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dc.contributor.authorBarber, Xavier-
dc.contributor.authorConesa, David-
dc.contributor.authorLópez Quiles, Antonio-
dc.contributor.authorMorales, Javier-
dc.contributor.otherDepartamentos de la UMH::Estadística, Matemáticas e Informáticaes_ES
dc.date.accessioned2024-12-13T09:50:13Z-
dc.date.available2024-12-13T09:50:13Z-
dc.date.created2019-01-23-
dc.identifier.citationJournal of Agricultural, Biological, and Environmental Statistics, Volume 24, Number 2, Pages 225–244es_ES
dc.identifier.issn1537-2693-
dc.identifier.issn1085-7117-
dc.identifier.urihttps://hdl.handle.net/11000/34138-
dc.description.abstractA 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.es_ES
dc.formatapplication/pdfes_ES
dc.format.extent20es_ES
dc.language.isoenges_ES
dc.publisherSpringeres_ES
dc.rightsinfo:eu-repo/semantics/closedAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectBioclimatologyes_ES
dc.subjectCoregionalised modelses_ES
dc.subjectMultivariate Bayesian spatial modelses_ES
dc.subjectSpatial predictiones_ES
dc.subjectSpatial bioclimatic probability distributiones_ES
dc.subject.otherCDU::5 - Ciencias puras y naturales::51 - Matemáticases_ES
dc.titleMultivariate Bioclimatic Indices Modelling: A Coregionalised Approaches_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherversionhttps://doi.org/10.1007/s13253-018-00345-zes_ES
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Artículos Estadística, Matemáticas e Informática


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