Symmetric Mean Absolute Percentage Error Calculator
Calculates a denominator-symmetric percentage error for paired actual and forecast values. The worked condition keeps the method and source values visible for an independent check.
Supply the comparison values during an independent check
Symmetric mean absolute percentage error
The boundary of the claim when the result is reused
sMAPE still depends on the chosen convention and becomes undefined when both actual and forecast are zero. Outliers, dependence, extrapolation, seasonality, or a mismatched convention can change the appropriate method. The page-specific quantity is symmetric mean absolute percentage error.
Choose an alternative because the design or data require it, not because its result is more favorable. Preserve the selected convention in the report. The chosen symmetric mean absolute percentage error convention remains attached to the source record. Before reusing this result, write down the observed scale, model boundary, and convention behind the displayed value. That record separates a changed dataset from a changed definition and gives the next analyst a clear route back to the original calculation.
A second look at the condition in the worked condition in this example
Save the entered values, units, formula version, exclusions, and unrounded output with symmetric mean absolute percentage error. A copied number without its condition is not reproducible.
Round after downstream calculations are complete. Extra digits cannot repair a biased sample, unstable fit, or unsupported distributional assumption. The chosen symmetric mean absolute percentage error convention remains attached to the source record. Before reusing this result, write down the observed scale, model boundary, and convention behind the displayed value. That record separates a changed dataset from a changed definition and gives the next analyst a clear route back to the original calculation.
Before changing the method, review mean absolute percentage error, root mean squared forecast error, mean absolute scaled error, and mean forecast error.
A direct numerical check before reporting
Construct a second plausible scenario that changes one uncertain input while keeping the rest coherent. Compare the statistic and practical interpretation across both cases. The page-specific quantity is symmetric mean absolute percentage error.
If a small defensible change reverses the conclusion, report the sensitivity rather than hiding it behind one preferred scenario. The chosen symmetric mean absolute percentage error convention remains attached to the source record.
A note on convention under the stated model
Calculates a denominator-symmetric percentage error for paired actual and forecast values. The displayed relationship is mean(2|a−f|/(|a|+|f|))×100, and each symbol is tied to a labeled field. The page-specific quantity is symmetric mean absolute percentage error.
The example sMAPE is approximately 5.5059%. This example is a numerical check, not proof that the model describes every dataset. The chosen symmetric mean absolute percentage error convention remains attached to the source record.
The quantity this page defines when the sample changes
sMAPE still depends on the chosen convention and becomes undefined when both actual and forecast are zero. The page-specific quantity is symmetric mean absolute percentage error.
The unit of analysis, time order, sample boundary, and treatment of ties or missing values remain outside the answer unless they are entered. Keep those choices beside this time-series result. The chosen symmetric mean absolute percentage error convention remains attached to the source record.
Where the method applies during an independent review
Check scales and domains before evaluating symmetric mean absolute percentage error. Counts, probabilities, rates, windows, and squared units are not interchangeable merely because a field accepts a number.
If one input changes, predict the direction of the result from the formula first. That catches reversed groups, invalid windows, and parameterization errors. The chosen symmetric mean absolute percentage error convention remains attached to the source record.
Keeping a reproducible record at the chosen parameters
Recalculate one intermediate quantity from mean(2|a−f|/(|a|+|f|))×100 and work back from the displayed answer. The source values should be enough for another analyst to reproduce symmetric mean absolute percentage error.
Use a boundary case when possible: equal values, a probability near zero, a window of two, or a rate of zero. Expected limiting behavior is often more informative than another decimal place. The chosen symmetric mean absolute percentage error convention remains attached to the source record.
Questions about interpretation during an independent check
When the parameterization changes, what belongs in the saved record?
Preserve the source data, formula convention, units, exclusions, and method version. The reported quantity here is symmetric mean absolute percentage error.
While checking the boundary, what should be checked before reusing this result for this calculation?
Keep the inputs, units, method name, exclusions, and unrounded output together. The reported quantity here is symmetric mean absolute percentage error.
For a new sample, why might another program return a different number for this calculation?
Parameterization, interpolation, tie rules, window placement, and rounding can differ. The reported quantity here is symmetric mean absolute percentage error.