FORECAST.ETS.SEASONALITY Function

The FORECAST.ETS.SEASONALITY function is one of the statistical functions. It is used to return the length of the repetitive pattern the application detects for the specified time series.

The FORECAST.ETS.SEASONALITY function syntax is:

FORECAST.ETS.SEASONALITY(values, timeline, [data_completion], [aggregation])

where

values is a range of the historical values for which you want to predict a new point.

timeline is a range of date/time values that correspond to the historical values. The timeline range must be of the same size as the values range. Date/time values must have a constant step between them (although up to 30% of missing values can be processed as specified by the data_completion argument and duplicate values can be aggregated as specified by the aggregation argument).

data_completion is a numeric value that specifies how to process the missing data points in the timeline data range. It is an optional argument. The possible values are listed in the table below.

Numeric value	Behavior
1 or omitted	Missing points are calculated as the average of the neighbouring points.
0	Missing points are treated as zero values.

aggregation is a numeric value that specifies which function should be used to aggregate identical time values in the timeline data range. It is an optional argument. The possible values are listed in the table below.

Numeric value	Function
1 or omitted	AVERAGE
2	COUNT
3	COUNTA
4	MAX
5	MEDIAN
6	MIN
7	SUM

To apply the FORECAST.ETS.SEASONALITY function,

1. select the cell where you wish to display the result,
2. click the Insert function
   icon situated at the top toolbar,
   or right-click within a selected cell and select the Insert Function option from the menu,
   or click the
   icon situated at the formula bar,
3. select the Statistical function group from the list,
4. click the FORECAST.ETS.SEASONALITY function,
5. enter the required arguments separating them by commas,
6. press the Enter button.

The result will be displayed in the selected cell.

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