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Winters' MethodStat > Time Series > Winters' Method
Winters' Method smoothes your data by Holt-Winters exponential smoothing and provides short to medium-range forecasting. You can use this procedure when both trend and seasonality are present, with these two components being either additive or multiplicative. Winters' Method calculates dynamic estimates for three components: level, trend, and seasonal.
Variable: Select the column containing the time series.
Seasonal Length: Enter the length of the seasonal pattern. This must be a positive integer greater than or equal to 2.
Model Type:
Multiplicative: Choose the multiplicative model when the seasonal pattern in the data depends on the size of the data. In other words, the magnitude of the seasonal pattern increases as the series goes up, and decreases as the series goes down.
Additive: Choose the additive model when the seasonal pattern in the data does not depend on the size of the data. In other words, the magnitude of the seasonal pattern does not change as the series goes up or down.
Weights to Use in Smoothing: By default, all three weights, or smoothing parameters, are set to 0.2. Since an equivalent ARIMA model exists only for a very restricted form of the Holt-Winters model, optimal parameters are not found for Winters' Method as they are for Single Exponential Smoothing and Double Exponential Smoothing.
Level: Specify the level component weight; must be a number from 0 to 1.
Trend: Specify the trend component weight; must be a number from 0 to 1.
Seasonal: Specify the seasonal component weight; must be a number from 0 to 1.
Generate forecasts: Check to generate forecasts. Forecasts appear in green on the time series plot with 95% prediction interval bands.
Number of forecasts: Enter an integer to indicate how many forecasts you want.
Starting from origin: Enter a positive integer to specify a starting point for the forecasts. For example, if you specify 4 forecasts and 48 for the origin, Minitab computes forecasts for periods 49, 50, 51, and 52, based on the level and trend components at period 48, and the corresponding seasonal components. If you leave this space blank, Minitab generates forecasts from the end of the data.