Use this if you are using igraph from R
| sample_sbm {igraph} | R Documentation | 
Sampling from the stochastic block model of networks
sample_sbm(n, pref.matrix, block.sizes, directed = FALSE, loops = FALSE)
sbm(...)
| n | Number of vertices in the graph. | 
| pref.matrix | The matrix giving the Bernoulli rates.  This is a
 | 
| block.sizes | Numeric vector giving the number of vertices in each group. The sum of the vector must match the number of vertices. | 
| directed | Logical scalar, whether to generate a directed graph. | 
| loops | Logical scalar, whether self-loops are allowed in the graph. | 
| ... | Passed to  | 
This function samples graphs from a stochastic block model by (doing the
equivalent of) Bernoulli trials for each potential edge with the
probabilities given by the Bernoulli rate matrix, pref.matrix.
The order of the vertices in the generated graph corresponds to the 
block.sizes argument.
An igraph graph.
Gabor Csardi csardi.gabor@gmail.com
Faust, K., & Wasserman, S. (1992a). Blockmodels: Interpretation and evaluation. Social Networks, 14, 5–61.
## Two groups with not only few connection between groups
pm <- cbind( c(.1, .001), c(.001, .05) )
g <- sample_sbm(1000, pref.matrix=pm, block.sizes=c(300,700))
g