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Method of the Geographically Weighted Regression and an Example for its Application

Harvard Dataverse (Africa Rice Center, Bioversity International, CCAFS, CIAT, IFPRI, IRRI and WorldFish)

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Title Method of the Geographically Weighted Regression and an Example for its Application
 
Identifier https://doi.org/10.7910/DVN/DJVXEH
 
Creator ZSÓFIA FÁBIÁN
 
Publisher Harvard Dataverse
 
Description This research is concerned with a statistical method that has recently become widespread in the international literature; although, it is still limited in Hungarian research. The method is geographically weighted regression (GWR), which is demonstrated through an example of its application. GWR is a local model that is founded on the basis of regression, prominently taking into consideration the geogra
phical distance. Since it does not calculate the global relations of the whole data, but concentrates on the relationship of the dependent and independent variables locally within a determined search area, it allows consideration of the spatially varying processes. Simply, GWR is a developed version of the global regression model, since, through its use, it is possible to take into account the local features that are hidden by the global approach.
 
Subject Social Sciences
GWR model, local regression
 
Language English
 
Contributor Toth, Geza