Abstract
In the last decade wildfires became a serious problem in Portugal due to socieconomic and climate change trends. In order to analyse wildfire data, we employ beta regression for modelling the proportion of burned wild area, under a Bayesian perspective. Our main goal is to find out fire risk factors that influence the proportion of area burned and what may make a wild area susceptible or resistant to fire. Then, we analyse wildfire data in Portugal during 1990–1994 through Bayesian normal and beta regression models that use Markov chain Monte Carlo methods for estimating quantities of interest.
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Acknowledgements
This paper was partially supported by the project PEst-OE/MAT/UI0006/ 2014 of the Fundação para a Ciência e a Tecnologia (FCT). We also thank FCT for funding the Post-Doctoral fellowship of Susete Marques “SFRH/BPD/96806/2013”. In addition the authors would like to thank the two referees for the valuable and comprehensive comments that have improved the final version of the paper.
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Silva, G.L., Soares, P., Marques, S., Dias, M.I., Oliveira, M.M., Borges, J.G. (2015). A Bayesian Modelling of Wildfires in Portugal. In: Bourguignon, JP., Jeltsch, R., Pinto, A., Viana, M. (eds) Dynamics, Games and Science. CIM Series in Mathematical Sciences, vol 1. Springer, Cham. https://doi.org/10.1007/978-3-319-16118-1_38
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DOI: https://doi.org/10.1007/978-3-319-16118-1_38
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