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  2. 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 ...

  3. Approximation error - Wikipedia

    en.wikipedia.org/wiki/Approximation_error

    Best rational approximants for π (green circle), e (blue diamond), ϕ (pink oblong), (√3)/2 (grey hexagon), 1/√2 (red octagon) and 1/√3 (orange triangle) calculated from their continued fraction expansions, plotted as slopes y/x with errors from their true values (black dashes)

  4. Mean absolute error - Wikipedia

    en.wikipedia.org/wiki/Mean_absolute_error

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  5. Condition number - Wikipedia

    en.wikipedia.org/wiki/Condition_number

    Condition numbers can also be defined for nonlinear functions, and can be computed using calculus.The condition number varies with the point; in some cases one can use the maximum (or supremum) condition number over the domain of the function or domain of the question as an overall condition number, while in other cases the condition number at a particular point is of more interest.

  6. Mean absolute percentage error - Wikipedia

    en.wikipedia.org/wiki/Mean_absolute_percentage_error

    It is a variant of MAPE in which the mean absolute percent errors is treated as a weighted arithmetic mean. Most commonly the absolute percent errors are weighted by the actuals (e.g. in case of sales forecasting, errors are weighted by sales volume). [3] Effectively, this overcomes the 'infinite error' issue. [4]

  7. Mean absolute scaled error - Wikipedia

    en.wikipedia.org/wiki/Mean_absolute_scaled_error

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  8. Symmetric mean absolute percentage error - Wikipedia

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

    The absolute difference between A t and F t is divided by half the sum of absolute values of the actual value A t and the forecast value F t. The value of this calculation is summed for every fitted point t and divided again by the number of fitted points n.

  9. Error function - Wikipedia

    en.wikipedia.org/wiki/Error_function

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