rmm: Generate data using a Multinomial Mixture

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

Generate data using a Multinomial Mixture

Description

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

Usage

rmm(N, pi, mu, lambda)

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 D with the clusters patterns to generate, all elements in [0,1].
lambda	A numeric value which specify the expectation for the row sums.

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

• lambda: expectation of row sums

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