Document de travail

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

Zaineb Smida, Thibault Laurent et Lionel Cucala

Résumé

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.

Mots-clés

Cluster detection, Functional data, Hotelling T2 test, Spatial Scan statistic.;

Codes JEL

  • C12: Hypothesis Testing: General
  • 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 • Global Warming

Référence

Zaineb Smida, Thibault Laurent et Lionel Cucala, « A Hotelling spatial scan statistic for functional data: application to economic and climate data », TSE Working Paper, n° 24-1583, octobre 2024.

Voir aussi

Publié dans

TSE Working Paper, n° 24-1583, octobre 2024