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]