{"title":"一个基于Pitman-Yor混合物的贝叶斯非参数建模的R包","authors":"R. Corradin, A. Canale, Bernardo Nipoti","doi":"10.18637/jss.v100.i15","DOIUrl":null,"url":null,"abstract":"This introduction to the R package BNPmix is currently in press in the Journal of Statistical Software. 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.","PeriodicalId":17237,"journal":{"name":"Journal of Statistical Software","volume":"79 1","pages":""},"PeriodicalIF":5.4000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"BNPmix: An R Package for Bayesian Nonparametric Modeling via Pitman-Yor Mixtures\",\"authors\":\"R. Corradin, A. Canale, Bernardo Nipoti\",\"doi\":\"10.18637/jss.v100.i15\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This introduction to the R package BNPmix is currently in press in the Journal of Statistical Software. 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.\",\"PeriodicalId\":17237,\"journal\":{\"name\":\"Journal of Statistical Software\",\"volume\":\"79 1\",\"pages\":\"\"},\"PeriodicalIF\":5.4000,\"publicationDate\":\"2021-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Statistical Software\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.18637/jss.v100.i15\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Statistical Software","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.18637/jss.v100.i15","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
BNPmix: An R Package for Bayesian Nonparametric Modeling via Pitman-Yor Mixtures
This introduction to the R package BNPmix is currently in press in the Journal of Statistical Software. 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.
期刊介绍:
The Journal of Statistical Software (JSS) publishes open-source software and corresponding reproducible articles discussing all aspects of the design, implementation, documentation, application, evaluation, comparison, maintainance and distribution of software dedicated to improvement of state-of-the-art in statistical computing in all areas of empirical research. Open-source code and articles are jointly reviewed and published in this journal and should be accessible to a broad community of practitioners, teachers, and researchers in the field of statistics.