Asymptotic properties of posterior distributions in nonparametric regression with non-Gaussian errors

DOI10.1007/s10463-008-0168-2zbMath1332.62130OpenAlexW2020355545MaRDI QIDQ904050

Taeryon Choi

Publication date: 15 January 2016

Published in: Annals of the Institute of Statistical Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10463-008-0168-2

zbMATH Keywords

Kullback-Leibler divergenceposterior consistencyHellinger metricsymmetric densityprior positivityuniformly consistent tests

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Asymptotic distribution theory in statistics (62E20) Asymptotic properties of nonparametric inference (62G20) Bayesian inference (62F15) Bayesian problems; characterization of Bayes procedures (62C10)

Related Items (5)

Bayesian quantile regression and variable selection for partial linear single-index model: Using free knot spline ⋮ On asymptotic properties of Bayesian partially linear models ⋮ Bayesian nonparametric regression with varying residual density ⋮ Bayesian spectral analysis models for quantile regression with Dirichlet process mixtures ⋮ Consistency of Posterior Distributions for Heteroscedastic Nonparametric Regression Models

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