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Simultaneous Spatial and Functional Form Transformations

  • R. Kelley Pace
  • Ronald Barry
  • V. Carlos SlawsonJr.
  • C. F. Sirmans
Part of the Advances in Spatial Science book series (ADVSPATIAL)

Abstract

Technological advances such as the global positioning system (GPS) and low-cost, high-quality geographic information systems (GIS) have led to an explosion in the volume of large data sets with locational coordinates for each observation. For example, the Census provides large amounts of data for over 250,000 locations in the US (block groups). Moreover, geographic information systems can often provide approximate locational coordinates for street addresses (geocoding). Given the volume of business information, which contains a street address field, this allows the creation of extremely large spatial data sets. Such data, as well as other types of spatial data, often exhibit spatial dependence and thus require spatial statistical methods for efficient estimation, valid inference, and optimal prediction.

Keywords

Geographic Information System Basis Vector Baton Rouge Spatial Weight Matrix Spatial Transformation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • R. Kelley Pace
    • 1
  • Ronald Barry
    • 2
  • V. Carlos SlawsonJr.
    • 1
  • C. F. Sirmans
    • 3
  1. 1.Louisiana State UniversityUSA
  2. 2.University of AlaskaUSA
  3. 3.University of ConnecticutUSA

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