`rmm`

returns a count matrix and the cluster labels generated randomly with a Mixture of Multinomial model.

rmm(N, pi, mu, lambda)

N | A numeric value the size of the graph to generate |
---|---|

pi | A numeric vector of length K with clusters proportions. Must sum up to 1. |

mu | A numeric matrix of dim k x D with the clusters patterns to generate, all elements in [0,1]. |

lambda | A numeric value which specify the expectation for the row sums. |

A list with fields:

x: the count matrix as a

`dgCMatrix`

K: number of generated clusters

N: number of vertex

cl: vector of clusters labels

pi: clusters proportions

mu: connectivity matrix

lambda: expectation of row sums

It takes the sample size, cluster proportions and emission matrix, and as input and sample a graph accordingly together with the clusters labels.