Hello, I am have fitted GLS models to time series data. Now I wish to bootstrap this data to produce confidence intervals for the model. However, because this is time series data, normal bootstrapping is not applicable. Secondly, 'tsboot' appears to only be useful for ar models - and does not seem to be applicable to GLS models. I have written code in R to randomly sample blocks of the data (as in Davison & Hinkley's book - bootstrap methods and their application) and use this resampling to re-run the model, but this does not seem to be the correct approach since Confidence Intervals produced do not show the underlying pattern (cycles) in the data [even when block length is increased, it only picks up a little of this variation]. Any help as to how to proceed with this would be greatly appreciated, as I cannot find anything applicable on the R pages. Alternatively, if there is another method to proceed with this (other than bootstrapping), I would also be happy to try it. Thankyou, Lillian.