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FORECAST.ETS.STAT Function
Summary
The FORECAST.ETS.STAT function returns specified statistical values from the underlying ETS forecast model, providing insights into model parameters, accuracy metrics, and forecast reliability for advanced time series analysis.
Syntax
FORECAST.ETS.STAT(values, timeline, statistic_type, [seasonality], [data_completion], [aggregation])Parameters
| Parameter | Type | Required | Description |
|---|---|---|---|
| values | range |
Yes | Historical data values for forecasting (numeric array or range) |
| timeline | range |
Yes | Corresponding dates/times for historical values (must be increasing) |
| statistic_type | number |
Yes | Statistic to return: 1=Alpha, 2=Beta, 3=Gamma, 4=MAE, 5=RMSE, 6=MASE, 7=MAPE |
| seasonality | number |
No | Seasonality period (auto-detected if omitted) |
| data_completion | number |
No | 1=connect gaps with zeros, 0=interpolate (default=1) |
| aggregation | number |
No | Aggregation method: 1=AVERAGE, 2=SUM, 3=COUNT, 4=COUNTA (default=1) |
Using the FORECAST.ETS.STAT Function
FORECAST.ETS.STAT extracts key statistics from the Exponential Triple Smoothing (ETS) model used by forecasting functions. This enables analysts to evaluate model fit, compare smoothing parameters, and validate forecast accuracy using industry-standard metrics like MAE, RMSE, and MASE.
Common FORECAST.ETS.STAT Examples
Get Smoothing Parameter Alpha
=FORECAST.ETS.STAT(B2:B13, A2:A13, 1)Returns the alpha smoothing parameter (1) from the ETS model fitted to monthly sales data.
Calculate Mean Absolute Error
=FORECAST.ETS.STAT(B2:B25, A2:A25, 4)Returns MAE (4) to measure average prediction error magnitude.
RMSE with Custom Seasonality
=FORECAST.ETS.STAT(sales_data, dates, 5, 12)Returns RMSE (5) for quarterly data with explicit 12-month seasonality.
Frequently Asked Questions
Common Errors and Solutions
#VALUE! error
Cause: Invalid statistic_type value or mismatched values/timeline arrays
Solution: Ensure statistic_type is 1-7 and arrays have equal length
#NUM! error
Cause: Timeline not strictly increasing or contains non-numeric values
Solution: Verify timeline dates are in ascending order
#N/A error
Cause: Insufficient data for ETS model fitting
Solution: Provide at least 2 full seasonal cycles
Notes
- Uses same ETS model as FORECAST.ETS
- Statistic types: 1=Alpha, 2=Beta, 3=Gamma, 4=MAE, 5=RMSE, 6=MASE, 7=MAPE
- MASE uses naive forecast as benchmark
- Excel auto-detects seasonality unless specified
Compatibility
Available in: Excel 2016, Excel 2019, Excel 2021, Microsoft 365
Not available in: Excel 2013, Excel 2010, Excel 2007, Excel 2003
Content last reviewed: December 9, 2025
Update frequency: As needed
Excel versions tested: Excel 2016+