Managing uncertainty in complex stochastic models: design and emulation of a Rabies model

Alexis Boukouvalas, Dan Cornford, Alexander Singer

Research output: Unpublished contribution to conferenceUnpublished Conference Paper


In this paper we present a novel method for emulating a stochastic, or random output, computer model and show its application to a complex rabies model. The method is evaluated both in terms of accuracy and computational efficiency on synthetic data and the rabies model. We address the issue of experimental design and provide empirical evidence on the effectiveness of utilizing replicate model evaluations compared to a space-filling design. We employ the Mahalanobis error measure to validate the heteroscedastic Gaussian process based emulator predictions for both the mean and (co)variance. The emulator allows efficient screening to identify important model inputs and better understanding of the complex behaviour of the rabies model.
Original languageEnglish
Number of pages3
Publication statusPublished - Jun 2009
Event6th St. Petersburg Workshop on Simulation - St Petersburg , Russian Federation
Duration: 28 Jun 20094 Jul 2009


Other6th St. Petersburg Workshop on Simulation
Country/TerritoryRussian Federation
CitySt Petersburg


  • stochastic computer model
  • complex rabies mode
  • Mahalanobis error measure
  • heteroscedastic Gaussian process
  • emulator predictions


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