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A computationally efficient method for delineating irregularly shaped spatial clusters

Author

Listed:
  • Juan Duque

    ()

  • Jared Aldstadt

    ()

  • Ermilson Velasquez
  • Jose Franco
  • Alejandro Betancourt

Abstract

No abstract is available for this item.

Suggested Citation

  • Juan Duque & Jared Aldstadt & Ermilson Velasquez & Jose Franco & Alejandro Betancourt, 2011. "A computationally efficient method for delineating irregularly shaped spatial clusters," Journal of Geographical Systems, Springer, vol. 13(4), pages 355-372, December.
  • Handle: RePEc:kap:jgeosy:v:13:y:2011:i:4:p:355-372 DOI: 10.1007/s10109-010-0137-1
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    File URL: http://hdl.handle.net/10.1007/s10109-010-0137-1
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    References listed on IDEAS

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    1. Ikuho Yamada & Peter Rogerson & Gyoungju Lee, 2009. "GeoSurveillance: a GIS-based system for the detection and monitoring of spatial clusters," Journal of Geographical Systems, Springer, vol. 11(2), pages 155-173, June.
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    Cited by:

    1. Juan C. Duque & Alejandro Betancourt & Freddy Marin, 2013. "An algorithmic approach for simulating realistic irregular lattices," DOCUMENTOS DE TRABAJO CIEF 010937, UNIVERSIDAD EAFIT.

    More about this item

    Keywords

    AMOEBA; Cluster detection; Local G statistic; Ecotope; C02 mathematical methods; C4 econometric and statistical methods: special topics;

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics

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