By popular request we introduced (in gretl 1.9.91) the --permanent option for the "smpl" command: this enables to the user to apply a sample restriction and permanently shrink the dataset to the new specification (as opposed to keeping the full dataset in the background). It has recently come to light that this can cause problems under some conditions, in the context of a GUI session in particular, and I'm trying to decide how to handle this. Consider a GUI gretl session of this sort: you open bigdata.gdt, estimate some models -- on the full dataset and/or on one or more subsamples -- and save these "as icons". Then you decide that bigdata is redundant for your purposes and you want to do a permanent subsampling. What happens with your saved models? There's an easy case: all the models were in fact estimated on the particular subsample of bigdata that you'd like to impose permanently (something we can detect and handle quite easily). Otherwise, some or all of the saved models are going to become zombies: in general there will be no way -- after the permanent subsampling -- to do things like running tests, saving residuals as series, plotting actual versus fitted and so on, since the dataset(s) on which these models were estimated will have disappeared. So here's my proposal: in the circumstances described above, if you issue a command to shrink the dataset permanently, gretl checks to see whether all saved models fall under the "easy case". If so, fine. If not, you get a warning that not all saved models can be preserved, with a "Go ahead? Yes/No" dialog. If you say "Yes", we destroy all the models that would turn into zombies. Any comments/suggestions? Allin