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

Abstract

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.

Keywords

• bayesian nonparametric mixture
• c
• density estimation
• clustering
• importance conditional sampler
• slice sampler
• marginal sampler