Gauss_Legen | R Documentation |
Convenience for computing the nodes x_k
and weights
w_k
of the Gauss–Legendre quadrature formula
in (a, b)
:
\int_a^b f(x) w(x)\,\mathrm{d}x\approx\sum_{k=1}^N w_k f(x_k).
.
Gauss_Legen_nodes(a = -1, b = 1, N = 40L)
Gauss_Legen_weights(a = -1, b = 1, N = 40L)
a , b |
scalars giving the interval |
N |
number of points used in the Gauss–Legendre quadrature. The
following choices are supported: |
For C^\infty
functions, Gauss–Legendre quadrature
can be very efficient. It is exact for polynomials up to degree
2N - 1
.
The nodes and weights up to N = 80
were retrieved from
NIST and have 10^{-21}
precision.
For N = 160
onwards, the nodes and weights were computed with the
gauss.quad
function from the
statmod
package (Smyth, 1998), and have 10^{-15}
precision.
A matrix of size c(N, 1)
with the nodes x_k
(Gauss_Legen_nodes
) or the corresponding weights w_k
(Gauss_Legen_weights
).
NIST Digital Library of Mathematical Functions. Release 1.0.20 of 2018-09-15. F. W. J. Olver, A. B. Olde Daalhuis, D. W. Lozier, B. I. Schneider, R. F. Boisvert, C. W. Clark, B. R. Miller, and B. V. Saunders, eds. https://dlmf.nist.gov/
Smyth, G. K. (1998). Numerical integration. In: Encyclopedia of Biostatistics, P. Armitage and T. Colton (eds.), Wiley, London, pp. 3088-3095.
## Integration of a smooth function in (1, 10)
# Weights and nodes for integrating
x_k <- Gauss_Legen_nodes(a = 1, b = 10, N = 40)
w_k <- Gauss_Legen_weights(a = 1, b = 10, N = 40)
# Check quadrature
f <- function(x) sin(x) * x^2 - log(x + 1)
integrate(f, lower = 1, upper = 10, rel.tol = 1e-12)
sum(w_k * f(x_k))
# Exact for polynomials up to degree 2 * N - 1
f <- function(x) (((x + 0.5) / 1e3)^5 - ((x - 0.5)/ 5)^4 +
((x - 0.25) / 10)^2 + 1)^20
sum(w_k * f(x_k))
integrate(f, lower = -1, upper = 1, rel.tol = 1e-12)
## Integration on (0, pi)
# Weights and nodes for integrating
th_k <- Gauss_Legen_nodes(a = 0, b = pi, N = 40)
w_k <- Gauss_Legen_weights(a = 0, b = pi, N = 40)
# Check quadrature
p <- 4
psi <- function(th) -sin(th / 2)
w <- function(th) sin(th)^(p - 2)
integrate(function(th) psi(th) * w(th), lower = 0, upper = pi,
rel.tol = 1e-12)
sum(w_k * psi(th_k) * w(th_k))
# Integral with Gegenbauer polynomial
k <- 3
C_k <- function(th) drop(Gegen_polyn(theta = th, k = k, p = p))
integrate(function(th) psi(th) * C_k(th) * w(th), lower = 0, upper = pi,
rel.tol = 1e-12)
th_k <- drop(Gauss_Legen_nodes(a = 0, b = pi, N = 80))
w_k <- drop(Gauss_Legen_weights(a = 0, b = pi, N = 80))
sum(w_k * psi(th_k) * C_k(th_k) * w(th_k))
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