In my attempt to forecast sales demand by month utilizing the last 3 years of history to predict balance of the year,
ets() from forecast() package yields an answer for some time series but not others. I'm following Dr Hyndman's presentation on best fist ets() function.
I understand while the flat forecast (average of the intermittent/volatile inputs) might be the best based on the intermittent history. My question is more of whether the process below has any validity or if it's tottay wonky. For the ones where ets() provides a flat forecast I tried the procedure outlined below to fix it, please let me know if I'm totally lost in my way of thinking:
- ETS() flat forecast when there are too many 0's (or volatile)
- I increase every observation of the time series by 100
- ETS() forecast a curve
- Can I just now reduce everything by 100 to get my forecast?