On the Bayesian calibration of computer model mixtures through experimental data, and the design of predictive models

DOI10.1016/j.jcp.2017.04.003zbMath1376.86005OpenAlexW2608757158MaRDI QIDQ1686611

Guang Lin, Georgios Karagiannis

Publication date: 15 December 2017

Published in: Journal of Computational Physics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jcp.2017.04.003

zbMATH Keywords

Gaussian processMarkov chain Monte Carlocomputer experimentsuncertainty quantificationpolynomial basesmultinomial logistic model

Mathematics Subject Classification ID

Bayesian inference (62F15) Monte Carlo methods (65C05) Meteorology and atmospheric physics (86A10)

Related Items (1)

Fixed inducing points online Bayesian calibration for computer models with an application to a scale-resolving CFD simulation

Uses Software

• gss
• CAM3

Cites Work

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