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  2. Muller's method - Wikipedia

    en.wikipedia.org/wiki/Muller's_method

    Muller's method is a recursive method that generates a new approximation of a root ξ of f at each iteration using the three prior iterations. Starting with three initial values x 0, x −1 and x −2, the first iteration calculates an approximation x 1 using those three, the second iteration calculates an approximation x 2 using x 1, x 0 and x −1, the third iteration calculates an ...

  3. Laguerre's method - Wikipedia

    en.wikipedia.org/wiki/Laguerre's_method

    If x is a simple root of the polynomial , then Laguerre's method converges cubically whenever the initial guess, , is close enough to the root . On the other hand, when x 1 {\displaystyle \ x_{1}\ } is a multiple root convergence is merely linear, with the penalty of calculating values for the polynomial and its first and second derivatives at ...

  4. Digital root - Wikipedia

    en.wikipedia.org/wiki/Digital_root

    The additive persistence counts how many times we must sum its digits to arrive at its digital root. For example, the additive persistence of 2718 in base 10 is 2: first we find that 2 + 7 + 1 + 8 = 18, then that 1 + 8 = 9. There is no limit to the additive persistence of a number in a number base .

  5. Root-finding algorithm - Wikipedia

    en.wikipedia.org/wiki/Root-finding_algorithm

    In numerical analysis, a root-finding algorithm is an algorithm for finding zeros, also called "roots", of continuous functions. A zero of a function f is a number x such that f ( x ) = 0 . As, generally, the zeros of a function cannot be computed exactly nor expressed in closed form , root-finding algorithms provide approximations to zeros.

  6. Bisection method - Wikipedia

    en.wikipedia.org/wiki/Bisection_method

    A few steps of the bisection method applied over the starting range [a 1;b 1].The bigger red dot is the root of the function. In mathematics, the bisection method is a root-finding method that applies to any continuous function for which one knows two values with opposite signs.

  7. Polynomial root-finding algorithms - Wikipedia

    en.wikipedia.org/wiki/Polynomial_root-finding...

    Finding roots in a specific region of the complex plane, typically the real roots or the real roots in a given interval (for example, when roots represents a physical quantity, only the real positive ones are interesting). For finding one root, Newton's method and other general iterative methods work generally well.

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  9. Newton's method - Wikipedia

    en.wikipedia.org/wiki/Newton's_method

    If the multiplicity m of the root is finite then g(x) = ⁠ f(x) / f ′ (x) ⁠ will have a root at the same location with multiplicity 1. Applying Newton's method to find the root of g(x) recovers quadratic convergence in many cases although it generally involves the second derivative of f(x).