x12/x13 is open source too;
unfortunately I was taught paper
fortran ~35 years ago and have never used since that times
So it's unrealistic for me to understand in a realistic time
what they really do
But, look at lnl difference between libgretl/transformed
and x-13 original: but for random last digits in numbers
the difference was constant
It is hard to imagine a different reason but for
they actually use a similar transformation
Only imaginable differences could be:
I used 'one' for everything
they could use another numbers: 10, 5, log(10), etc
may be, they defined a range for non-traaforming
I am sure this is all difference
Oleh
On Thu, 1 Nov 2018, oleg_komashko@ukr.net wrote:
>> I didn't mean for my verdict to be humiliating
> I it was just poorly selected English word
> I meant I was disappointed to see results
> of the first script and didn't mean to
> characterize intentions.
> I was disappointed since I forgot to
> insert smpl 1 194 into the first code (with my_arima)
> With smpl 1 194 mean(diff_series) is O(10^-18)
> and everything looks quite different
OK!
> --x-12-arima comparison showed that
> my transformations do actually nothing to
> --x-12-arima estimation results
> In my opinion this is an evidence that they
> do something similar [...]
That's possible, though maybe they don't need to standardize. We know
they use a switching algorithm -- ML for the ARMA terms plus GLS for
the regression terms -- and since GLS has an analytical solution it
shouldn't be so vulnerable to numerical problems in face of "wacky"
data for the exogenous variables.
Speaking of x12a, I've now (in git) enabled the $vcv accessor for this
case. The covariances between the ARMA and regression terms will be
identically zero since x12a doesn't calculate them. IIRC they argue
that they should be uncorrelated asymptotically.
Allin
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