ArticleAdvances in data analysis and classification2019
From here to infinity: sparse finite versus Dirichlet process mixtures in model-based clustering.
Article in Advances in data analysis and classification, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- VICatMix: variational Bayesian clustering and variable selection for discrete biomedical data.Bioinformatics advances · 2025Article
- A Bayesian nonparametric model for bounded directional data on the positive orthant of the unit sphere.Journal of applied statistics · 2024Article
- Bayesian cluster analysis.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2023Review
- Escaping The Curse of Dimensionality in Bayesian Model-Based Clustering.Journal of machine learning research : JMLR · 2023Article
- COVID-19 clinical footprint to infer about mortality.Journal of the Royal Statistical Society. Series A, (Statistics in Society) · 2022Article
- Bayesian Mixture Model of Extended Redundancy Analysis.Psychometrika · 2022Article
- Dynamic Dirichlet process mixture model for identifying voting coalitions in the United Nations General Assembly human rights roll call votes.Journal of applied statistics · 2022Article
- Article
- Integrating latent classes in the Bayesian shared parameter joint model of longitudinal and survival outcomes.Statistical methods in medical research · 2020Article
Corrections and comments
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Authors and funding
2 authors.
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Abstract
In model-based clustering mixture models are used to group data points into clusters. A useful concept introduced for Gaussian mixtures by Malsiner Walli et al. (Stat Comput 26:303-324, 2016) are sparse finite mixtures, where the prior distribution on the weight distribution of a mixture with
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.