Investigating spatial scan statistics for ...
Document type :
Article dans une revue scientifique: Article original
DOI :
Permalink :
Title :
Investigating spatial scan statistics for multivariate functional data
Author(s) :
Frevent, Camille [Auteur]
METRICS : Evaluation des technologies de santé et des pratiques médicales - ULR 2694
AHMED, Mohamed-Salem [Auteur]
Evaluation des technologies de santé et des pratiques médicales - ULR 2694 [METRICS]
METRICS : Evaluation des technologies de santé et des pratiques médicales - ULR 2694
Dabo, Sophie [Auteur]
Laboratoire Paul Painlevé - UMR 8524
MOdel for Data Analysis and Learning [MODAL]
Genin, Michaël [Auteur]
METRICS : Evaluation des technologies de santé et des pratiques médicales - ULR 2694
METRICS : Evaluation des technologies de santé et des pratiques médicales - ULR 2694
AHMED, Mohamed-Salem [Auteur]
Evaluation des technologies de santé et des pratiques médicales - ULR 2694 [METRICS]
METRICS : Evaluation des technologies de santé et des pratiques médicales - ULR 2694
Dabo, Sophie [Auteur]

Laboratoire Paul Painlevé - UMR 8524
MOdel for Data Analysis and Learning [MODAL]
Genin, Michaël [Auteur]

METRICS : Evaluation des technologies de santé et des pratiques médicales - ULR 2694
Journal title :
Journal of the Royal Statistical Society: Series C Applied Statistics
Abbreviated title :
J. R. Stat. Soc. Ser. C-Appl. Stat.
Volume number :
-
Pages :
-
Publication date :
2023-03-26
ISSN :
0035-9254
English keyword(s) :
Wilcoxon rank-sum test
spatial scan statistics
spatial clusters
multivariate functional data
MANOVA
Hotelling T-2-test
spatial scan statistics
spatial clusters
multivariate functional data
MANOVA
Hotelling T-2-test
HAL domain(s) :
Sciences du Vivant [q-bio]
English abstract : [en]
In environmental surveillance, cluster detection of environmental black spots is of major interest due to the adverse health effects of pollutants, as well as their known synergistic effect. Thus, this paper introduces ...
Show more >In environmental surveillance, cluster detection of environmental black spots is of major interest due to the adverse health effects of pollutants, as well as their known synergistic effect. Thus, this paper introduces three new spatial scan statistics for multivariate functional data, applicable for detecting clusters of abnormal air pollutants concentrations measured spatially at a very fine scale in northern France in October 2021 taking into account their correlations. Mathematically, our methodology is derived from a functional multivariate analysis of variance, an adaptation of the Hotelling T2-test statistic, and a multivariate extension of the Wilcoxon test statistic. The approaches were evaluated in a simulation study and then applied to the air pollution dataset.Show less >
Show more >In environmental surveillance, cluster detection of environmental black spots is of major interest due to the adverse health effects of pollutants, as well as their known synergistic effect. Thus, this paper introduces three new spatial scan statistics for multivariate functional data, applicable for detecting clusters of abnormal air pollutants concentrations measured spatially at a very fine scale in northern France in October 2021 taking into account their correlations. Mathematically, our methodology is derived from a functional multivariate analysis of variance, an adaptation of the Hotelling T2-test statistic, and a multivariate extension of the Wilcoxon test statistic. The approaches were evaluated in a simulation study and then applied to the air pollution dataset.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
Administrative institution(s) :
Université de Lille
CHU Lille
CHU Lille
Submission date :
2023-11-15T10:25:28Z
2024-04-11T09:50:33Z
2024-06-25T07:22:54Z
2024-04-11T09:50:33Z
2024-06-25T07:22:54Z