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statnet Components

A list of the required and optional packages in statnet.

Required packages

  • ergm 3.0-1 is a collection of functions to fit, simulate from, plot and evaluate exponential family random graph models. The main functions within the ergm package are ergm, a function to fit exponential-family random graph models in which the probability of a network is dependent upon a vector of network statistics specified by the user; simulate, a function to simulate random networks using an ERGM; and gof, a function to evaluate the goodness of fit of an ERGM to the data. ergm contains many other functions as well; for a guide to the basic types of functionality these functions provide, see Hunter et al. (2008), Morris, Handcock, and Hunter (2008), and Goodreau et al. (2008). The ergm package also contains some of the classic network datasets (including Sampson's monastery data and the Padgett Florentine networks). The list of available datasets can be found by typing the R command: data(). The datasets are listed at the end of the output.
  • network 1.7-1 is a package to create, store, modify and plot the data in network objects. The network object class, defined in the network package (Butts, Handcock, and Hunter 2007; Butts 2008), can represent a range of relational data types and it supports arbitrary vertex / edge / network attributes. Data stored as network objects can then be analyzed using all of the component packages in the statnet suite.
  • sna 2.2-0: A set of tools for traditional social network analysis (Butts 2008).
  • networkDynamic 0.2-2: A package with routines to facilitate the handling of network objects with complex temporal data. (Leslie-Cook, Almquist, Krivitsky, Bender-deMoll, Hunter, Morris, Butts 2012).

Optional packages

  • degreenet 1.1: This package was developed for the degree distributions of networks. It implements likelihood-based inference, bootstrapping, and model selection, and 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. (Handcock 2003b). The theory behind these methods is described in Jones and Handcock (2003a,b); Handcock and Jones (2004, 2006).
  • netperm 0.2: This package provides simulation and inference tools for exponential families of permutation models on relational structures (Butts 2006).
  • latentnet 2.4-1: A package to fit and evaluate latent position and cluster models for statistical networks based on Hoff, Raftery, and Handcock (2002) and Handcock, Raftery, and Tantrum (2007). 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. For details about this package, see Krivitsky and Handcock (2008).
  • networksis 1.4: A package to simulate bipartite networks with fixed marginals through sequential importance sampling (Admiraal and Handcock 2007).
  • ergm.userterms 3.0-1: A template package to demonstrate the use of user-specified statistics for use in ergm models (Handcock, Hunter, Butts, Goodreau, Krivitsky, Morris 2012).
  • relevent 1.0-2: A package with tools to fit relational event models (Butts 2012).

Information on these packages is available in the online users guide and in their runtime help files. These packages are installed during the standard statnet installation process, or during any update. These packages also require other R packages for their use that are automatically installed during the installation process.

Additional optional packages for visualization are available on request from Skye Bender de-Moll (

  • dynamicnetwork: A set of tools for visualizing dynamically changing networks (Bender-deMoll, Morris, and Moody 2008).
  • rSonia: Provides a set of methods to facilitate exporting data and parameter settings and launching SoNIA, which stands for Social Network Image Animator (Bender-deMoll and McFarland 2003). SoNIA facilitates interactive browsing of dynamic network data and exporting animations as a QuickTime Apple (1999) movies.
  • ndtv: Exports dynamic network data in the form of networkDynamic objects as animated movies or other representations of relational structure and node attributes that change over time (Bender-deMoll 2012).

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