Poster (Scientific congresses and symposiums)
Robustness of spatial autocorrelation tests
Ernst, Marie
2016BSS 2016 - 24nd meeting of the Belgian Statistical Society
 

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Keywords :
hypothesis testing; robust inference; spatial statistics
Abstract :
[en] Spatial autocorrelation expresses the dependence between values at neighbouring locations. Testing if the spatial autocorrelation is significant may confirm or deny the need to consider spatial analysis over the classical one. Indeed, the analysis of spatial data is only meaningful if the spatial components bring information. Several measures of spatial autocorrelation are defined in the literature. Moran’s index, Geary’s ratio and Getis-Ord statistic are the most used statistics. Tests based on these measures have been developed in the literature using asymptotic and permutation results. They are used in practice in many fields, for instance in geography, economics, biogeosciences, medicine, ... However, these tests should be cautiously applied because they are not robust. A single contaminated observation can significantly modify their results. This poster is composed of two parts. Firstly, the robustness of already available tools for measuring spatial autocorrelation will be analysed. Secondly, alternative methods will be proposed to robustly test the spatial autocorrelation.
Disciplines :
Mathematics
Author, co-author :
Ernst, Marie  ;  Université de Liège > Département de mathématique > Statistique mathématique
Language :
English
Title :
Robustness of spatial autocorrelation tests
Publication date :
November 2016
Number of pages :
A0
Event name :
BSS 2016 - 24nd meeting of the Belgian Statistical Society
Event organizer :
Belgian Statistical Society
Event date :
du 12 au 14 octobre 2016
Funders :
IAP Research Network P7/06 of the Belgian State
Available on ORBi :
since 15 November 2016

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