Calibration and Uncertainty Analysis for Computer Simulations with Multivariate Output

By John M. McFarland, Sankaran Mahadevan, Vicente J. Romero, Laura Painton Swiler. 2008

97 citations recorded by the source corpus.

How researchers see this paper

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1. Mauricio A Álvarez
2. Maria J. Bayarri
3. Lorenzo Rosasco
4. Neil D. Lawrence
5. James O. Berger
6. Haitao Liu
7. Athanasios Kottas
8. J. Sacks

Citations in the corpus

• Kernels for Vector-Valued Functions: a Review (2011, background): “In [63], the time series is the temperature of a particular location of a container with decomposing foam.”
• Predicting Vehicle Crashworthiness: Validation of Computer Models for Functional and Hierarchical Data (2009, methodology): “Similar approaches are taken in Conti and O’Hagan (2007), Rougier (2007), and McFarkand et al. (2008).”
• Quantification of model uncertainty: Calibration, model discrepancy, and identifiability (2012, methodology): “We argue that model uncertainty quantification as it is typically implemented in a model updating process, using only a single response variable, is challenging due to a lack of identifiability of calibration parameters in conjunction with the model discrepancy.”