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One obvious way of approximating the value of
is by
, where p is an interpolating polynomial to f at
various points, usually but not necessarily, in [a,b]. We write the
Lagrange form with interpolation points
, as
f(x)=p(x)+e(x), where
in the
usual notation, and e(x) is the pointwise error.
Integrating this, we obtain

The first part of this gives the quadrature formula, and is simply a
weighted sum of the values of the function at the interpolation or
quadrature points, xi; the quadrature weights are
. The second part gives the quadrature error, which is

Recall that, when f(x) is any polynomial of degree n or less,
it is represented exactly by p(x), and so the quadrature error
vanishes in this case. Taking successively f(x) as
we find

These are of course exactly the equations we used previously in the
method of undetermined coefficients. Can we always solve them? They are, in
displayed form,

or in matrix form
![\begin{displaymath}
\left[ \begin{array}
{cccc}
1 & 1 & \cdots & 1\\ x_0 & x_1 &...
...2}\\ \vdots
\\ \frac{b^{n+1}-a^{n+1}}{n+1}\end{array} \right]. \end{displaymath}](img196.gif)
We know that the Vandermonde determinant is nonzero if the interpolating
points are distinct, so we can always solve the problem in this case.
With the coefficients determined in this way, let
. Then

This shows that the formula derived in this way is exact for all
polynomials of degree n or less.
Next: Quadrature Error
Up: M243 Lecture Notes
Previous: Convergence Rate of Secant
John Gilbert
5/8/1998