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  2. Mean absolute scaled error - Wikipedia

    en.wikipedia.org/wiki/Mean_absolute_scaled_error

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  3. Mean absolute percentage error - Wikipedia

    en.wikipedia.org/wiki/Mean_absolute_percentage_error

    This little-known but serious issue can be overcome by using an accuracy measure based on the logarithm of the accuracy ratio (the ratio of the predicted to actual value), given by ⁡ (). This approach leads to superior statistical properties and also leads to predictions which can be interpreted in terms of the geometric mean.

  4. Symmetric mean absolute percentage error - Wikipedia

    en.wikipedia.org/wiki/Symmetric_mean_absolute...

    where A t is the actual value and F t is the forecast value. The absolute difference between A t and F t is divided by half the sum of absolute values of the actual value A t and the forecast value F t. The value of this calculation is summed for every fitted point t and divided again by the number of fitted points n.

  5. Demand forecasting - Wikipedia

    en.wikipedia.org/wiki/Demand_forecasting

    Calculating demand forecast accuracy is the process of determining the accuracy of forecasts made regarding customer demand for a product. [13] [14] Understanding and predicting customer demand is vital to manufacturers and distributors to avoid stock-outs and to maintain adequate inventory levels. While forecasts are never perfect, they are ...

  6. Nash–Sutcliffe model efficiency coefficient - Wikipedia

    en.wikipedia.org/wiki/Nash–Sutcliffe_model...

    Nash–Sutcliffe model efficiency coefficient. The Nash–Sutcliffe model efficiency coefficient (NSE) is used to assess the predictive skill of hydrological models. It is defined as: where is the mean of observed discharges, and is modeled discharge. is observed discharge at time t. [1]

  7. Root mean square deviation - Wikipedia

    en.wikipedia.org/wiki/Root_mean_square_deviation

    The RMSD serves to aggregate the magnitudes of the errors in predictions for various data points into a single measure of predictive power. RMSD is a measure of accuracy, to compare forecasting errors of different models for a particular dataset and not between datasets, as it is scale-dependent. [1]

  8. Forecast error - Wikipedia

    en.wikipedia.org/wiki/Forecast_error

    If a main application of the forecast is to predict when certain thresholds will be crossed, one possible way of assessing the forecast is to use the timing-error—the difference in time between when the outcome crosses the threshold and when the forecast does so.

  9. Linear trend estimation - Wikipedia

    en.wikipedia.org/wiki/Linear_trend_estimation

    Linear trend estimation is a statistical technique used to analyze data patterns. Data patterns, or trends, occur when the information gathered, tends to increase or decrease over time, or is influenced by changes in an external factor. Linear trend estimation essentially creates a straight line on a graph of data that models the general ...