I an making something similar to R::forecast:ets
It uses NMmin to find set of alpha, beta, gamma
and starting values which maximize likelyhood
for e-smoothing model (for additive models
it is the same as minimize sum of squared errors
Empirically, I detected that setting maxiter to 100
gives minimal sum of squares comparable to
that of Hyndman. I think , empirical
setting of the tolerance could bring a better
time to exactness tradeoff
Oleh
P.S. Your unwilling to accept Rforecast made me
code a couple non-rubbish things, e.g. lagreg
On Fri, 16 Feb 2018, oleg_komashko@ukr.net wrote:
> Dear all,
>
> The question is:
>
> How to change tolerance in these functions?
As of now, you can't. You can set the maximum number of iterations,
though. Can you provide an example of what you need to set the tolerance
for?
-------------------------------------------------------
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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