Bootstrap for estimating the MSE of the spatial EBLUP
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.
empirical best linear unbiased prediction
scientific article; zbMATH DE number 5697319