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Exploring Spatial Data Analysis Techniques Using R: The Case of Observations with No Neighbors

In: Advances in Spatial Econometrics

Author

Listed:
  • Roger S. Bivand

    (Norwegian School of Economics and Business Administration)

  • Boris A. Portnov

    (Ben-Gurion University of the Negev)

Abstract

It is widely acknowledged that one of the impediments to a broader acceptance of techniques for spatial data analysis is that handling spatial data involves more insight and possibly the use of additional applications than other forms of data (Anselin, 2000, p. 217). We are perhaps more familiar with the potential difficulties caused by the inadequate mapping of data into temporal reference frameworks, such as the predicted complications attributed to the year 2000 problem, when a circular measure (99 + 1 = 0) was treated as linear. Spatial data come with many assumptions about their reference frameworks, including projection metadata, and are often derived from geographical information systems or other archives of spatial position data. Some of these are also time-specific, where boundary segments are introduced to or removed from maps of polygon representations of spatial objects.

Suggested Citation

  • Roger S. Bivand & Boris A. Portnov, 2004. "Exploring Spatial Data Analysis Techniques Using R: The Case of Observations with No Neighbors," Advances in Spatial Science, in: Luc Anselin & Raymond J. G. M. Florax & Sergio J. Rey (ed.), Advances in Spatial Econometrics, chapter 6, pages 121-142, Springer.
    • Handle: RePEc:spr:adspcp:978-3-662-05617-2_6
    DOI: 10.1007/978-3-662-05617-2_6
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    Citations

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    Cited by:

    1. Alejandro Quiroz Flores, 2011. "Alliances as Contiguity in Spatial Models of Military Expenditures," Conflict Management and Peace Science, Peace Science Society (International), vol. 28(4), pages 402-418, September.
    2. repec:jss:jstsof:35:i01 is not listed on IDEAS
    3. repec:jss:jstsof:47:i01 is not listed on IDEAS
    4. repec:asg:wpaper:1008 is not listed on IDEAS
    5. Agnieszka Kozera & Romana Głowicka-Wołoszyn, 2016. "Spatial Autocorrelation in Assessment of Financial Self-Sufficiency of Communes of Wielkopolska Province," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 17(3), pages 525-540, September.
    6. Xingjian Liu & James LeSage, 2010. "Arc_Mat: a Matlab-based spatial data analysis toolbox," Journal of Geographical Systems, Springer, vol. 12(1), pages 69-87, March.
    7. Roger S. Bivand & David W. S. Wong, 2018. "Comparing implementations of global and local indicators of spatial association," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(3), pages 716-748, September.
    8. Agnieszka Kozera & Romana Głowicka-Wołoszyn, 2016. "Spatial Autocorrelation In Assessment Of Financial Self-Sufficiency Of Communes Of Wielkopolska Province," Statistics in Transition New Series, Polish Statistical Association, vol. 17(3), pages 525-540, September.
    9. Liviano Solís, Daniel & Arauzo Carod, Josep Maria, 2011. "Industrial Location and Space: New Insights," Working Papers 2072/152137, Universitat Rovira i Virgili, Department of Economics.

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