Semiparametric Bayesian Small Area Estimation Based on Dirichlet Process Priors

DOI10.1007/978-1-4939-0569-0_24zbMath1357.62050OpenAlexW2281936105MaRDI QIDQ2787381

Silvia Polettini

Publication date: 25 February 2016

Published in: Springer Proceedings in Mathematics & Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-1-4939-0569-0_24

zbMATH Keywords

Dirichlet processGibbs samplingsmall area estimationhierarchical Bayesmixed modelFay-Herriotnonparametric random effects

Mathematics Subject Classification ID

Nonparametric estimation (62G05) Bayesian inference (62F15) Sampling theory, sample surveys (62D05)

Cites Work

• On a class of Bayesian nonparametric estimates: I. Density estimates
• Linear mixed models with skew-elliptical distributions: a Bayesian approach
• Characterizing the variance improvement in linear Dirichlet random effects models
• Robust linear mixed models for small area estimation
• Mixtures of Dirichlet processes with applications to Bayesian nonparametric problems
• Ferguson distributions via Polya urn schemes
• Nonparametric hierarchical Bayes via sequential imputations
• Robust hierarchical Bayes estimation of small area characteristics in the presence of covariates and outliers
• On selecting a prior for the precision parameter of Dirichlet process mixture models
• A Bayesian analysis of some nonparametric problems
• Smooth Random Effects Distribution in a Linear Mixed Model
• Robust small area estimation
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