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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. First-order second-moment method - Wikipedia

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

    In engineering practice, the objective function often is not given as analytic expression, but for instance as a result of a finite-element simulation. Then the derivatives of the objective function need to be estimated by the central differences method. The number of evaluations of the objective function equals +. Depending on the number of ...

  4. Taylor series - Wikipedia

    en.wikipedia.org/wiki/Taylor_series

    In mathematics, the Taylor series or Taylor expansion of a function is an infinite sum of terms that are expressed in terms of the function's derivatives at a single point. For most common functions, the function and the sum of its Taylor series are equal near this point. Taylor series are named after Brook Taylor, who introduced them in 1715.

  5. Numerical methods for ordinary differential equations - Wikipedia

    en.wikipedia.org/wiki/Numerical_methods_for...

    where is a function : [,), and the initial condition is a given vector. First-order means that only the first derivative of y appears in the equation, and higher derivatives are absent. Without loss of generality to higher-order systems, we restrict ourselves to first-order differential equations, because a higher-order ODE can be converted ...

  6. Algebra of random variables - Wikipedia

    en.wikipedia.org/wiki/Algebra_of_random_variables

    Similarly for normal random variables, it is also possible to approximate the variance of the non-linear function as a Taylor series expansion as: V a r [ f ( X ) ] ≈ ∑ n = 1 n m a x ( σ n n ! ( d n f d X n ) X = μ ) 2 V a r [ Z n ] + ∑ n = 1 n m a x ∑ m ≠ n σ n + m n ! m !

  7. Numerical differentiation - Wikipedia

    en.wikipedia.org/wiki/Numerical_differentiation

    This formula can be obtained by Taylor series expansion: (+) = + ′ ()! ″ ()! () +. The complex-step derivative formula is only valid for calculating first-order derivatives. A generalization of the above for calculating derivatives of any order employs multicomplex numbers , resulting in multicomplex derivatives.

  8. Puzzle solutions for Saturday, Nov. 30, 2024

    www.aol.com/news/puzzle-solutions-saturday-nov...

    fancy, lavish event that steaks and hamburgers attend if they feel like dancing: meat balls. (distributed by king features) other puzzles boggle. oman mali poland brazil bolivia

  9. Taylor's theorem - Wikipedia

    en.wikipedia.org/wiki/Taylor's_theorem

    For a smooth function, the Taylor polynomial is the truncation at the order of the Taylor series of the function. The first-order Taylor polynomial is the linear approximation of the function, and the second-order Taylor polynomial is often referred to as the quadratic approximation. [1] There are several versions of Taylor's theorem, some ...