Smida, ZainebIdRef, Laurent, ThibaultIdRefORCIDORCID: https://orcid.org/0000-0001-7487-7671 and Cucala, LionelIdRef (2025) A Hotelling spatial scan statistic for functional data: Application to economic and climate data. Spatial Statistics, Vol.66 (n°100888).

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Identification Number : 10.1016/j.spasta.2025.100888

Abstract

A scan method for functional data indexed in space has been developed. The scan statistic is derived from the Hotelling test statistic for functional data, extending the univariate and multivariate Gaussian spatial scan statistics. This method consistently outperforms existing techniques in detecting and locating spatial clusters, as demonstrated through simulations. It has been applied to two types of real data: economic data in order to identify spatial clusters of abnormal unemployment rates in Spain and climatic data in order to detect unusual climate change patterns in Great Britain, Nigeria, Pakistan, and Venezuela.

Item Type: Article
Language: English
Date: April 2025
Refereed: Yes
Uncontrolled Keywords: Cluster detection, Functional data, Hotelling T2 test, Spatialscan statistic
Subjects: B- ECONOMIE ET FINANCE
Divisions: TSE-R (Toulouse)
Site: UT1
Date Deposited: 28 Jan 2026 14:23
Last Modified: 28 Jan 2026 14:23
OAI Identifier: oai:tse-fr.eu:131229
URI: https://publications.ut-capitole.fr/id/eprint/51760
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