Work

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

Year: 2008

Type: article

Abstract: 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 estimating the null distribution of graph statistics. This paper describes the networksis package for R and how its simulate and simulate_sis functions can be used to address both of these tasks as well as generate initial graphs for Markov chain Monte Carlo simulations

Source: Journal of Statistical Software

DOI: 10.18637/jss.v024.i08

Authors: Ryan Admiraal, Mark S. Handcock

Institution: University of Washington

Language: English

Topic: Complex Network Analysis Techniques

Subfield: Statistical and Nonlinear Physics

Field: Physics and Astronomy

Domain: Physical Sciences

Open Access status: diamond

Funders: National Institutes of Health, National Institute on Drug Abuse, Eunice Kennedy Shriver National Institute of Child Health and Human Development

Awards: G1431855629, Quantifying HIV Transmission Risk in Sex/Drug Networks, Modeling HIV and STD in Drug User and Social Networks