Global Scan Methods for Comparing Two Spatial Point Processes

Florent Bonneu () and Lionel Cucala ()
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Florent Bonneu: Avignon Université
Lionel Cucala: Université de Montpellier

A chapter in Advances in Contemporary Statistics and Econometrics, 2021, pp 305-318 from Springer

Abstract: Abstract In many scientific areas such as forestry, ecology, or epidemiology, deciding whether two spatial point patterns are equally distributed is an important issue. This work proposes an adaptation of spatial scan methods, originally designed for local cluster detection, in order to test for the global similarity between two spatial point patterns. We design two spatial global scan statistics based on likelihood ratio on the one hand and on moments on the other, and explain how to compute their significance. A simulation procedure is conducted to compare these global scan methods to others based on kernel density estimation or second-order summary statistics. We also apply them to a dataset of wildfires registered in France.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-73249-3_16

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DOI: 10.1007/978-3-030-73249-3_16

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