Molina, IsabelSalvati, NicolaPratesi, MonicaUniversidad Carlos III de Madrid. Departamento de Estadística2007-04-232007-04-232007-04https://hdl.handle.net/10016/707This work assumes that the small area quantities of interest follow a Fay-Herriot model with spatially correlated random area effects. Under this model, parametric and nonparametric bootstrap procedures are proposed for estimating the mean squared error of the EBLUP (Empirical Best Linear Unbiased Predictor). A simulation study compares the bootstrap estimates with an asymptotic analytical approximation and studies the robustness to non-normality. Finally, two applications with real data are described.619319 bytesapplication/pdfengAtribución-NoComercial-SinDerivadas 3.0 EspañaSpatial correlationSimultaneously autoregressive processParametric bootstrapNonparametric bootstrapworking paperEstadísticaopen accessws073408