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.
机构:
Yonsei Univ, Dept Biostat & Med Informat, Coll Med, Seoul 120752, South KoreaYonsei Univ, Dept Biostat & Med Informat, Coll Med, Seoul 120752, South Korea
Jung, Inkyung
Cho, Ho Jin
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Yonsei Univ, Dept Biostat & Med Informat, Coll Med, Seoul 120752, South KoreaYonsei Univ, Dept Biostat & Med Informat, Coll Med, Seoul 120752, South Korea
Cho, Ho Jin
INTERNATIONAL JOURNAL OF HEALTH GEOGRAPHICS,
2015,
14
机构:
Yonsei Univ, Coll Med, Dept Biostat, Seoul 120752, South KoreaYonsei Univ, Coll Med, Dept Biostat, Seoul 120752, South Korea
Jung, Inkyung
Kulldorff, Martin
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Harvard Univ, Sch Med, Dept Populat Med, Boston, MA 02215 USA
Harvard Pilgrim Hlth Care Inst, Boston, MA 02215 USAYonsei Univ, Coll Med, Dept Biostat, Seoul 120752, South Korea
Kulldorff, Martin
Richard, Otukei John
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Makerere Univ, Dept Surveying, Kampala, UgandaYonsei Univ, Coll Med, Dept Biostat, Seoul 120752, South Korea