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How to estimate kernel bandwidth function with cross-validation gwrr package

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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?

r geographically-weighted-regression

share|improve this question

edited Jul 1 '18 at 4:11

Stefan

1,460218

asked Nov 8 '17 at 21:25

Smky29Smky29

11

bumped to the homepage by Community♦ 13 mins ago

This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.

add a comment | 

0

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?

r geographically-weighted-regression

share|improve this question

edited Jul 1 '18 at 4:11

Stefan

1,460218

asked Nov 8 '17 at 21:25

Smky29Smky29

11

bumped to the homepage by Community♦ 13 mins ago

This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.

add a comment | 

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?

r geographically-weighted-regression

share|improve this question

edited Jul 1 '18 at 4:11

Stefan

1,460218

asked Nov 8 '17 at 21:25

Smky29Smky29

11

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)

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

share|improve this question

edited Jul 1 '18 at 4:11

Stefan

1,460218

asked Nov 8 '17 at 21:25

Smky29Smky29

11

share|improve this question

edited Jul 1 '18 at 4:11

Stefan

1,460218

asked Nov 8 '17 at 21:25

Smky29Smky29

11

edited Jul 1 '18 at 4:11

Stefan

1,460218

edited Jul 1 '18 at 4:11

Stefan

1,460218

asked Nov 8 '17 at 21:25

Smky29Smky29

11

asked Nov 8 '17 at 21:25

Smky29Smky29

11

1 Answer
1

active

oldest

votes

0

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.

share|improve this answer

answered Nov 8 '17 at 21:42

Liam GLiam G

1,55858

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Thank you for your response. My object is of a spatial polygon class. I read in a shapefile using package rgdal. How do I extract the x and y coordinates to work with this formula?
  
  – Smky29
  Nov 8 '17 at 23:51
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  I just figured this part out, but I still have the error! #Fetch coordinates cordy<-coordinates(diab) #Add coordinates to data frame newz<-cbind(diab, cordy) locs <- cbind(newz$X1, newz$X2) tt<-gwr.bw.est(dia2013~pctblacks + pcthis + pctpov+ lcollege+ newden+hosden10 +optden13 + totmdden13 + phyden13 + den13 + nurseden13 + nohealthin + unemploy + transport, locs, data=newz, kernel = "gauss", cv.tol=30)
  
  – Smky29
  Nov 9 '17 at 1:17
  
  
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  With polygon data, your ariel units are non-uniform and as such, violate assumptions of the spatial model. In evaluating autocorrelation on lattice data one defines Wij as Nth-order neighbor contingency and not distance. Since you cannot account for contingency in the spatial relationships nor correct for variable polygon size, the resulting GWR model will be biased if not outright erroneous.
  
  – Jeffrey Evans
  Jun 30 '18 at 23:46
  
  
  

  
  
  
  

add a comment | 

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0

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.

share|improve this answer

answered Nov 8 '17 at 21:42

Liam GLiam G

1,55858

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Thank you for your response. My object is of a spatial polygon class. I read in a shapefile using package rgdal. How do I extract the x and y coordinates to work with this formula?
  
  – Smky29
  Nov 8 '17 at 23:51
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  I just figured this part out, but I still have the error! #Fetch coordinates cordy<-coordinates(diab) #Add coordinates to data frame newz<-cbind(diab, cordy) locs <- cbind(newz$X1, newz$X2) tt<-gwr.bw.est(dia2013~pctblacks + pcthis + pctpov+ lcollege+ newden+hosden10 +optden13 + totmdden13 + phyden13 + den13 + nurseden13 + nohealthin + unemploy + transport, locs, data=newz, kernel = "gauss", cv.tol=30)
  
  – Smky29
  Nov 9 '17 at 1:17
  
  
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  With polygon data, your ariel units are non-uniform and as such, violate assumptions of the spatial model. In evaluating autocorrelation on lattice data one defines Wij as Nth-order neighbor contingency and not distance. Since you cannot account for contingency in the spatial relationships nor correct for variable polygon size, the resulting GWR model will be biased if not outright erroneous.
  
  – Jeffrey Evans
  Jun 30 '18 at 23:46
  
  
  

  
  
  
  

add a comment | 

0

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.

share|improve this answer

answered Nov 8 '17 at 21:42

Liam GLiam G

1,55858

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Thank you for your response. My object is of a spatial polygon class. I read in a shapefile using package rgdal. How do I extract the x and y coordinates to work with this formula?
  
  – Smky29
  Nov 8 '17 at 23:51
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  I just figured this part out, but I still have the error! #Fetch coordinates cordy<-coordinates(diab) #Add coordinates to data frame newz<-cbind(diab, cordy) locs <- cbind(newz$X1, newz$X2) tt<-gwr.bw.est(dia2013~pctblacks + pcthis + pctpov+ lcollege+ newden+hosden10 +optden13 + totmdden13 + phyden13 + den13 + nurseden13 + nohealthin + unemploy + transport, locs, data=newz, kernel = "gauss", cv.tol=30)
  
  – Smky29
  Nov 9 '17 at 1:17
  
  
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  With polygon data, your ariel units are non-uniform and as such, violate assumptions of the spatial model. In evaluating autocorrelation on lattice data one defines Wij as Nth-order neighbor contingency and not distance. Since you cannot account for contingency in the spatial relationships nor correct for variable polygon size, the resulting GWR model will be biased if not outright erroneous.
  
  – Jeffrey Evans
  Jun 30 '18 at 23:46
  
  
  

  
  
  
  

add a comment | 

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.

share|improve this answer

answered Nov 8 '17 at 21:42

Liam GLiam G

1,55858

c(columbus$x,columbus$y). 

 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)

share|improve this answer

answered Nov 8 '17 at 21:42

Liam GLiam G

1,55858

answered Nov 8 '17 at 21:42

Liam GLiam G

1,55858

answered Nov 8 '17 at 21:42

Liam GLiam G

1,55858