# FORECAST.ETS.CONFINT

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## Content



This function returns a confidence interval for the forecast value at the specified target date. 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

The function has the following arguments:

| **Argument** | **Description** |
| -------- | ----------- |
| *target\_date* | [Required] is a date for which you want to predict a new value. Must be after the last date in the timeline. |
| *values* | [Required] is a range of the historical values for which you want to predict a new point. |
| *timeline* | [Required] is a range of date/time values that correspond to the historical values. The timeline range must be of the same size as the values range. Date/time values must have a constant step between them. |
| *confidence\_level* | [Optional] is a numeric value between 0 and 1 (exclusive) that specifies the confidence level for the calculated confidence interval. If it is omitted, the default value of 0.95 is used. |
| *seasonality* | [Optional] is a numeric value that specifies which method should be used to detect the seasonality. The possible values are listed in the table below. \* **1 or omitted**: Seasonality is detected automatically. Positive, whole numbers are used for the length of the seasonal pattern. \* **0:** No seasonality, the prediction will be linear. \* **an integer greater than or equal to 2:** The specified number is used for the length of the seasonal pattern. |
| *data\_completion* | [Optional] is a numeric value that specifies how to process the missing data points in the timeline data range. The possible values are listed below. \* **1 or omitted**: Missing points are calculated as the average of the neighboring points. \* **0:** Missing points are treated as zero values. |
| *aggregation* | [Optional] is a numeric value that specifies which function should be used to aggregate identical time values in the timeline data range. The possible values are listed below. |

### Aggregation values

| **Value** | **Description** |
| ----- | ----------- |
| 1 or omitted | AVERAGE |
| 2 | COUNT |
| 3 | COUNTA |
| 4 | MAX |
| 5 | MEDIAN |
| 6 | MIN |
| 7 | SUM |

## Remarks

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).

## Data Types

Returns a specified statistical value relating to a time series.

## Examples

![](https://cdn.mescius.io/document-site-files/images/0ed25d3e-6b2a-4cf0-8f1b-7ed5ab18cf12/images/forecast-ets-confint.png)

## Version Available

This function is available in product version 16.0 or later.