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...
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| Format: | Article |
| Language: | English |
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Foundation for Open Access Statistics
2025-03-01
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| Series: | Journal of Statistical Software |
| Online Access: | https://www.jstatsoft.org/index.php/jss/article/view/4925 |
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| _version_ | 1849418961744035840 |
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| 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.
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| 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 |