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Smida, Zaineb
, Laurent, Thibault and Cucala, Lionel
(2024)
A Hotelling spatial scan statistic for functional data: application to economic and climate data.
TSE Working Paper, n. 24-1583, Toulouse
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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: | Monograph (Working Paper) |
|---|---|
| Language: | English |
| Date: | October 2024 |
| Place of Publication: | Toulouse |
| Uncontrolled Keywords: | Cluster detection, Functional data, Hotelling T2 test, Spatial Scan statistic. |
| JEL Classification: | C12 - Hypothesis Testing C21 - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions E24 - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital Q54 - Climate; Natural Disasters |
| Subjects: | B- ECONOMIE ET FINANCE |
| Divisions: | TSE-R (Toulouse) |
| Institution: | Université Toulouse Capitole |
| Site: | UT1 |
| Date Deposited: | 10 Oct 2024 10:37 |
| Last Modified: | 10 Oct 2024 10:37 |
| OAI Identifier: | oai:tse-fr.eu:129819 |
| URI: | https://publications.ut-capitole.fr/id/eprint/49767 |
