Simple exponential smoothing (SES) incorporates most of the elements used in the smoothing approach to forecasting, such as a level smoothing constant, self-correction, and the gradual weakening of the influence of older observations on new forecasts. But SES works poorly with baselines that display either trends or seasonality. The trended time series is one step up in complexity from the stationary time series analyzed by SES—its baseline trends up or down. The use of exponential smoothing with a trended baseline is often called Holt's method, and this course was designed to equip you with this technique. Here, instructor Conrad Carlberg explains how to use Holt's method to create forecasts in R that deal with trends in a baseline.
President at Network Control Systems, Inc.Conrad Carlberg is a writer and consultant specializing in quantitative and statistical analysis.
He has authored 15 books on using Microsoft Excel for quantitative analysis. He holds a PhD in statistics and has run a consulting business specializing in statistical analysis in the medical and financial fields since 1995.
Skills covered in this course
For each course you will get
- Exercise files and quizzes
- Certificate of completion from LinkedIn
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Why trended baseline smoothing will help your regression“
- [Instructor] Welcome to my course on forecasting trended baselines. Now if you take this course here's what you can expect to learn. Trended baselines such as the sales of a new and successful product tend to increase over time and if you chart them you often see a line that's trending upwards. Products entering the final stage of their life cycle trend down. There are many other examples but the characteristic that they all have in common is the need for a forecasting technique that recognizes and accounts for the trend. That's what you'll find here, an approach to forecasting, often called Holt's Method that can deal with trend in a baseline. I show you how to create those forecasts using Holt's Method in R so that you can get to the results quickly as well as in Excel so that you can see what's going on behind the scenes in R. So let's get started.
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