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  2. 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. A simulation-based alternative to this approximation is the application of Monte Carlo simulations.

  3. 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 ...

  4. Taylor's theorem - Wikipedia

    en.wikipedia.org/wiki/Taylor's_theorem

    Now its Taylor series centered at z 0 converges on any disc B(z 0, r) with r < |z − z 0 |, where the same Taylor series converges at z ∈ C. Therefore, Taylor series of f centered at 0 converges on B(0, 1) and it does not converge for any z ∈ C with |z| > 1 due to the poles at i and −i.

  5. First-order second-moment method - Wikipedia

    en.wikipedia.org/wiki/First-order_second-moment...

    For the second-order approximations of the third central moment as well as for the derivation of all higher-order approximations see Appendix D of Ref. [3] Taking into account the quadratic terms of the Taylor series and the third moments of the input variables is referred to as second-order third-moment method. [4]

  6. Experimental uncertainty analysis - Wikipedia

    en.wikipedia.org/wiki/Experimental_uncertainty...

    4. The solution is to expand the function z in a second-order Taylor series; the expansion is done around the mean values of the several variables x. (Usually the expansion is done to first order; the second-order terms are needed to find the bias in the mean. Those second-order terms are usually dropped when finding the variance; see below). 5.

  7. Analytic function - Wikipedia

    en.wikipedia.org/wiki/Analytic_function

    Analytic functions of several variables have some of the same properties as analytic functions of one variable. However, especially for complex analytic functions, new and interesting phenomena show up in 2 or more complex dimensions: Zero sets of complex analytic functions in more than one variable are never discrete.

  8. Grassmann number - Wikipedia

    en.wikipedia.org/wiki/Grassmann_number

    The usage of the term "Grassmann variables" is historic; they are not variables, per se; they are better understood as the basis elements of a unital algebra. The terminology comes from the fact that a primary use is to define integrals, and that the variable of integration is Grassmann-valued, and thus, by abuse of language, is called a ...

  9. Multi-index notation - Wikipedia

    en.wikipedia.org/wiki/Multi-index_notation

    Multi-index notation is a mathematical notation that simplifies formulas used in multivariable calculus, partial differential equations and the theory of distributions, by generalising the concept of an integer index to an ordered tuple of indices.

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