Symmetric Mean Absolute Percentage Error Calculator
Calculates a denominator-symmetric percentage error for paired actual and forecast values. The form displays mean(2|a−f|/(|a|+|f|))×100 beside symmetric mean absolute percentage error, using a worked condition that can be recalculated with the labeled inputs.
Supply the comparison values during an independent check
Symmetric mean absolute percentage error
The question behind symmetric mean absolute percentage error
The symmetric mean absolute percentage error page calculates a denominator-symmetric percentage error for paired actual and forecast values.
Symmetric mean absolute percentage error is limited to the statistical quantity named by the result panel. The symmetric mean absolute percentage error calculation does not silently add a population, time horizon, causal direction, or decision threshold that is absent from the fields.
Reading the symmetric mean absolute percentage error fields
- Actual values: For symmetric mean absolute percentage error, the displayed actual values sequence is 12, 15, 18, 21, 24, 27. Preserve actual values order when symmetric mean absolute percentage error depends on pairing, lag, rank, or time position, and distinguish an observed zero from a missing actual values entry.
- Forecast values: For symmetric mean absolute percentage error, the displayed forecast values sequence is 13, 14, 19, 20, 25, 26. Preserve forecast values order when symmetric mean absolute percentage error depends on pairing, lag, rank, or time position, and distinguish an observed zero from a missing forecast values entry.
The entries used for symmetric mean absolute percentage error must refer to one coherent analysis condition. Combining incompatible populations, periods, or measurement definitions can produce valid symmetric mean absolute percentage error arithmetic for a nonexistent study.
Following the symmetric mean absolute percentage error relationship
For symmetric mean absolute percentage error, match every symbol in the relationship to a labeled field before substituting numbers. Symmetric mean absolute percentage error is reported in %.
While checking symmetric mean absolute percentage error, use actual values observations from one defined analysis set rather than totals copied from incompatible groups.
Worked values for symmetric mean absolute percentage error
The default symmetric mean absolute percentage error condition is Actual values = 12, 15, 18, 21, 24, 27, Forecast values = 13, 14, 19, 20, 25, 26.
The example sMAPE is approximately 5.5059%.
The live calculator reports sMAPE 5.5058706 %. Repeating one intermediate step from mean(2|a−f|/(|a|+|f|))×100 provides a fixed symmetric mean absolute percentage error reference check for later code changes.
What the symmetric mean absolute percentage error arithmetic assumes
sMAPE still depends on the chosen convention and becomes undefined when both actual and forecast are zero.
For symmetric mean absolute percentage error, time order is part of the data. For symmetric mean absolute percentage error, reordering observations, changing the forecast origin, or mixing incomplete seasonal cycles changes the statistical question.
A nearby method may answer the next question: mean absolute percentage error, root mean squared forecast error, mean absolute scaled error, and mean forecast error.
When symmetric mean absolute percentage error can mislead
When interpreting symmetric mean absolute percentage error, keep the lag, window, seasonal period, initialization rule, and forecast horizon with the result so a later calculation uses the same timeline.
As a second check for symmetric mean absolute percentage error, outliers, ties, ordering, and missing entries can affect symmetric mean absolute percentage error even when the number of observations stays unchanged.
Input and rounding traps
Before accepting symmetric mean absolute percentage error, compare every entered value with its label, unit, and allowed domain after reading the printed relationship from left to right.
For symmetric mean absolute percentage error, do not substitute zero for an unobserved value; missingness and a measured zero describe different data.
Another symmetric mean absolute percentage error failure occurs when a rounded output is reused as though it were the original measurement. Carry guard digits through calculations that depend on symmetric mean absolute percentage error, then round only the reported value.
Reporting symmetric mean absolute percentage error reproducibly
Report symmetric mean absolute percentage error using mean(2|a−f|/(|a|+|f|))×100, followed by the entered values, units, exclusions, and analysis date. Name the symmetric mean absolute percentage error population or dataset boundary instead of leaving it implicit.
Keep the full calculator output with the record, including sMAPE 5.5058706 %. A later symmetric mean absolute percentage error review can then distinguish a changed input from a different convention or software implementation.
Questions about symmetric mean absolute percentage error
Does symmetric mean absolute percentage error establish a causal or population conclusion?
No. The displayed symmetric mean absolute percentage error value is conditional on the entered data and named method. The symmetric mean absolute percentage error design, measurement process, and assumptions determine what can be concluded beyond those values.
How should symmetric mean absolute percentage error be rounded?
Keep the unrounded symmetric mean absolute percentage error for subsequent arithmetic, then report only the precision supported by the source measurements and the decision context. Extra digits in symmetric mean absolute percentage error do not correct sampling or model error.