Bayesian Inference for Multistate ‘Step and Turn’ Animal Movement in Continuous Time
Published 2017 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Bayesian Inference for Multistate ‘Step and Turn’ Animal Movement in Continuous Time
Authors
Keywords
Movement modelling, Switching behaviour, Random walk, GPS data, Markov chain Monte Carlo, Elk
Journal
JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS
Volume 22, Issue 3, Pages 373-392
Publisher
Springer Nature
Online
2017-06-20
DOI
10.1007/s13253-017-0286-5
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- moveHMM: anRpackage for the statistical modelling of animal movement data using hidden Markov models
- (2016) Théo Michelot et al. Methods in Ecology and Evolution
- Continuous-time discrete-space models for animal movement
- (2015) Ephraim M. Hanks et al. Annals of Applied Statistics
- Exact Bayesian inference for animal movement in continuous time
- (2015) Paul G. Blackwell et al. Methods in Ecology and Evolution
- A functional model for characterizing long-distance movement behaviour
- (2015) Frances E. Buderman et al. Methods in Ecology and Evolution
- Proximate cues to phases of movement in a highly dispersive waterfowl, Anas superciliosa
- (2015) John F. McEvoy et al. Movement Ecology
- From Fine-Scale Foraging to Home Ranges: A Semivariance Approach to Identifying Movement Modes across Spatiotemporal Scales
- (2014) Chris H. Fleming et al. AMERICAN NATURALIST
- Using mixed hidden Markov models to examine behavioral states in a cooperatively breeding bird
- (2014) Ann E. McKellar et al. BEHAVIORAL ECOLOGY
- Combining animal movements and behavioural data to detect behavioural states
- (2014) Vilis O. Nams ECOLOGY LETTERS
- When to be discrete: the importance of time formulation in understanding animal movement
- (2014) Brett T McClintock et al. Movement Ecology
- Sampling Animal Movement Paths Causes Turn Autocorrelation
- (2013) Vilis O. Nams ACTA BIOTHEORETICA
- Flexible continuous-time modelling for heterogeneous animal movement
- (2013) Keith J. Harris et al. ECOLOGICAL MODELLING
- State-space models for bio-loggers: A methodological road map
- (2012) I.D. Jonsen et al. DEEP-SEA RESEARCH PART II-TOPICAL STUDIES IN OCEANOGRAPHY
- State-space methods for more completely capturing behavioral dynamics from animal tracks
- (2012) Greg A. Breed et al. ECOLOGICAL MODELLING
- A general discrete-time modeling framework for animal movement using multistate random walks
- (2012) Brett T. McClintock et al. ECOLOGICAL MONOGRAPHS
- Flexible and practical modeling of animal telemetry data: hidden Markov models and extensions
- (2012) Roland Langrock et al. ECOLOGY
- Bias in estimating animal travel distance: the effect of sampling frequency
- (2012) J. Marcus Rowcliffe et al. Methods in Ecology and Evolution
- Velocity-Based Movement Modeling for Individual and Population Level Inference
- (2011) Ephraim M. Hanks et al. PLoS One
- Using GPS data to evaluate the accuracy of state–space methods for correction of Argos satellite telemetry error
- (2010) Toby A. Patterson et al. ECOLOGY
- Analysis and modelling of swimming behaviour in Oxyrrhis marina
- (2010) D. E. Boakes et al. JOURNAL OF PLANKTON RESEARCH
- A novel method for identifying behavioural changes in animal movement data
- (2009) Eliezer Gurarie et al. ECOLOGY LETTERS
- Advances in the tracking of marine species: using GPS locations to evaluate satellite track data and a continuous-time movement model
- (2009) CE Kuhn et al. MARINE ECOLOGY PROGRESS SERIES
- CONTINUOUS-TIME CORRELATED RANDOM WALK MODEL FOR ANIMAL TELEMETRY DATA
- (2008) Devin S. Johnson et al. ECOLOGY
Discover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversationPublish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn More