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)
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