Comparison of Statistical and Deterministic Frameworks of Uncertainty Quantification

DOI10.1137/15M1019131zbMath1356.62037MaRDI QIDQ3179311

Jerome Sacks, Michael Frenklach, Gonzalo García-Donato, Rui Paulo, Andrew K. Packard

Publication date: 21 December 2016

Published in: SIAM/ASA Journal on Uncertainty Quantification (Search for Journal in Brave)

zbMATH Keywords

Bayesian analysisuncertainty quantificationcomputer modelsmodel predictionbound-to-bound data collaborationnatural-gas combustion

Mathematics Subject Classification ID

Related Items (5)

Identification of dynamical systems with structured uncertainty ⋮ Consistency Analysis for Massively Inconsistent Datasets in Bound-to-Bound Data Collaboration ⋮ A bridge between invariant dynamical structures and uncertainty quantification ⋮ Analyzing stochastic computer models: a review with opportunities ⋮ Representing Model Discrepancy in Bound-to-Bound Data Collaboration

Uses Software

• R
• WinBUGS
• GRI-Mech 3.0
• BayesDA

Cites Work

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• Numerical approaches for collaborative data processing
• Computer model validation with functional output
• Bayesian Calibration of Computer Models
• Numerical Challenges in the Use of Polynomial Chaos Representations for Stochastic Processes
• Prior distributions for variance parameters in hierarchical models (Comment on article by Browne and Draper)

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