The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.
moveHMM: an R package for the statistical modelling of animal movement data using hidden Markov models
Open accessAbstract
Summary: Due to the substantial progress in tracking technology, recent years have seen an explosion in the amount of movement data being collected. This has led to a huge demand for statistical tools that allow ecologists to draw meaningful inference from large tracking data sets. The class of hidden Markov models (HMMs) matches the intuitive understanding that animal movement is driven by underlying behavioural modes and has proven to be very useful for analysing movement data. For data that involve a regular sampling unit and negligible measurement error, these models usually are sufficiently flexible to capture the complex correlation structure found in movement data, yet are computationally inexpensive compared to alternative methods. The R package moveHMM allows ecologists to process GPS tracking data into series of step lengths and turning angles, and to fit an HMM to these data, allowing, in particular, for the incorporation of environmental covariates. The package includes assessment and visualization tools for the fitted model. We illustrate the use of moveHMM using (simulated) movement of the legendary wild haggis Haggis scoticus. Our findings illustrate the role our software, and movement modelling in general, can play in conservation and management by illuminating environmental constraints.
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R: A Language and Environment for Statistical Computing
R Core Team (2025) · doi:10.32614/r.manuals · Cited by 352,181
Calenge, C. (2006) · Ecological Modelling · doi:10.1016/j.ecolmodel.2006.03.017 · Cited by 4,074
Applied Spatial Data Analysis with R
Bivand, R. S., Pebesma, E., & Gómez-Rubio, V. (2013) · Springer eBooks · doi:10.1007/978-1-4614-7618-4 · Cited by 3,206
Codling, E. A., Plank, M. J., & Benhamou, S. (2008) · Journal of The Royal Society Interface · doi:10.1098/rsif.2008.0014 · Cited by 1,482
Rcpp: Seamless R and C++Integration
Eddelbuettel, D., & François, R. (2011) · Journal of Statistical Software · doi:10.18637/jss.v040.i08 · Cited by 1,318
Multi-State Models for Panel Data: The msm Package for R
Jackson, C. H. (2011) · Journal of Statistical Software · doi:10.18637/jss.v038.i08 · Cited by 1,297
EXTRACTING MORE OUT OF RELOCATION DATA: BUILDING MOVEMENT MODELS AS MIXTURES OF RANDOM WALKS
Morales, J. M., Haydon, D. T., Frair, J., Holsinger, K. E., & Fryxell, J. M. (2004) · Ecology · doi:10.1890/03-0269 · Cited by 799
Hidden Markov Models for Time Series: An Introduction Using R
Zucchini, W., & MacDonald, I. L. (2009) · Thammasat University Digital Collections · Cited by 701
ctmm: an r package for analyzing animal relocation data as a continuous‐time stochastic process
Calabrese, J. M., Fleming, C. H., & Gurarie, E. (2016) · Methods in Ecology and Evolution · doi:10.1111/2041-210x.12559 · Cited by 673
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 461
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Pohle, J., Langrock, R., van Beest, F. M., & Schmidt, N. M. (2017) · Journal of Agricultural, Biological and Environmental Statistics · doi:10.1007/s13253-017-0283-8 · Cited by 288
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Wang, G. (2019) · Ecological Informatics · doi:10.1016/j.ecoinf.2018.12.002 · Cited by 154
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Husson, L., Salles, T., Lebatard, A.-E., Zerathe, S., Braucher, R., Noerwidi, S., Aribowo, S., Mallard, C., Carcaillet, J., Natawidjaja, D. H., et al. (2022) · Scientific Reports · doi:10.1038/s41598-022-23206-9 · Cited by 28
Metadata
- Authors
- Michelot, T., Langrock, R., & Patterson, T. A.
- Venue
- Methods in Ecology and Evolution
- Publisher
- Wiley
- Published
- 2016-05-28
- Volume
- 7
- Issue
- 11
- Pages
- 1308-1315
- ISSN
- 2041-210X (ISSN-L)
- OpenAlex
- W2341959691
- Cited by
- 432
- References
- 23
- FWCI
- 28.11
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Michelot, T., Langrock, R., & Patterson, T. A. (2016). moveHMM: an R package for the statistical modelling of animal movement data using hidden Markov models. Methods in Ecology and Evolution. https://doi.org/10.1111/2041-210x.12578
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