autologistic modelling in R

Charlotte Bell <charlotte.bell <at> sheffield.ac.uk> writes:

Hi,

I have spatially autocorrelated data (with a binary response variable and
continuous predictor variables). I believe I need to do an autologistic
model, does anyone know a method for doing this in R?

There are several approaches that you could try. One direct spatial approach is
the off-CRAN Rcitrus package:

http://www.leg.ufpr.br/Rcitrus/

which although the documentation is in Portuguese, should get you most of the 
way there. You could also look at geoRglm on CRAN, which handles a similar 
setting in a geostatistical way. You may also find it helpful to look at 
the handling of spatial autocorrelation in the nlme package in a GLMM context, 
using the CorSpatial approach. If you like, you could also look at a GAMM 
approach in mgcv. The glmmBUGS package can be used for preparing a GLMM for 
running in *BUGS if the spatial autocorrelation is expressed through a 
spatial weights matrix rather than as a function of distance.

Hope this helps,

Roger Bivand.

PS. RSiteSearch on autologistic does find:

http://finzi.psych.upenn.edu/R/Rhelp02a/archive/147538.html

which is a posting by Elias Krainski on R-sig-geo, where a further link
is given for a forthcoming stLattice package.

Many thanks

C Bell