Estimation of a probability with guaranteed normalized mean absolute error [PDF]
IEEE Communications Letters, 2009 The estimation of a probability p from repeated Bernoulli trials is considered in this paper. A sequential approach is followed, using a simple stopping rule. A closed-form expression and an upper bound are obtained for the mean absolute error of the unbiased estimator of p.
L. Mendo
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A note on the Mean Absolute Scaled Error [PDF]
International Journal of Forecasting, 2016 Hyndman and Koehler (2006) recommend that the Mean Absolute Scaled Error (MASE) should become the standard when comparing forecast accuracies. This note supports their claim by showing that the MASE fits nicely within the standard statistical procedures initiated by Diebold and Mariano (1995) for testing equal forecast accuracies.
P. Franses
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Forecasting Error Calculation with Mean Absolute Deviation and Mean Absolute Percentage Error
Journal of Physics: Conference Series, 2017 Prediction using a forecasting method is one of the most important things for an organization, the selection of appropriate forecasting methods is also important but the percentage error of a method is more important in order for decision makers to adopt the right culture, the use of the Mean Absolute Deviation and Mean Absolute Percentage Error to ...
Ummul Khair +3 more
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Forecast Error Calculation with Mean Squared Error (MSE) and Mean Absolute Percentage Error (MAPE)
JINAV: Journal of Information and Visualization, 2020 Calculation errors in forecasting a data are very important from a forecasting process. The high level of forecasting accuracy will affect the level of confidence in forecasting decision making.
A. Ahmar
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Dynamic mean absolute error as new measure for assessing forecasting errors
Energy Conversion and Management, 2018 Accurate wind power forecast is essential for grid integration, system planning, and electricity trading in certain electricity markets. Therefore, analyzing prediction errors is a critical task that allows a comparison of prediction models and the selection of the most suitable model.
Frías Paredes, Laura +3 more
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Using the Mean Absolute Percentage Error for Regression Models [PDF]
, 2015 We study in this paper the consequences of using the Mean Absolute Percentage Error (MAPE) as a measure of quality for regression models. We show that finding the best model under the MAPE is equivalent to doing weighted Mean Absolute Error (MAE) regression.
de Myttenaere, Arnaud +3 more
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Case study in evaluating time series prediction models using the relative mean absolute error. [PDF]
Am Stat, 2016 Reich NG +5 more
europepmc +2 more sources
IOP Conference Series: Materials Science and Engineering, 2018 Most existing Collaborative Filtering (CF) algorithms predict a rating as the preference of an active user toward a given item, which is always a decimal fraction. Meanwhile, the actual ratings in most data sets are integers. In this paper, we discuss and demonstrate why rounding can bring different influences to these two metrics; prove that rounding ...
Weijie Wang, Yanmin Lu
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Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance [PDF]
, 2005 C. Willmott, K. Matsuura
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Empirical risk minimization is consistent with the mean absolute percentage error [PDF]
, 2015 We study in this paper the consequences of using the Mean Absolute Percentage Error (MAPE) as a measure of quality for regression models. We show that finding the best model under the MAPE is equivalent to doing weighted Mean Absolute Error (MAE) regression.
de Myttenaere, Arnaud +2 more
openaire +4 more sources