[R-sig-Geo] ggwr residual types question and a few others

[Edzer Pebesma]

Seth, I believe that response residuals are the residuals obtaind by 
(measurement - prediction) on the measurement scale ([0,1], for logit); 
working residuals are the residuals obtained in the last step of the 
weighted minimization, i.e. on the transformed measurements. Note that 
predictions are not 0 or 1, but usually somewhere between 0 and 1.

Individual elements of the object returned can be obtained by addressing 
them explicitly. Finding out how they are called, e.g. by

example(gwr)
names(nc)
lapply(nc,class)
summary(nc$SDF)

for the additional fields, you probably need to specify more input 
arguments (e.g. hatmatrix, fit.points). Look into the help page of gwr, 
and please provide us with a reproducable example!
--
Edzer

Seth J Myers wrote:
> Hi,
>
> First post, thanks for this list.  I've just spent the last few days learning how to use ggwr in spgwr.  I fit a glm with family=binomial(link="logit"), and have discovered how to export my SpatialPointsDataFrame as a text file so I can work with it in other packages I'm more familiar with (not ready to tackle the full R learning curve yet).  I have a few basic questions first, for a logistic regression I understand pearson and deviance residuals, but what would the residual types of response and working be?  I specified response thinking it would be binary response(0 or 1) - probability of 1, but it returned values that indicate this isn't the case.  Also, in the spgwr documentation it states that ggwr returns a SpatialPointsDataFrame of class "gwr" and that its "data" slot can (will?) have the following: fit.points, weights, GWR coefficient estimates, R-sqaured, and coefficient standard errors.  So, far the output I get from exporting mymodel to a txt using write.table or !
>  viewed on the screen by simply mymodel$SDF only includes the following: row ID, intercept value, coefficient estimates for predictors, dispersion (always 1 in my case), working_resids, and x and y coordinates.  Is there some 'switch' internal to ggwr function or something else to specify to get such things as SE of coefficients and (more importantly to me) a residual that truly is reponse(0 or 1)-prediction(0 to 1)?  Thanks. -Seth Myers
>
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-- 
Edzer Pebesma
Institute for Geoinformatics (ifgi), University of Münster 
Weseler Straße 253, 48151 Münster, Germany. Phone: +49 251 
8333081, Fax: +49 251 8339763  http://ifgi.uni-muenster.de 
http://www.52north.org/geostatistics      e.pebesma at wwu.de