[R] predict.glm - how to?

[Laurits Søgaard Nielsen]

Hi

I have a little R problem. I have created a GLM model in R and now I want to
predict some values outside the values I have in the model (extrapolate).

I have this code:

fitted.model4 <- glm(Yval ~ time, family=gaussian, data=Fuel)

The question is - How do I predict a value of Yval ie with a value of time =
340 and also get confidence/prediction intervals for Yvar?

I have tried the predict.glm but cannot make it work - any suggestions how
to do this using predict.glm?

****

Yval are 312 fuel prices ranging from 60 to 140 and time is a sequence from
1 to 312.

The GLM summary output is as follows:

Deviance Residuals: 
    Min       1Q   Median       3Q      Max  
-24.978   -4.033   -0.391    4.747   15.323  

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept) 79.698229   0.871830   91.42   <2e-16 ***
seq(1:312)  0.180127   0.004828   37.31   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

(Dispersion parameter for gaussian family taken to be 59.00219)

Null deviance: 100408  on 311  degrees of freedom
Residual deviance:  18291  on 310  degrees of freedom
AIC: 2161.6

Number of Fisher Scoring iterations: 2