https://www.selleckchem.com/pr....oducts/ly2880070.htm
Background Tackling behavioural questions often requires identifying points in space and time where animals make decisions and linking these to environmental variables. State-space modeling is useful for analysing movement trajectories, particularly with hidden Markov models (HMM). Yet importantly, the ontogeny of underlying (unobservable) behavioural states revealed by the HMMs has rarely been verified in the field. Methods Using hidden Markov models of individual movement from animal location, biotelemetry, and environmental data, w