network-modeling

ergm: A Package to Fit, Simulate and Diagnose Exponential-Family Models for Networks

We describe some of the capabilities of the ergm package and the statistical theory underlying it. This package contains tools for accomplishing three important, and inter-related, tasks involving exponential-family random graph models (ERGMs): …

Fitting Position Latent Cluster Models for Social Networks with latentnet

latentnet is a package to fit and evaluate statistical latent position and cluster models for networks. Hoff, Raftery, and Handcock (2002) suggested an approach to modeling networks based on positing the existence of an latent space of …

networksis: A Package to Simulate Bipartite Graphs with Fixed Marginals through Sequential Importance Sampling

The ability to simulate graphs with given properties is important for the analysis of social networks. Sequential importance sampling has been shown to be particularly effective in estimating the number of graphs adhering to fixed marginals and in …

Specification of Exponential-Family Random Graph Models: Terms and Computational Aspects

Exponential-family random graph models (ERGMs) represent the processes that govern the formation of links in networks through the terms selected by the user. The terms specify network statistics that are sufficient to represent the probability …

statnet: Software Tools for the Representation, Visualization, Analysis and Simulation of Network Data

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). The components of the package provide a comprehensive …

Goodness of Fit of Social Network Models

We present a systematic examination of a real network data set using maximum likelihood estimation for exponential random graph models as well as new procedures to evaluate how well the models fit the observed networks. These procedures compare …

Model-Based Combination of Spatial Information for Stream Networks

Evolutionary improvements in Geographic Information Systems (GIS) now routinely allow the management and mapping of spatial-temporal information. In response, the development of statistical models to combine information of different types and spatial …

Recent developments in Exponential Random Graph (p*) Models for Social Networks

This article reviews new specifications for exponential random graph models proposed by Snijders et al. [Snijders, T.A.B., Pattison, P., Robins, G.L., Handcock, M., 2006. New specifications for exponential random graph models. Sociological …

Model-Based Clustering for Social Networks

Network models are widely used to represent relations between interacting units or actors. Network data often exhibit transitivity, meaning that two actors that have ties to a third actor are more likely to be tied than actors that do not, homophily …

A Simple Model for Complex Networks with Arbitrary Degree Distribution and Clustering

This is a paper as part of the reviewed proceedings of the ICML 2006 Workshop on Statistical Network Analysis, entitled 'Statistical Network Analysis: Models, Issues, and New Directions' published in the Lecture Notes in Computer Science Series. We …