[R] analysing non-normal spatially autocorrelated data

From: Carsten Dormann <carsten.dormann_at_ufz.de>
Date: Wed 20 Jul 2005 - 16:40:46 EST


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
Fax: ++49(0)341 2352534
Email: carsten.dormann@ufz.de
internet: http://www.ufz.de/index.php?de=4205

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Received on Wed Jul 20 16:47:01 2005

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