Kernel regression estimation with errors-in-variables for random fields - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Journal Articles Afrika Matematika Year : 2020

Kernel regression estimation with errors-in-variables for random fields

Abstract

In this paper, we investigate kernel regression estimation when the data are contaminated by measurement errors in the context of random fields. We establish sharp rate of weak and strong convergence of the kernel regression estimator under both the ordinary smooth and super-smooth assumptions. Numerical studies were carried out in order to illustrate the performance of the estimator with simulated data.
No file

Dates and versions

hal-02334993 , version 1 (28-10-2019)

Identifiers

Cite

Sophie Dabo-Niang, Baba Thiam. Kernel regression estimation with errors-in-variables for random fields. Afrika Matematika, 2020, 31, pp.29-56. ⟨10.1007/s13370-019-00654-7⟩. ⟨hal-02334993⟩
51 View
0 Download

Altmetric

Share

Gmail Facebook X LinkedIn More