A signature-based spatial scan statistic for functional data

Fuente: arXiv
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Main Author: Frévent, Camille
Format: Preprint
Published: 2025
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author Frévent, Camille
author_facet Frévent, Camille
contents We have developed a new signature-based spatial scan statistic for functional data (SigFSS). This scan statistic can be applied to both univariate and multivariate functional data. In a simulation study, SigFSS almost always performed better than the literature approaches and yielded more precise clusters in geographic terms. Lastly, we used SigFSS to search for spatial clusters of abnormally high or abnormally low mortality rates in mainland France.
format Preprint
id arxiv_https___arxiv_org_abs_2511_22432
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle A signature-based spatial scan statistic for functional data
Frévent, Camille
Methodology
We have developed a new signature-based spatial scan statistic for functional data (SigFSS). This scan statistic can be applied to both univariate and multivariate functional data. In a simulation study, SigFSS almost always performed better than the literature approaches and yielded more precise clusters in geographic terms. Lastly, we used SigFSS to search for spatial clusters of abnormally high or abnormally low mortality rates in mainland France.
title A signature-based spatial scan statistic for functional data
topic Methodology
url https://arxiv.org/abs/2511.22432