Generate random graphs according to the \(G(n,p)\) Erdős-Rényi model
Source:R/games.R
sample_gnp.Rd
Every possible edge is created independently with the same probability p
.
This model is also referred to as a Bernoulli random graph since the
connectivity status of vertex pairs follows a Bernoulli distribution.
Arguments
- n
The number of vertices in the graph.
- p
The probability for drawing an edge between two arbitrary vertices (\(G(n,p)\) 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_gnp()
.
Details
The graph has n
vertices and each pair of vertices is connected
with the same probability p
. The loops
parameter controls whether
self-connections are also considered. This model effectively constrains
the average number of edges, \(p m_\text{max}\), where \(m_\text{max}\)
is the largest possible number of edges, which depends on whether the
graph is directed or undirected and whether self-loops are allowed.
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_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_()
Author
Gabor Csardi csardi.gabor@gmail.com
Examples
g <- sample_gnp(1000, 1 / 1000)
degree_distribution(g)
#> [1] 0.372 0.389 0.168 0.055 0.010 0.006