Hi All,
I have a data set with hierarchy City----Store, and several independent variable (var1-var3), time is daily, there is one ratio variable I'm interested to forecast (Ratio=Total # y1/ Total # y2 at that level), I have those two variables (y1, y2) in the data. I wonder whether it's possible to forecast the ratio? Thank you!
The data sample is as below:
Time | City | Store | Var1 | Var2 | Var3 | Total # y1 | Total # y2 | Ratio(y1/y2) |
| A | 1 | | | | | | |
| A | 2 | | | | | | |
| A | 3 | | | | | | |
| B | 1 | | | | | | |
| B | 2 | | | | | | |
| B | 3 | | | | | | |
| B | 4 | | | | | | |
| C | 1 | | | | | | |
| C | 2 | | | | | | |
| C | 5 | | | | | | |
In my understanding, we have the data of ratio (y1 and y2) at the store level and at daily frequency, but we could not use this ratio to get the weekly and city level data (which means we could not use the ratio directly for aggregation and Accumulation), we need to get the total # of y1 and total # of y2 at city level and weekly frequency, then get the ratio= total# y1/ Total# y2. Thus I don't think we can forecast the ratio at this data structure.
Please share your insight on this problem. Thank you!
Jade