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  2. Taylor's theorem - Wikipedia

    en.wikipedia.org/wiki/Taylor's_theorem

    In calculus, Taylor's theorem gives an approximation of a -times differentiable function around a given point by a polynomial of degree , called the -th-order Taylor polynomial. For a smooth function , the Taylor polynomial is the truncation at the order k {\textstyle k} of the Taylor series of the function.

  3. Taylor series - Wikipedia

    en.wikipedia.org/wiki/Taylor_series

    Taylor's theorem can be used to obtain a bound on the size of the remainder. In general, Taylor series need not be convergent at all. In fact, the set of functions with a convergent Taylor series is a meager set in the Fréchet space of smooth functions .

  4. Linear approximation - Wikipedia

    en.wikipedia.org/wiki/Linear_approximation

    Given a twice continuously differentiable function of one real variable, Taylor's theorem for the case = states that = + ′ () + where is the remainder term. The linear approximation is obtained by dropping the remainder: () + ′ ().

  5. Finite difference method - Wikipedia

    en.wikipedia.org/wiki/Finite_difference_method

    For a n-times differentiable function, by Taylor's theorem the Taylor series expansion is given as (+) = + ′ ()! + ()! + + ()! + (),. Where n! denotes the factorial of n, and R n (x) is a remainder term, denoting the difference between the Taylor polynomial of degree n and the original function.

  6. Talk:Taylor's theorem - Wikipedia

    en.wikipedia.org/wiki/Talk:Taylor's_theorem

    For instance, formulas (1) (2) and (3) may give a reasonable inductive definition for (0); formula (4), already used in the paper for the proof of the mean value form of the remainder, also gives directly the integral form of the remainder, by a short plain application of the fundamental theorem of calculus, with no need of iterated integration ...

  7. 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.

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  9. Arctangent series - Wikipedia

    en.wikipedia.org/wiki/Arctangent_series

    The extremely slow convergence of the arctangent series for | | makes this formula impractical per se. Kerala-school mathematicians used additional correction terms to speed convergence. John Machin (1706) expressed ⁠ 1 4 π {\displaystyle {\tfrac {1}{4}}\pi } ⁠ as a sum of arctangents of smaller values, eventually resulting in a variety of ...