Nonasymptotic approach to Bayesian semiparametric inference

DOI10.1134/S1064562416020101zbMath1353.62034OpenAlexW2403524553MaRDI QIDQ2631198

Maxim E. Panov

Publication date: 29 July 2016

Published in: Doklady Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1134/s1064562416020101

Mathematics Subject Classification ID

Nonparametric estimation (62G05) Bayesian inference (62F15)

Related Items (1)

On accuracy of Gaussian approximation in Bayesian semiparametric problems

Cites Work

• Finite sample Bernstein-von Mises theorem for semiparametric problems
• The semiparametric Bernstein-von Mises theorem
• Critical dimension in profile semiparametric estimation
• Statistics for high-dimensional data. Methods, theory and applications.
• A semiparametric Bernstein-von Mises theorem for Gaussian process priors
• Bernstein-von Mises theorem for linear functionals of the density
• General frequentist properties of the posterior profile distribution
• Asymptotics in statistics: some basic concepts
• The consistency of posterior distributions in nonparametric problems
• Properties of the Bayesian parameter estimation of a regression based on Gaussian processes
• Asymptotic Normality of Semiparametric and Nonparametric Posterior Distributions
• On Bayes procedures

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