A Hotelling spatial scan statistic for functional data: Application to economic and climate data
Year: 2025
Type: article
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.
Source: Spatial Statistics
Authors: Zaineb Smida, Thibault Laurent, Lionel Cucala
Institutions: Lyon 1 Université, Centre National de la Recherche Scientifique, Institut Camille Jordan, Institut National des Sciences Appliquées de Lyon, Université Toulouse-I-Capitole, Toulouse School of Economics, Toulouse School of Economics Research, Université de Montpellier, Institut Montpelliérain Alexander Grothendieck, Université Montpellier 2
Language: English
Subfield: Economics and Econometrics
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid: $3,590
Funder: Agence Nationale de la Recherche
OpenAlex ID: W4403407053