Journal
SIAM JOURNAL ON SCIENTIFIC COMPUTING
Volume 26, Issue 2, Pages 467-487Publisher
SIAM PUBLICATIONS
DOI: 10.1137/S106482750342670X
Keywords
direct simulator; indirect simulator; top simulator; measurable inputs; tuning inputs; Bayesian inference; calibration; history matching; calibrated prediction; uncertainty analysis
Categories
Funding
- Natural Environment Research Council [NER/T/S/2002/00450] Funding Source: researchfish
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We outline a probabilistic framework for linking mathematical models to the physical systems that they represent, taking account of all sources of uncertainty including model and simulator imperfections. This framework is a necessary precondition for making probabilistic statements about the system on the basis of evaluations of computer simulators. We distinguish simulators according to their quality and the nature of their inputs. Where necessary, we introduce further hypothetical simulators as modelling constructs to account for imperfections in the available simulators and to unify the available simulators with the underlying system.
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