| Literature DB >> 29129971 |
Ryan Admiraal1, Mark S Handcock2.
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.Keywords: Markov chain Monte Carlo; R; bipartite network; graph counting; networks; social network analysis; statnet
Year: 2008 PMID: 29129971 PMCID: PMC5679483 DOI: 10.18637/jss.v024.i08
Source DB: PubMed Journal: J Stat Softw ISSN: 1548-7660 Impact factor: 6.440