Two-step Bayesian methods for generalized regression driven by partial differential equations

DOI10.3150/21-BEJ1363OpenAlexW4224309056WikidataQ114038748 ScholiaQ114038748MaRDI QIDQ2137034

Wenli Shi, Prithwish Bhaumik, Subhashis Ghosal

Publication date: 16 May 2022

Published in: Bernoulli (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/journals/bernoulli/volume-28/issue-3/Two-step-Bayesian-methods-for-generalized-regression-driven-by-partial/10.3150/21-BEJ1363.full

zbMATH Keywords

tensor productsBernstein-von Mises theorempartial differential equationcontiguityB-splinestwo-step methodgeneralized regressionprojection posterior

Mathematics Subject Classification ID

Parametric inference (62Fxx) Numerical methods for ordinary differential equations (65Lxx) Nonparametric inference (62Gxx)

Related Items (1)

Coverage of credible intervals in Bayesian multivariate isotonic regression

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