SCREENING FOR SPATIAL DEPENDENCE IN REGRESSION ANALYSIS

Arthur Getis

Papers in Regional Science, 1990, vol. 69, issue 1, 69-81

Abstract: ABSTRACT A technique of analysis is presented that is designed to circumvent the problem of finding wasy to estimate parameters of spatially stochastic independent variables. It is based on 1) a type of second‐order analysis that describes the spatial association among weighted observations, and 2) a screening procedure that removes most of the spatial dependence in the dependent variable. The approach is illustrated by a study of the incidence of certain crimes in 49 districts of Columbus, Ohio. It is concluded that spatial justaposition of observations plays a large role in regression analyses that are based on spatial series.

Date: 1990
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https://doi.org/10.1111/j.1435-5597.1990.tb01204.x

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Persistent link: https://EconPapers.repec.org/RePEc:bla:presci:v:69:y:1990:i:1:p:69-81

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