sharp (version 1.4.6)

GMMClustering: Model-based clustering

Description

Runs clustering with Gaussian Mixture Models (GMM) using implementation from Mclust. This function is not using stability.

Usage

GMMClustering(xdata, nc = NULL, ...)

Value

A list with:

comembership

an array of binary and symmetric co-membership matrices.

weights

a matrix of median weights by feature.

Arguments

xdata

data matrix with observations as rows and variables as columns.

nc

matrix of parameters controlling the number of clusters in the underlying algorithm specified in implementation. If nc is not provided, it is set to seq(1, tau*nrow(xdata)).

...

additional parameters passed to Mclust.

See Also

Other clustering algorithms: DBSCANClustering(), HierarchicalClustering(), KMeansClustering(), PAMClustering()

Examples

# Data simulation
set.seed(1)
simul <- SimulateClustering(n = c(10, 10), pk = 50)

# Clustering using Gaussian Mixture Models
mygmm <- GMMClustering(xdata = simul$data, nc = seq_len(30))