On estimation and prediction in a spatial semi-functional linear regression model
Statistics Theory
2022-11-22 v1 Statistics Theory
Abstract
We tackle estimation and prediction at non-visted sites in a spatial semi-functional linear regression model with derivatives that combines a functional linear model with a nonparametric regression one. The parametric part is estimated by a method of moments and the other one by a local linear estimator. We establish the convergence rate of the resulting estimators and predictor. A simulation study and an application to ozone pollution prediction at non-visted sites are proposed to illustrate our results.
Cite
@article{arxiv.2211.10817,
title = {On estimation and prediction in a spatial semi-functional linear regression model},
author = {Stéphane Bouka and Kowir Pambo Bello and Guy Martial Nkiet},
journal= {arXiv preprint arXiv:2211.10817},
year = {2022}
}