[R] variance explained by each predictor in GAM

[David Winsemius]

On Jul 12, 2009, at 5:06 PM, Kayce Anderson wrote:

> Hi,
> I am using mgcv:gam and have developed a model with 5 smoothed  
> predictors
> and one factor.
>
> gam1 <- gam(log.sp~ s(Spr.precip,bs="ts")  + s(Win.precip,bs="ts") +  
> s(
> Spr.Tmin,bs="ts")  + s(P.sum.Tmin,bs="ts") + s( Win.Tmax,bs="ts")
> +factor(site),data=dat3)
>
>
> The total deviance explained = 70.4%.
>
>
> I would like to extract the variance explained by each predictor.   
> Is there
> a straightforward way to do this?  I have tried dropping a term and
> recalculating the model, but the edf's change if there is any  
> correlation
> among variables, thereby making all of the relationships different.  I
> haven't yet figured out how to fix the smoothing terms- I get syntax  
> error
> messages.  Among other variations, I tried, for example,
> log.sp~s(Spr.precip, sp=3.9, fx=TRUE) +...
>
>

?anova.gam

Obviously I cannot test this with your dat3. You get an F-statistic  
for each s() term by default and you are referred to saummary.gam for  
further explanation.

David Winsemius, MD
Heritage Laboratories
West Hartford, CT