sample_gnp | R Documentation |

`G(n,p)`

Erdős-Rényi modelThis model is very simple, every possible edge is created with the same constant probability.

```
sample_gnp(n, p, directed = FALSE, loops = FALSE)
gnp(...)
```

`n` |
The number of vertices in the graph. |

`p` |
The probability for drawing an edge between two
arbitrary vertices ( |

`directed` |
Logical, whether the graph will be directed, defaults to FALSE. |

`loops` |
Logical, whether to add loop edges, defaults to FALSE. |

`...` |
Passed to |

The graph has ‘n’ vertices and for each edge the probability that it is present in the graph is ‘p’.

A graph object.

Gabor Csardi csardi.gabor@gmail.com

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

`sample_gnm()`

, `sample_pa()`

Random graph models (games)
`erdos.renyi.game()`

,
`sample_bipartite()`

,
`sample_correlated_gnp_pair()`

,
`sample_correlated_gnp()`

,
`sample_degseq()`

,
`sample_dot_product()`

,
`sample_fitness_pl()`

,
`sample_fitness()`

,
`sample_forestfire()`

,
`sample_gnm()`

,
`sample_grg()`

,
`sample_growing()`

,
`sample_hierarchical_sbm()`

,
`sample_islands()`

,
`sample_k_regular()`

,
`sample_last_cit()`

,
`sample_pa_age()`

,
`sample_pa()`

,
`sample_pref()`

,
`sample_sbm()`

,
`sample_smallworld()`

,
`sample_traits_callaway()`

,
`sample_tree()`

,
`sample_()`

Random graph models (games)
`erdos.renyi.game()`

,
`sample_bipartite()`

,
`sample_correlated_gnp_pair()`

,
`sample_correlated_gnp()`

,
`sample_degseq()`

,
`sample_dot_product()`

,
`sample_fitness_pl()`

,
`sample_fitness()`

,
`sample_forestfire()`

,
`sample_gnm()`

,
`sample_grg()`

,
`sample_growing()`

,
`sample_hierarchical_sbm()`

,
`sample_islands()`

,
`sample_k_regular()`

,
`sample_last_cit()`

,
`sample_pa_age()`

,
`sample_pa()`

,
`sample_pref()`

,
`sample_sbm()`

,
`sample_smallworld()`

,
`sample_traits_callaway()`

,
`sample_tree()`

,
`sample_()`

```
g <- sample_gnp(1000, 1 / 1000)
degree_distribution(g)
```

igraph documentation built on Aug. 10, 2023, 9:08 a.m.

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