igraph (version 1.3.1)

sample_hierarchical_sbm: Sample the hierarchical stochastic block model

Description

Sampling from a hierarchical stochastic block model of networks.

Usage

sample_hierarchical_sbm(n, m, rho, C, p)
hierarchical_sbm(...)

Arguments

n

Integer scalar, the number of vertices.

m

Integer scalar, the number of vertices per block. n / m must be integer. Alternatively, an integer vector of block sizes, if not all the blocks have equal sizes.

rho

Numeric vector, the fraction of vertices per cluster, within a block. Must sum up to 1, and rho * m must be integer for all elements of rho. Alternatively a list of rho vectors, one for each block, if they are not the same for all blocks.

C

A square, symmetric numeric matrix, the Bernoulli rates for the clusters within a block. Its size must mach the size of the rho vector. Alternatively, a list of square matrices, if the Bernoulli rates differ in different blocks.

p

Numeric scalar, the Bernoulli rate of connections between vertices in different blocks.

...

Passed to sample_hierarchical_sbm.

Value

An igraph graph.

Details

The function generates a random graph according to the hierarchical stochastic block model.

See Also

sbm.game

Examples

# NOT RUN {
## Ten blocks with three clusters each
C <- matrix(c(1  , 3/4,   0,
              3/4,   0, 3/4,
              0  , 3/4, 3/4), nrow=3)
g <- sample_hierarchical_sbm(100, 10, rho=c(3, 3, 4)/10, C=C, p=1/20)
g
if (require(Matrix)) { image(g[]) }
# }