Perform nonparametric Bayesian analysis using Dirichlet processes without the need to program the inference algorithms. Utilise included pre-built models or specify custom models and allow the 'dirichletprocess' package to handle the Markov chain Monte Carlo sampling. Our Dirichlet process objects can act as building blocks for a variety of statistical models including and not limited to: density estimation, clustering and prior distributions in hierarchical models. See Teh, Y. W. (2011) <https://www.stats.ox.ac.uk/~teh/research/npbayes/Teh2010a.pdf>, among many other sources.
copied from cf-post-staging / r-dirichletprocess