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Measuring Bandwidth Uncertainty in Multiscale Geographically Weighted Regression Using Akaike Weights
10 references·2 citing·34 second hop
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References

  • 2002Geographically Weighted Regression: The Analysis of Spatially Varying Relationships3,946 cited
  • 2017Multiscale Geographically Weighted Regression (MGWR)1,381 cited
  • 2011Researching Volunteered Geographic Information: Spatial Data, Geographic Research, and New Social Practice864 cited
  • 2019mgwr: A Python Implementation of Multiscale Geographically Weighted Regression for Investigating Process Spatial Heterogeneity and Scale829 cited
  • 2019Inference in Multiscale Geographically Weighted Regression414 cited
  • 2015The Multiple Testing Issue in Geographically Weighted Regression173 cited
  • 2020Computational improvements to multi-scale geographically weighted regression170 cited
  • 2017Single and Multiscale Models of Process Spatial Heterogeneity102 cited
  • 2018Fast Geographically Weighted Regression (FastGWR): a scalable algorithm to investigate spatial process heterogeneity in millions of observations92 cited
  • 2018The Importance of Scale in Spatially Varying Coefficient Modeling90 cited

Cited by

  • 2022On the notion of ‘bandwidth’ in geographically weighted regression models of spatially varying processes79 cited
  • 2025The Auckland Urban Liveability Index: A Mechanism for Quantifying and Evaluating Modern Urban Densification4 cited

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