[R-sig-eco] explained variation in GAM/GAMM

[Zoltan Botta-Dukat]

Dear All,

I would like to estimate the variation explained by different sets of 
predictors. My response is binary, and I want to capture the possible 
non-linear relationships, thus first I chooose GAM with binomial family.
Summary of the model gives adjusted R-squared and explained deviance (in 
%). The latter seems to be what I need, and I'm not sure what  the 
R-squared is in this situation. Could someone explain it?

Then, I recognzed that residuals are highly spatially autocorrelated, so 
I changed to GAMM. It handle the spatial autocorrelation, but the 
summary of gam part of the fitted model gives adjusted R-squared only, 
but not the expalined variance. R-squared is lower in GAMM than in GAM, 
so I think  considering spatial autocorrelation is necessary. My 
question is whether I can use this adjusted R-squared or I should 
calculate something else, for example Efron's pseudo-R-squared, from the 
predicted values.

Thanks for your advice

Zoltan