BNPmix is an R package for Bayesian nonparametric multivariate density estima-tion, 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.

Corradin, R., Canale, A., Nipoti, B. (2021). BNPmix: An R Package for Bayesian Nonparametric Modeling via Pitman-Yor Mixtures. JOURNAL OF STATISTICAL SOFTWARE, 100(15), 1-33 [10.18637/JSS.V100.I15].

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

Corradin R.
;
Nipoti B.
2021

Abstract

BNPmix is an R package for Bayesian nonparametric multivariate density estima-tion, 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.
Articolo in rivista - Articolo scientifico
Bayesian nonparametric mixture; C++; Clustering; Importance conditional sampler; Marginal sampler; Multivariate density estimation; Slice sampler;
English
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33
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Corradin, R., Canale, A., Nipoti, B. (2021). BNPmix: An R Package for Bayesian Nonparametric Modeling via Pitman-Yor Mixtures. JOURNAL OF STATISTICAL SOFTWARE, 100(15), 1-33 [10.18637/JSS.V100.I15].
Corradin, R; Canale, A; Nipoti, B
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/352946
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