Henk Sierdsema wrote:
Hi Ivan,
Can you tell me what the purpose is of your modelling? Is it simply producing
spatial predictions based on a logistic model or do you want to incorporate
spatial autocorrelation in the models? Given your last mail it seems you want
to incorporate spatial autocorrelation despite the fact that you deny this in
your second mail. So please extend more on the type of data you have and your
aim. Next to geoRglm, which is only suitable for small datasets, you might also
try regression-kriging.
Is there by the way anyone who has experience with autoregressive models?
Henk
Henk Sierdsema
SOVON Vogelonderzoek Nederland / SOVON Dutch Centre for Field Ornithology
Rijksstraatweg 178
6573 DG Beek-Ubbergen
The Netherlands
tel: +31 (0)24 6848145
fax: +31 (0)24 6848122
What do you mean by small datasets?
I have used geoRglm to fit spatial binomial models with hundreds of
point observations.
One approach that would allow the fit of models with even thousand of
point observations with geoRglm is to create spatial cells (i.e.
logistic regression with grouped data) and count the number of trials
and successes in each cell. I implemented that approach in Roa-Ureta and
Niklitschek, 2007, Biomass estimation from surveys with liklihood-based
geostatistics, ICES Journal of Marine Science 64:1723-1734.
Rubén
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