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

IF 5.4 2区 计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
R. Corradin, A. Canale, Bernardo Nipoti
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引用次数: 12

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.
一个基于Pitman-Yor混合物的贝叶斯非参数建模的R包
这篇关于R包BNPmix的介绍目前正在统计软件杂志上出版。BNPmix是一个R软件包,用于贝叶斯非参数多元密度估计,聚类和回归,使用Pitman-Yor混合模型,这是流行的Dirichlet过程混合模型的灵活而稳健的推广。各种模型规格和国家的最先进的后验抽样实施。为了提高计算效率,所有的采样方法都是用c++编写的,并通过Rcpp和RcppArmadillo包无缝集成到R中。BNPmix利用ggplot2功能,实现了一系列通用函数来绘制和打印后验密度和数据的诱导聚类的摘要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Statistical Software
Journal of Statistical Software 工程技术-计算机:跨学科应用
CiteScore
10.70
自引率
1.70%
发文量
40
审稿时长
6-12 weeks
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.
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