MAPE (Mean Absolute Percentage Error)

The mean absolute percentage error (MAPE), also referred to as mean absolute percentage deviation (MAPD), serves as a statistical measure to assess the accuracy of a forecasting method, often employed in trend estimation within statistics and as a loss function in regression problems in Machine Learning. MAPE quantifies the magnitude of error in percentage terms, offering insight into the predictive performance of a model. It is computed as the average of the unsigned percentage errors, as demonstrated in the formula below:

Where Obs_i represents the observed value and Model_i denotes the forecast value for each data point i. The MAPE provides a standardized measure of prediction accuracy, allowing for comparisons across different forecasting models or techniques.

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Please provide the data in a two-column format (observed vs. simulated). You can copy from Excel, text, or any other format, separated by space.

Mean Absolute Percentage Error: %

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MAPE (Mean Absolute Percentage Error)