numberOfClusters {clusternomics}R Documentation

Estimate number of clusters from global cluster assignments.

Description

Estimate number of clusters from global cluster assignments.

Usage

numberOfClusters(assignments)

Arguments

assignments

Matrix of cluster assignments, where each row corresponds to cluster assignments sampled in one MCMC iteration

Value

Number of unique clusters in each MCMC iteration.

Examples

# Generate simple test dataset
groupCounts <- c(50, 10, 40, 60)
means <- c(-1.5,1.5)
testData <- generateTestData_2D(groupCounts, means)
datasets <- testData$data

# Fit the model
# 1. specify number of clusters
clusterCounts <- list(global=10, context=c(3,3))
# 2. Run inference
# Number of iterations is just for demonstration purposes, use
# a larger number of iterations in practice!
results <- contextCluster(datasets, clusterCounts,
     maxIter = 10, burnin = 5, lag = 1,
     dataDistributions = 'diagNormal',
     verbose = TRUE)

# Extract only the sampled global assignments
samples <- results$samples
clusters <- plyr::laply(1:length(samples), function(i) samples[[i]]$Global)
numberOfClusters(clusters)


[Package clusternomics version 0.1.1 Index]