Am 13.09.2017 um 23:38 schrieb Allin Cottrell:
On Wed, 13 Sep 2017, Sven Schreiber wrote:
> Am 13.09.2017 um 23:01 schrieb Allin Cottrell:
>
>> My impression is that "sane" values of theta have theta_1 around 1.0
>> and theta_2 > theta_1 -- and that such vectors will respect the "zero
>> last lag" condition. Admittedly, this is not explicitly stated
>> anywhere (that I'm aware of).
>
> Right, but then the estimation can steer the hyperparameters into the
> "unsane" region, can't it?
In principle, I suppose, but I haven't seen it happen.
Well I have a case here where I set the initial values to {0.5, 0}, and
that's where the routine converges. The results have various obvious and
visible problems, but I think it constitutes a proof of concept.
So I'm wondering whether a condition like th2 > th1 should be imposed at
least on the starting values. (It's more difficult to impose it overall
I guess.) But of course it would be nice to have some literature on that.
And while I experimented with those Midas weights, another question came
up: Is $model.seplist after midasreg properly implemented? Consider this
example:
<hansl>
open gdp_midas.gdt
list mi = ld_indpro_m?
list mp = ld_payems_m?
midasreg ld_qgdp const ld_qgdp(-1) ; \
mds(mi, 0,2, 2, null) mds(mp, 1,5, 2, null)
check = $model.seplist
list check print # I get: ld_qgdp payems_m1
</hansl>
Note that the members of 'check' have ID numbers 2 and 5 in the dataset
-- and that the first set of Midas coefficients is in positions 2-4, the
second set is in positions 5-7. So I'm guessing that this provides
information where the Midas coefficients are located in the $coeff
vector, but somehow this is erroneously (?) put into a list container?
Also, $model does not seem to contain information about the hi-freq
regressors: $model.xlist gives me the same as $model.lfxlist.
thanks,
sven