Chapter 63. Winters’s method
You often need to predict future values of a time series, such as monthly costs or monthly product revenues. This is usually difficult because the characteristics of any time series are constantly changing. Smoothing or adaptive methods are usually best suited for forecasting future values of a time series. This chapter describes the most powerful smoothing method: Winters’s method. To help you understand how Winters’s method works, I’ll use it to forecast monthly housing starts in the United States. Housing starts are simply the number of new homes whose construction begins during a month. I’ll begin by describing the three key characteristics of a time series.
Time series characteristics
The behavior of most time series ...
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