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Assessing Spatial Dependence in Count Data: Winsorized and Spatial Filter Specification Alternatives to the Auto‐Poisson Model
Author(s) -
Griffith Daniel A.
Publication year - 2006
Publication title -
geographical analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.773
H-Index - 65
eISSN - 1538-4632
pISSN - 0016-7363
DOI - 10.1111/j.0016-7363.2006.00681.x
Subject(s) - count data , poisson distribution , computer science , autocorrelation , poisson regression , spatial analysis , specification , econometrics , statistics , mathematics , population , demography , sociology
The auto‐Poisson probability model furnishes an obvious tool for modeling counts of geographically distributed rare events. Unfortunately, its original specification can accommodate only negative spatial autocorrelation, which itself is a rare event. More recent alternative reformulations, namely, the Winsorized and spatial filter specifications, circumvent this drawback. A comparison of their performances presented in this article reveals some of their relative advantages and disadvantages.