Robust quantile estimation and prediction for spatial processes

In this paper, we present a statistical framework for modeling conditional quantiles of spatial processes assumed to be strongly mixing in space. We establish the L1 consistency and the asymptotic normality of the kernel conditional quantile estimator in the case of random fields. We also define a nonparametric spatial predictor and illustrate the methodology used with some simulations.

MoreLess

Year of publication:	2010
Authors:	Dabo-Niang, Sophie ; Thiam, Baba
Published in:	Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 80.2010, 17-18, p. 1447-1458
Publisher:	Elsevier
Keywords:	Spatial processes Kernel estimate Conditional quantile Spatial prediction

More details

Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://ebvufind01.dmz1.zbw.eu/10008868806