Dear R users, I have a question regarding accounting for spatioautocorrelation in the residuals of gls models. I would like the error term of my GLS model (in the nlme package) to account/control for spatialautocorrelation among my sample units. So I use a model that looks something along the lines of: ## specify correlation structure Cor1<-corSpher(form = ~Lat + Lon, nugget = TRUE) #### model m1<-gls(InvSpCt ~ lPD1900 + lPD2010 + lPC2012 + DP + lRd, method = "ML", correlation = Cor1) What the response and explanatory variables are don't matter for the purpose of my inquiry. My sample size is very large (N ~2500). For this reason, it is simply not possible to run this model (at least not from my computer!). What would make it possible is if I could limit the distance at which spatioautocorrlation is accounted for. For example, if I could account for spatioautocorrlation up to a certain distance, but disregard it after that point. Inspection of variograms justifies this approach. So my question....is there a way to limit the distance at which the spatial correlation function is applied to the error term in gls models. I read the R documentation and have searched online but have found no mention of such a 'creature'. NOTE: I am also trying to work with SARerr models, but I thought I would look at the data using a statistical modeling approach that I am more familiar with as well. Thank you in advance for your help. Also, thank you in advance for your patience if I am missing some major point here in how gls models incorporate spatioautocorrelation in the error term. -- Basil V. Iannone III, Ph.D. Department of Forestry and Natural Resources Purdue University 195 Marsteller St. West Lafayette, IN 47907 765 - 543 - 2081 [[alternative HTML version deleted]]