On selecting a prior for the precision parameter of Dirichlet process mixture models

DOI10.1016/j.jspi.2009.03.009zbMath1168.62022OpenAlexW1986430351MaRDI QIDQ2388972

Robert M. Dorazio

Publication date: 22 July 2009

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jspi.2009.03.009

zbMATH Keywords

empirical BayesBayesian nonparametricsDirichlet processmodel uncertaintymixture modelsobjective prior

Mathematics Subject Classification ID

Related Items (17)

The apparent fine-tuning of the cosmological, gravitational and fine structure constants ⋮ Borrowing Strength with Nonexchangeable Priors over Subpopulations ⋮ Adjusting background noise in cluster analyses of longitudinal data ⋮ The determination of uncertainty levels in robust clustering of subjects with longitudinal observations using the Dirichlet process mixture ⋮ Life, the multiverse, and fine-tuning. Fact, fiction, and misconceptions ⋮ Selecting the precision parameter prior in Dirichlet process mixture models ⋮ Bayesian clustering of animal abundance trends for inference and dimension reduction ⋮ Goodness-of-fit tests based on the distance between the Dirichlet process and its base measure ⋮ Topics on Dynamic Panel Data Models with Random Effects Using Semi-Parametric Bayesian Approach ⋮ Semi-parametric Bayesian estimation of mixed-effects models using the multivariate skew-normal distribution ⋮ Semiparametric Bayesian Small Area Estimation Based on Dirichlet Process Priors ⋮ Stylometric analyses using Dirichlet process mixture models ⋮ Mitigating bias in generalized linear mixed models: the case for Bayesian nonparametrics ⋮ Generalized mixtures of finite mixtures and telescoping sampling ⋮ Bayesian test of normality versus a Dirichlet process mixture alternative ⋮ An Adversarial Risk Analysis Framework for Batch Acceptance Problems ⋮ Bayesian generalizations of the integer-valued autoregressive model

Uses Software

• R
• DPpackage

Cites Work

• Unnamed Item
• Unnamed Item
• A Dirichlet process mixture model for the analysis of correlated binary responses
• Mixtures of Dirichlet processes with applications to Bayesian nonparametric problems
• Ferguson distributions via Polya urn schemes
• Nonparametric Bayesian data analysis
• Nonparametric hierarchical Bayes via sequential imputations
• Some new results for Dirichlet priors.
• Bayesian nonparametrics
• Estimation in Dirichlet random effects models
• A Bayesian analysis of some nonparametric problems
• Contributions to the theory of Dirichlet processes
• Hierarchical Dirichlet Processes
• Modeling Unobserved Sources of Heterogeneity in Animal Abundance Using a Dirichlet Process Prior
• Bayesian curve fitting using multivariate normal mixtures
• Dirichlet Process Mixed Generalized Linear Models
• Bayesian Density Estimation and Inference Using Mixtures
• Semiparametric Bayesian Analysis of Case–Control Data under Conditional Gene‐Environment Independence
• Semiparametric Bayesian Analysis of Matched Case-Control Studies With Missing Exposure
• Bayesian Nonparametric Spatial Modeling With Dirichlet Process Mixing

This page was built for publication: On selecting a prior for the precision parameter of Dirichlet process mixture models