Bootstrap for estimating the mean squared error of the spatial EBLUP

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Show simple item record Molina, Isabel Salvati, Nicola Pratesi, Monica
dc.contributor.editor Universidad Carlos III de Madrid. Departamento de Estadística 2007-04-23T15:56:32Z 2007-04-23T15:56:32Z 2007-04
dc.description.abstract This 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.
dc.format.extent 619319 bytes
dc.format.mimetype application/pdf
dc.language.iso eng
dc.language.iso eng
dc.relation.ispartofseries UC3M Working papers. Statistics and Econometrics
dc.relation.ispartofseries 07-08
dc.rights Atribución-NoComercial-SinDerivadas 3.0 España
dc.subject.other Spatial correlation
dc.subject.other Simultaneously autoregressive process
dc.subject.other Parametric bootstrap
dc.subject.other Nonparametric bootstrap
dc.title Bootstrap for estimating the mean squared error of the spatial EBLUP
dc.type workingPaper
dc.subject.eciencia Estadística
dc.rights.accessRights openAccess
dc.identifier.repec ws073408
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