Year: 2005
Type: preprint
Abstract: We investigate the nonparametric estimation for regression in a fixed-design setting when the errors are given by a field of dependent random variables. Sufficient conditions for kernel estimators to converge uniformly are obtained. These estimators can attain the optimal rates of uniform convergence and the results apply to a large class of random fields which contains martingale-difference random fields and mixing random fields.
Source: arXiv (Cornell University)
Author: Machkouri, Mohamed El
Institution: Laboratoire de Mathématiques Raphaël Salem
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4394651958