pyrichlet: A Python Package for Density Estimation and Clustering Using Gaussian Mixture Models

Bayesian nonparametric models have proven to be successful tools for clustering and density estimation. While there exists a nourished ecosystem of implementations in R, for Python there are only a few. Here we develop a Python package called pyrichlet, for Bayesian nonparametric density estimation...

Full description

Saved in:
Bibliographic Details
Main Authors: Fidel Selva, Ruth Fuentes-García, María Fernanda Gil-Leyva
Format: Article
Language:English
Published: Foundation for Open Access Statistics 2025-03-01
Series:Journal of Statistical Software
Online Access:https://www.jstatsoft.org/index.php/jss/article/view/4925
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1849418961744035840
author Fidel Selva
Ruth Fuentes-García
María Fernanda Gil-Leyva
author_facet Fidel Selva
Ruth Fuentes-García
María Fernanda Gil-Leyva
author_sort Fidel Selva
collection DOAJ
description Bayesian nonparametric models have proven to be successful tools for clustering and density estimation. While there exists a nourished ecosystem of implementations in R, for Python there are only a few. Here we develop a Python package called pyrichlet, for Bayesian nonparametric density estimation and clustering using various state-of-the-art Gaussian mixture models that generalize the well established Dirichlet process mixture, many of which are fairly new. Implementation is performed using Markov chain Monte Carlo techniques as well as variational Bayes methods. This article contains a detailed description of pyrichlet and examples for its usage with a real dataset.
format Article
id doaj-art-99ef006a24df4d05bbb0a2a59323480b
institution Kabale University
issn 1548-7660
language English
publishDate 2025-03-01
publisher Foundation for Open Access Statistics
record_format Article
series Journal of Statistical Software
spelling doaj-art-99ef006a24df4d05bbb0a2a59323480b2025-08-20T03:32:16ZengFoundation for Open Access StatisticsJournal of Statistical Software1548-76602025-03-01112110.18637/jss.v112.i08pyrichlet: A Python Package for Density Estimation and Clustering Using Gaussian Mixture ModelsFidel Selva0https://orcid.org/0009-0004-5822-635XRuth Fuentes-García1https://orcid.org/0000-0002-8253-3518María Fernanda Gil-Leyva2https://orcid.org/0000-0003-0811-5083Uiversidad Nacional Autónoma de MéxicoUiversidad Nacional Autónoma de MéxicoUiversidad Nacional Autónoma de México Bayesian nonparametric models have proven to be successful tools for clustering and density estimation. While there exists a nourished ecosystem of implementations in R, for Python there are only a few. Here we develop a Python package called pyrichlet, for Bayesian nonparametric density estimation and clustering using various state-of-the-art Gaussian mixture models that generalize the well established Dirichlet process mixture, many of which are fairly new. Implementation is performed using Markov chain Monte Carlo techniques as well as variational Bayes methods. This article contains a detailed description of pyrichlet and examples for its usage with a real dataset. https://www.jstatsoft.org/index.php/jss/article/view/4925
spellingShingle Fidel Selva
Ruth Fuentes-García
María Fernanda Gil-Leyva
pyrichlet: A Python Package for Density Estimation and Clustering Using Gaussian Mixture Models
Journal of Statistical Software
title pyrichlet: A Python Package for Density Estimation and Clustering Using Gaussian Mixture Models
title_full pyrichlet: A Python Package for Density Estimation and Clustering Using Gaussian Mixture Models
title_fullStr pyrichlet: A Python Package for Density Estimation and Clustering Using Gaussian Mixture Models
title_full_unstemmed pyrichlet: A Python Package for Density Estimation and Clustering Using Gaussian Mixture Models
title_short pyrichlet: A Python Package for Density Estimation and Clustering Using Gaussian Mixture Models
title_sort pyrichlet a python package for density estimation and clustering using gaussian mixture models
url https://www.jstatsoft.org/index.php/jss/article/view/4925
work_keys_str_mv AT fidelselva pyrichletapythonpackagefordensityestimationandclusteringusinggaussianmixturemodels
AT ruthfuentesgarcia pyrichletapythonpackagefordensityestimationandclusteringusinggaussianmixturemodels
AT mariafernandagilleyva pyrichletapythonpackagefordensityestimationandclusteringusinggaussianmixturemodels