The semi-parametric Bernstein-von Mises theorem for regression models with symmetric errors

DOI10.5705/ss.202017.0074zbMath1432.62202arXiv1607.04367OpenAlexW3098907311MaRDI QIDQ5226643

Yongdai Kim, B. J. K. Kleijn, Minwoo Chae

Publication date: 1 August 2019

Published in: Statistica Sinica (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1607.04367

zbMATH Keywords

Bernstein-von Mises theoremlinear regressionsemiparametric efficiencylinear mixed-effect modelsymmetric error

Mathematics Subject Classification ID

Asymptotic distribution theory in statistics (62E20) Asymptotic properties of nonparametric inference (62G20) Linear regression; mixed models (62J05) Nonparametric estimation (62G05)

Related Items (4)

Semiparametric estimation for linear regression with symmetric errors ⋮ Bayesian high-dimensional semi-parametric inference beyond sub-Gaussian errors ⋮ Posterior asymptotics in Wasserstein metrics on the real line ⋮ Construction of credible intervals for nonlinear regression models with unknown error distributions

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