GLS Estimation and Empirical Bayes Prediction for Linear Mixed Models with Heteroskedasticity and Sampling Weights : A Background Study for the POVMAP Project

This note adapts results by Huang and Hidiroglou (2003) on Generalized Least Squares estimation and Empirical Bayes prediction for linear mixed models with sampling weights. The objective is to incorporate these results into the poverty mapping approach put forward by Elbers et al. (2003). The estimators presented here have been implemented in version 2.5 of POVMAP, the custom-made poverty mapping software developed by the World Bank

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Year of publication:	2014
Authors:	van der Weide, Roy
Publisher:	2014: World Bank Group, Washington, DC
Subject:	Kleinste-Quadrate-Methode \| Least squares method \| Stichprobenerhebung \| Sampling \| Bayes-Statistik \| Bayesian inference \| Mathematische Optimierung \| Mathematical programming \| Empirische Methode \| Empirical method \| Theorie \| Theory

Extent:	1 Online-Ressource
Series:	Policy Research Working Paper ; No. 7028
Type of publication:	Book / Working Paper
Language:	English
Notes:	English en_US
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10012572280