It appears you are conflating beta coefficients (individual covariate
effect measures) with overall model fit measures. Beta coefficients
are not directly comparable to R-squared measures in ordinary least
squares analyses, so why would they be so in gam models?
I cannot tell whether you actually looked at anova.gam or consulted
Wood's book (which is really the better place to go for advice
regarding mgcv function questions. You were offered an apportioned F-
statistic for each covariate smooth. How was that not satisfactory?
What is your goal in this search?
--
DW
--
On Jul 13, 2009, at 10:09 AM, Kayce Anderson wrote:
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.
You may need to define your terms and there may not be an analog
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
David Winsemius, MD
Heritage Laboratories
West Hartford, CT
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