Sample an ErdosRenyi graph
erdos_renyi(n, p = NULL, avg_deg = NULL, directed = FALSE, ...)
erdos_renyi_params(n, p = NULL, avg_deg = NULL, directed = FALSE,
...)
Arguments
n 
Number of nodes in graph. 
p 
Probability of an edge between any two nodes. You must specify
either p or avg_deg . If you do not specify p , uses avg_deg / n . 
avg_deg 
Desired average out degree. When specified, rescales
sampling probabilities to achieve the desired average out degree.
Defaults to NULL , such that there is no rescaling. 
directed 
Defaults to FALSE for ErdosRenyi graphs. The default
in the more general fastRG() is TRUE . 
... 
Arguments passed on to fastRG
 X
An n by k_1 matrix.
 S
A k_1 by k_2 matrix.
 Y
A d by k_2 matrix. Defaults to X .
 avg_deg
When specified, rescales parameter such that the
expected degree is avg_deg in the Poisson multigraph. When
poisson_edges = FALSE , the resulting graph will have lower a
average degree than avg_deg due to lack of multiedges. When
the graph is sparse, the expected number of edges for the Poisson
multigraph and Bernoulli graph are nearly the
same. Defaults to NULL , such that no scaling occurs.
 simple
When TRUE , indicates that you want to work with undirected
graphs where selfloops and multiedges are prohibited. Accomplishes
this by setting directed = FALSE , allow_self_loops = FALSE , and
poisson_edges = FALSE , and then ignoring arguments directed ,
allow_self_loops and poisson_edges . Defaults to FALSE .
 poisson_edges
Logical indicating whether or not multiedges are
allowed. Defaults to TRUE , which keeps multiedges and produces
a multigraph. When FALSE , only single edges are allowed, resulting
in a graph. See details for some additional comments. Effected by
simple argument.
 directed
Logical indicating whether or not the graph should be
directed. Default is directed = TRUE . When directed = FALSE ,
symmetrizes S internally. When X = Y (which is the default when
no Y is specified), this results in a symmetric adjacency matrix
as output. When avg_deg is specified and the desired graph is directed,
the average degree scaling is on the outdegree of each node (or the
row sums if you prefer to think in terms of the adjacency matrix).
Effected by the simple argument.
 allow_self_loops
Logical indicating whether edges are allowed from
a node back to itself. Defaults to TRUE . When FALSE , sampling
proceeds normally, and then selfloops are removed after sampling
is completed. Effected by the simple argument.
 return_edge_list
Logical indicating whether to return an edgelist
rather than an adjacency matrix. Defaults to FALSE .

Value
Never returns Poisson edges.
See also
Examples
#> $X
#> [,1]
#> [1,] 1
#> [2,] 1
#> [3,] 1
#> [4,] 1
#> [5,] 1
#> [6,] 1
#> [7,] 1
#> [8,] 1
#> [9,] 1
#> [10,] 1
#>
#> $S
#> [,1]
#> [1,] 0.1053605
#>
#> $Y
#> [,1]
#> [1,] 1
#> [2,] 1
#> [3,] 1
#> [4,] 1
#> [5,] 1
#> [6,] 1
#> [7,] 1
#> [8,] 1
#> [9,] 1
#> [10,] 1
#>
# sample a small graph
A < erdos_renyi(n = 10, p = 0.1)
A
#> 10 x 10 sparse Matrix of class "nsCMatrix"
#>
#> [1,] .  . . . . . . . .
#> [2,]    . . . .  . 
#> [3,] .  . . . .  . . .
#> [4,] . . . . . . . . . 
#> [5,] . . . . . . . .  .
#> [6,] . . . . . . . .  .
#> [7,] . .  . . . . . . 
#> [8,] .  . . . . . . . .
#> [9,] . . . .   . . . .
#> [10,] .  .  . .  . . .
#> [1] 1 5 2 1 1 1 2 1 2 3
#> [1] 1 5 2 1 1 1 2 1 2 3
# sample a much larger graph
B < erdos_renyi(n = 10^6, avg_deg = 5)