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Bayesian Calibration of a Stochastic Kinetic Computer Model Using Multiple Data Sources

Lookup NU author(s): Dr Daniel Henderson, Professor Richard Boys, Professor Darren Wilkinson

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Abstract

In this article, we describe a Bayesian approach to the calibration of a stochastic computer model of chemical kinetics. As with many applications in the biological sciences, the data available to calibrate the model come from different sources. Furthermore, these data appear to provide somewhat conflicting information about the model parameters. We describe a modeling framework that allows us to synthesize this conflicting information and arrive at a consensus inference. In particular, we show how random effects can be incorporated into the model to account for between-individual heterogeneity that may be the source of the apparent conflict.

Publication metadata

Author(s): Henderson DA, Boys RJ, Wilkinson DJ

Publication type: Article

Publication status: Published

Journal: Biometrics

Year: 2010

Volume: 66

Issue: 1

Pages: 249-256

ISSN (print): 0006-341X

ISSN (electronic): 1541-0420

Publisher: Wiley-Blackwell Publishing Ltd.

URL: http://dx.doi.org/10.1111/j.1541-0420.2009.01245.x

DOI: 10.1111/j.1541-0420.2009.01245.x

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