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

页码：1 / 14

页数：14