Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Perspectives on Spatial Data AnalysisThe Analysis of Spatial Association by Use of Distance Statistics

Perspectives on Spatial Data Analysis: The Analysis of Spatial Association by Use of Distance... [Introduced in this paper is a family of statistics, G, that can be used as a measure of spatial association in a number of circumstances. The basic statistic is derived, its properties are identified, and its advantages explained. Several of the G statistics make it possible to evaluate the spatial association of a variable within a specified distance of a single point. A comparison is made between a general G statistic and Moran’s I for similar hypothetical and empirical conditions. The empirical work includes studies of sudden infant death syndrome by county in North Carolina and dwelling unit prices in metropolitan San Diego by zip-code districts. Results indicate that G statistics should be used in conjunction with I in order to identify characteristics of patterns not revealed by the I statistic alone and, specifically, the Gi and Gi∗ statistics enable us to detect local “pockets” of dependence that may not show up when using global statistics.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Perspectives on Spatial Data AnalysisThe Analysis of Spatial Association by Use of Distance Statistics

Part of the Advances in Spatial Science Book Series
Editors: Anselin, Luc; Rey, Sergio J.

Loading next page...
 
/lp/springer-journals/perspectives-on-spatial-data-analysis-the-analysis-of-spatial-8kxBTJxI6O

References (0)

References for this paper are not available at this time. We will be adding them shortly, thank you for your patience.

Publisher
Springer Berlin Heidelberg
Copyright
© Springer-Verlag Berlin Heidelberg 2010
ISBN
978-3-642-01975-3
Pages
127 –145
DOI
10.1007/978-3-642-01976-0_10
Publisher site
See Chapter on Publisher Site

Abstract

[Introduced in this paper is a family of statistics, G, that can be used as a measure of spatial association in a number of circumstances. The basic statistic is derived, its properties are identified, and its advantages explained. Several of the G statistics make it possible to evaluate the spatial association of a variable within a specified distance of a single point. A comparison is made between a general G statistic and Moran’s I for similar hypothetical and empirical conditions. The empirical work includes studies of sudden infant death syndrome by county in North Carolina and dwelling unit prices in metropolitan San Diego by zip-code districts. Results indicate that G statistics should be used in conjunction with I in order to identify characteristics of patterns not revealed by the I statistic alone and, specifically, the Gi and Gi∗ statistics enable us to detect local “pockets” of dependence that may not show up when using global statistics.]

Published: Aug 25, 2008

Keywords: Spatial Autocorrelation; Sudden Infant Death Syndrome; Spatial Association; Common Neighbor; Standard Normal Variate

There are no references for this article.