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  2. Error function - Wikipedia

    en.wikipedia.org/wiki/Error_function

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  3. 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 ...

  4. Loss function - Wikipedia

    en.wikipedia.org/wiki/Loss_function

    In many applications, objective functions, including loss functions as a particular case, are determined by the problem formulation. In other situations, the decision maker’s preference must be elicited and represented by a scalar-valued function (called also utility function) in a form suitable for optimization — the problem that Ragnar Frisch has highlighted in his Nobel Prize lecture. [4]

  5. Special functions - Wikipedia

    en.wikipedia.org/wiki/Special_functions

    Many special functions appear as solutions of differential equations or integrals of elementary functions.Therefore, tables of integrals [1] usually include descriptions of special functions, and tables of special functions [2] include most important integrals; at least, the integral representation of special functions.

  6. Confusion matrix - Wikipedia

    en.wikipedia.org/wiki/Confusion_matrix

    In predictive analytics, a table of confusion (sometimes also called a confusion matrix) is a table with two rows and two columns that reports the number of true positives, false negatives, false positives, and true negatives. This allows more detailed analysis than simply observing the proportion of correct classifications (accuracy).

  7. Romberg's method - Wikipedia

    en.wikipedia.org/wiki/Romberg's_method

    Free online integration tool using Romberg, Fox–Romberg, Gauss–Legendre and other numerical methods SciPy implementation of Romberg's method Romberg.jl — Julia implementation (supporting arbitrary factorizations, not just 2 n + 1 {\displaystyle 2^{n}+1} points)

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  9. Errors and residuals - Wikipedia

    en.wikipedia.org/wiki/Errors_and_residuals

    It is remarkable that the sum of squares of the residuals and the sample mean can be shown to be independent of each other, using, e.g. Basu's theorem.That fact, and the normal and chi-squared distributions given above form the basis of calculations involving the t-statistic: