期刊
JOURNAL OF STATISTICAL SOFTWARE
卷 100, 期 15, 页码 1-33出版社
JOURNAL STATISTICAL SOFTWARE
DOI: 10.18637/jss.v100.i15
关键词
Bayesian nonparametric mixture; C plus; multivariate density estimation; clustering; importance conditional sampler; slice sampler; marginal sampler
资金
- University of Padova
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.
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.
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