A Wilcoxon-Mann-Whitney spatial scan statistic for functional data

Zaineb Smida, Lionel Cucala, Ali Gannoun and Ghislain Durif

Computational Statistics & Data Analysis, 2022, vol. 167, issue C

Abstract: A nonparametric scan method for functional data indexed in space is introduced. The associated scan statistic is derived from the Wilcoxon-Mann-Whitney test statistic defined for infinite dimensional data. It is completely nonparametric as it does not assume any distribution concerning the functional marks. Whatever the clustering scenario, this scan test seems to be efficient to detect and locate the cluster. This method is applied to a data set for extracting features in Spanish province population growth. A significant spatial cluster of low demographic evolution rates is found, exhibiting a specific phenomenon in the North-West of Spain.

Keywords: Cluster detection; Functional data; Hilbert space; Spatial scan statistic; Wilcoxon-Mann-Whitney test (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:167:y:2022:i:c:s0167947321002127

DOI: 10.1016/j.csda.2021.107378

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