Gauss–Jacobi quadrature
In numerical analysis, Gauss–Jacobi quadrature (named after Carl Friedrich Gauss and Carl Gustav Jacob Jacobi) is a method of numerical quadrature based on Gaussian quadrature. Gauss–Jacobi quadrature can be used to approximate integrals of the form
where ƒ is a smooth function on Template:Math and Template:Math. The interval Template:Math can be replaced by any other interval by a linear transformation. Thus, Gauss–Jacobi quadrature can be used to approximate integrals with singularities at the end points. Gauss–Legendre quadrature is a special case of Gauss–Jacobi quadrature with Template:Math. Similarly, the Chebyshev–Gauss quadrature of the first (second) kind arises when one takes Template:Math. More generally, the special case Template:Math turns Jacobi polynomials into Gegenbauer polynomials, in which case the technique is sometimes called Gauss–Gegenbauer quadrature.
Gauss–Jacobi quadrature uses Template:Math as the weight function. The corresponding sequence of orthogonal polynomials consist of Jacobi polynomials. Thus, the Gauss–Jacobi quadrature rule on Template:Math points has the form
where Template:Math are the roots of the Jacobi polynomial of degree Template:Math. The weights Template:Math are given by the formula
where Γ denotes the Gamma function and Template:Math the Jacobi polynomial of degree n.
The error term (difference between approximate and accurate value) is:
where .
References
External links
- Jacobi rule - free software (Matlab, C++, and Fortran) to evaluate integrals by Gauss–Jacobi quadrature rules.
- Gegenbauer rule - free software (Matlab, C++, and Fortran) for Gauss–Gegenbauer quadrature