Royal Statistical Society Ordinary Meeting
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December 13, 2000, 5pm (Tea from 4.30pm)
at the Royal Statistical Society lecture room
12 Errol Street, London EC1Y 8LX.
Bayesian Calibration of Computer Models
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Marc Kennedy (NISS) and
Tony O'Hagan (University of Sheffield)
Summary
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The importance of quantifying uncertainty in computer models is
increasingly recognised by users and developers of models. Often, data
are available with which to calibrate the model, i.e. to learn about
those unknown parameters which define the context in which the model
is to be used. We present a Bayesian approach in which residual
uncertainty after calibration is recognised. Our model also offers the
possibility of 'correcting' model deficiencies.
A PostScript copy of the paper can be downloaded from
http://www.maths.soton.ac.uk/staff/JJForster/RS
Contact Val Evans (email [log in to unmask]) at the RSS for further
details and for a hard copy of the galleys (stating your full address).
Discussion at RSS ordinary meetings
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