R help - Aug 2015 - Predict Function use with GLM

I am currently using a GLM with Gaussian family to model fish depth~length +
distance from shore: 

model1 <- glm(Depth ~ length + distance from shore,
family=gaussian(link="log"))

There are no zero depths. I would like to use the above model with the
predict function in R to generate three lines (with confidence intervals)
for the depth at size for three distances, say 100 m, 500 m and 1000m.
Problem is I am unable to figure out how to do this? 

Any advice / assistance would be gratefully received...

Thank you

Tris




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trisgutt <trisgutt <at> hotmail.com> writes:
> 
> I am currently using a GLM with Gaussian family to model fish depth~length
+
> distance from shore: 
> 
> model1 <- glm(Depth ~ length + distance from shore,
> family=gaussian(link="log"))
> 
> There are no zero depths. I would like to use the above model with the
> predict function in R to generate three lines (with confidence intervals)
> for the depth at size for three distances, say 100 m, 500 m and 1000m.
> Problem is I am unable to figure out how to do this? 
> 
> Any advice / assistance would be gratefully received...
> 
> Thank you
> 
> Tris
> 
Something like:

pp <- expand.grid(distance=c(100,500,1000),
                       length=seq(min_depth,max_depth,length.out=51))
## 51 is arbitrary -- you just need enough points to make the curve
## appear smooth

predvals <- predict(model1,newdata=newdata,se.fit=TRUE,type="link")
pp <- transform(pp,est=exp(predvals$fit),
            lwr=exp(predvals$fit-1.96*predvals$se),
            upr=exp(predvals$fit+1.96*predvals$se))