Hidden Markov Models

Teo explains how hidden Markov models go beyond traditional mixture models by incorporating temporal dependence, allowing for the identification of different behaviors based on transitions between probability distributions. The complexity lies in understanding how animals transition between states, making it a nuanced approach to analyzing movement data.