On Wed, 21 Feb 2018, oleg_komashko@ukr.net wrote:
> when mle block fails to compute hessian it tries to compute opg
> arima fails in such situations one should input --opg by hand
Thanks for pointing this out.
The intended behavior of "arma" is that we fall back to OPG for the
covariance matrix if computation of the Hessian fails -- unless the
--hessian option is given, in which case an error is flagged if the
request cannot be met.
This facility got broken at some point, but it's now reinstated in
git.
Speed:
> With bjg.gdt arima 2 1 2; 2 1 2; lg takes ~60 seconds
> (R's arima only ~ 14 seconds)
> If insert [initializer] from arima 2 1 2; 2 1 2; lg --x-12-arima
> with arima 2 1 2; 2 1 2; lg I have ~40 seconds: the gain from
> very good inits gives very little
We're aware that our exact ML estimation of complex ARIMA models via
the Kalman filter is slow compared to some other software. This is
something we're looking into. One point to note is that our
implementation arguably offers "surplus precision" as it stands. For
the specification above, for example, gretl gets a somewhat greater
loglikelihood than x13as. (I haven't yet figured out how to get R's
arima() to estimate this model.)
Allin