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Spatial Regression Models

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Encyclopedia of GIS

Synonyms

Spatial autoregressive models; Dependence, spatial; Simultaneous autoregressive model (SAR); Moving average (MA) process model; Spatial lag model; Spatial error model; Geographic weighted regression (GWR)

Definition

Spatial dependence is measured by spatial autocorrelation, which is a property of data that arises whenever there is a spatial pattern in the values located on a map, as opposed to a random pattern that indicates no spatial autocorrelation. To measure the spatial pattern (spatial association and spatial autocorrelation), some standard global and local spatial statistics have been developed. These include Moran's I, Geary's C, Getis, LISA and GLISA statistics. Besides spatial dependence in the data, there can be spatial heterogeneity. This means that the underlying process being studied may vary systematically over space. This creates problems for regression and other econometric methods that do not accommodate spatial variation in the relationships being modeled....

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Author information

Authors and Affiliations

  1. School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA

    Sumeeta Srinivasan

Authors
  1. Sumeeta Srinivasan
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Editor information

Editors and Affiliations

  1. Faculty of Computer Science and Engineering, University of Minnesota, Minneapolis, MN, 55455, USA

    Shashi Shekhar (McKnight Distinguished University Professor) (McKnight Distinguished University Professor)

  2. Management Science and Information Systems Department, Rutgers Business School Newark and New Brunswick Rutgers, the State University of New Jersey, Newark, NJ, 07102, USA

    Hui Xiong (Assistant Professor) (Assistant Professor)

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© 2008 Springer-Verlag

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Srinivasan, S. (2008). Spatial Regression Models. In: Shekhar, S., Xiong, H. (eds) Encyclopedia of GIS. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-35973-1_1294

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