Web of Science: 7 citations, Scopus: 7 citations, Google Scholar: citations
Bayesian hierarchical models for analysing the spatial distribution of bioclimatic indices
Barber Valles, Josep Xavier (Universidad Miguel Hernández de Elche. Departamento de Estadística, Matemáticas e Informática)
Conesa, David (Universitat de València. Departament d'Estadística i Investigació Operativa)
López-Quílez, Antonio (Universitat de València. Departament d'Estadística i Investigació Operativa)
Martínez Mayoral, Asuncion (Departamento de Estadística)
Morales Socuéllamos, Javier (Departamento de Estadística)
Barber, Antoni (IDENTIA Institute)

Date: 2017
Abstract: A methodological approach for modelling the spatial distribution of bioclimatic indices is proposed in this paper. The value of the bioclimatic index is modelled with a hierarchical Bayesian model that incorporates both structured and unstructured random effects. Selection of prior distributions is also discussed in order to better incorporate any possible prior knowledge about the parameters that could refer to the particular characteristics of bioclimatic indices. MCMC methods and distributed programming are used to obtain an approximation of the posterior distribution of the parameters and also the posterior predictive distribution of the indices. One main outcome of the proposal is the spatial bioclimatic probability distribution of each bioclimatic index, which allows researchers to obtain the probability of each location belonging to different bioclimates. The methodology is evaluated on two indices in the Island of Cyprus.
Rights: Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades. Creative Commons
Language: Anglès
Document: Article ; recerca ; Versió publicada
Subject: Bioclimatology ; Geostatistics ; Parallel computation ; Spatial prediction
Published in: SORT : statistics and operations research transactions, Vol. 41 Núm. 2 (July-December 2017) , p. 277-296 (Articles) , ISSN 2013-8830

Adreça alternativa: https://raco.cat/index.php/SORT/article/view/330285
DOI: 10.2436/20.8080.02.60


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The record appears in these collections:
Articles > Published articles > SORT
Articles > Research articles

 Record created 2017-12-21, last modified 2022-10-10



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