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Spatial Regression Models

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Encyclopedia of GIS

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Synonyms

Spatial autoregressive models

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, as opposed to a random pattern that indicates no spatial autocorrelation. This spatial pattern can be measured through standard global and local spatial statistics. Global and local measures of spatial autocorrelation include Moran’s I, Geary’s C, Getis-Ord, and Anselin Local Moran’s I statistics. Besides spatial dependence in the data, there can be spatial heterogeneity. The underlying process may vary systematically over space due to correlations with other variables such as population. This can also be problematic for regression and other econometric methods that do not accommodate spatial variation in the relationships being modeled. For an ordinary least squares (OLS) estimation of the regression model, it is assumed that the values of the coefficients of the independent (explanatory)...

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Recommended Reading

  • Cliff A, Ord JK (1973) Spatial autocorrelation. Pion, London

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Author information

Authors and Affiliations

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

    Sumeeta Srinivasan

  2. Department of Urban and Environmental Planning, Tufts University, 02155, Medford, MA, USA

    Sumeeta Srinivasan

Authors
  1. Sumeeta Srinivasan
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Editor information

Editors and Affiliations

  1. University of Minnesota, Minneapolis, MN, USA

    Shashi Shekhar

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

    Hui Xiong

  3. Department of Management Sciences, Tippie College of Business, University of Iowa, Iowa City, IA, USA

    Xun Zhou

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Srinivasan, S. (2017). Spatial Regression Models. In: Shekhar, S., Xiong, H., Zhou, X. (eds) Encyclopedia of GIS. Springer, Cham. https://doi.org/10.1007/978-3-319-17885-1_1294

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