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Activity Number: 176 - Modeling
Type: Contributed
Date/Time: Monday, July 30, 2018 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistical Computing
Abstract #329262 Presentation
Title: Bayesian Emulation and Calibration of an Individual-Based Model Simulation of Microbial Communities
Author(s): Oluwole Oyebamiji* and Darren James Wilkinson
Companies: Newcastle University and Newcastle University
Keywords: Biofilm; Individual-based models; Dynamic linear models; Bayesian MCMC; Gaussian process; Calibration

Individual-based (IB) modelling has been widely used for studying the emergence of complex interactions of bacterial biofilms and their environment. We describe the emulation and calibration of an expensive dynamic simulator of an IB model of microbial communities. We used a combination of dynamic linear models and a Gaussian process to estimate the model parameters of our dynamic emulators. The emulators incorporated a smoothly varying and nonstationary trend that is modelled as a deterministic function of explanatory variables while the Gaussian process is allowed to capture the remaining intrinsic local variations. We applied this emulation strategy for parameter calibration of an IB model simulation of microbial communities. The calibration results are evaluated and compared where the best model explained 83.3% of output variance with RMSECV of 1.55. The simulation-based sensitivity analysis identified carbon substrate, oxygen concentration and maximum growth rate for heterotrophic bacteria as the most critical variables for predictions. The approach illustrated provides a tractable and computationally efficient technique for calibrating the parameters of an expensive model.

Authors who are presenting talks have a * after their name.

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