About predictions in spatial autoregressive models

Thomas-Agnan, Christine, Laurent, Thibault and Goulard, Michel (2014) About predictions in spatial autoregressive models : Optimal and almost optimal strategies. TSE Working Paper, n. 13-452, Toulouse

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Official URL: http://tse-fr.eu/pub/27788


We address the problem of prediction in the spatial autoregressive SAR model for areal data which is classically used in spatial econometrics. With the Kriging theory, prediction using Best Linear Unbiased Predictors is at the heart of the geostatistical literature. From the methodological point of view, we explore the limits of the extension of BLUP formulas in the context of the spatial autoregressive SAR models for out-of-sample prediction simultaneously at several sites. We propose a more tractable \almost best" alternative and clarify the relationship between the BLUP and a proper EM-algorithm predictor. From an empirical perspective, we present data-based simulations to compare the efficiency of the classical formulas with the best and almost best predictions.

Item Type: Monograph (Working Paper)
Sub-title: Optimal and almost optimal strategies
Language: French
Date: 25 September 2014
Place of Publication: Toulouse
Uncontrolled Keywords: Spatial simultaneous autoregressive models, out of sample prediction, best linear unbiased prediction
Divisions: TSE-R (Toulouse)
Institution: Université Toulouse 1 Capitole
Site: UT1
Date Deposited: 09 Jul 2014 17:40
Last Modified: 07 Mar 2018 13:22
OAI ID: oai:tse-fr.eu:27788
URI: http://publications.ut-capitole.fr/id/eprint/15788

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