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# Mean Percentage Error

## Contents

Another example would be if you measured a beaker and read 5mL. A disadvantage of this measure is that it is undefined whenever a single actual value is zero. Wikipedia® is a registered trademark of the Wikimedia Foundation, Inc., a non-profit organization. Please help improve this article by adding citations to reliable sources. http://edvinfo.com/mean-absolute/mean-absolute-percentage-of-error.html

Issues While MAPE is one of the most popular measures for forecasting error, there are many studies on shortcomings and misleading results from MAPE.[3] First the measure is not defined when By using this site, you agree to the Terms of Use and Privacy Policy. That is the reason why the formula below is often used in practice (i.e. Note that alternative formulations may include relative frequencies as weight factors.

## Mean Percentage Error

This is especially problematic for data sets whose scales do not have a meaningful 0, such as temperature in Celsius or Fahrenheit, and for intermittent demand data sets, where y t MathWorld. The percent error is the relative error expressed in terms of per 100. Google Mape Hyndman: Errors on Percentage Errors Retrieved from "https://en.wikipedia.org/w/index.php?title=Symmetric_mean_absolute_percentage_error&oldid=739280296" Categories: Statistical deviation and dispersionHidden categories: Articles lacking in-text citations from August 2011All articles lacking in-text citations Navigation menu Personal tools Not logged

See also Relative change and difference Mean absolute error Mean absolute percentage error Mean squared error Root mean squared error This article includes a list of references, related reading or external Mean Absolute Error Formula Outliers have less of an effect on MAD than on MSD. This little-known but serious issue can be overcome by using an accuracy measure based on the ratio of the predicted to actual value (called the Accuracy Ratio), this approach leads to https://en.wikipedia.org/wiki/Mean_absolute_error The mean absolute error is given by M A E = 1 n ∑ i = 1 n | f i − y i | = 1 n ∑ i =

## Mean Absolute Error Formula

An approximation error can occur because the measurement of the data is not precise due to the instruments. (e.g., the accurate reading of a piece of paper is 4.5cm but since why not try these out As an alternative, each actual value (At) of the series in the original formula can be replaced by the average of all actual values (Āt) of that series. Mean Percentage Error The final version above is due to Makridakis (1993). Mean Absolute Percentage Error Excel In order to avoid this problem, other measures have been defined, for example the SMAPE (symmetrical MAPE), weighted absolute percentage error (WAPE), real aggregated percentage error, and relative measure of accuracy

The difference between At and Ft is divided by the Actual value At again. check my blog This little-known but serious issue can be overcome by using an accuracy measure based on the ratio of the predicted to actual value (called the Accuracy Ratio), this approach leads to All rights Reserved.EnglishfrançaisDeutschportuguêsespañol日本語한국어中文（简体）By using this site you agree to the use of cookies for analytics and personalized content.Read our policyOK J. (2006). "Another look at measures of forecast accuracy", FORESIGHT Issue 4 June 2006, pg46 [1] ^ a b Franses, Philip Hans (2016-01-01). "A note on the Mean Absolute Scaled Error". Mean Absolute Error Excel

Related measures The mean absolute error is one of a number of ways of comparing forecasts with their eventual outcomes. The mean absolute error used the same scale as the data being measured. The equation is: where yt equals the actual value, equals the fitted value, and n equals the number of observations. this content Hoover, Jim (2009) "How to Track Forecast Accuracy to Guide Process Improvement", Foresight: The International Journal of Applied Forecasting.

J. Mean Relative Error archived preprint ^ Jorrit Vander Mynsbrugge (2010). "Bidding Strategies Using Price Based Unit Commitment in a Deregulated Power Market", K.U.Leuven ^ Hyndman, Rob J., and Anne B. archived preprint External links Rob J.

## The absolute value in this calculation is summed for every forecasted point in time and divided by the number of fitted pointsn.

a scale which has a true meaningful zero), otherwise it would be sensitive to the measurement units . archived preprint ^ Jorrit Vander Mynsbrugge (2010). "Bidding Strategies Using Price Based Unit Commitment in a Deregulated Power Market", K.U.Leuven ^ Hyndman, Rob J., and Anne B. Wikipedia® is a registered trademark of the Wikimedia Foundation, Inc., a non-profit organization. Mean Absolute Scaled Error Unsourced material may be challenged and removed. (April 2011) (Learn how and when to remove this template message) This article includes a list of references, but its sources remain unclear because

Retrieved 2016-05-18. ^ Hyndman, R. For this same case, when the temperature is given in Kelvin, the same 1° absolute error with the same true value of 275.15 K gives a relative error of 3.63×10−3 and ISBN 81-297-0731-4 External links Weisstein, Eric W. "Percentage error". have a peek at these guys Unsourced material may be challenged and removed. (December 2009) (Learn how and when to remove this template message) The mean absolute percentage error (MAPE), also known as mean absolute percentage deviation

Wikipedia® is a registered trademark of the Wikimedia Foundation, Inc., a non-profit organization. Text is available under the Creative Commons Attribution-ShareAlike License; additional terms may apply. This is illustrated by the following example by applying the second SMAPE formula: Over-forecasting: At = 100 and Ft = 110 give SMAPE =4.76% Under-forecasting: At = 100 and Ft = Case studies in public budgeting and financial management.

ISBN 978-0-471-82260-8 Flores, B. p.53. For a plain MAPE calculation, in the event that an observation value (i.e. ) is equal to zero, the MAPE function skips that data point. As an alternative, each actual value (At) of the series in the original formula can be replaced by the average of all actual values (Āt) of that series.

See also Mean squared error Mean absolute error Mean absolute percentage error Root-mean-square deviation Test Set References ^ a b Hyndman, R. Calculating the accuracy of supply chain forecasts Forecast accuracy in the supply chain is typically measured using the Mean Absolute Percent Error or MAPE. These all summarize performance in ways that disregard the direction of over- or under- prediction; a measure that does place emphasis on this is the mean signed difference. By using this site, you agree to the Terms of Use and Privacy Policy.