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Geographically weighted regression

4 messages · i-c-b m@iii@g oii web@de, Sarah Goslee, bi@bi@iu m@iii@g oii whu@edu@c@ +1 more

Original
Sarah Goslee
# 
The first step should be to look at

str(Daten90)
str(Daten10)

and if that doesn't solve the problem, then consider a reproducible
example, or at the very least posting the results of the above to this
list.

Sarah
On Fri, Feb 22, 2019 at 7:38 AM <f-c-b at web.de> wrote:

  
    

      
      
    

  


  


      

    

    

      
      

        


  

        

      bi@bi@iu m@iii@g oii whu@edu@c@
    

    

      
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Hi,
The formula is wrongly specified, Ziel~ as.factor(Var1) + log(Var2, base = exp(1)) + Var3, use the corresponding var-names only.

As I understand, you want to do some calculations with the variables, and you can process them in the data frame before using it in this command, not in the formula.

Binbin




Dr Binbin Lu
Lecturer in School of Remote Sensing and Information Engineering, Wuhan University
Email: binbinlu at whu.edu.cn
 
From: f-c-b
Date: 2019-02-22 20:37
To: r-sig-geo
Subject: [R-sig-Geo] Geographically weighted regression
Dear all,
 
I am currently working out a geographically weighted regression, in which 90% of the data set the model should be calculated and for 10% of the values to be predicted. For the prediction I use the function gwr.predict from the package GWModel:

 Erg<-gwr.predict(formula=Ziel~ as.factor(Var1) + log(Var2, base = exp(1)) + Var3, data = Daten90,predictdata = Daten10,bw = bwG, kernel = "gaussian",adaptive = FALSE, p = 2, theta = 0, longlat = FALSE)

I always get this error, although Daten10 and Daten90 have the same structure:
Error in gwr.predict(formula = Ziel~ as.factor(Var1) + log(Var2, base = exp(1)) + Var3, :
All the independent variables should be included in the predictdata.
 
Can you tell me what the problem with this code is?
Or is there any other way for a GWR and the prediction?

Thank you,
Christoph

  
  


  


      

    

    

      
      

        


  

        

      Roger Bivand
    

    

      
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On Sat, 23 Feb 2019, binbinlu at whu.edu.cn wrote:

        

            

      
      
      
    

        
Correct, not in the formula in the way that these functions handle the 
names made by formula() and model.matrix(). lm() and its prediction 
function do seem to handle them correctly, but it is very hard in more 
complicated fitting/prediction functions to get this right. Pre-compute 
the modified variables so that the package functions just see simple 
variables.

Roger