ARIMA And ETS Forecasting In R
Accurately forecasting costs, sales, user growth, patient readmission, etc is an important step to providing directors actionable information. This can be difficult to model by hand or in Excel. In addition, using traditional methods like moving averages might not provide enough insight into the various trends and seasonality.
Using models like the ARIMA and ETS provides analysts the ability to predict more accurately and robustly by considering multiple factors like seasonality and trend. What is even better is that languages like R and Python make it much easier for analysts and data teams to avoid all the work they would usually have to do by hand. This can reduce the time to develop a model by more than half and increase accuracy.
Our team has developed a course to help upskill your analysts in the skills of R programming, ARIMA and ETS. It covers not only the programming aspect, but also helps cover many of the important topics that have to do with time series forecasting like stationarity, autocorrelation and unit roots. This class will help educate your team and improve their ability to use R and develop models for forecasting.
Call To Action
If your department is looking to develop an improve your forecasts and upskill your employees contact us today! We would love to help instruct you and your teams
The Goals Of This Service Are:
- To understand how to develop and gauge the quality of a complex forecasting model
- To implement the ARIMA and ETS models in R
- To understand forecasting vocabulary and concepts
- To understand how data drives model choice
