This function evaluates the future value based on existing values using Exponential Smoothing (ETS) algorithm.
FORECAST.ETS(target_date, values, timeline, [seasonality], [data_completion], [aggregation])
This function has the following arguments:
| Argument | Description |
|---|---|
| target_date | Refers to the numeric data specifying the date to predict the value. |
| values | Refers to the numeric data (array) specifying the historical values to forecast the value for. |
| timeline | Refers to the numeric data (range,or array) specifying dates for the values. |
| seasonality | [Optional] Refers to the numeric data specifying the length of the season, or number of date periods. |
| data_completion | [Optional] Refers to the numeric data specifying how the algorithm should handle missing points in the timeline. |
| aggregation | [Optional] Refers to the numeric data specifying how the algorithm should aggregate values that have the same timestamp. |
Accepts numeric values.
This function is available in product version 11.0 or later.