Continuous-time discrete-space models for animal movement
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Title
Continuous-time discrete-space models for animal movement
Description
The processes influencing animal movement and resource selection are complex and varied. Past efforts to model behavioral changes over time used Bayesian statistical models with variable parameter space, such as reversible-jump Markov chain Monte Carlo approaches, which are computationally demanding and inaccessible to many practitioners. We present a continuous-time discrete-space (CTDS) model of animal movement that can be fit using standard generalized linear modeling (GLM) methods. This CTDS approach allows for the joint modeling of location-based as well as directional drivers of movement. Changing behavior over time is modeled using a varying-coefficient framework which maintains the computational simplicity of a GLM approach, and variable selection is accomplished using a group lasso penalty. We apply our approach to a study of two mountain lions (Puma concolor) in Colorado, USA.
Bibliographic Citation
Hanks, E. M., M. B. Hooten, and M. W. Alldredge. 2015. Continuous-time discrete-space models for animal movement. The Annals of Applied Statistics 9:145-165. https://doi.org/10.1214/14-AOAS803
Creator
Hanks, Ephraim M.
Hooten, Mevin B.
Alldredge, Mathew W.
Subject
Animal movement
Multiple imputation
Varying-coefficient model
Markov chain
Extent
21 pages
Date Created
2015-03
Type
Article
Format
application/pdf
Language
English
Is Part Of
The Annals of Applied Statistics
Collection
Citation
Hanks, Ephraim M., Hooten, Mevin B., and Alldredge, Mathew W., “Continuous-time discrete-space models for animal movement,” CPW Digital Collections, accessed October 31, 2025, https://cpw.cvlcollections.org/items/show/72.