I'd like to compare two models which were fitted using gls, however I'm having trouble interpreting the results of gls. If any of you could offer me some advice, I'd greatly appreciate it.
Short explanation of models: These two models have the same fixed-effects structure (two independent, linear effects), and differ only in that the second model includes a corExp structure for spatial autocorrelation. (more detailed explanation of the models at end). Specific questions: 1. The second model estimates two additional parameters in the process of fitting the corSpatial object - the range and nugget of the spatial autocorrelation. Based on this, I would expect the second model to have two fewer residual degrees of freedom. However, the summary function reports that both models have the same number of residual degrees of freedom. Why is this? (Interestingly, the difference in AIC between the two models reflects this difference in the number of model parameters) 2. In the model summary, what is the meaning of the small correlation 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 fit by maximum likelihood Model: all.all.rch ~ l10area + newx Data: gtemp AIC BIC logLik 567.4893 578.572 -279.7446 Coefficients: Value Std.Error t-value p-value (Intercept) 6.891867 0.3295097 20.915522 0e+00 l10area 6.586182 0.3048870 21.602046 0e+00 newx 0.047901 0.0117281 4.084307 1e-04 Correlation: (Intr) l10are l10area -0.364 newx 0.577 -0.007 Standardized residuals: Min Q1 Med Q3 Max -3.34307266 -0.57949890 -0.07214605 0.64309760 2.66409931 Residual standard error: 2.590313 Degrees of freedom: 118 total; 115 residual 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 15.4448835 0.3741476 Coefficients: Value Std.Error t-value p-value (Intercept) 7.621306 0.7648135 9.964921 0.0000 l10area 6.400442 0.5588160 11.453576 0.0000 newx 0.066535 0.0204417 3.254857 0.0015 Correlation: (Intr) l10are l10area -0.592 newx 0.358 0.014 Standardized residuals: Min Q1 Med Q3 Max -3.0035983 -0.5990432 -0.2226852 0.5113270 2.4444263 Residual standard error: 2.820337 Degrees of freedom: 118 total; 115 residual Tim Handley Fire Effects Monitor Santa Monica Mountains National Recreation Area 401 W. Hillcrest Dr. Thousand Oaks, CA 91360 805-370-2347 ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.