FORECAST.ETS can be used to predict numeric values like sales, inventory, expenses, etc.
with a seasonal pattern.
To calculate predicted values, FORECAST.ETS uses something called triple exponential smoothing.
This is an algorithm that applies overall smoothing, trend smoothing, and seasonal smoothing.
With these inputs, the FORECAST.ETS function returns 618.29 in cell D13.
The chart to the right shows this data plotted in ascatter plot.
Argument notes
Thetarget_dateargument represents the point on the timeline that a prediction should be calculated.
Thevaluesargument contains the dependent array or range of data, also called y values.
These are existing historical values from which a prediction will be calculated.
Thetimelineargument is the independent array or range of values, also called x values.
The timeline, must consist of numeric values with a constant step interval.
For example, the timeline could be yearly, quarterly, monthly, daily, etc.
The timeline can also be a simple list of numeric periods, as in the example shown.
Theseasonalityargument is optional and represents the length of the seasonal pattern expressed in timeline units.
The number 8784 = 366 x 24, the number of hours in a leap year.
Thedata_completionargument is optional and specifies how FORECAST.ETS should handle missing data points.
The options are 1 (default) and zero.
By default, FORECAST.ETS will provide missing data points by averaging neighboring data points.
If zero is provided, FORECAST.ETS will treat missing data points as zero.
The default is 1, which specifies AVERAGE.
Other options are given in the table below.
Note: It is better to perform aggregation before using FORECAST.ETS to make forecasting as accurate as possible.
Errors
The FORECAST.ETS function will return errors as shown below.
FORECAST.ETS can be used to predict numeric values like sales, inventory, expenses, etc.
with a seasonal pattern.
It is designed to be used along with theFORECAST.ETS functionas a way to show forecast accuracy.
Thestatistic_typeargument determines which statistic is returned by FORECAST.ETS.STAT…
