Joint estimation over multiple individuals improves behavioural state inference from animal movement data
Abstract
State-space models provide a powerful way to scale up inference of movement behaviours from individuals to populations when the inference is made across multiple individuals. Here, I show how a joint estimation approach that assumes individuals share identical movement parameters can lead to improved inference of behavioural states associated with different movement processes. I use simulated movement paths with known behavioural states to...
Paper Details
Title
Joint estimation over multiple individuals improves behavioural state inference from animal movement data
Published Date
Feb 8, 2016
Journal
Volume
6
Issue
1
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