A Hotelling spatial scan statistic for functional data: application to economic and climate data

Zaineb Smida, Thibault Laurent and Lionel Cucala

No 24-1583, TSE Working Papers from Toulouse School of Economics (TSE)

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.

Keywords: Cluster detection; Functional data; Hotelling T2 test; Spatial Scan statistic. (search for similar items in EconPapers)
JEL-codes: C12 C21 E24 Q54 (search for similar items in EconPapers)
Date: 2024-10
New Economics Papers: this item is included in nep-ecm and nep-env
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