Hidden Markov Models - An introduction

** Our speaker
Theoni Photopoulou, a Quantitative ecologist and Marine biologist, currently at the University of St Andrews, Scotland, working on animal movement models.

** Details
Hidden Markov models (HMMs) are flexible, general-purpose models for time series data. They are discrete time models and can be used to analyse time-regular data. One area in which they have been increasing in popularity is animal movement, where they are used to better understand the structure in animal location data, such as GPS tracks. I will present an introduction to HMMs and some examples using two R packages, moveHMM and momentuHMM.

Photo by Barth Bailey on Unsplash.