R: Process an MCMC Sample of Clusterings

# Process an MCMC Sample of Clusterings

## Documentation for package ‘mcclust’ version 1.0.1

- DESCRIPTION file

## Help Pages

mcclust-package | Process MCMC Sample of Clusterings.
arandi | (Adjusted) Rand Index for Clusterings
binder | Minimize/Compute Posterior Expectation of Binders Loss Function
cls.draw1.5 | Sample of Clusterings from Posterior Distribution of Bayesian Cluster Model
cls.draw2 | Sample of Clusterings from Posterior Distribution of Bayesian Cluster Model
cltoSim | Compute Similarity Matrix for a Clustering and vice versa
comp.psm | Estimate Posterior Similarity Matrix
laugreen | Minimize/Compute Posterior Expectation of Binders Loss Function
maxpear | Maximize/Compute Posterior Expected Adjusted Rand Index
mcclust | Process MCMC Sample of Clusterings.
medv | Clustering Method of Medvedovic
minbinder | Minimize/Compute Posterior Expectation of Binders Loss Function
norm.label | Norm Labelling of a Clustering
pear | Maximize/Compute Posterior Expected Adjusted Rand Index
relabel | Stephens' Relabelling Algorithm for Clusterings
Simtocl | Compute Similarity Matrix for a Clustering and vice versa
vi.dist | Variation of Information Distance for Clusterings
Ysim1.5 | Simulated 3-dimensional Normal Data Containing 8 Clusters
Ysim2 | Simulated 3-dimensional Normal Data Containing 8 Clusters