On the small sample behavior of Dirichlet process mixture models for data supported on compact intervals

DOI10.1080/03610918.2019.1568470zbMath1489.62119OpenAlexW2912821314MaRDI QIDQ5082570

Alejandro Jara, Andrés F. Barrientos, Claudia Wehrhahn

Publication date: 21 June 2022

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2019.1568470

zbMATH Keywords

Bayesian nonparametricsdensity estimationrandom Bernstein polynomialsmixture of beta distributionsposterior convergence rate

Mathematics Subject Classification ID

Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20) Bayesian inference (62F15)

Related Items (1)

Bayesian estimation of a decreasing density

Uses Software

• boa
• DPpackage

Cites Work

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• On a class of Bayesian nonparametric estimates: I. Density estimates
• Rates of convergence for the posterior distributions of mixtures of betas and adaptive nonparametric estimation of the density
• Posterior convergence rates of Dirichlet mixtures at smooth densities
• Posterior consistency of Dirichlet mixtures in density estimation
• Prior distributions on spaces of probability measures
• Convergence rates of posterior distributions.
• Rates of convergence of posterior distributions.
• Convergence rates for density estimation with Bernstein polynomials.
• Bayesian nonparametric data analysis
• Posterior convergence rates for Dirichlet mixtures of beta densities
• A Bayesian analysis of some nonparametric problems
• Nonparametric Bayesian survival analysis using mixtures of Weibull distributions
• Posterior concentration rates for infinite dimensional exponential families
• A Predictive Approach to Model Selection
• Bayesian density estimation using bernstein polynomials
• Consistency of Bernstein Polynomial Posteriors
• Bayesian Density Estimation and Inference Using Mixtures
• Random Bernstein Polynomials
• On Consistency of Nonparametric Normal Mixtures for Bayesian Density Estimation

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