An Approximation for the Rank Adjacency Statistic for Spatial Clustering with Sparse Data

The rank adjacency statistic D provides a simple method to assess regional clustering. It is defined as the weighted average absolute difference in ranks of the data, taken over all possible pairs of adjacent regions. In this paper the usual normal approximation to the D statistic is found to give i...

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Veröffentlicht in:Geographical analysis 2001-01, Vol.33 (1), p.19-28
Hauptverfasser: Ekwaru, John Paul, Walter, Stephen D.
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description The rank adjacency statistic D provides a simple method to assess regional clustering. It is defined as the weighted average absolute difference in ranks of the data, taken over all possible pairs of adjacent regions. In this paper the usual normal approximation to the D statistic is found to give inaccurate results if the data are sparse and some regions have tied ranks. Adjusted formulae for the moments of D that allow for the existence of ties are derived. An example of analyses of sparse mortality data (with many regions having no deaths, and hence tied ranks) showed satisfactory agreement between the adjusted formulae and the empirical distribution of the D statistic. We conclude that the D statistic, when used with adjusted moments, provides a valid approximate method to evaluate spatial clustering, even in sparse data situations.
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subjects Cancer
Geography
Italy
Mortality
Regions
Simulation
Spatial analysis
Spatial distribution
Statistical models
title An Approximation for the Rank Adjacency Statistic for Spatial Clustering with Sparse Data
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