Continuous-time discrete-space models for animal movement

Annals of Applied Statistics
By: , and 

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Abstract

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.

Additional publication details

Publication type Article
Publication Subtype Journal Article
Title Continuous-time discrete-space models for animal movement
Series title Annals of Applied Statistics
DOI 10.1214/14-AOAS803
Volume 9
Issue 1
Year Published 2015
Language English
Publisher Institute of Mathematical Statistics
Publisher location Cleveland, OH
Contributing office(s) Coop Res Unit Seattle
Description 21 p.
First page 145
Last page 165
Online Only (Y/N) N
Additional Online Files (Y/N) N