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  2. 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 ...

  3. Mean absolute percentage error - Wikipedia

    en.wikipedia.org/wiki/Mean_absolute_percentage_error

    It is a measure used to evaluate the performance of regression or forecasting models. It is a variant of MAPE in which the mean absolute percent errors is treated as a weighted arithmetic mean. Most commonly the absolute percent errors are weighted by the actuals (e.g. in case of sales forecasting, errors are weighted by sales volume). [3]

  4. Mean absolute scaled error - Wikipedia

    en.wikipedia.org/wiki/Mean_absolute_scaled_error

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  5. Forecasting - Wikipedia

    en.wikipedia.org/wiki/Forecasting

    Forecasting is the process of making predictions based on past and present data. Later these can be compared (resolved) against what happens. For example, a company might estimate their revenue in the next year, then compare it against the actual results creating a variance actual analysis. Prediction is a similar but more general term.

  6. Forecast bias - Wikipedia

    en.wikipedia.org/wiki/Forecast_bias

    A typical measure of bias of forecasting procedure is the arithmetic mean or expected value of the forecast errors, but other measures of bias are possible. For example, a median-unbiased forecast would be one where half of the forecasts are too low and half too high: see Bias of an estimator .

  7. 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.

  8. Symmetric mean absolute percentage error - Wikipedia

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

    One supposed problem with SMAPE is that it is not symmetric since over- and under-forecasts are not treated equally. This is illustrated by the following example by applying the second SMAPE formula: Over-forecasting: A t = 100 and F t = 110 give SMAPE = 4.76%; Under-forecasting: A t = 100 and F t = 90 give SMAPE = 5.26%.

  9. Economic forecasting - Wikipedia

    en.wikipedia.org/wiki/Economic_forecasting

    Economic forecasting is the process of making predictions about the economy. Forecasts can be carried out at a high level of aggregation—for example for GDP, inflation, unemployment or the fiscal deficit —or at a more disaggregated level, for specific sectors of the economy or even specific firms. Economic forecasting is a measure to find ...

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