rlbm returns the adjacency matrix and the cluster labels generated randomly with a Latent Block Model.

rlbm(Nr, Nc, pir, pic, mu)

## Arguments

Nr desired Number of rows desired Number of column A numeric vector of length Kr with rows clusters proportions (will be normalized to sum up to 1). A numeric vector of length Kc with columns clusters proportions (will be normalized to sum up to 1). A numeric matrix of dim Kr x Kc with the connectivity pattern to generate. elements in [0,1].

## Value

A list with fields:

• x: the generated data matrix as a dgCMatrix

• clr: vector of row clusters labels

• clc: vector of column clusters labels

• Kr: number of generated row clusters

• Kc: number of generated column clusters

• Nr: number of rows

• Nc: number of column

• pir: row clusters proportions

• pic: column clusters proportions

• mu: connectivity matrix

## 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 = rlbm(500,1000,rep(1/5,5),rep(1/10,10),matrix(runif(50),5,10))