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14 relations: Demand forecasting, Errors and residuals, Forecast bias, Forecasting, Mean absolute percentage error, Mean percentage error, Mean squared error, Mean squared prediction error, Optimism bias, Reference class forecasting, Root-mean-square deviation, Statistics, Time series, Tracking signal.
Demand forecasting
Demand forecasting is the art and science of forecasting customer demand to optimize supply decisions by corporate supply chain and business management.
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Errors and residuals
In statistics and optimization, errors and residuals are two closely related and easily confused measures of the deviation of an observed value of an element of a statistical sample from its "theoretical value".
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Forecast bias
A forecast bias occurs when there are consistent differences between actual outcomes and previously generated forecasts of those quantities; that is: forecasts may have a general tendency to be too high or too low.
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Forecasting
Forecasting is the process of making predictions of the future based on past and present data and most commonly by analysis of trends.
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Mean absolute percentage error
The mean absolute percentage error (MAPE), also known as mean absolute percentage deviation (MAPD), is a measure of prediction accuracy of a forecasting method in statistics, for example in trend estimation.
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Mean percentage error
In statistics, the mean percentage error (MPE) is the computed average of percentage errors by which forecasts of a model differ from actual values of the quantity being forecast.
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Mean squared error
In statistics, the mean squared error (MSE) or mean squared deviation (MSD) of an estimator (of a procedure for estimating an unobserved quantity) measures the average of the squares of the errors—that is, the average squared difference between the estimated values and what is estimated.
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Mean squared prediction error
In statistics the mean squared prediction error or mean squared error of the predictions of a smoothing or curve fitting procedure is the expected value of the squared difference between the fitted values implied by the predictive function \widehat and the values of the (unobservable) function g. It is an inverse measure of the explanatory power of \widehat, and can be used in the process of cross-validation of an estimated model.
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Optimism bias
Optimism bias (also known as unrealistic or comparative optimism) is a cognitive bias that causes a person to believe that they are at a lesser risk of experiencing a negative event compared to others.
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Reference class forecasting
Reference class forecasting or comparison class forecasting is a method of predicting the future by looking at similar past situations and their outcomes.
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Root-mean-square deviation
The root-mean-square deviation (RMSD) or root-mean-square error (RMSE) (or sometimes root-mean-squared error) is a frequently used measure of the differences between values (sample or population values) predicted by a model or an estimator and the values observed.
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Statistics
Statistics is a branch of mathematics dealing with the collection, analysis, interpretation, presentation, and organization of data.
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Time series
A time series is a series of data points indexed (or listed or graphed) in time order.
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Tracking signal
In statistics and management science, a tracking signal monitors any forecasts that have been made in comparison with actuals, and warns when there are unexpected departures of the outcomes from the forecasts.
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