I'm working on a forecasting weekly sales by category. I want to make sure I'm doing it correctly.
date DiningSales 3/1/2015 243334 3/8/2015 556637 3/15/2015 554315 ...... 10/1/2017 343660
I've read Rob Hyndman website and see he recommends TBATS for weekly data. My date range is from 3/1/2015-10/1/2017. I want to predict the next 4 weeks. Here is my code:
dining.data <- read.csv("sales_dining.csv", fileEncoding="UTF-8-BOM") dining.df <- dining.data$DiningSales dining.ts <- ts(dining.df, freq=365.25/7, start=2015+59/365.25) dining.tbats <- tbats(dining.ts) dining.fc <- forecast(dining.tbats, h=4) plot(dining.fc, ylab="dining orders")
The code runs but my predictions for the next 4 weeks seem way off. My questions are:
- Did I use the correct frequency to get weekly data?
- Is my start date correct? I want the start date to be 3/1/2015.
- The next four predictions change the date to 10/7 to 2017.768. Is there a way to have the date in the results be in an actual date format?
- Finally it seems like there isn't a lot out there for weekly forecast, rather monthly, annual or even daily or hourly. Is weekly data harder to have a more accurate prediction?