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 poster...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Foundation for Open Access Statistics
2021-11-01
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| Series: | Journal of Statistical Software |
| Subjects: | |
| Online Access: | https://www.jstatsoft.org/index.php/jss/article/view/3867 |
| _version_ | 1797813965038813184 |
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| author | Riccardo Corradin Antonio Canale Bernardo Nipoti |
| author_facet | Riccardo Corradin Antonio Canale Bernardo Nipoti |
| author_sort | Riccardo Corradin |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-13T08:00:31Z |
| format | Article |
| id | doaj.art-d021f452c6ef4d469e2932877afd7104 |
| institution | Directory Open Access Journal |
| issn | 1548-7660 |
| language | English |
| last_indexed | 2024-03-13T08:00:31Z |
| publishDate | 2021-11-01 |
| publisher | Foundation for Open Access Statistics |
| record_format | Article |
| series | Journal of Statistical Software |
| spelling | doaj.art-d021f452c6ef4d469e2932877afd71042023-06-01T18:48:04ZengFoundation for Open Access StatisticsJournal of Statistical Software1548-76602021-11-0110013310.18637/jss.v100.i153680BNPmix: An R Package for Bayesian Nonparametric Modeling via Pitman-Yor MixturesRiccardo Corradin0https://orcid.org/0000-0001-5389-6873Antonio Canale1https://orcid.org/0000-0002-5403-0040Bernardo Nipoti2https://orcid.org/0000-0003-1138-951XUniversity of Milano-BicoccaUniversity of PadovaUniversity of Milano-BicoccaBNPmix 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.https://www.jstatsoft.org/index.php/jss/article/view/3867bayesian nonparametric mixturec density estimationclusteringimportance conditional samplerslice samplermarginal sampler |
| spellingShingle | Riccardo Corradin Antonio Canale Bernardo Nipoti BNPmix: An R Package for Bayesian Nonparametric Modeling via Pitman-Yor Mixtures Journal of Statistical Software bayesian nonparametric mixture c density estimation clustering importance conditional sampler slice sampler marginal sampler |
| title | BNPmix: An R Package for Bayesian Nonparametric Modeling via Pitman-Yor Mixtures |
| title_full | BNPmix: An R Package for Bayesian Nonparametric Modeling via Pitman-Yor Mixtures |
| title_fullStr | BNPmix: An R Package for Bayesian Nonparametric Modeling via Pitman-Yor Mixtures |
| title_full_unstemmed | BNPmix: An R Package for Bayesian Nonparametric Modeling via Pitman-Yor Mixtures |
| title_short | BNPmix: An R Package for Bayesian Nonparametric Modeling via Pitman-Yor Mixtures |
| title_sort | bnpmix an r package for bayesian nonparametric modeling via pitman yor mixtures |
| topic | bayesian nonparametric mixture c density estimation clustering importance conditional sampler slice sampler marginal sampler |
| url | https://www.jstatsoft.org/index.php/jss/article/view/3867 |
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