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I will try to use both statnet and igraph together again. My problem was not in using ergm, however. My issues occurred when I was trying to extract a subgraph. I have a large network consisting of 5K+ nodes and organized into groups of 30-70 nodes each. I'm investigating collaboration change in one group as they move from a closed office to open plan facility. I can write scripts that work when either igraph or statnet are loaded, but when both are loaded, I have difficulty with extracting a subnet, converting from the network to graph data structure, and with visualization using plot (I imagine I need to use the actual package command ie gplot).
I think if I knew how to convert between the network and graph data structures, I'd be able to leverage both packages.
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I use statnet and igraph at the same time, and have found the R intergraph package by Michal Bojanowski:http://cran.r-project.org/web/packages/intergraph/index.html
to be very useful for converting between the igraph and statnet network formats.
netscience <- nexus.get('netscience')
nNetscience <- asNetwork(netscience)
system.time(nsmodel <- ergm(nNetscience ~ edges + altkstar(2.0, fixed=TRUE) + gwesp(log(2.0), fixed=TRUE) + gwdsp(log(2.0), fixed=TRUE), control=control.ergm(main.method="Stepping", MCMC.burnin=1e+6,MCMC.interval=1e+04,MCMC.samplesize=1e+05)))
Note sure I can help with your other particular questions, I prefer to use igraph for plotting (where it is relatively easy to do things like your question 3) and computing various statistics (question 1), I use statnet primarily for ergm.