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Durham University

Department of Mathematical Sciences

Academic Staff

Publication details for Camila Caiado

Caiado, C.C.S. & Goldstein, M. (2015). Bayesian uncertainty analysis for complex physical systems modelled by computer simulators with applications to tipping points. Communications in Nonlinear Science and Numerical Simulation 26(1-3): 123-136.

Author(s) from Durham


In this paper we present and illustrate basic Bayesian techniques for the uncertainty analysis of complex physical systems modelled by computer simulators. We focus on emulation and history matching and also discuss the treatment of observational errors and structural discrepancies in time series. We exemplify such methods using a four-box model for the termohaline circulation. We show how these methods may be applied to systems containing tipping points and how to treat possible discontinuities using multiple emulators.