BNPmix: An R Package for Bayesian Nonparametric Modeling via Pitman-Yor Mixtures

BNPmix is an R package for Bayesian nonparametric multivariate density estimation, clustering, and regression, using Pitman-Yor mixture models, a flexible and robust generalization of the popular class of Dirichlet process mixture models. A variety of model specifications and state-of-the-art posterior samplers are implemented. In order to achieve computational efficiency, all sampling methods are written in C++ and seamless integrated into R by means of the Rcpp and RcppArmadillo packages. BNPmix exploits the ggplot2 capabilities and implements a series of generic functions to plot and print summaries of posterior densities and induced clustering of the data.

Automated summary

BNPmix is an R package for Bayesian nonparametric multivariate density estimation, clustering, and regression, utilizing Pitman-Yor mixture models with various model specifications and state-of-the-art posterior samplers. To enhance computational efficiency, all sampling methods are written in C++ and seamlessly integrated into R with the help of Rcpp and RcppArmadillo packages. BNPmix makes use of ggplot2 capabilities and offers generic functions for plotting and summarizing posterior densities and clustering results.