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
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 shared?
Thanks in advance,