<b>networksis</b>: A Package to Simulate Bipartite Graphs with Fixed Marginals Through Sequential Importance Sampling

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 <b>networksis</b> 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.