Network Data}.
Statnet Project, Seattle, WA.
Version 2. Project homepage at \url{http://statnet.org},
URL: \url{http://CRAN.R-project.org/package=statnet}.
Hunter, D. R. and Handcock, M. S. (2006)
\emph{Inference in curved exponential family models for networks},
Journal of Computational and Graphical Statistics.
Hunter DR, Handcock MS, Butts CT, Goodreau SM, Morris M (2008{{b}}).
{\pkg{ergm}: {A} Package to Fit, Simulate and Diagnose
Exponential-Family Models for Networks.}
{Journal of Statistical Software}, {24}(3).
\url{http://www.jstatsoft.org/v24/i03/}.
Krivitsky PN (2012). Exponential-Family Random Graph Models for Valued
Networks. \emph{Electronic Journal of Statistics}, 2012, 6,
1100-1128. \href{http://dx.doi.org/10.1214/12-EJS696}{\code{doi:10.1214/12-EJS696}}
Krivitsky PN, Handcock MS (2008).
Fitting Latent Cluster Models for Social Networks with \pkg{latentnet}.
{Journal of Statistical Software}, {24}(5).
\url{http://www.jstatsoft.org/v24/i05/}.
Krivitsky PN, Handcock MS (2007).
{\pkg{latentnet}: Latent position and cluster models for
statistical networks}.
Seattle, WA.
Version 2. Project homepage at \url{http://statnet.org},
URL: \url{http://CRAN.R-project.org/package=latentnet}.
Morris M, Handcock MS, Hunter DR (2008).
{Specification of Exponential-Family Random Graph Models:
Terms and Computational Aspects.}
{Journal of Statistical Software}, {24}(4).
\url{http://www.jstatsoft.org/v24/i04/}.
Strauss, D., and Ikeda, M.(1990). Pseudolikelihood estimation for social
networks. Journal of the American Statistical Association, 85, 204-212.
}
\keyword{ package }
\keyword{ models }
```