Bootstrap for estimating the MSE of the spatial EBLUP
type: Item
instance of: scholarly article
title: Bootstrap for estimating the MSE of the spatial EBLUP
zbMATH Open document ID: 1197.62079
author: Isabel Molina
author: Nicola Salvati
author: Monica Pratesi
published in: Computational Statistics
publication date: 2010-04-22T00:00:00Z
review text: Linear regression models with correlated random effects are considered for spatial data modeling. An empirical best linear unbiased predictor (EBLUP) and its mean square error (MSE) are discussed. Three approaches to EBLUP MSE estimation are considered: plug-in with analytic approximations, and parametric and nonparametric bootstrap. These approaches are compared via simulations.
Mathematics Subject Classification ID: 62J05
Mathematics Subject Classification ID: 62H11
Mathematics Subject Classification ID: 62F40
Mathematics Subject Classification ID: 62G09
Mathematics Subject Classification ID: 62-08
zbMATH DE Number: 5697319
zbMATH Keywords: empirical best linear unbiased prediction
zbMATH Keywords: correlated random effects
zbMATH Keywords: spatial data
zbMATH Keywords: MSE estimation
describes a project that uses: spBayes
MaRDI profile type: Publication
full work available at URL: s00180-008-0138-4
OpenAlex ID: W2018031037
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DOI: 10.1007/S00180-008-0138-4
description: scientific article; zbMATH DE number 5697319