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Activity Number: 409 - Bayesian Space-Time Modeling
Type: Contributed
Date/Time: Tuesday, July 30, 2019 : 2:00 PM to 3:50 PM
Sponsor: Section on Bayesian Statistical Science
Abstract #306706
Title: Animal Movement Through Space and Time in a Hierarchical Bayesian Framework
Author(s): Alex Oard* and Athanasios Micheas
Companies: and University of Missouri
Keywords: hierarchical; Bayesian; mixture model; animal movement

Animal movement over space and time can depend on various environmental factors, such as bodies of water and roads, as well as their interaction with other animals. In this paper, we propose a hierarchical Bayesian framework to model animal movement over time, and consider several types of interactions between animals, including independent movement, attraction, inhibition, or collective movement. We develop a mixture model to account for the movement of animals based on their relationship with one another and their past locations. The evolution is captured using underlying process models for the parameters of the data and the parameter of the process models in the hierarchy. We illustrate the use of this model using ecological data.

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