@article{JSSv100i15, title={BNPmix: An R Package for Bayesian Nonparametric Modeling via Pitman-Yor Mixtures}, volume={100}, url={https://www.jstatsoft.org/index.php/jss/article/view/v100i15}, doi={10.18637/jss.v100.i15}, abstract={<p>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.</p>}, number={15}, journal={Journal of Statistical Software}, author={Corradin, Riccardo and Canale, Antonio and Nipoti, Bernardo}, year={2021}, pages={1–33} }