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Efficient Bayesian Filtering and Inference for Integro-Difference Equation Models
Integro-Difference Equation (IDE) models are a class of dynamic spatio-temporal models which describe the temporal evolution of a spatial process, usually to model advection and diffusion of some random field over time. While several papers have focused on inference and performance of these models
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