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Multivariate Bioclimatic Indices Modelling: A Coregionalised Approach
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Title: Multivariate Bioclimatic Indices Modelling: A Coregionalised Approach |
Authors: Barber, Xavier  Conesa, David  López Quiles, Antonio Morales-Socuéllamos, Javier |
Editor: Springer |
Department: Departamentos de la UMH::Estadística, Matemáticas e Informática |
Issue Date: 2019-01-23 |
URI: https://hdl.handle.net/11000/34138 |
Abstract:
A methodological approach for modelling the spatial multivariate distribution of multiple bioclimatic indices is presented. The value of the indices is modelled by means of a
Bayesian conditional coregionalised linear model. Elicitation of prior distributions and
approximation of posterior distributions of the parameters in the proposed model are
also discussed. A posterior predictive distribution and a spatial bioclimatic probability
distribution for each bioclimatic index are obtained. This allows researchers to obtain the
probability of each location belonging to different bioclimates. The presented methodology is applied in a practical setting showing that the spatial bioclimatic probability
distributions are more realistic than the ones obtained in the univariate setting, while
providing an interesting tool in the context of climate change.
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Keywords/Subjects: Bioclimatology Coregionalised models Multivariate Bayesian spatial models Spatial prediction Spatial bioclimatic probability distribution |
Knowledge area: CDU: Ciencias puras y naturales: Matemáticas |
Type of document: info:eu-repo/semantics/article |
Access rights: info:eu-repo/semantics/closedAccess |
DOI: https://doi.org/10.1007/s13253-018-00345-z |
Published in: Journal of Agricultural, Biological, and Environmental Statistics, Volume 24, Number 2, Pages 225–244 |
Appears in Collections: Artículos Estadística, Matemáticas e Informática
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