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  2. Error function - Wikipedia

    en.wikipedia.org/wiki/Error_function

    Download QR code; Print/export Download as PDF ... Taylor series ⁡ = = + +! The ... Exponential bounds and a pure exponential approximation for the complementary ...

  3. Taylor's theorem - Wikipedia

    en.wikipedia.org/wiki/Taylor's_theorem

    The Taylor series of f converges uniformly to the zero function T f (x) = 0, which is analytic with all coefficients equal to zero. The function f is unequal to this Taylor series, and hence non-analytic. For any order k ∈ N and radius r > 0 there exists M k,r > 0 satisfying the remainder bound above.

  4. Taylor expansions for the moments of functions of random ...

    en.wikipedia.org/wiki/Taylor_expansions_for_the...

    In probability theory, it is possible to approximate the moments of a function f of a random variable X using Taylor expansions, provided that f is sufficiently differentiable and that the moments of X are finite.

  5. Taylor series - Wikipedia

    en.wikipedia.org/wiki/Taylor_series

    That is, the Taylor series diverges at x if the distance between x and b is larger than the radius of convergence. The Taylor series can be used to calculate the value of an entire function at every point, if the value of the function, and of all of its derivatives, are known at a single point. Uses of the Taylor series for analytic functions ...

  6. Delta method - Wikipedia

    en.wikipedia.org/wiki/Delta_method

    The intuition of the delta method is that any such g function, in a "small enough" range of the function, can be approximated via a first order Taylor series (which is basically a linear function). If the random variable is roughly normal then a linear transformation of it is also normal. Small range can be achieved when approximating the ...

  7. 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 ...

  8. Runge's phenomenon - Wikipedia

    en.wikipedia.org/wiki/Runge's_phenomenon

    The Weierstrass approximation theorem states that for every continuous function f(x) defined on an interval [a,b], there exists a set of polynomial functions P n (x) for n=0, 1, 2, ..., each of degree at most n, that approximates f(x) with uniform convergence over [a,b] as n tends to infinity, that is,

  9. Universal approximation theorem - Wikipedia

    en.wikipedia.org/wiki/Universal_approximation...

    For the algorithm and the corresponding computer code see. [14] The theoretical result can be formulated as follows. Universal approximation theorem: [ 14 ] [ 15 ] — Let [ a , b ] {\displaystyle [a,b]} be a finite segment of the real line, s = b − a {\displaystyle s=b-a} and λ {\displaystyle \lambda } be any positive number.