R help - May 2003 - Confidence intervals for gls models?

Is there an easy way to compute confidence intervals (or prediction
intervals) for gls models?

E.g. for standard linear models, with the predict.lm function, we can set
interval="confidence" , level = 0.95 and type="response".

Thanks in advance!

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What about the obvious:

tstDf <- data.frame(x=1:9, y=rnorm(9), w=1:9)
fit <- lm(y~x, tstDf, weights=w)
pred <- predict(fit, se.fit=T)
pred$fit + outer(pred$se.fit, c(-2, 2))

"predict.lm" might need weights for interval="prediction"
with newdata,
but not with interval="confidence" ... or am I missing something?

hth.  spencer graves

Brown, David wrote:
> Is there an easy way to compute confidence intervals (or prediction
> intervals) for gls models?
> 
> E.g. for standard linear models, with the predict.lm function, we can set
> interval="confidence" , level = 0.95 and
type="response".
> 
> Thanks in advance!
> 
> 	[[alternate HTML version deleted]]
> 
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