Stochastic differential equation based on a multimodal potential to model movement data in ecology

Pierre Gloaguen (1) , Marie-Pierre Etienne (2) , Sylvain Le Corff (3)

1 IFREMER - Institut Français de Recherche pour l'Exploitation de la Mer
2 MIA-Paris - Mathématiques et Informatique Appliquées
3 Département de Mathématiques-Université de Paris XI

This paper proposes a new model for individuals movement in ecology. The movement process is defined as a solution to a stochastic differential equation whose drift is the gradient of a multimodal potential surface. This offers a new flexible approach among the popular potential based movement models in ecology. To perform parameter inference, the widely used Euler method is compared with two other pseudo-likelihood procedures and with a Monte Carlo Expectation Maximization approach based on exact simulation of diffusions. Performances of all methods are assessed with simulated data and with a data set of fishing vessels trajectories. We show that the usual Euler method performs worse than the other procedures for all sampling schemes.

Mots clés: Movement model; Stochastic differential equation; Exact simulation; Local linearization; Pseudo-likelihood methods

Domaines: Applications [stat.AP]; Biodiversité et Ecologie

Pierre Gloaguen, Marie-Pierre Etienne, Sylvain Le Corff. Stochastic differential equation based on a multimodal potential to model movement data in ecology. Journal of the Royal Statistical Society: Series C Applied Statistics, 2018, 67 (3). ⟨hal-01207001v3⟩