Generate a graph adjacency matrix using a Stochastic Block Model

Source: R/tools_generator.R

rmultsbm returns the multi-graph adjacency matrix and the cluster labels generated randomly with a Multinomial Stochastic Block Model.

rmultsbm(N, pi, mu, lambda)

Arguments

N

The size of the graph to generate

pi

A numeric vector of length K with clusters proportions (will be normalized to sum up to 1).

mu

A numeric array of dim K x K x M with the connectivity pattern to generate. elements in [0,1].

lambda

A double with the Poisson intensity to generate the total counts

Value

A list with fields:

  • x: the multi-graph adjacency matrix as an array

  • K: number of generated clusters

  • N: number of vertex

  • cl: vector of clusters labels

  • pi: clusters proportions

  • mu: connectivity matrix

  • lambda:

Details

This function takes the desired graph size, cluster proportions and connectivity matrix as input and sample a graph accordingly together with the clusters labels.

Examples

simu <- rsbm(100, rep(1 / 5, 5), diag(rep(0.1, 5)) + 0.001)