Business Analytics: Forecasting with Trended Baseline Smoothing

Learn about a forecasting technique that recognizes and accounts for trends in a baseline, as well as how to run the trend forecast analysis in R.

Introduction

• Why trended baseline smoothing will help your regression
• Software setup

1. Simple Exponential Smoothing (SES) and Trend

• A review of SES with a stationary baseline
• Problems using SES with a trended baseline
• Forecasting differences
• Using R for SES
• Using ARIMA(0,1,1) for SES

2. Understanding the Forecast Equation

• Distinguish between a level component and a trend component
• The trend constant compared to the level constant
• Compare smoothing and error correction forms
• Initialize the trend forecasts
• Build the full worksheet and optimize with Solver

3. Running the Trend Forecast Analysis in R

• Prepare for analysis with R
• Run and interpret the analysis in R

Conclusion

• Next steps