Identifying latent behavioural states in animal movement with M4, a nonparametric Bayesian method

Abstract

Understanding animal movement often relies upon telemetry and biologging devices. These data are frequently used to estimate latent behavioural states to help understand why animals move across the landscape. While there are a variety of methods that make behavioural inferences from biotelemetry data, some features of these methods (e.g. analysis of a single data stream, use of parametric distributions) may limit their generality to reliably discriminate among behavioural states.

Document Details

Document Type
Pub Defense Publication
Publication Date
Oct 31, 2021
Source ID
10.1111/2041-210x.13745

Entities

People

  • Caroline L Poli
  • Denis Valle
  • Joshua A Cullen
  • Robert J. Fletcher

Organizations

  • Florida Fish and Wildlife Conservation Commission
  • National Institute of Food and Agriculture
  • National Science Foundation
  • United States Army Corps of Engineers
  • University of Florida

Tags

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Marine Mammal Biology
  • Regression Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference