A multivariate spatial regression model using signatures

Camille Frévent; Issa-Mbenard Dabo

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arXiv · 2410.07899

A multivariate spatial regression model using signatures

Camille Frévent·Issa-Mbenard Dabo

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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.

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Camille Frévent, Issa-Mbenard Dabo. 2024-10-10. A multivariate spatial regression model using signatures. https://arxiv.org/abs/2410.07899

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