Thestatistic_typeargument determines which statistic is returned by FORECAST.ETS.STAT.
These are statistics relevant to the forecast created by the feature, which relies on theFORECAST.ETS function.
Thestatistic_typevalues come from column F.
Statistical values
The statistical value to return is determined by thestatistic_typeargument.
The table below shows the eight possible values and corresponding results.
Argument notes
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.
It is not required that the timeline be sorted.
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.
Theaggregationargument is optional and controls what function is used to aggregate data points when the timeline contains duplicate values.
The default is 1, which specifies AVERAGE.
Other options are given in the table below.
Errors
The FORECAST.ETS.STAT 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…
