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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.
Linear multistep method — the other main class of methods for initial-value problems Backward differentiation formula — implicit methods of order 2 to 6; especially suitable for stiff equations; Numerov's method — fourth-order method for equations of the form ″ = (,)
The Davidon–Fletcher–Powell formula (or DFP; named after William C. Davidon, Roger Fletcher, and Michael J. D. Powell) finds the solution to the secant equation that is closest to the current estimate and satisfies the curvature condition. It was the first quasi-Newton method to generalize the secant method to a
Most of the section consists in explaining in full details how substituting variables for numerical values in the previously given formulas, and computing with these numerical values. This is not useful in Wikipedia, since one may suppose that people interested in the method know how to do such elementary operations (otherwise, they would ...
Brent's method is a combination of the bisection method, the secant method and inverse quadratic interpolation. At every iteration, Brent's method decides which method out of these three is likely to do best, and proceeds by doing a step according to that method. This gives a robust and fast method, which therefore enjoys considerable popularity.
Numerical methods for ordinary differential equations. Euler method; Runge–Kutta methods; Shooting method; Numerical methods for partial differential equations. Crank–Nicolson method; Finite element method; Method of lines; Dirichlet problem; Elliptic operator; System of differential equations
The method is a generalization of the secant method. Like the secant method, it is an iterative method which requires one evaluation of in each iteration and no derivatives of . The method can converge much faster though, with an order which approaches 2 provided that satisfies the regularity conditions described below.
The secant method increases the number of correct digits by "only" a factor of roughly 1.6 per step, but one can do twice as many steps of the secant method within a given time. 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 ...