Am 07.10.2017 um 17:17 schrieb Allin Cottrell:
On Sat, 7 Oct 2017, Sven Schreiber wrote:
> Am 07.10.2017 um 02:12 schrieb Allin Cottrell:
>> On Fri, 6 Oct 2017, Sven Schreiber wrote:
>
>> This, however, is more substantive: at present we're not saving
>> enough information on a midasreg model to generate a forecast, when
>> the model comprises more than one mds() or mdsl() term. I need to
>> think a bit about how best to arrange that.
Thanks for the offer, but this is now fixed in git and snapshots. The
thing is that for forecasting we need the "gross" MIDAS coefficients
(hfslope, if any, times the weights implied by the hyperparams, for each
midas term).
I'm not sure if this is now correct, I seem to be getting some strange
results for the Umidas case, where I _believe_ they were different (more
plausible) before. I'll have to check, and will report back.
"midas_info" bundles, but I think it's easier to
compute it when the
model is estimated and stick the consolidated vector onto the model. We
now do that (under the name "hfb").
Will compare with that one, too.
thanks,
sven