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  2. Forecasting - Wikipedia

    en.wikipedia.org/wiki/Forecasting

    Forecasting can be described as predicting what the future will look like, whereas planning predicts what the future should look like. [6] There is no single right forecasting method to use. Selection of a method should be based on your objectives and your conditions (data etc.). [9] A good way to find a method is by visiting a selection tree.

  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

    When comparing forecasting methods, the method with the lowest MASE is the preferred method. Non-time series data. For non-time series data, ...

  5. Tracking signal - Wikipedia

    en.wikipedia.org/wiki/Tracking_signal

    There have also been proposed methods for adjusting the smoothing constants used in forecasting methods based on some measure of prior performance of the forecasting model. One such approach is suggested by Trigg and Leach (1967), which requires the calculation of the tracking signal.

  6. Mean percentage error - Wikipedia

    en.wikipedia.org/wiki/Mean_percentage_error

    where is the actual value of the quantity being forecast, is the forecast, and is the number of different times for which the variable is forecast. Because actual rather than absolute values of the forecast errors are used in the formula, positive and negative forecast errors can offset each other; as a result, the formula can be used as a ...

  7. 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.

  8. Bass diffusion model - Wikipedia

    en.wikipedia.org/wiki/Bass_diffusion_model

    The Bass model has been widely used in forecasting, especially new product sales forecasting and technology forecasting. Mathematically, the basic Bass diffusion is a Riccati equation with constant coefficients equivalent to Verhulst—Pearl logistic growth. In 1969, Frank Bass published his paper on a new product growth model for consumer ...

  9. Predictive modelling - Wikipedia

    en.wikipedia.org/wiki/Predictive_modelling

    Predictive modelling gives lead generators a head start by forecasting data-driven outcomes for each potential campaign. This method saves time and exposes potential blind spots to help client make smarter decisions.