Many thanks for the advice David. I would really like to figure out, though,
how to get the contribution of each factor to the Rsq - something like a
Beta coefficient for GAM. Ideas?
KC
On Sun, Jul 12, 2009 at 5:41 PM, David Winsemius <dwinsem...@comcast.net>wrote:
>
> 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
>
>
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