Cited by 288Bayesian Methods and Mixture ModelsStatistical Methods and InferenceWildlife Ecology and Conservation

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Selecting the Number of States in Hidden Markov Models: Pragmatic Solutions Illustrated Using Animal Movement

Pohle, Jennifer, Langrock, Roland, van Beest, Floris M., Schmidt, Niels Martin·2017·Journal of Agricultural, Biological and Environmental Statistics

DOI 10.1007/s13253-017-0283-8

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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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Authors: Pohle, J., Langrock, R., van Beest, F. M., & Schmidt, N. M.
Affiliations: Bielefeld University (DE)
Aarhus University (DK)
Corresponding author: Pohle, Jennifer
ORCID: Pohle, Jennifer
Langrock, Roland
Schmidt, Niels Martin
Venue: Journal of Agricultural, Biological and Environmental Statistics
Publisher: Springer Science and Business Media LLC
Published: 2017-06-05
Volume: 22
Issue: 3
Pages: 270-293
ISSN: 1085-7117 (ISSN-L)
1537-2693
DOI: 10.1007/s13253-017-0283-8
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
Licence: www.springer.com/tdm (unspecified)
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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Selecting the Number of States in Hidden Markov Models: Pragmatic Solutions Illustrated Using Animal Movement

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