Edhe but also opportunities! Hidden Markov Models (HMM) and their extensions are attractive methods for analyzing ecological data. In recent years, a number of extensions of the base model have been proposed, providing great opportunities for ecological conclusions. However, as these models become more complex and challenging to understand, it is important to consider what pitfalls these methods have and what opportunities there are for future research to address these pitfalls.
Glennie et al. review the five pitfalls you may encounter when using HMM or their extensions to solve environmental problems. Their purpose is to raise awareness of the pitfalls that ecologists may encounter when applying these more advanced methods, but also, by highlighting future research opportunities, to inspire ecological statisticians to weaken these pitfalls and provide improved methods. . The following infographic illustrates the five pitfalls discussed in the paper:
To learn more, read the full article here: Hidden Markov Patterns: Traps and Opportunities in Ecology
This post was provided by the author Timo Adama researcher in statistics at St Andrews University.