Melded Bayesian Inference for Stochastic Theoretical Models with Applications in Agent Based Modelling
Bayesian melding is extended for applications to stochastic theoretical models. Agent Based models, a class of stochastic theoretical models, are investigated and it is found that the common challenge of parameter specification can be addressed with the extensions to Bayesian melding. Two versions of the extended framework are applied to the Agent Based model of bumblebee foraging behaviour published in Smolla, Alem, et al. 2016. The applications demonstrate...[Show more]
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