View source: R/undirected_erdos_renyi.R
erdos_renyi | R Documentation |
Create an undirected erdos renyi object
erdos_renyi(n, ..., p = NULL, poisson_edges = TRUE, allow_self_loops = TRUE)
n |
Number of nodes in graph. |
... |
Arguments passed on to
|
p |
Probability of an edge between any two nodes. You must specify
either |
poisson_edges |
Logical indicating whether or not
multiple edges are allowed to form between a pair of
nodes. Defaults to |
allow_self_loops |
Logical indicating whether or not
nodes should be allowed to form edges with themselves.
Defaults to |
An undirected_factor_model
S3 class based on a list
with the following elements:
X
: The latent positions as a Matrix()
object.
S
: The mixing matrix as a Matrix()
object.
n
: The number of nodes in the network.
k
: The rank of expectation matrix. Equivalently,
the dimension of the latent node position vectors.
Other erdos renyi:
directed_erdos_renyi()
Other undirected graphs:
chung_lu()
,
dcsbm()
,
mmsbm()
,
overlapping_sbm()
,
planted_partition()
,
sbm()
set.seed(87)
er <- erdos_renyi(n = 10, p = 0.1)
er
er <- erdos_renyi(n = 10, expected_density = 0.1)
er
big_er <- erdos_renyi(n = 10^6, expected_degree = 5)
big_er
A <- sample_sparse(er)
A
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