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
Abstract 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. Howe...
| Autors principals: | , , , |
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| Format: | Article |
| Idioma: | English |
| Publicat: |
BMC
2023-07-01
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| Col·lecció: | Movement Ecology |
| Matèries: | |
| Accés en línia: | https://doi.org/10.1186/s40462-023-00401-5 |