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- W1921891227 abstract "This chapter presents general results on empirical best linear unbiased prediction (EBLUP) estimation. It considers the more difficult problem of estimating the mean squared error (MSE) of EBLUP estimators, taking account of the variability in the estimated variance and covariance components. Results are spelled out for the special case of a linear mixed model with block diagonal covariance structure, which covers many commonly used small area models. The chapter gives a brief account of model diagnostics based on residuals and influence measures for particular cases of the general linear mixed model. Finally, the chapter gives a few examples of software packages used for such EBLUP." @default.
- W1921891227 created "2016-06-24" @default.
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- W1921891227 date "2015-08-14" @default.
- W1921891227 modified "2023-10-16" @default.
- W1921891227 title "Empirical Best Linear Unbiased Prediction (EBLUP): Theory" @default.
- W1921891227 doi "https://doi.org/10.1002/9781118735855.ch5" @default.
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