A multivariate spatial regression model using signatures
Statistics Theory
2025-07-16 v2 Methodology
Statistics Theory
Abstract
We propose a spatial autoregressive model for a multivariate response variable and functional covariates. The approach is based on the notion of signature, which represents a function as an infinite series of its iterated integrals and presents the advantage of being applicable to a wide range of processes. We have provided theoretical guarantees for the choice of the signature truncation order, and we have shown in a simulation study and an application to pollution data that this approach outperforms existing approaches in the literature.
Keywords
Cite
@article{arxiv.2410.07899,
title = {A multivariate spatial regression model using signatures},
author = {Camille Frévent and Issa-Mbenard Dabo},
journal= {arXiv preprint arXiv:2410.07899},
year = {2025}
}