Mapping the results of local statistics
AbstractThe application of geographically weighted regression (GWR) â€“ a local spatial statistical technique used to test for spatial nonstationarity â€“ has grown rapidly in the social, health and demographic sciences. GWR is a useful exploratory analytical tool that generates a set of location-specific parameter estimates which can be mapped and analysed to provide information on spatial nonstationarity in relationships between predictors and the outcome variable. A major challenge to GWR users, however, is how best to map these parameter estimates. This paper introduces a simple mapping technique that combines local parameter estimates and local t-values on one map. The resultant map can facilitate the exploration and interpretation of nonstationarity.
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Bibliographic InfoArticle provided by Max Planck Institute for Demographic Research, Rostock, Germany in its journal Demographic Research.
Volume (Year): 26 (2012)
Issue (Month): 6 (March)
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Web page: http://www.demogr.mpg.de/
geographically weighted regression; local statistics; mapping; nonstationarity;
Find related papers by JEL classification:
- J1 - Labor and Demographic Economics - - Demographic Economics
- Z0 - Other Special Topics - - General
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