A new spatial regression estimator in the multivariate context - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Journal Articles Comptes rendus de l'Académie des sciences. Série I, Mathématique Year : 2015

A new spatial regression estimator in the multivariate context

Abstract

In this note, we propose a nonparametric spatial estimator of the regression function View the MathML sourcex→r(x):=E[Yi|Xi=x],x∈Rd, of a stationary (d+1)(d+1)-dimensional spatial process View the MathML source{(Yi,Xi),i∈ZN}, at a point located at some station j. The proposed estimator depends on two kernels in order to control both the distance between observations and the spatial locations. Almost complete convergence and consistency in LqLq norm (q∈N⁎)(q∈N⁎) of the kernel estimate are obtained when the sample considered is an α-mixing sequence.

Dates and versions

hal-01206781 , version 1 (29-09-2015)

Identifiers

Cite

Sophie Dabo-Niang, Anne-Françoise Yao, Camille Ternynck. A new spatial regression estimator in the multivariate context. Comptes rendus de l'Académie des sciences. Série I, Mathématique, 2015, 353 (7), pp.635 - 639. ⟨10.1016/j.crma.2015.04.004⟩. ⟨hal-01206781⟩
165 View
0 Download

Altmetric

Share

Gmail Facebook X LinkedIn More