Timeline for Forecasting daily sales by handling multiple seasonality and zero sales in R
Current License: CC BY-SA 4.0
6 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| May 20, 2018 at 6:35 | vote | accept | spv92 | ||
| May 20, 2018 at 4:04 | comment | added | Rob Hyndman | This is not a general consulting forum. Please ask new questions if you have them. | |
| May 20, 2018 at 3:43 | comment | added | spv92 | Thanks a lot! I have two more questions: 1. When replacing 0's with NA's, how to handle increasing variance with time? 2.I have another example of a different store where the sales tend to peak on particularly around last two weeks of the year ..say around 23rd dec, 30th dec and the promotion was applied on most of these days. Since this happened for consecutive 2 years, I expect that to happen in the next year also. I am thinking of extracting the week of the year and creating a dummy variable for week 51 and 52. and including fourier and promotion terms. do you have any suggestions? | |
| May 20, 2018 at 3:19 | comment | added | Rob Hyndman | You have a periodic pattern with a peak around time 0, one at time 52, another at time 104. As you have set the frequency to 7, they correspond to peaks that are 52 weeks apart. Yes, adding the dummy to xreg along with fourier terms is what I was suggesting. | |
| May 19, 2018 at 21:23 | comment | added | spv92 | Thank you very much Rob! I really appreciate it! May I ask how did you determine that it has annual seasonality? Also, the dataset I have has already a binary variable to indicate whether a promotion was run on that day or not. So, as per your answer I am thinking of fitting a harmonic regression model and add this binary promotion variable as predictor to the xreg matrix along with the fourier term. Would this work?? | |
| May 19, 2018 at 7:12 | history | answered | Rob Hyndman | CC BY-SA 4.0 |