On the Bayesian calibration of computer model mixtures through experimental data, and the design of predictive models
type: Item
instance of: scholarly article
title: On the Bayesian calibration of computer model mixtures through experimental data, and the design of predictive models
zbMATH Open document ID: 1376.86005
author: Georgios Karagiannis
author: Guang Lin
published in: Journal of Computational Physics
publication date: 2017-12-15T00:00:00Z
Mathematics Subject Classification ID: 86A10
Mathematics Subject Classification ID: 62F15
Mathematics Subject Classification ID: 65C05
zbMATH DE Number: 6819102
zbMATH Keywords: uncertainty quantification
zbMATH Keywords: computer experiments
zbMATH Keywords: Gaussian process
zbMATH Keywords: polynomial bases
zbMATH Keywords: multinomial logistic model
zbMATH Keywords: Markov chain Monte Carlo
describes a project that uses: CAM3
describes a project that uses: gss
MaRDI profile type: Publication
full work available at URL: j.jcp.2017.04.003
OpenAlex ID: W2608757158
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DOI: 10.1016/J.JCP.2017.04.003
description: scientific article; zbMATH DE number 6819102