I have two sets of time series data for 36 months. It contains seasonal trends with a 12-month cycle.
- How to determine whether it is a good model? The smaller the AIC, the better the model?
- Do I need to do any transformation before using auto.arima? As I find in google that auto.arima has already dealt with seasonal trends.
- Do I need to re-model if the residuals of the forecast not following $\mathcal N(0,1)$?
- Do I need more data to do the forecasting? (now only 3 sets of data to do forecasting, due to seasonal trends).