Crossvalidation of bandwidth for generalised GWR
Description
The function finds a bandwidth for a given generalised geographically weighted regression by optimzing a selected function. For crossvalidation, this scores the root mean square prediction error for the generalised geographically weighted regressions, choosing the bandwidth minimizing this quantity.
Usage
1 2 3 
Arguments
formula 
regression model formula as in 
data 
model data frame as in 
coords 
matrix of coordinates of points representing the spatial positions of the observations 
adapt 
either TRUE: find the proportion between 0 and 1 of observations to include in weighting scheme (knearest neighbours), or FALSE — find global bandwidth 
gweight 
geographical weighting function, at present

family 
a description of the error distribution and link function to
be used in the model, see 
verbose 
if TRUE (default), reports the progress of search for bandwidth 
longlat 
TRUE if point coordinates are longitudelatitude decimal degrees, in which case distances are measured in kilometers; if x is a SpatialPoints object, the value is taken from the object itself 
RMSE 
default FALSE to correspond with CV scores in newer references (sum of squared CV errors), if TRUE the previous behaviour of scoring by LOO CV RMSE 
tol 
the desired accuracy to be passed to 
Value
returns the crossvalidation bandwidth.
Note
The use of GWR on GLM is only at the initial proof of concept stage, nothing should be treated as an accepted method at this stage.
Author(s)
Roger Bivand Roger.Bivand@nhh.no
References
Fotheringham, A.S., Brunsdon, C., and Charlton, M.E., 2002, Geographically Weighted Regression, Chichester: Wiley; http://gwr.nuim.ie/
See Also
gwr.sel
, ggwr
Examples
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