Animal behaviour on the move: the use of auxiliary information and semi-supervision to improve behavioural inferences from Hidden Markov Models applied to GPS tracking datasets

BACKGROUND: State-space models, such as Hidden Markov Models (HMMs), are increasingly used to classify animal tracks into behavioural states. Typically, step length and turning angles of successive locations are used to infer where and when an animal is resting, foraging, or travelling. However, the...

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Detalles Bibliográficos
Autores principales: Saldanha, Sarah, Cox, Sam L., Militão, Teresa, González-Solís, Jacob
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10367325/
https://www.ncbi.nlm.nih.gov/pubmed/37488611
http://dx.doi.org/10.1186/s40462-023-00401-5

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10367325/
https://www.ncbi.nlm.nih.gov/pubmed/37488611
http://dx.doi.org/10.1186/s40462-023-00401-5

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