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

  1. Lookup NU author(s)
  2. Dr Daniel Henderson
  3. Professor Richard Boys
  4. Professor Darren Wilkinson
Author(s)Henderson DA, Boys RJ, Wilkinson DJ
Publication type Article
JournalBiometrics
Year2010
Volume66
Issue1
Pages249-256
ISSN (print)0006-341X
ISSN (electronic)1541-0420
Full text for this publication is not currently held within this repository. Alternative links are provided below where available.
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.
PublisherWiley-Blackwell Publishing Ltd.
URLhttp://dx.doi.org/10.1111/j.1541-0420.2009.01245.x
DOI10.1111/j.1541-0420.2009.01245.x
Actions    Link to this publication