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 shared?
Thanks in advance,