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FORECAST.ETS.SEASONALITY Function
Description
The FORECAST.ETS.SEASONALITY function returns the length of the repetitive pattern Excel detects for the specified time series.
FORECAST.ETS.Seasonality can be used following FORECAST.ETS to identify which automatic seasonality was detected and used in FORECAST.ETS. While it can also be used independently of FORECAST.ETS, the functions are tied since the seasonality detected in this function is identical to the one used by FORECAST.ETS, considering the same input parameters that affect data completion.
Syntax
FORECAST.ETS.SEASONALITY (values, timeline, [data_completion], [aggregation])
Arguments
| Argument | Description | Required/ Optional |
|---|---|---|
| Values | Values are the historical values, for which you want to forecast the next points. | Required |
| Timeline | The independent array or range of numeric data. The dates in the timeline must have a consistent step between them and cannot be zero. However, FORECAST.ETS.SEASONALITY supports up to 30% missing data, and will automatically adjust for it. The timeline is not required to be sorted, as FORECAST.ETS.SEASONALITY will sort it implicitly for calculations. |
Required |
| Data_completion |
FORECAST.ETS.SEASONALITY supports up to 30% missing data in the timeline and will automatically adjust for it based on Data_completion. The default value of 1 will account for missing points by completing them to be the average of the neighboring points. 0 will indicate the algorithm to account for missing points as zeros. |
Optional |
| Aggregation | Although the timeline requires a constant step between data points, FORECAST.ETS.SEASONALITY will aggregate multiple points which have the same time stamp. The aggregation parameter is a numeric value indicating which method will be used to aggregate several values with the same time stamp. The default value of 0 will use AVERAGE, while other options are SUM, COUNT, COUNTA, MIN, MAX, and MEDIAN. |
Optional |
Notes
FORECAST.ETS.SEASONALITY Function is added in Excel 2016.
This Function uses advanced machine learning algorithms, such as Exponential Triple Smoothing (ETS).
If a constant step cannot be identified in the provided timeline, FORECAST.ETS.SEASONALITY returns the #NUM! error.
If timeline contains duplicate values, FORECAST.ETS.SEASONALITY returns the #VALUE! Error.
If the ranges of the timeline and values are not of same size, FORECAST.ETS.SEASONALITY returns the #N/A error.
Applicability
Excel 2016