Generate random graphs according to the \(G(n,m)\) Erdős-Rényi model
Source:R/games.R
sample_gnm.RdThis model is very simple, every possible edge is created with the same constant probability.
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,
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.
References
Erdos, P. and Renyi, A., On random graphs, Publicationes Mathematicae 6, 290--297 (1959).
See also
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_gnp(),
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_gnp(),
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_()
Author
Gabor Csardi csardi.gabor@gmail.com
Examples
g <- sample_gnm(1000, 1000)
degree_distribution(g)
#> [1] 0.125 0.295 0.255 0.182 0.091 0.034 0.012 0.005 0.001