Fig. 3

The structure of a hidden Markov model, where the hidden states (Zt) depend on the previous state, and the observed data (Yt) depends on the hidden state. In the case of modeling animal movement, the observed process is composed of empirical data such as step lengths and turning angles, and the hidden state may represent behaviours such as foraging, resting, and traveling