6533b858fe1ef96bd12b55d8

RESEARCH PRODUCT

Bayesian hierarchical models for analysing the spatial distribution of bioclimatic indices

Antoni BarberJavier MoralesAsuncion MayoralAntonio Lopez-quílezDavid ConesaXavier Barber

subject

Bioclimatologia:62 Statistics::62M Inference from stochastic processes [Classificació AMS]BioclimatologyBioclimatology geostatistics parallel computation spatial prediction:62 Statistics::62P Applications [Classificació AMS]62F15 62M30 62P10 62P12 86A32Estadística bayesiana:Matemàtiques i estadística::Estadística matemàtica [Àrees temàtiques de la UPC]spatial prediction:62 Statistics::62F Parametric inference [Classificació AMS]geostatistics:86 Geophysics [Classificació AMS]parallel computation

description

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. Peer Reviewed

yearjournalcountryeditionlanguage
2017-12-19
https://hdl.handle.net/2117/178491