The Analysis of Spatial Association by Use of Distance Statistics

Authors

  • Arthur Getis,

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      Arthur Getis is professor of geography at San Diego State University. J. K. Ord is the David H. McKinley Professor of Business Administration in the department of management science and information systems at The Pennsylvania State University.

  • J. K. Ord

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      Arthur Getis is professor of geography at San Diego State University. J. K. Ord is the David H. McKinley Professor of Business Administration in the department of management science and information systems at The Pennsylvania State University.


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.

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