[R] predict.glm and predict.gam output

[sw283 at bath.ac.uk]

Anke,

mgcv:predict.gam certainly didn't produce `something like a
negative log-likelihood of occurrence', but is it possible that one of  
your maps is on the probability scale and the other on the linear  
predictor scale?
If you used predict.glm(model1,type="response"), but  
predict.gam(model2,type="link"), then you'd get the sort of difference  
that you are maybe describing. ?predict.gam and ?predict.glm give more  
details.
If that doesn't resolve the issue, then a few more details about the  
models actually being fitted are probably needed.

best,
Simon


Quoting Anke Konrad <akonrad at nmsu.edu>:

> Hi all,
>
> I am currently trying to compare different plant occurrence prediction
> maps generated in R and exported into GRASS. One of these maps was
> generated from a glm fitted to some data, and subsequently applying
> this glm model to a wider region using predict.glm. The outcome here
> was a probability of occurrence. The second map I generated using a gam
> (mgcv), however, this map seems to have assigned something like a
> negative log-likelihood of occurrence to each raster cell in the
> region. Since I would like to compare the two, I would like to figure
> out a way of having the same kind of output from the "predict"
> functions (either probability OR negative log-likelihood). Does anyone
> know of a way of changing the output options? And if not, does anyone
> have any suggestions of how I could deal with this issue?
>
> Thank you!
>
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