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Calibration of computer models with multivariate output. (English) Zbl 1255.62187

Summary: The problem of calibrating computer models that produce multivariate output is considered, with a particular emphasis on the situation where the model is computationally demanding. The proposed methodology builds on Gaussian process-based response-surface approximations to each of the components of the output of the computer model to produce an emulator of the multivariate output. This emulator is then combined in a statistical model involving field observations, which is then used to produce calibration strategies for the parameters of the computer model. The results of applying this methodology to a simulated example and to a real application are presented.

MSC:

62H99 Multivariate analysis
62M99 Inference from stochastic processes
68U99 Computing methodologies and applications
65C60 Computational problems in statistics (MSC2010)

Software:

DiceKriging; mlegp
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Full Text: DOI

References:

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