FORECAST.ETS.CONFINT Function

Description

The FORECAST.ETS.CONFINT function returns a confidence interval for the forecast value at the specified target date.

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

Syntax

FORECAST.ETS.CONFINT (target_date, values, timeline, 
[confidence_level], [seasonality], [data_completion], [aggregation])

Arguments

Argument	Description	Required/ Optional
Target_date	The data point for which you want to predict a value. Target date can be date/time or numeric.	Required
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.CONFINT supports up to 30% missing data, and will automatically adjust for it. The timeline is not required to be sorted, as FORECAST.ETS.CONFINT will sort it implicitly for calculations.	Required
Confidence_level	A numerical value between 0 and 1 (exclusive), indicating a confidence_level for the calculated confidence interval. For example, for a 90% confidence interval, a 90% confidence level will be computed (90% of future points are to fall within this radius from prediction). The default value is 95%.	Optional
Seasonality	A numeric value. The default value of 1 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 will indicate to the algorithm to use patterns of this length as the seasonality. Maximum supported seasonality is 8,760 (number of hours in a year.	Optional
Data_completion	FORECAST.ETS.CONFINT 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.CONFINT 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.CONFINT Function is added in Excel 2016.
This Function uses advanced machine learning algorithms, such as Exponential Triple Smoothing (ETS).
If the target date is chronologically before the end of the historical timeline, FORECAST.ETS.CONFINT returns the #NUM! error.
If a constant step cannot be identified in the provided timeline, FORECAST.ETS.CONFINT returns the #NUM! error.
If timeline contains duplicate values, FORECAST.ETS.CONFINT returns the #VALUE! Error.
If the ranges of the timeline and values are not of same size, FORECAST.ETS.CONFINT returns the #N/A error.
If the Confidence level is outside the range (0,1), FORECAST.ETS.CONFINT returns the #NUM! error.
If the Seasonality is <0, or >8760, or a non-numeric value, FORECAST.ETS.CONFINT returns the #NUM! error.

Applicability

Excel 2016

advanced_excel_statistical_functions.htm