Geographically weighted regression problems

[RobertSchwartz]

Geographically weighted regression: ArcGIS Pro 2.4 and MGWR

#GWR

There are large difference between the results of an ArcGIS Pro gwr and those of Fotheringham et al. Multiscale Geographically weighted regression. The difference is stark when mapping one of the parameter estimates. Results below suggest that some kind of smoothing function is applied in Pro. Can anyone point me to the  Pro documentation. There are quite a few settings, such as variable standardization, that are not readily apparent in Pro. @

[JenoraD_Acosta]

Hi there!

As you point out there are significant differences between the two maps you shared above, but this is because the outputs are based on two very different methodologies, standard GWR and multiscale GWR.  We would not expect the two outputs to be the same.  Currently, we have not implemented multiscale GWR.  Our implementation of standard GWR closely matches the implementation in open source packages such as GWR4.  We do not provide an option to standardize the variables within our implementation of GWR (this is done primarily for computational efficiency).  We are intrigued by the multiscale GWR methodology and it is on our list of research and potential enhancements.

Documentation for the tool in ArcGIS Pro can be found here:

Geographically Weighted Regression

How Geographically Weighted Regression Works

References:

Brunsdon, C., Fotheringham, A. S., & Charlton, M. E. (1996). Geographically weighted regression: a method for exploring spatial nonstationarity. Geographical analysis, 28(4), 281-298.

Fotheringham, Stewart A., Chris Brunsdon, and Martin Charlton. Geographically Weighted Regression: the analysis of spatially varying relationships. John Wiley & Sons, 2002.

I hope this is helpful and please reach out if there are any other questions!

- Jenora D'Acosta