rdcsbm: Generates graph adjacency matrix using a degree corrected SBM

In comeetie/greed: Clustering and Model Selection with the Integrated Classification Likelihood

Generates graph adjacency matrix using a degree corrected SBM

Description

rdcsbm returns an adjacency matrix and the cluster labels generated randomly using a Degree Corrected Stochastic Block Model.

Usage

rdcsbm(N, pi, mu, betain, betaout)

Arguments

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 K with the connectivity pattern to generate, elements in [0,1].
betain	A numeric vector of length N which specify the in-degree correction will be normalized per cluster during the generation.
betaout	A numeric vector of length N which specify the out-degree correction will be normalized per cluster during the generation.

Details

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

Value

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

• betain: normalized in-degree parameters

• betaout: normalized out-degree parameters

comeetie/greed documentation built on Oct. 10, 2022, 5:37 p.m.