# sample_hierarchical_sbm

0th

Percentile

##### Sample the hierarchical stochastic block model

Sampling from a hierarchical stochastic block model of networks.

Keywords
, graphs, random
##### Usage
sample_hierarchical_sbm(n, m, rho, C, p)
##### 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.

##### Details

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

##### Value

An igraph graph.

sbm.game

##### Aliases
• sample_hierarchical_sbm
• hierarchical_sbm
##### 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[]) }
# }

Documentation reproduced from package igraph, version 1.2.2, License: GPL (>= 2)

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