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  2. Rate of convergence - Wikipedia

    en.wikipedia.org/wiki/Rate_of_convergence

    Non-asymptotic rates of convergence do not have the common, standard definitions that asymptotic rates of convergence have. Among formal techniques, Lyapunov theory is one of the most powerful and widely applied frameworks for characterizing and analyzing non-asymptotic convergence behavior.

  3. Steffensen's method - Wikipedia

    en.wikipedia.org/wiki/Steffensen's_method

    Since the secant method can carry out twice as many steps in the same time as Steffensen's method, [b] in practical use the secant method actually converges faster than Steffensen's method, when both algorithms succeed: The secant method achieves a factor of about (1.6) 2 ≈ 2.6 times as many digits for every two steps (two function ...

  4. Aitken's delta-squared process - Wikipedia

    en.wikipedia.org/wiki/Aitken's_delta-squared_process

    In numerical analysis, Aitken's delta-squared process or Aitken extrapolation is a series acceleration method used for accelerating the rate of convergence of a sequence. It is named after Alexander Aitken, who introduced this method in 1926. [1] It is most useful for accelerating the convergence of a sequence that is converging linearly.

  5. Secant method - Wikipedia

    en.wikipedia.org/wiki/Secant_method

    In numerical analysis, the secant method is a root-finding algorithm that uses a succession of roots of secant lines to better approximate a root of a function f. The secant method can be thought of as a finite-difference approximation of Newton's method , so it is considered a quasi-Newton method .

  6. Asymptotic theory (statistics) - Wikipedia

    en.wikipedia.org/wiki/Asymptotic_theory_(statistics)

    The rate of convergence must be chosen carefully, though, usually h ∝ n −1/5. In many cases, highly accurate results for finite samples can be obtained via numerical methods (i.e. computers); even in such cases, though, asymptotic analysis can be useful. This point was made by Small (2010, §1.4), as follows.

  7. Numerical methods for ordinary differential equations - Wikipedia

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

    The (forward) Euler method (4) and the backward Euler method (6) introduced above both have order 1, so they are consistent. Most methods being used in practice attain higher order. Consistency is a necessary condition for convergence [citation needed], but not sufficient; for a method to be convergent, it must be both consistent and zero-stable.

  8. Sidi's generalized secant method - Wikipedia

    en.wikipedia.org/wiki/Sidi's_generalized_secant...

    Sidi's generalized secant method is a root-finding algorithm, that is, a numerical method for solving equations of the form () =.The method was published by Avram Sidi. [1]The method is a generalization of the secant method.

  9. Series acceleration - Wikipedia

    en.wikipedia.org/wiki/Series_acceleration

    Two classical techniques for series acceleration are Euler's transformation of series [1] and Kummer's transformation of series. [2] A variety of much more rapidly convergent and special-case tools have been developed in the 20th century, including Richardson extrapolation, introduced by Lewis Fry Richardson in the early 20th century but also known and used by Katahiro Takebe in 1722; the ...