# erdos.renyi.game

##### Generate random graphs according to the Erdos-Renyi model

This model is very simple, every possible edge is created with the same constant probability.

- Keywords
- graphs

##### Usage

```
erdos.renyi.game(
n,
p.or.m,
type = c("gnp", "gnm"),
directed = FALSE,
loops = FALSE,
...
)
```

##### Arguments

- n
The number of vertices in the graph.

- p.or.m
Either the probability for drawing an edge between two arbitrary vertices (G(n,p) graph), or the number of edges in the graph (for G(n,m) graphs).

- type
The type of the random graph to create, either

`gnp`

(G(n,p) graph) or`gnm`

(G(n,m) graph).- directed
Logical, whether the graph will be directed, defaults to FALSE.

- loops
Logical, whether to add loop edges, defaults to FALSE.

- …
Additional arguments, ignored.

##### Details

In G(n,p) graphs, the graph has ‘n’ vertices and for each edge the probability that it is present in the graph is ‘p’.

In G(n,m) graphs, the graph has ‘n’ vertices and ‘m’ edges,
and the ‘m’ edges are chosen uniformly randomly from the set of all
possible edges. This set includes loop edges as well if the `loops`

parameter is TRUE.

`random.graph.game`

is an alias to this function.

##### Value

A graph object.

##### Deprecated

Since igraph version 0.8.0, both `erdos.renyi.game`

and
`random.graph.game`

are deprecated, and `sample_gnp`

and
`sample_gnm`

should be used instead.

##### References

Erdos, P. and Renyi, A., On random graphs, *Publicationes
Mathematicae* 6, 290--297 (1959).

##### See Also

##### Examples

```
# NOT RUN {
g <- erdos.renyi.game(1000, 1/1000)
degree_distribution(g)
# }
```

*Documentation reproduced from package igraph, version 1.2.5, License: GPL (>= 2)*