Double Exponential Smoothingoverview how to example data see also
Double Exponential SmoothingStat > Time Series > Double Exp Smoothing
Double exponential smoothing smoothes your data by Holt (and Brown as a special case) double exponential smoothing and provides short-term forecasts. This procedure can work well when a trend is present but it can also serve as a general smoothing method. Dynamic estimates are calculated for two components: level and trend.
Variable: Enter the column containing the time series.
Weights to Use in Smoothing: The method Minitab uses to calculate level and trend components is determined by the option chosen below. See Calculating Level and Trend Components for details.
Optimal ARIMA: Choose to use the default weights, or smoothing parameters, which Minitab computes by fitting an ARIMA (0,2,2) model to the data.
Use: Choose to enter specific values for the smoothing parameters. You must specify the appropriate weights greater than 0 and less than 2 for the level component and greater than 0 and less than [4 / (weight for level component) - 2] for the trend component.
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 that 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. If you leave this space blank, Minitab generates forecasts from the end of the data.