Biometrics. 2010 Mar;66(1):249-56. Epub 2009 Apr 13.

Bayesian calibration of a stochastic kinetic computer model using multiple data sources.

Source

School of Mathematics & Statistics, Newcastle University, Newcastle upon Tyne, NE1 7RU, U.K. d.a.henderson@ncl.ac.uk

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.

PMID:: 19397580; [PubMed - indexed for MEDLINE]

Publication Types, MeSH Terms, Substances, Grant Support

Publication Types

Research Support, Non-U.S. Gov't

MeSH Terms

Substances

Biopolymers

Grant Support

BBS/B/16550/Biotechnology and Biological Sciences Research Council/United Kingdom

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