To apply the methodModels series values using the Exponential Smoothing method. It is included into the Forecast group.
The Exponential Smoothing method is a technique of averaging values of a time series. In contrast to moving average method, all observations of source time series take part in calculating the exponential mean, but these observations have different weight coefficients. The time of the time series value plays the key role for the exponential smoothing. Exponentially decreasing weights are assigned to older observations; all previous series observations are taken into account.
After the method is applied, a series with the name of the Exponential Smoothing(<Series_Name>) type and containing calculation results is added to the data table for each of the selected series. For example:
To set up specific calculation options, use the side panel tabs:
Parameters. It enables the user to change basic calculation options: seasonality and growth models.
Autofit Parameters. It enables the user to set up parameters of coefficient values autofit, used on method calculation.
See also:
Calculation Methods | Forecast | Exponential Smoothing
Forecasting button on the Calculations ribbon tab.