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A sequence of approximate grid solutions () of some problem that converges to a true solution with a corresponding sequence of regular grid spacings () that converge to 0 is said to have asymptotic order of convergence and asymptotic rate of convergence if
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 .
One can also show that if a sequence converges to its limit at a rate strictly greater than 1, [] does not have a better rate of convergence. (In practice, one rarely has e.g. quadratic convergence which would mean over 30 (respectively 100) correct decimal places after 5 (respectively 7) iterations (starting with 1 correct digit); usually no ...
Is there a fixed order of convergence for repeated roots with the secant method? For instance, with the Newton-Raphson method, R=2 (quadratic) for simple roots and R=1 for repeated roots. For the Secant Method, R=1.618.... for simple roots, but what about repeated/complex roots? Computer Guru 21:40, 26 May 2008 (UTC)
The rate of convergence is distinguished from the number of iterations required to reach a given accuracy. For example, the function f ( x ) = x 20 − 1 has a root at 1. Since f ′(1) ≠ 0 and f is smooth, it is known that any Newton iteration convergent to 1 will converge quadratically.
The convergence rate of the bisection method could possibly be improved by using a different solution estimate. The regula falsi method calculates the new solution estimate as the x-intercept of the line segment joining the endpoints of the function on the current bracketing interval. Essentially, the root is being approximated by replacing the ...
The Symmetric Rank 1 (SR1) method is a quasi-Newton method to update the second derivative (Hessian) based on the derivatives (gradients) calculated at two points. It is a generalization to the secant method for a multidimensional problem.
Replacing the derivative in Newton's method with a finite difference, we get the secant method. This method does not require the computation (nor the existence) of a derivative, but the price is slower convergence (the order of convergence is the golden ratio, approximately 1.62 [2]).