Generate a cluster-affiliation graph
Generate a cluster-affiliation graph.
net.cluster.affiliation( DEG, community_affiliation_alpha, community_affiliation_lambda, community_affiliation_min, community_size_alpha, community_size_lambda, community_size_min )
DEG
: Degree sequence.community_affiliation_alpha
: First scaling parameter of the membership distribution.community_affiliation_lambda
: Second scaling parameter of the membership distribution.community_affiliation_min
: Minimal membership.community_size_alpha
: First scaling parameter of the cluster-size distribution.community_size_lambda
: Second scaling parameter of the cluster-size distribution.community_size_min
: Minimal size of a cluster.A list containing the nodes of the network and their respective neighbors.
The generated network has multiple (overlapping) densely-connected clusters.
## Not run: DEG <- sample(seq(5,15),100, replace=TRUE) x <- net.cluster.affiliation(DEG, community_affiliation_alpha=1.5, community_affiliation_lambda=10, community_affiliation_min=1, community_size_alpha=2.5, community_size_lambda=40, community_size_min=3) ## End(Not run)
Dong X, Castro L, Shaikh N (2020). “fastnet: An R Package for Fast Simulation and Analysis of Large-Scale Social Networks.” Journal of Statistical Software, 96(7), 1-23. doi:10.18637/jss.v096.i07 (URL: https://doi.org/10.18637/jss.v096.i07)
Xu Dong, Nazrul Shaikh
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