A semiparametric autorregresive spatial prediction model
Methodology
2026-04-30 v1 Statistics Theory
Statistics Theory
Abstract
In this paper we propose a semiparametric spatial autoregressive model that combines a linear covariate component with a nonparametrically estimated spatial term, allowing flexible dependence modeling without restrictive covariance structure while preserving interpretability. We establish asymptotic properties, including consistency and asymptotic normality, and evaluate performance through simulations and real data. Results show competitive predictive accuracy relative to geostatistical methods and improved interpretability compared to spatial econometric models.
Cite
@article{arxiv.2604.26041,
title = {A semiparametric autorregresive spatial prediction model},
author = {Rodrigo García Arancibia and Pamela Llop and Mariel Lovatto},
journal= {arXiv preprint arXiv:2604.26041},
year = {2026}
}