sample2_sbm | R Documentation |
This function generates two samples of networks according to the stochastic
block model (SBM). This is essentially a wrapper around
sample_sbm
which allows to sample a single network from
the SBM.
sample2_sbm(n, nv, p1, b1, p2 = p1, b2 = b1, seed = NULL)
n |
Integer scalar giving the sample size. |
nv |
Integer scalar giving the number of vertices of the generated networks, common to all networks in both samples. |
p1 |
The matrix giving the Bernoulli rates for the 1st sample. This is a KxK matrix, where K is the number of groups. The probability of creating an edge between vertices from groups i and j is given by element (i,j). For undirected graphs, this matrix must be symmetric. |
b1 |
Numeric vector giving the number of vertices in each group for the first sample. The sum of the vector must match the number of vertices. |
p2 |
The matrix giving the Bernoulli rates for the 2nd sample (default: same as 1st sample). This is a KxK matrix, where K is the number of groups. The probability of creating an edge between vertices from groups i and j is given by element (i,j). For undirected graphs, this matrix must be symmetric. |
b2 |
Numeric vector giving the number of vertices in each group for the second sample (default: same as 1st sample). The sum of the vector must match the number of vertices. |
seed |
The seed for the random number generator (default: |
A length-2 list containing the two samples stored as
nvd
objects.
n <- 10
p1 <- matrix(
data = c(0.1, 0.4, 0.1, 0.4,
0.4, 0.4, 0.1, 0.4,
0.1, 0.1, 0.4, 0.4,
0.4, 0.4, 0.4, 0.4),
nrow = 4,
ncol = 4,
byrow = TRUE
)
p2 <- matrix(
data = c(0.1, 0.4, 0.4, 0.4,
0.4, 0.4, 0.4, 0.4,
0.4, 0.4, 0.1, 0.1,
0.4, 0.4, 0.1, 0.4),
nrow = 4,
ncol = 4,
byrow = TRUE
)
sim <- sample2_sbm(n, 68, p1, c(17, 17, 17, 17), p2, seed = 1234)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.