On Mon, 26 Sep 2011, Jeevan Tambuluri wrote:
I have time-series data with a large number of samples (anywhere
from 180 to 360 daily samples). I would like to use GRETL to
automatically pick a ARIMA model to forecast values for as many as
30-60 days into future. I would like to also model for seasonality
in the data.
I have been playing with gretl tool to explore my data with
various ARMIA models - like ARIMA (1,0,1), ARIMA (1,1,1) and it
has been a great experience so far.
Now, here is my issue. I would like to write a library to
basically take time series data as input, try various ARIMA models
and pick the most appropriate one "automatically" without human
input or intervention. I understand this is fairly novice way to
looking at the forecasting, but my application's use-case is
simple enough to do it this way.
Now, has anyone tried this using GRETL where multiple models are
tried and results (fstats output) are compared to pick one over
the other? If so is there a GRETL script out there that can be
I'm not aware of any such script, although that doesn't mean that
such a script doesn't exist somewhere.
However, my understanding is that TRAMO -- which is available in a
form compatible with gretl, see for example
-- does this sort of thing
(automatic ARIMA model selection). But (I may be wrong) TRAMO
probably does not handle intra-day "seasonality"; I think it's
mostly oriented to monthly or quarterly data.
Maybe Ignacio Diaz-Emparanza, our resident expert on ARIMA models,