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Spatio-temporal models have the potential to represent a wide variety of dynamic behaviour such as the growth of bacteria, the dispersion of a pollutant or the changing spatial patterns in house prices. Classical methods for the simulation of such behaviours suffer from large computational demands due to their high dimensionality. Recent advances in spatiotemporal modelling have proposed a method based on a statespace representation of the spatio-temporal integro-difference equation. Although the dimension reduction obtained when using this model is significant, it is frequently not sufficient for online computation or rapid simulation.
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