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  2. Gauss–Legendre method - Wikipedia

    en.wikipedia.org/wiki/GaussLegendre_method

    The Gauss-Legendre methods are implicit, so in general they cannot be applied exactly. Instead one makes an educated guess of , and then uses Newton's method to converge arbitrarily close to the true solution. Below is a Matlab function which implements the Gauss-Legendre method of order four.

  3. Gauss–Legendre quadrature - Wikipedia

    en.wikipedia.org/wiki/GaussLegendre_quadrature

    Carl Friedrich Gauss was the first to derive the GaussLegendre quadrature rule, doing so by a calculation with continued fractions in 1814. [4] He calculated the nodes and weights to 16 digits up to order n=7 by hand. Carl Gustav Jacob Jacobi discovered the connection between the quadrature rule and the orthogonal family of Legendre polynomials.

  4. Collocation method - Wikipedia

    en.wikipedia.org/wiki/Collocation_method

    In mathematics, a collocation method is a method for the numerical solution of ordinary differential equations, partial differential equations and integral equations.The idea is to choose a finite-dimensional space of candidate solutions (usually polynomials up to a certain degree) and a number of points in the domain (called collocation points), and to select that solution which satisfies the ...

  5. Gaussian quadrature - Wikipedia

    en.wikipedia.org/wiki/Gaussian_quadrature

    This exact rule is known as the GaussLegendre quadrature rule. The quadrature rule will only be an accurate approximation to the integral above if f (x) is well-approximated by a polynomial of degree 2n − 1 or less on [−1, 1]. The GaussLegendre quadrature rule is not typically used for integrable functions with endpoint singularities ...

  6. Least squares - Wikipedia

    en.wikipedia.org/wiki/Least_squares

    The result of fitting a set of data points with a quadratic function Conic fitting a set of points using least-squares approximation. In regression analysis, least squares is a parameter estimation method based on minimizing the sum of the squares of the residuals (a residual being the difference between an observed value and the fitted value provided by a model) made in the results of each ...

  7. Runge–Kutta methods - Wikipedia

    en.wikipedia.org/wiki/Runge–Kutta_methods

    The GaussLegendre method with s stages has order 2s, so its stability function is the Padé approximant with m = n = s. It follows that the method is A-stable. [34] This shows that A-stable Runge–Kutta can have arbitrarily high order. In contrast, the order of A-stable linear multistep methods cannot exceed two. [35]

  8. Gauss–Legendre algorithm - Wikipedia

    en.wikipedia.org/wiki/GaussLegendre_algorithm

    The GaussLegendre algorithm is an algorithm to compute the digits of π. It is notable for being rapidly convergent, with only 25 iterations producing 45 million correct digits of π . However, it has some drawbacks (for example, it is computer memory -intensive) and therefore all record-breaking calculations for many years have used other ...

  9. Hypergeometric function - Wikipedia

    en.wikipedia.org/wiki/Hypergeometric_function

    The equation has two linearly independent solutions. At each of the three singular points 0, 1, ∞, there are usually two special solutions of the form x s times a holomorphic function of x, where s is one of the two roots of the indicial equation and x is a local variable vanishing at a regular singular point. This gives 3 × 2 = 6 special ...