A multivariate nonparametric scan statistic for spatial data

被引：8
|
作者：
Cucala, Lionel [1 ]
Genin, Michael [2 ]
Occelli, Florent [3 ]
Soula, Julien [2 ]
机构：
[1] Univ Montpellier, CNRS, IMAG, Montpellier, France
[2] Univ Lille, Sante Publ Epidemiol & Qualite Soins EA 2694, Lille, France
[3] Univ Lille, CHU Lille, Inst Pasteur Lille, IMPact Environm Chim Sante Humaine EA 4483, Lille, France
来源：
SPATIAL STATISTICS | 2019年 / 29卷
关键词：
Spatial statistics; Scan statistics; Cluster detection; DISEASE;
D O I：
10.1016/j.spasta.2018.10.002
中图分类号：
P [天文学、地球科学];
学科分类号：
07 ;
摘要：
This paper introduces a nonparametric scan method for multivariate data indexed in space. Contrary to many other scan methods, it does not rely on a generalized likelihood ratio but is completely distribution-free as it is based on so-called multivariate ranks. This spatial scan test seems to be more reliable for analysing data that are not Gaussian, such as environmental measurements. We apply this method to a dataset recording the levels of metallic pollutants for two areas in the North of France. (C) 2018 Elsevier B.V. All rights reserved.
引用
收藏
页码：1 / 14
页数：14
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