`rgnm`

returns draws from the density-conditioned uniform random graph first popularized by the famous work of Erdos and Renyi (the \(G(N,M)\) process). In particular, the pmf of a \(G(N,M)\) process is given by

$$
p(G=g|N,M) = \left( {E_m \atop M} \right)^{-1}
$$

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 Erdos and Renyi) and the U|MAN model of dyadic independence. These are implemented within `sna`

as `rgraph`

and `rgnm`

, respectively.