Prediction of forest fires occurrences with area-level Poisson mixed models.
The number of fires in forest areas of Galicia (north-west of Spain) during the summer period is quite high. Local authorities are interested in analyzing the factors that explain this phenomenon. Poisson regression models are good tools for describing and predicting the number of fires per forest areas. This work employs area-level Poisson mixed models for treating real data about fires in forest areas. A parametric bootstrap method is applied for estimating the mean squared errors of fires predictors. The developed methodology and software are applied to a real data set of fires in forest areas of Galicia.
Universidade da Coruña, Spain.
Miguel
M
Boubeta
Universidade da Coruña, Spain. Electronic address: maria.jose.lombardia@udc.es.
María José
MJ
Lombardía
Universidad de Santiago de Compostela, Spain.
Manuel Francisco
MF
Marey-Pérez
Universidad Miguel Hernández de Elche, Spain.
Domingo
D
Morales
D005390:Fires; D016468:Forestry; D006801:Humans; D008962:Models, Theoretical; D016012:Poisson Distribution; D012621:Seasons; D013030:Spain
Bootstrap; Forest fires; Poisson mixed models; Prediction