Local Spatial Autocorrelation Statistics: Distributional Issues and an Application

Authors

  • J. K. Ord,

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    • 1

      J. K. Ord is the David H. McKinley Professor of Business Administration in the department of management science and information systems at The Pennsylcania State University.

  • Arthur Getis

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      Arthur Getis is Stephen and Mary Birch Professor of Geographical Studies in the department of geography at San Diego State University.


Abstract

The statistics Gi(d) and Gi*(d), introduced in Getis and Ord (1992) for the study of local pattern in spatial data, are extended and their properties further explored. In particular, nonbinary weights are allowed and the statistics are related to Moran's autocorrelation statistic, I. The correlations between nearby values of the statistics are derived and verified by simulation. A Bonferroni criterion is used to approximate significance levels when testing extreme values from the set of statistics. An example of the use of the statistics is given using spatial-temporal data on the AIDS epidemic centering on San Francisco. Results indicate that in recent years the disease is intensifying in the counties surrounding the city.

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