FORECAST_ETS

FORECAST_ETS(arg1, arg2, arg3, arg4, arg5, arg6) → { number }

–°alculates or predicts a future value based on existing (historical) values by using the AAA version of the Exponential Smoothing (ETS) algorithm.

Parameters:

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.

Returns:

Type
number