Generate a data matrix using a Latent Block Model

Source: R/tools_generator.R

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

Nc

desired Number of column

pir

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

pic

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

mu

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))