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Interpretation of gwr output ~ where is the fitted/predicted y?

6 messages · Debarchana Ghosh, Roger Bivand, Danlin Yu

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On Tue, 17 Jun 2008, Debarchana Ghosh wrote:

            
No, gwr.e is (currently) the i'th element of the vector of residuals in 
each GWR (that is for each fit point). On examination, neither it nor the 
R2 has any meaning when the fit points are not identical with the data 
points - I will investigate and patch if need be. If data points are fit 
points, you can, perhaps, use it to get fitted values with the y values 
- as in CV bandwidth selection. What do you need them for?

Hope this helps,

Roger

  
    
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Debarchana:

As Roger has pointed out, since gwr.e is the gwr residuals, it is easy 
to calculate the estimated Y from the observed Y since residual = 
(observed Y) - (estimated Y).

To extract the gwr.e, just do this:

residuals.gwr<-test500.gwr$SDF$gwr.e

and the estimated Y would be:

est.gwr<-yimp00-residuals.gwr

And then you can compare all Ys.

Hope this helps.

Cheers,
Danlin
Debarchana Ghosh wrote:

  
    
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On Wed, 18 Jun 2008, Debarchana Ghosh wrote:

            
By arithmetic. If yi = yhati + ei, and you have yi (from the input 
data) and ei (from gwr.e), you can get yhati. I don't know what they give 
you, though, since they are dependent on the choice of kernel and 
bandwidth, as well as the relative arrangement of the data points, so they 
are just one of many possible sets of GWR fitted values.

Roger

PS. The erroneous local R2 and gwr.e where fit points are not data 
points will be removed from the results at the next release and replaced 
by NAs.