Using approximate Bayesian inference for a "steps and turns" continuous-time random walk observed at regular time intervals.

ABSTRACT: The study of animal movement is challenging because movement is a process modulated by many factors acting at different spatial and temporal scales. In order to describe and analyse animal movement, several models have been proposed which differ primarily in the temporal conceptualization, namely continuous and discrete time formulations. Naturally, animal movement occurs in continuous time but we tend to observe it at fixed time intervals. To account for the temporal mismatch between observations and movement decisions, we used a state-space model where movement decisions (steps and turns) are made in continuous time. That is, at any time there is a non-zero probability of making a change in movement direction. The movement process is then observed at regular time intervals. As the likeli

SUBMITTER: Ruiz-Suarez S 

PROVIDER: S-EPMC7020826 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature