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A Note on the Mixed Geographically Weighted Regression Model*

Chang‐Lin Mei, Shu‐Yuan He and Kai‐Tai Fang

Journal of Regional Science, 2004, vol. 44, issue 1, 143-157

Abstract: Abstract. A mixed, geographically weighted regression (GWR) model is useful in the situation where certain explanatory variables influencing the response are global while others are local. Undoubtedly, how to identify these two types of the explanatory variables is essential for building such a model. Nevertheless, It seems that there has not been a formal way to achieve this task. Based on some work on the GWR technique and the distribution theory of quadratic forms in normal variables, a statistical test approach is suggested here to identify a mixed GWR model. Then, this note mainly focuses on simulation studies to examine the performance of the test and to provide some guidelines for performing the test in practice. The simulation studies demonstrate that the test works quite well and provides a feasible way to choose an appropriate mixed GWR model for a given data set.

Date: 2004
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Citations: View citations in EconPapers (14)

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Journal of Regional Science is currently edited by Marlon G. Boarnet, Matthew Kahn and Mark D. Partridge

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