I a sorry, of course, I mean standarizing
Note: here we(you)  have more work:
shifting constant becomes a function of
other parameters, so covariance matrix should
be also adjusted
It seems a range should be determined for
no shifting of the exogenous variables

Oleh

28 жовтня 2018, 20:53:43, від oleg_komashko@ukr.net:

Obviously, the right setps
What is left is re-scale exogenous variables:

Compare:
open bad_data.gdt
smpl 1 194
z = y_two+10^5
arima 3 0 0; 1 0 0; diff_series const y_one y_two --x-12-arima
arima 3 0 0; 1 0 0; diff_series const y_one z --x-12-arima
arima 3 0 0; 1 0 0; diff_series const y_one z
Oleh


28 жовтня 2018, 20:27:54, від "Riccardo (Jack) Lucchetti" <r.lucchetti@univpm.it>:

On Sun, 28 Oct 2018, oleg_komashko@ukr.net wrote:

> Current scaling factor makes mean ~10
> with 1 196 sample mean is ~10^-8
> Hence, scaling factor ~10^18

I just pushed to git a one-liner that seems to solve the first issue you 
raised. Now

<hansl>
open bad_data.gdt
smpl 1 194
arima 3 0 0; 1 0 0; diff_series const y_one y_two
</hansl>

produces sensible results. Allin: the fix is rather trivial, but please 
take a look.



-------------------------------------------------------
   Riccardo (Jack) Lucchetti
   Dipartimento di Scienze Economiche e Sociali (DiSES)

   Università Politecnica delle Marche
   (formerly known as Università di Ancona)

   r.lucchetti@univpm.it
   http://www2.econ.univpm.it/servizi/hpp/lucchetti
-------------------------------------------------------
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