Provides a systematic approach for forecasting sales data based on historical quarterly sales figures. Different time series models are explored, and the best model is selected based on its performance on a validation set. The forecast is then visualized as a probability density function (PDF), and weighted averages for different sales regions are calculated based on the PDF.
Necessary packages installation code:
install.packages(c("readxl", "dplyr", "lubridate", "zoo", "forecast"))
Thanks for checking out this project, hope it helps! You may not hear this on GitHub a lot, but I appreciate you.
Best luck and wishes,
Alexander Baker.