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