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...ation matrix under the heading "Correlation:"? At first, I thought that this was describing possible correlations among the predictor variables, but then I saw that it also included the model intercept. What do these correlation value mean? ##More detailed information ##function calls: sppl.i.xx = gls(all.all.rch~l10area+newx, data = gtemp, method="ML") sppl.i.ex = gls(all.all.rch~l10area+newx, data = gtemp, method="ML", correlation = corExp(c(20,.8), form=~x+y|area, nugget=TRUE)) ##model summaries > summary(sppl.i.xx) Generalized least squares...

...pp", "n.plot", "n.sp") bugs.data(datalist) parmlist<-c("b.lev", "b.light", "b.con", "b.dcon", "b.s1", "b.s2", "b.s3", "sigma.ind", "sigma.plt", "sigma.sp", "sigma.sppl") initlist<-list(list(b.lev=0.01, b.light=0.01, b.con=0.01, b.s1=0.01, b.s2=0.01, b.s3=0.01, b.dcon=0.01, tau.ind=rep(0,N), tau.plt=rep(0,n.plot), tau.sp=rep(0,n.sp), tau=array(0, c(n.sp, n.plot))), list(b.lev=0.01, b.light=0.01, b.con=0.01, b.s1=0.01, b....

...6) + 2*5 = 557.2. However, summary.gls reports an AIC of 559.2. If one works backwards from the reported AIC of 559.2, it seems that gls believes it has estimated 6 parameters in the fitting process. Again, is this an error in gls, or an error on my part? Copied from R terminal: > > summary(sppl.i.ex) Generalized least squares fit by maximum likelihood Model: all.all.rch ~ l10area + newx Data: gtemp AIC BIC logLik 559.167 575.7911 -273.5835 Correlation Structure: Exponential spatial correlation Formula: ~x + y | area Parameter estimate(s): range nugget 15.44...