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WorksheetFunction.Forecast_ETS_ConfInt method (Excel)

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Returns a confidence interval for the forecast value at the specified target date.

Syntax

expression.Forecast_ETS_ConfInt (Arg1, Arg2, Arg3, Arg4, Arg5, Arg6, Arg7)

expression A variable that represents a WorksheetFunction object.

Parameters

Name Required/Optional Data type Description
Arg1 Required Double Target Date: the data point for which you want to predict a value. Target date can be date/time or numeric. See Remarks.
Arg2 Required Variant Values: the historical values, for which you want to forecast the next points.
Arg3 Required Variant Timeline: the independent array or range of dates or numeric data. The values in the timeline must have a consistent step between them and can't be zero. See Remarks.
Arg4 Optional Variant Confidence level: A numerical value between 0 and 1 (exclusive), indicating a confidence level for the calculated confidence interval. See Remarks.
Arg5 Optional Variant Seasonality: A numeric value. See Remarks.
Arg6 Optional Variant Data completions: Although the timeline requires a constant step between data points, Forecast_ETS_ConfInt supports up to 30% missing data, and automatically adjusts for it. See Remarks.
Arg7 Optional Variant Aggregation: Although the timeline requires a constant step between data points, Forecast_ETS_ConfInt aggregates multiple points that have the same time stamp. See Remarks.

Return value

Double

Remarks

It'sn't necessary to sort the timeline (Arg3), because Forecast_ETS_ConfInt sorts it implicitly for calculations. If Forecast_ETS_ConfInt can't identify a constant step in the timeline, it returns run-time error 1004. If the timeline contains duplicate values, Forecast_ETS_ConfInt also returns an error. If the ranges of the timeline and values aren't all of the same size, Forecast_ETS_ConfInt returns run-time error 1004.

A confidence interval (Arg4) of 95% means that 95% of future points are expected to fall within this radius from the result that Forecast_ETS forecasted (with normal distribution). Using confidence intervals can help you grasp the accuracy of the predicted model. A smaller interval implies more confidence in the prediction for this specific point.

For example, for a 90% confidence interval, a 90% confidence level is computed (90% of future points are to fall within this radius from prediction). The default value is 95%. For numbers outside of the range (0,1), Forecast_ETS_ConfInt returns an error.

The default value of 1 for seasonality (Arg5) means Excel detects seasonality automatically for the forecast and uses positive, whole numbers for the length of the seasonal pattern. 0 indicates no seasonality, meaning the prediction will be linear. Positive whole numbers indicate to the algorithm to use patterns of this length as the seasonality. For any other value, Forecast_ETS_ConfInt returns an error. Maximum supported seasonality is 8,760 (the number of hours in a year). Any seasonality value above that number results in an error.

Passing 0 for the data completions parameter (Arg6) instructs the algorithm to account for missing points as zeros. The default value of 1 accounts for missing points by computing them to be the average of the neighboring points. If there is more than 30% missing data, Forecast_ETS_ConfInt returns run-time error 1004.

The aggregation parameter (Arg7) is a numeric value specifying the method to use to aggregate several values that have the same time stamp. The default value of 0 specifies AVERAGE, while other numbers between 1 and 6 specify SUM, COUNT, COUNTA, MIN, MAX, and MEDIAN.

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