From the course: Business Analytics: Forecasting with Exponential Smoothing
Join today to access over 22,600 courses taught by industry experts or purchase this course individually.
From error correction to smoothing
From the course: Business Analytics: Forecasting with Exponential Smoothing
From error correction to smoothing
- [Instructor] Let's take a look at the relationship between the error correction form of the smoothing equation and it's smoothing form. I'll start with the error correction form. That's shown in the first line of the screen. Y hat sub t plus one is the forecast for the next period, identified as period t plus one. To make that forecast, we add the forecast for time t, that is y hat sub t to the product of alpha, the smoothing constant, and the error in the prior forecast symbolized by the Greek letter epsilon sub t. The next step is to expand the reference to the error in the forecast for time t. We do that by replacing epsilon sub t in the first line, with y sub t minus y hat sub t in the parenthesis in the second line. Y sub t is just the actual observation made at time time t and y hat sub t is the forecast made for time t. The difference between the two is the forecast error, or epsilon sub t. Next we distribute the alpha across the actual observation and the forecast for time…
Practice while you learn with exercise files
Download the files the instructor uses to teach the course. Follow along and learn by watching, listening and practicing.
Download courses and learn on the go
Watch courses on your mobile device without an internet connection. Download courses using your iOS or Android LinkedIn Learning app.