Investigating new, signature-based, spatial autoregressive models for functional covariates

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1. Verfasser: Frévent, Camille
Format: Preprint
Veröffentlicht: 2025
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author Frévent, Camille
author_facet Frévent, Camille
contents We developed two new alternatives to signature-based, spatial autoregressive models. In a simulation study, we found that the new models performed at least as well as existing approaches but presented shorter computation times. We then used the new models to analyze the premature mortality rate and the mortality rate for people aged 65 and over.
format Preprint
id arxiv_https___arxiv_org_abs_2511_22414
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Investigating new, signature-based, spatial autoregressive models for functional covariates
Frévent, Camille
Methodology
We developed two new alternatives to signature-based, spatial autoregressive models. In a simulation study, we found that the new models performed at least as well as existing approaches but presented shorter computation times. We then used the new models to analyze the premature mortality rate and the mortality rate for people aged 65 and over.
title Investigating new, signature-based, spatial autoregressive models for functional covariates
topic Methodology
url https://arxiv.org/abs/2511.22414