Estimating Behavioral States Using Hidden Markov Models | Live-coding in R

Part 6 of the Space-Use and Behavioral State Estimation Workshop.

This shows a live-coding exercise on estimating behavioral states, including the effects of environmental covariates, with a green sea turtle (Chelonia mydas) satellite telemetry dataset. All coding is performed using the R programming language within the RStudio IDE, where models are formulated using different numbers of discrete behavioral states, different sets of data streams, and the evaluation of sea surface temperature and hour of day on state transitions. Modeling is performed using the {momentuHMM} R package, developed by Brett McClintock and Théo Michelot. 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.