[R] analysing non-normal spatially autocorrelated data

[Carsten Dormann]

Dear fellow R-users,

I wish to analyse a lattice of presence-absence data which are spatially 
autocorrelated.

For normally distributed errors I used gls {nlme} with the "appropriate" 
corStruct-method.
Is there any method for other families (binomial and poisson)?

A method that look suitable to me as a non-statistician is called gllamm 
(generalised linear latent mixed model), by Rabe-Hesketh et al (2001), 
available apparently only for Stata.
In R, I found the gamm {Matrix} function doing what I want, but I am 
interested in the parameter values of the covariates, using the model 
for prediction, hence gamm is no option.
Finally, Dan Bebber posted a similar question to the R-help list in 
September 2004 (about using corStruct in glmmPQL), but there is no reply 
in the thread (http://tolstoy.newcastle.edu.au/R/help/04/09/3103.html).

Any suggestions are highly welcome.

Many thanks,

Carsten

-- 
Dr. Carsten F. Dormann
Department of Applied Landscape Ecology
UFZ Centre of Environmental Research
Permoserstr. 15
04318 Leipzig
Germany

Tel: ++49(0)341 2352953
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Email: carsten.dormann at ufz.de
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