Selection of polynomial chaos bases via Bayesian model uncertainty methods with applications to sparse approximation of PDEs with stochastic inputs

DOI10.1016/j.jcp.2013.11.016zbMath1349.62080OpenAlexW1987784373MaRDI QIDQ348681

Guang Lin, Georgios Karagiannis

Publication date: 5 December 2016

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

Full work available at URL: http://dro.dur.ac.uk/22660/1/22660.pdf

zbMATH Keywords

splinesMCMCuncertainty quantificationLassogeneralized polynomial chaosBayesian model averageBayesian model uncertaintymedian probability model

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Ridge regression; shrinkage estimators (Lasso) (62J07) Nonparametric estimation (62G05) Bayesian inference (62F15) Computational methods for stochastic equations (aspects of stochastic analysis) (60H35)

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