Article ID Journal Published Year Pages File Type
1149182 Journal of Statistical Planning and Inference 2010 15 Pages PDF
Abstract

In this paper, we investigate a nonparametric robust estimation for spatial regression. More precisely, given a strictly stationary random field Zi=(Xi,Yi)i∈NNN≥1Zi=(Xi,Yi)i∈NNN≥1, we consider a family of robust nonparametric estimators for a regression function based on the kernel method. Under some general mixing assumptions, the almost complete consistency and the asymptotic normality of these estimators are obtained. A robust procedure to select the smoothing parameter adapted to the spatial data is also discussed.

Related Topics
Physical Sciences and Engineering Mathematics Applied Mathematics
Authors
, , ,