Synonyms
Spatial prediction; Regression; Global and local spatial modeling; Simultaneous autoregression; Moving average regression; Conditional spatial regression
Definition
Spatial regression (SR) is a global spatial modeling technique in which spatial autocorrelation among the regression parameters are taken into account. SR is usually performed for spatial data obtained from spatial zones or areas. The basic aim in SR modeling is to establish the relationship between a dependent variable measured over a spatial zone and other attributes of the spatial zone, for a given study area, where the spatial zones are the subset of the study area. While SR is known to be a modeling method in spatial data analysis literature [1,2,3,4,5,6], in spatial data-mining literature it is considered to be a classification technique [7].
Geographically weighted regression (GWR) is a powerful exploratory method in spatial data analysis. It serves for detecting local variations in spatial behavior and...
Recommended Reading
Bailey, T., Gatrell, A.C.: Interactive Spatial Data Analysis. Pearson, Essex, England (1995)
Haining, R.: Spatial Data Analysis in the Social and Environmental Sciences. Cambridge University Press, Cambridge, UK (1993)
Schabengerger, O., Gotway, C.A.: Statistical Methods for Spatial Data Analysis. Chapman & Hall/CRC, Boca Raton, Florida, USA (2005)
Haining, R.P., Spatial Data Analysis Theory and Practice, Cambridge University Press, Cambridge, UK (2003)
Fotheringham, A.S., Brunsdon, C., Charlton, M.: Quantitative Geography Perspectives on Spatial Data Analysis. Sage, London, UK (2000)
Anselin, L.: Spatial Econometrics: Methods and Models. Kluwer, Dordrecht (1988)
Shekhar, S., Chawla, S.: Spatial Databases: a Tour. Pearson, New Jersey, USA (2003)
Cliff, A.D., Ord, J.K.: Spatial Autocorrelation. Pion, London (1973)
Gamerman, D., Moreira, A.R.B.: Multivariate spatial regression models. J. Multivariate Anal. 91, 262–281 (2004)
Fotheringham, A.S., Brunsdon, C., Charlton, M.: Geographically Weigthed Regression the Analysis of Spatially Varying Relationships. Wiley, West Sussex, UK (2002)
Brunsdon, C., Fotheringham, A.S., Charlton, M.: Geographically weighted regression: a method for exploring spatial nonstationarity. Geogr. Anal. 28, 281–98 (1996)
Griffith, D.A.: Some guidelines for specifying the geographic weights matrix contained in spatial statistical models. In: Arlinghous, S.L., Griffith, A.D., Drake, W.D., Nystuen, J.D. (eds.) Practical Handbook of Spatial Statistics, pp. 65–82, CRC, Boca Raton, Florida, USA (1995)
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© 2008 Springer-Verlag
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Düzgün, H., Kemeç, S. (2008). Spatial and Geographically Weighted Regression. In: Shekhar, S., Xiong, H. (eds) Encyclopedia of GIS. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-35973-1_1242
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DOI: https://doi.org/10.1007/978-0-387-35973-1_1242
Publisher Name: Springer, Boston, MA
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