Part 7 of the Space-Use and Behavioral State Estimation Workshop.
This presentation provides an in-depth perspective on how non-parametric Bayesian models can be used to estimate behavioral states (and the likely number of states) from animal telemetry data. This includes conceptual descriptions about how Bayesian mixture models (observation-level) and mixed-membership models (segment-level) operate, as well as detailed annotations of mathematical expressions showing how different parameters are used to estimate breakpoints, the likely number of states, and state-dependent distributions. Additional details about the workshop and associated materials can be found at the workshop website https://joshcullen.github.io/Behavior_and_SpaceUse_Workshop/.
This material is based upon work supported by the National Science Foundation under Grant Numbers 2126583 and 1904818. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.