Estimating kernel bandwidth function with cross-validation gwrr package?

Question

I am relatively new to R. I am attempting to use the gwrr package because I suspect that local collinearity may be an issue in my geographic weighted regression model.

If I am not mistaken, I first estimate the kernel bandwidth function using cross-validation. Below please find my R script. Diab is a spatial data set projected in Albers Equal Area Conic.

tt<-gwr.bw.est(dia2013~pctblacks + pcthis + pctpov+ lcollege+ newden+hosden10 +optden13 + totmdden13 + phyden13 + den13  +  nurseden13 + nohealthin + unemploy + transport, data=diab, kernel = "gauss", cv.tol=30)

However, I get the following error:

Error in (function (classes, fdef, mtable)  :

unable to find an inherited method for function ‘geometry’ for signature ‘"numeric"’

Does anyone know what is going on?

Liam G · Answer

The issue is that you haven't actually specified the coordinates to perform the function.

In the vignette example found below. They had the data parameter set to a variable 'columbus' then they set the locs paramter to

c(columbus$x,columbus$y).

https://cran.r-project.org/web/packages/gwrr/gwrr.pdf

I'm not sure how your data is set out but you would need to change it to something like this

tt<-gwr.bw.est(dia2013~pctblacks + pcthis + pctpov+ lcollege+ newden+hosden10 +optden13 + totmdden13 + phyden13 + den13 + nurseden13 + nohealthin + unemploy + transport, locs = c(diab$X,diab$Y) data=diab, kernel = "gauss", cv.tol=30)

You would just need to change the X and Y to whatever your coordinate labels are in your data frame.

Estimating kernel bandwidth function with cross-validation gwrr package?

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