Incorporating Biotic Information in Species Distribution Models: A Coregionalized Approach
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- Xavier Barber & David Conesa & Antonio López-Quílez & Javier Morales, 2019. "Multivariate Bioclimatic Indices Modelling: A Coregionalised Approach," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 24(2), pages 225-244, June.
- Charlotte M. Jones‐Todd & Ben Swallow & Janine B. Illian & Mike Toms, 2018. "A spatiotemporal multispecies model of a semicontinuous response," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(3), pages 705-722, April.
- Geir-Arne Fuglstad & Daniel Simpson & Finn Lindgren & Håvard Rue, 2019. "Constructing Priors that Penalize the Complexity of Gaussian Random Fields," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 114(525), pages 445-452, January.
- Noel Cressie & Andrew Zammit-Mangion, 2016. "Multivariate spatial covariance models: a conditional approach," Biometrika, Biometrika Trust, vol. 103(4), pages 915-935.
- Ludwig Fahrmeir & Stefan Lang, 2001. "Bayesian Semiparametric Regression Analysis of Multicategorical Time-Space Data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 53(1), pages 11-30, March.
- Schlather, Martin & Malinowski, Alexander & Menck, Peter J. & Oesting, Marco & Strokorb, Kirstin, 2015. "Analysis, Simulation and Prediction of Multivariate Random Fields with Package RandomFields," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i08).
- Fois, Mauro & Cuena-Lombraña, Alba & Fenu, Giuseppe & Bacchetta, Gianluigi, 2018. "Using species distribution models at local scale to guide the search of poorly known species: Review, methodological issues and future directions," Ecological Modelling, Elsevier, vol. 385(C), pages 124-132.
- Coll, M. & Pennino, M. Grazia & Steenbeek, J. & Sole, J. & Bellido, J.M., 2019. "Predicting marine species distributions: Complementarity of food-web and Bayesian hierarchical modelling approaches," Ecological Modelling, Elsevier, vol. 405(C), pages 86-101.
- Håvard Rue & Sara Martino & Nicolas Chopin, 2009. "Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(2), pages 319-392, April.
- Finn Lindgren & Håvard Rue & Johan Lindström, 2011. "An explicit link between Gaussian fields and Gaussian Markov random fields: the stochastic partial differential equation approach," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 73(4), pages 423-498, September.
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- Rodrigues, Lucas dos Santos & Daudt, Nicholas Winterle & Cardoso, Luis Gustavo & Kinas, Paul Gerhard & Conesa, David & Pennino, Maria Grazia, 2023. "Species distribution modelling in the Southwestern Atlantic Ocean: A systematic review and trends," Ecological Modelling, Elsevier, vol. 486(C).
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Keywords
Bayesian hierarchical models; coregionalized models; fisheries; INLA; predation; SPDE; species interaction;All these keywords.
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