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Screening for spatial dependence in regression analysis

  • Spatial Analysis
  • Published:
Papers of the Regional Science Association

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.

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Authors and Affiliations

  1. Department of Geography, University of Illinois at Urbana-Champaign, 220 Davenport Hall, 607 S. Mathews, 61801, Urbana, Illinois, USA

    Arthur Getis

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  1. Arthur Getis
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Getis, A. Screening for spatial dependence in regression analysis. Papers of the Regional Science Association 69, 69–81 (1990). https://doi.org/10.1007/BF01933897

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  • DOI: https://doi.org/10.1007/BF01933897

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