Accounting for individual-specific variation in habitat-selection studies: Efficient estimation of mixed-effects models using Bayesian or frequentist computation

Popular frameworks for studying habitat selection include resource‐selection functions (RSFs) and step‐selection functions (SSFs), estimated using logistic and conditional logistic regression, respectively. Both frameworks compare environmental covariates associated with locations animals visit with...

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Bibliographic Details
Published in:The Journal of animal ecology 2020-01, Vol.89 (1), p.80-92
Main Authors: Muff, Stefanie, Signer, Johannes, Fieberg, John
Format: Article
Language:English
Subjects:
Algorithms
Animals
Bayesian analysis
Bayesian theory
BIOLOGGING
Coefficients
Computer simulation
computer software
conditional logistic regression
glmmTMB
Goats
habitat preferences
Habitat selection
Habitats
Heterogeneity
Inference
integrated nested Laplace approximations (INLA)
Lutra lutra
Mathematical models
Mountains
multinomial regression
Oreamnos americanus
random effects
Regression analysis
Regression models
resource‐selection functions
Slopes
step‐selection functions
Variance
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