RT Monograph
SR 00
A1 Thomas-Agnan, Christine
A1 Laurent, Thibault
A1 Goulard, Michel
T1 About predictions in spatial autoregressive models
YR 2014
FD 2014-09-25
VO 13-452
SP 19
K1 Spatial simultaneous autoregressive models
K1 out of sample prediction
K1 best linear unbiased prediction
AB 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.
T2 TSE Working Paper
PB TSE Working Paper
PP Toulouse
AV Published
LK https://publications.ut-capitole.fr/id/eprint/15788/
UL http://tse-fr.eu/pub/27788