Niu, M., Blackwell, P. G. orcid.org/0000-0002-3141-4914 and Skarin, A. (2016) Modeling interdependent animal movement in continuous time. Biometrics, 72 (2). pp. 315-324. ISSN 0006-341X
Abstract
This article presents a new approach to modeling group animal movement in continuous time. The movement of a group of animals is modeled as a multivariate Ornstein Uhlenbeck diffusion process in a high-dimensional space. Each individual of the group is attracted to a leading point which is generally unobserved, and the movement of the leading point is also an Ornstein Uhlenbeck process attracted to an unknown attractor. The Ornstein Uhlenbeck bridge is applied to reconstruct the location of the leading point. All movement parameters are estimated using Markov chain Monte Carlo sampling, specifically a Metropolis Hastings algorithm. We apply the method to a small group of simultaneously tracked reindeer, Rangifer tarandus tarandus, showing that the method detects dependency in movement between individuals.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2016 The Authors Biometrics published by Wiley Periodicals, Inc. on behalf of International Biometric Society. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
Keywords: | Animal movement; Bayesian inference; Multivariate Ornstein Uhlenbeck process; Ornstein Uhlenbeck bridge; Stochastic differential equation |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Science (Sheffield) > School of Mathematics and Statistics (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 19 Jul 2016 14:53 |
Last Modified: | 19 Jul 2016 14:53 |
Published Version: | http://dx.doi.org/10.1111/biom.12454 |
Status: | Published |
Publisher: | Wiley |
Refereed: | Yes |
Identification Number: | 10.1111/biom.12454 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:101235 |