rgnm {sna}R Documentation

Draw Density-Conditioned Random Graphs

Description

rgnm generates random draws from a density-conditioned uniform random graph distribution.

Usage

rgnm(n, nv, m, mode = "digraph", diag = FALSE)

Arguments

n the number of graphs to generate.
nv the size of the vertex set (|V(G)|) for the random graphs.
m the number of edges on which to condition.
mode "digraph" for directed graphs, or "graph" for undirected graphs.
diag boolean; should loops be allowed?

Details

rgnm returns draws from the density-conditioned uniform random graph first popularized by the famous work of Erd"{o}s and R'{e}nyi (the G(N,M) process). In particular, the pmf of a G(N,M) process is given by

p(G=g|N,M) = 1/Choose(E_m,M)

where E_m is the maximum number of edges in the graph. (E_m is equal to nv*(nv-diag)/(1+(mode=="graph")).)

The G(N,M) process is one of several process which are used as baseline models of social structure. Other well-known baseline models include the Bernoulli graph (the G(N,p) model of Erd"{o}s and R'{e}nyi) and the U|MAN model of dyadic independence. These are implemented within sna as rgraph and rgnm, respectively.

Value

A matrix or array containing the drawn adjacency matrices

Author(s)

Carter T. Butts buttsc@uci.edu

References

Erd"{o}s, P. and R'{e}nyi, A. (1960). ``On the Evolution of Random Graphs.'' Public Mathematical Institute of Hungary Academy of Sciences, 5:17-61.

See Also

rgraph, rguman

Examples

#Draw 5 random graphs of order 10 
all(gden(rgnm(5,10,9,mode="graph"))==0.2) #Density 0.2
all(gden(rgnm(5,10,9))==0.1)              #Density 0.1

#Plot a random graph
gplot(rgnm(1,10,20))

[Package sna version 1.2 Index]