Efficient MCMC implementation of multi-state mark-recapture models
Inherent differences in behaviour of individual animal movement can introduce bias into estimates of population parameters derived from mark-recapture data. Additionally, quantifying individual heterogeneity is of considerable interest in it's own right as numerous studies have shown how hetero...
| Main Authors: | , , |
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| Format: | Report |
| Language: | unknown |
| Published: |
arXiv
2015
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| Subjects: | |
| Online Access: | https://dx.doi.org/10.48550/arxiv.1511.07102 https://arxiv.org/abs/1511.07102 |
| Summary: | Inherent differences in behaviour of individual animal movement can introduce bias into estimates of population parameters derived from mark-recapture data. Additionally, quantifying individual heterogeneity is of considerable interest in it's own right as numerous studies have shown how heterogeneity can drive population dynamics. In this paper we incorporate multiple measures of individual heterogeneity into a multi-state mark-recapture model, using a Beta-Binomial Gibbs sampler using MCMC estimation. We also present a novel Independent Metropolis-Hastings sampler which allows for efficient updating of the hyper-parameters which cannot be updated using Gibbs sampling. We tested the model using simulation studies and applied the model to mark-resight data of North Atlantic humpback whales observed in the Stellwagen Bank National Marine Sanctuary where heterogeneity is present in both sighting probability and site preference. Simulation studies show asymptotic convergence of the posterior distribution for each of the hyper-parameters to true parameter values. In application to humpback whales individual heterogeneity is evident in sighting probability and propensity to use the marine sanctuary. : 23 pages, 9 figures |
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