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  2. Relative change - Wikipedia

    en.wikipedia.org/wiki/Relative_change

    A percentage change is a way to express a change in a variable. It represents the relative change between the old value and the new one. [6]For example, if a house is worth $100,000 today and the year after its value goes up to $110,000, the percentage change of its value can be expressed as = = %.

  3. Symmetric mean absolute percentage error - Wikipedia

    en.wikipedia.org/wiki/Symmetric_mean_absolute...

    The earliest reference to a similar formula appears to be Armstrong (1985, p. 348), where it is called "adjusted MAPE" and is defined without the absolute values in the denominator. It was later discussed, modified, and re-proposed by Flores (1986).

  4. Mean absolute percentage error - Wikipedia

    en.wikipedia.org/wiki/Mean_absolute_percentage_error

    It cannot be used if there are zero or close-to-zero values (which sometimes happens, for example in demand data) because there would be a division by zero or values of MAPE tending to infinity. [ 8 ]

  5. Mean percentage error - Wikipedia

    en.wikipedia.org/wiki/Mean_percentage_error

    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 measure of the bias in the forecasts. A disadvantage of this measure is that it is undefined whenever a single actual value is zero.

  6. Propagation of uncertainty - Wikipedia

    en.wikipedia.org/wiki/Propagation_of_uncertainty

    Any non-linear differentiable function, (,), of two variables, and , can be expanded as + +. If we take the variance on both sides and use the formula [11] for the variance of a linear combination of variables ⁡ (+) = ⁡ + ⁡ + ⁡ (,), then we obtain | | + | | +, where is the standard deviation of the function , is the standard deviation of , is the standard deviation of and = is the ...

  7. Least squares - Wikipedia

    en.wikipedia.org/wiki/Least_squares

    The result of fitting a set of data points with a quadratic function Conic fitting a set of points using least-squares approximation. In regression analysis, least squares is a parameter estimation method based on minimizing the sum of the squares of the residuals (a residual being the difference between an observed value and the fitted value provided by a model) made in the results of each ...

  8. Percent difference - Wikipedia

    en.wikipedia.org/?title=Percent_difference&...

    This page was last edited on 11 October 2023, at 21:06 (UTC).; Text is available under the Creative Commons Attribution-ShareAlike 4.0 License; additional terms may apply.

  9. Arc elasticity - Wikipedia

    en.wikipedia.org/wiki/Arc_elasticity

    The y arc elasticity of x is defined as: , = % % where the percentage change in going from point 1 to point 2 is usually calculated relative to the midpoint: % = (+) /; % = (+) /. The use of the midpoint arc elasticity formula (with the midpoint used for the base of the change, rather than the initial point (x 1, y 1) which is used in almost all other contexts for calculating percentages) was ...