sample_gnm: Generate random graphs according to the G(n,m) Erdős-Rényi...

In igraph: Network Analysis and Visualization

Generate random graphs according to the G(n,m) Erdős-Rényi model

Description

Random graph with a fixed number of edges and vertices.

Usage

sample_gnm(n, m, directed = FALSE, loops = FALSE)

gnm(...)

Arguments

n	The number of vertices in the graph.
m	The number of edges in the graph.
directed	Logical, whether the graph will be directed, defaults to FALSE.
loops	Logical, whether to add loop edges, defaults to FALSE.
...	Passed to sample_gnm().

Details

The graph has n vertices and m edges. The edges are chosen uniformly at random from the set of all vertex pairs. This set includes potential self-connections as well if the loops parameter is TRUE.

Value

A graph object.

Author(s)

Gabor Csardi [e-mail]

References

Erdős, P. and Rényi, A., On random graphs, Publicationes Mathematicae 6, 290–297 (1959).

See Also

Random graph models (games) erdos.renyi.game(), sample_(), sample_bipartite(), sample_chung_lu(), sample_correlated_gnp(), sample_correlated_gnp_pair(), sample_degseq(), sample_dot_product(), sample_fitness(), sample_fitness_pl(), sample_forestfire(), sample_gnp(), sample_grg(), sample_growing(), sample_hierarchical_sbm(), sample_islands(), sample_k_regular(), sample_last_cit(), sample_pa(), sample_pa_age(), sample_pref(), sample_sbm(), sample_smallworld(), sample_traits_callaway(), sample_tree()

Examples

g <- sample_gnm(1000, 1000)
degree_distribution(g)

igraph documentation built on Oct. 20, 2024, 1:06 a.m.