[R-sig-Geo] unable to remove spatial autocorrelation from a binomial gam

[Carlos Bautista]

Dear list members,

I am using gam (from mgcv package in R) to model presence/absence data in
3355 cells of 1x1km (151 presences and 3204 absences). Even though I
include a smooth with the spatial locations in the model to address the
spatial dependence in my data, the results from a variogram show spatial
autocorrelation in the residuals of my gam (range=6000 meters). Since I am
modelling a binary response, using a gamm with a correlation structure is
not advisable because it "performs poorly with binary data", neither gamm4
because (although is supposed to be appropriate for binary data) it has "no
facility for nlme style correlation structures".

The alternative I have found is to fit my model using the function magic
from the same mgcv package. Because I found no examples of how to use magic
for spatially correlated data I have adapted the ?magic example for
temporally correlated data. The results of the output change the
coefficients of the model but do not remove the spatial autocorrelation and
the smooth plots show the same effect.
You can find find the output from my models and figures of the variograms
and plots of the smooth effects in the following link
https://stackoverflow.com/questions/61110762/gam-with-binomial-distribution-and-with-spatial-autocorrelation-in-r


Could someone tell me if there is something wrong in my script? Does anyone
know another alternative to remove the residuals' spatial autocorrelation
from a binomial gam?

Thank you very much.
Kind regards,
Carlos
-- 
Carlos Bautista
Institute of Nature Conservation
Polish Academy of Sciences
Mickiewicza 33
31-120 Krakow, Poland
www.carpathianbear.pl
www.iop.krakow.pl

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