A functional spatial autoregressive model using signatures

Fuente: arXiv
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1. Verfasser: Frévent, Camille
Format: Preprint
Veröffentlicht: 2023
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author Frévent, Camille
author_facet Frévent, Camille
contents We propose a new approach to the autoregressive spatial functional model, based on the notion of signature, which represents a function as an infinite series of its iterated integrals. It presents the advantage of being applicable to a wide range of processes. After having provided theoretical guarantees to the proposed model, we have shown in a simulation study and on a real data set that this new approach presents competitive performances compared to the traditional model.
format Preprint
id arxiv_https___arxiv_org_abs_2303_12378
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle A functional spatial autoregressive model using signatures
Frévent, Camille
Methodology
We propose a new approach to the autoregressive spatial functional model, based on the notion of signature, which represents a function as an infinite series of its iterated integrals. It presents the advantage of being applicable to a wide range of processes. After having provided theoretical guarantees to the proposed model, we have shown in a simulation study and on a real data set that this new approach presents competitive performances compared to the traditional model.
title A functional spatial autoregressive model using signatures
topic Methodology
url https://arxiv.org/abs/2303.12378