The DOI matches its Crossref record; 26 of the 27 references it cites were found in a registry or an index.
Selecting the Number of States in Hidden Markov Models: Pragmatic Solutions Illustrated Using Animal Movement
Abstract
We discuss the notorious problem of order selection in hidden Markov models, that is of selecting an adequate number of states, highlighting typical pitfalls and practical challenges arising when analyzing real data. Extensive simulations are used to demonstrate the reasons that render order selection particularly challenging in practice despite the conceptual simplicity of the task. In particular, we demonstrate why well-established formal procedures for model selection, such as those based on standard information criteria, tend to favor models with numbers of states that are undesirably large in situations where states shall be meaningful entities. We also offer a pragmatic step-by-step approach together with comprehensive advice for how practitioners can implement order selection. Our proposed strategy is illustrated with a real-data case study on muskox movement.Supplementary materials accompanying this paper appear online.
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“For animal behavior data, formal model selection techniques tend to select more HMM states than seem biologically reasonable (i.e., additional states compensate for the inability to capture all the structure in such complex data); therefore, we first considered a simple (2-state) model and then built up complexity until a reasonable goodness-of-fit was achieved, but such that the model states were”
From Seasonal activity levels of a farm-island population of striated caracaras (Phalcoboenus australis) in the Falkland Islands (2020) · cites this paper as [72]
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Cites
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Assessing a mixture model for clustering with the integrated completed likelihood
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EXTRACTING MORE OUT OF RELOCATION DATA: BUILDING MOVEMENT MODELS AS MIXTURES OF RANDOM WALKS
Morales, J., Haydon, D., Frair, J., Holsinger, K., & Fryxell, J. (2004) · Ecology · doi:10.1890/03-0269 · Cited by 837
Hidden Markov Models for Time Series: An Introduction Using R
Zucchini, W., & MacDonald, I. L. (2009) · Thammasat University Digital Collections · Cited by 686
Multievent: An Extension of Multistate Capture–Recapture Models to Uncertain States
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An Introduction to Model Selection
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Flexible and practical modeling of animal telemetry data: hidden Markov models and extensions
Langrock, R., King, R., Matthiopoulos, J., Thomas, L., Fortin, D., & Morales, J. M. (2012) · Ecology · doi:10.1890/11-2241.1 · Cited by 465
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Sensitivity and specificity of information criteria
(2019) · doi:10.1093/bib/bbz016 · Cited by 718
Uncovering ecological state dynamics with hidden Markov models
McClintock, B. T., Langrock, R., Giménez, O., Cam, E., Borchers, D. L., Glennie, R., & Patterson, T. A. (2020) · Ecology Letters · doi:10.1111/ele.13610 · Cited by 264
Self-citationGrecian, W. J., Lane, J. V., Michelot, T., Wade, H. M., & Hamer, K. C. (2018) · Journal of The Royal Society Interface · doi:10.1098/rsif.2018.0084 · Cited by 107
Hidden Markov models: Pitfalls and opportunities in ecology
Glennie, R., Adam, T., Barajas, V. L., Michelot, T., Photopoulou, T., & McClintock, B. T. (2022) · Methods in Ecology and Evolution · doi:10.1111/2041-210x.13801 · Cited by 124
Joint modelling of multi‐scale animal movement data using hierarchical hidden Markov models
Adam, T., Griffiths, C. A., Barajas, V. L., Meese, E. N., Lowe, C. G., Blackwell, P. G., Righton, D. A., & Langrock, R. (2019) · Methods in Ecology and Evolution · doi:10.1111/2041-210x.13241 · Cited by 83
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Metadata
- Authors
- Pohle, J., Langrock, R., van Beest, F. M., & Schmidt, N. M.
- Affiliations
- Bielefeld University (DE)
- Aarhus University (DK)
- Corresponding author
- Pohle, Jennifer
- Venue
- Journal of Agricultural, Biological and Environmental Statistics
- Published
- 2017-06-05
- Volume
- 22
- Issue
- 3
- Pages
- 270-293
- ISSN
- 1085-7117 (ISSN-L)
- 1537-2693
- OpenAlex
- W2622738426
- Cited by
- 288
- References
- 27
- Citations by year
- 2026: 29 · 2025: 37 · 2024: 38 · 2023: 40 · 2022: 43 · 2021: 43 · 2020: 22 · 2019: 21 · 2018: 10 · 2017: 4
- FWCI
- 9.17
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Agricultural Biological and Environmental Statistics (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- PUB – Publications at Bielefeld University (Bielefeld University) (submittedVersion)
- Publikationen an der Universität Bielefeld (Universität Bielefeld) (submittedVersion)
- Scopus (Elsevier) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Bayesian Methods and Mixture Models
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Inference
- Physical Sciences › Environmental Science › Ecology › Wildlife Ecology and Conservation
- Keywords
- hidden Markov models, model order selection, number of states, model selection, information criteria, animal movement, Ovibos moschatus
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