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Smape vs mape4/4/2023 ![]() ![]() The parameters are thus adapted to the historic data, and reflect any of its peculiarities. This is due to the fact that the parameters of a statistical model are selected to minimize the fitted error over the historic data. Within-sample statistics and confidence limits provide some insight into expected accuracy however, they almost always underestimate the actual (out-of-sample) forecasting error. ![]() To use a forecast effectively you need an understanding of the expected accuracy. Tracking accuracy provides insight into expected performance.Ī forecast is more than a number. This knowledge allows them to focus their time and attention on the items where the adjustments are adding value.Ģ. Organizations that track the accuracy of both the statistical and adjusted forecasts learn where the adjustments improve the forecasts and where they make them worse. Doing so requires knowing what is working and what is not.įor example, many organizations generate baseline forecasts using statistical approaches and then make judgmental adjustments to them to capture their knowledge of future events. Your forecasting team should be constantly striving to improve the forecasting process and forecast accuracy. Improving your forecasting process requires the ability to track accuracy.įorecasting should be viewed as a continuous improvement process. ![]()
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