Hello,
I'm still learning about spatial statistics so this may be basic, but I would like some guidance 🙂
I have some count data (electric vehicle chargers). I'm trying to model its relationship with % of cars that are electric within an area. They have significant correlation linearly.
Normally I would use Poisson model because it is count data. However, both the dependent and independent variables show very strong spatial autocorrelation. From my understanding, normal linear regression won't work because of this so I need to use Geographically-weighted regression- this measures regression locally, giving different models for each area.
My question is, if autocorrelation is present, is there no way to have an overall regression model for the whole area I'm looking at? I'm unsure what conclusions I can draw from GWR other than regression varies significantly across the whole area- isn't this basically saying there is no relationship between the data unless we significantly narrow down? What's the point of having such a non-general model? I could be being ignorant but I'm at a bit of a loss.