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

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