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Modified Moran's I for Small Samples
Author(s) -
Carrijo Tomaz Back,
da Silva Alan Ricardo
Publication year - 2017
Publication title -
geographical analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.773
H-Index - 65
eISSN - 1538-4632
pISSN - 0016-7363
DOI - 10.1111/gean.12130
Subject(s) - measure (data warehouse) , autocorrelation , statistics , spatial analysis , statistician , mathematics , index (typography) , spatial dependence , statistical physics , computer science , data mining , physics , world wide web
The most common indicator used to measure spatial dependence is Moran's I proposed by statistician Patrick A. P. Moran in 1950. The index is simple to use and applies the principle of the Pearson correlation coefficient, although it incorporates a proximity measure between elements. However, Moran's I tends to underestimate real spatial autocorrelation when the number of locations are few. This study aims to present a modified version of Moran's I that can measure real spatial autocorrelation even with small samples and check for spatial dependence.