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Multivariate Bioclimatic Indices Modelling: A Coregionalised Approach

  • Xavier BarberEmail author
  • David Conesa
  • Antonio López-Quílez
  • Javier Morales
Article
  • 36 Downloads

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.

Keywords

Bioclimatology Coregionalised models Multivariate Bayesian spatial models Spatial prediction Spatial bioclimatic probability distribution 

Notes

Acknowledgements

This work was partially supported by research Grants MTM2016-77501-P and TEC2016-81900-REDT from the Spanish Ministry of Economy and Competiveness. We thank Dr. J.J. López-Espín, Miguel Hernández University-Center for Operations Research, for assistance with parallel computing code.

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Copyright information

© International Biometric Society 2019

Authors and Affiliations

  1. 1.Centro de Investigación OperativaUniversidad Miguel Hernández de ElcheElcheSpain
  2. 2.Dpt. Estadística i Investigació OperativaUniversitat de ValènciaValenciaSpain

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