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Spatial and Geographically Weighted Regression

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Encyclopedia of GIS

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...

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Recommended Reading

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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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