Hierarchical Bayesian nonparametric mixture models for clustering with variable relevance determination

DOI10.1214/11-BA612zbMath1330.62265OpenAlexW2046405061WikidataQ42770864 ScholiaQ42770864MaRDI QIDQ2634092

Christopher Yau, Christopher C. Holmes

Publication date: 8 February 2016

Published in: Bayesian Analysis (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/euclid.ba/1339612049

zbMATH Keywords

unsupervised learningvariable selectionBayesian mixture modelsBayesian nonparametric priors

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Random measures (60G57) Statistical aspects of information-theoretic topics (62B10)

Related Items (11)

A Bayesian mixture of Lasso regressions with \(t\)-errors ⋮ Bayesian nonparametric clustering as a community detection problem ⋮ Bayesian sparse convex clustering via global-local shrinkage priors ⋮ Bayesian variable selection for finite mixture model of linear regressions ⋮ A Bayesian panel vector autoregression to analyze the impact of climate shocks on high-income economies ⋮ Stochastic model specification in Markov switching vector error correction models ⋮ The M-Bayesian Credible Limits of the Reliability Derived from Binomial Distribution ⋮ Model-based clustering based on sparse finite Gaussian mixtures ⋮ Modeling the Association Between Clusters of SNPs and Disease Responses ⋮ Clustering in linear mixed models with approximate Dirichlet process mixtures using EM algorithm ⋮ Bayesian variable selection in clustering high-dimensional data via a mixture of finite mixtures

This page was built for publication: Hierarchical Bayesian nonparametric mixture models for clustering with variable relevance determination