Сalculates or predicts a future value based on existing (historical) values by using the AAA version of the Exponential Smoothing (ETS) algorithm.
| Name | Type | Description |
| arg1 | number | A date for which a new value will be predicted. Must be after the last date in the timeline. |
| arg2 | ApiRange | Array.<number> | A range or an array of numeric data that determines the historical values for which a new point will be predicted. |
| arg3 | ApiRange | A range of date/time values that correspond to the historical values. The timeline range must be of the same size as the second argument. Date/time values must have a constant step between them and can't be zero. |
| arg4 | number | An optional numeric value that specifies the length of the seasonal pattern. The default value of 1 indicates seasonality is detected automatically. The 0 value means no seasonality. |
| arg5 | number | An optional numeric value to handle missing values. The default value of 1 replaces missing values by interpolation, and 0 replaces them with zeros. |
| arg6 | Aggregation | An optional numeric value to aggregate multiple values with the same time stamp. |