Sample stochastic block model
Sampling from the stochastic block model of networks
sample_sbm(n, pref.matrix, block.sizes, directed = FALSE, loops = FALSE)
- Number of vertices in the graph.
- The matrix giving the Bernoulli rates. This is a $K\times K$ matrix, where $K$ is the number of groups. The probability of creating an edge between vertices from groups $i$ and $j$ is given by element $(i,j)$. For undirected graphs, this matrix must be s
- Numeric vector giving the number of vertices in each group. The sum of the vector must match the number of vertices.
- Logical scalar, whether to generate a directed graph.
- 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,
- An igraph graph.
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