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Designing and implementing software for spatial statistical analysis in a GIS environment

  • Published: September 2000
  • Volume 2, pages 257–286, (2000)
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Designing and implementing software for spatial statistical analysis in a GIS environment
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  • Robert Haining1,
  • Stephen Wise1 &
  • Jingsheng Ma1 
  • 252 Accesses

  • 31 Citations

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Abstract.

This paper provides a description of SAGE, a software package linked to the Arc/Info GIS that can be used to undertake spatial statistical analysis of area based data. The paper is written from the perspective of the user who wishes to undertake exploratory and confirmatory spatial data analysis. The paper discusses design aspects of the package and also the statistical analysis philosophy underlying its contents. The paper describes the statistical analyses which SAGE can perform and details on how it performs them together with some illustrative examples. Detail on visualisation aspects of SAGE are discussed in a separate paper (Haining et al. 2000). The wider contribution of the paper is to build on earlier developments in this area and identify the needs of software packages if they are to enable users to implement effective spatial statistical analysis.

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Authors and Affiliations

  1. Department of Geography, Sheffield Centre for Geographic Information and Spatial Analysis, University of Sheffield, UK (e-mail: R.Haining@Sheffield.ac.uk), , , , , , GB

    Robert Haining, Stephen Wise & Jingsheng Ma

Authors
  1. Robert Haining
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  2. Stephen Wise
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  3. Jingsheng Ma
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Additional information

Received: 20 March 1999 / Accepted: 13 September 1999

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Haining, R., Wise, S. & Ma, J. Designing and implementing software for spatial statistical analysis in a GIS environment. J Geograph Syst 2, 257–286 (2000). https://doi.org/10.1007/PL00011458

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  • Issue date: September 2000

  • DOI: https://doi.org/10.1007/PL00011458

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  • Key words: Exploratory analysis, regionalisation, visualisation, autocorrelation, spatial regressions, client-server computing, brushing
  • JEL classification: C21, C51, C52, C87, C88

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