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.pebe...@wwu.de
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