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Quantile local spatial autocorrelation

Luc Anselin ()
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Luc Anselin: The University of Chicago

Letters in Spatial and Resource Sciences, 2019, vol. 12, issue 2, No 7, 155-166

Abstract: Abstract This note introduces the concept of quantile local spatial autocorrelation as a special case of a local indicator of spatial association (LISA) for the situation where the variables of interest are binary. This provides additional insight into the spatial distribution of observations at the extremes of the distribution. The concept is illustrated with an analysis of local spatial clusters and outliers for health outcomes using data for 791 Chicago census tracts in 2014.

Keywords: Spatial clusters; LISA; Join count statistic; Multivariate spatial association; Spatial data science (search for similar items in EconPapers)
JEL-codes: C12 C21 I14 (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/s12076-019-00234-0

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