Small area estimation under spatial nonstationarity

Chandra, Hukum, Salvati, Nicola, Chambers, Ray and Tzavidis, Nikos (2012) Small area estimation under spatial nonstationarity [in special issue: Small Area Estimation] Computational Statistics & Data Analysis, 56, (10), pp. 2875-2888. (doi:10.1016/j.csda.2012.02.006).


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A geographical weighted empirical best linear unbiased predictor (GWEBLUP) for a small area average is proposed, and an estimator of its conditional mean squared error is developed. The popular empirical best linear unbiased predictor under the linear mixed model is obtained as a special case of the GWEBLUP. Empirical results using both model-based and design-based simulations, with the latter based on two real data sets, show that the GWEBLUP predictor can lead to efficiency gains when spatial nonstationarity is present in the data. A practical gain from using the GWEBLUP is in small area estimation for out of sample areas. In this case the efficient use of geographical information can potentially improve upon conventional synthetic estimation.

Item Type: Article
Digital Object Identifier (DOI): doi:10.1016/j.csda.2012.02.006
Additional Information: 3rd Special Issue on Optimization Heuristics in Estimation and Modelling Problems
ISSNs: 0167-9473 (print)
Keywords: borrowing strength over space, geographical weighted regression, out of sample small area estimation, spatial analysis
ePrint ID: 181967
Date :
Date Event
December 2011Submitted
15 February 2012e-pub ahead of print
October 2012Published
Date Deposited: 27 Apr 2011 14:42
Last Modified: 18 Apr 2017 02:26
Further Information:Google Scholar

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