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Spatial extremes of wildfire sizes: Bayesian hieralquical models for extremes

dc.contributor.authorMendes, Jorge M.
dc.contributor.authorBermudez, Patricia Cortés de Zea
dc.contributor.authorPereira, J.M.C.
dc.contributor.authorTurkman, K.F.
dc.contributor.authorVasconcelos, M.J.P.
dc.date.accessioned2013-09-05T14:59:57Z
dc.date.available2013-09-05T14:59:57Z
dc.date.issued2010
dc.description.abstractIn Portugal, due to the combination of climatological and ecological factors, large wildfires are a constant threat and due to their economic impact, a big policy issue. In order to organize efficient fire fighting capacity and resource management, correct quantification of the risk of large wildfires are needed. In this paper, we quantify the regional risk of large wildfire sizes, by fitting a Generalized Pareto distribution to excesses over a suitably chosen high threshold. Spatio-temporal variations are introduced into the model through model parameters with suitably chosen link functions. The inference on these models are carried using Bayesian Hierarchical Models and Markov chain Monte Carlo methods.por
dc.identifier.citation"Environmental and Ecological Statistics". ISSN 1352-8505. 17 (2010) 1-28por
dc.identifier.issn1352-8505
dc.identifier.urihttp://hdl.handle.net/10400.5/5956
dc.language.isoengpor
dc.peerreviewedyespor
dc.publisherSpringerpor
dc.relation.publisherversionDOI 10.1007/s10651-008-0099-3por
dc.subjectBayesian hierarchical modelspor
dc.subjectgeneralized Pareto distributionpor
dc.subjectspatial and temporal processespor
dc.subjectMCMCpor
dc.titleSpatial extremes of wildfire sizes: Bayesian hieralquical models for extremespor
dc.typejournal article
dspace.entity.typePublication
oaire.citation.titleEnvironmental and Ecological Statisticspor
rcaap.rightsopenAccesspor
rcaap.typearticlepor

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