# sample_sbm

0th

Percentile

##### Sample stochastic block model

Sampling from the stochastic block model of networks

Keywords
graphs
##### Usage
sample_sbm(n, pref.matrix, block.sizes, directed = FALSE, loops = FALSE)
##### Arguments
n
Number of vertices in the graph.
pref.matrix
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
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 sample_sbm.
##### Details

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.

##### Value

• An igraph graph.

##### References

Faust, K., & Wasserman, S. (1992a). Blockmodels: Interpretation and evaluation. Social Networks, 14, 5--61.

sample_gnp, sample_gnm

• sample_sbm
• sbm
• sbm.game
##### Examples
## 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
Documentation reproduced from package igraph, version 1.0.0, License: GPL (>= 2)

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