# R igraph manual pages

Use this if you are using igraph from R

## Sample stochastic block model

### Description

Sampling from the stochastic block model of networks

### Usage

```sample_sbm(n, pref.matrix, block.sizes, directed = FALSE, loops = FALSE)

sbm(...)
```

### Arguments

 `n` Number of vertices in the graph. `pref.matrix` The matrix giving the Bernoulli rates. This is a KxK 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 symmetric. `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`.

An igraph graph.

### Author(s)

Gabor Csardi csardi.gabor@gmail.com

### References

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

`sample_gnp`, `sample_gnm`

### 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
```

[Package igraph version 1.3.0 Index]