R · Open source
dirichlet-process-mixtures
Bayesian Nonparametric Clustering With Gibbs Sampling
An R implementation of truncated Dirichlet process Gaussian mixtures with Gibbs sampling and automatic cluster discovery.
Overview
This is a compact implementation of a truncated stick-breaking Dirichlet process Gaussian mixture model. Conjugate Gibbs updates estimate the component parameters and mixture weights, while the posterior can leave unnecessary components empty.
The repository includes a reproducible simulation and MCMC trace plots so each part of the sampler can be inspected.
Technical highlights
- Stick-breaking mixture weights
- Conjugate Gibbs updates
- Automatic cluster discovery
- MCMC trace diagnostics and reproducible simulation
Topics
Dirichlet processesGibbs samplingBayesian clusteringMixture modelsR