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Stochastic process models of animal movement, maximum entropy, and approximation theory

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MMVW01 - Summer School on Mathematics of Movement

I detail a class of maximum-entropy stochastic-process models that contains within it all of the continuous-time stationary processes that have been commonly used to model animal movement—including Brownian motion, Ornstein-Uhlenbeck motion, and integrated Ornstein-Uhlenbeck motion. Then I show how linear combinations of these maximum-entropy processes can approximate more general stationary processes by way of Padé approximants. I end with discussion of some simpler ways that these stationary processes can be generalized into more realistic non-stationary processes.

This talk is part of the Isaac Newton Institute Seminar Series series.

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