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for
Background
We will now study the iterated interpolation
methods of Aitken and Neville. Alexander
Craig Aitken (1895-1967) was one of New
Zealand's prominent mathematicians. Eric
Harold Neville (1889-1961) was a mathematics professor at
University of Reading, Berkshire, U.K. The algorithms we
seek are remarkably similar:
To assist with understanding these algorithms
we must study iterated polynomial interpolation.
Existence and Uniqueness
Theorem (Polynomial Existence and
Uniqueness). Given a
set n+1 of
distinct nodes
(where
whenever
). There
is a unique polynomial of degree
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that passes through the n+1 points
, i.e.
for
.
Proof Aitken and Neville Methods
Iterated Interpolation
We now discuss some heuristic methods of
constructing interpolation polynomials recursively. The
methods of Aitken
and Neville
are examples of how iteration is used to construct a sequence of
polynomial approximating of increasing order.
Definition (Selected
Interpolation). Given the
function
that
is to be approximated, and the set of nodes:
.
For any subset of k nodes
the polynomial that agrees with f[x] at
the points
is denoted
.
The polynomial
of
degree k-1 agrees
with f[x] at
these knots
for
.
Exploration Aitken and Neville Methods Scroll down to this exploration.
Successive Interpolation
Consider polynomial interpolation based on
equally spaced nodes
If all
nodes
are used then a loose claim is that the interpolating
polynomial
will
have order of approximation
. Usually
there is an abundance of nodes (think 50, 100,...) and the degree of
the interpolating polynomial is small (think 2, 3, 4, 5 or
6). Polynomials of smaller degree
are
of practical value:
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The accuracy of interpolation increases with the degree of the polynomial. Since the polynomial constructions are unique the following theorem applies for the Lagrange Polynomial, Newton polynomial and the polynomials constructed with both Aitken's method and Neville's method too.
Theorem (Remainder
Term). Assume that
and
for
are
distinct values. Then
, where
is a polynomial that can be used to approximate
, for
example, the Lagrange polynomial
, and
we write
.
The Lagrange polynomial goes through the
points
, i.e.
for
.
The remainder term
has the form
, for
some value
that lies in the interval
.
Proof See Lagrange Polynomials
The Main Results
In practice the subset
of
nodes
is not chosen at random over the larger set
. Instead,
the nodes are clustered near a specific value
of x at which
the function f[x] is
to be approximated by
. Often
times it is a sequential subset of nodes
with
. It
is desired to have the ability to use permutations of the list
when constructing the interpolating polynomial. It is also
useful to use a sequence of polynomial approximations with increasing
degree. The following theorem gives the recursive step for
generating such a sequence.
Theorem (Recursive Polynomial
Construction). Given the
function
that
is to be approximated, and the set of
distinct nodes
.
For any pair of nodes
, suppose
that we have constructed the polynomials:
which
agrees with
at the nodes
,
which
agrees with
at the nodes
.
Then
is
formed by making a combination of the above two polynomials
,
or
,
and it agrees with
at all the nodes
.
Remark. Other equivalent ways
to write
are
,
or
.
Proof Aitken and Neville Methods Scroll down to this theorem.
Example 1. Given
the three distinct nodes
and
the function
.
Use recursion to construct the polynomial
.
The Interpolation Tableau
The methods of Aitken and Neville use
recursive polynomial construction. The following tables
indicate how the two constructions are made. The extra
column at the right (the values
) have
been included to assist with performing hand
calculations. This extra column is not necessary for hand
computations. It will be revealed that the diagonals are
equivalent.
Neville's
Method. In
each new elements is computed using the element in the {same row,
preceding column} and {preceding row, preceding column}.
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Aitken's
Method. In
each new elements is computed using the element in the {same row,
preceding column} and {top row, preceding column}.
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Exploration Aitken and Neville Methods Scroll down to this exploration.
Recursive Programming
Aitken's and Neville's polynomials can be
programmed recursively with the following subroutines.
Computer Programs Aitken's and Neville's Interpolation Methods
Mathematica Subroutine (Neville Polynomials).
![[Graphics:Images/NevilleAlgorithmMod_gr_199.gif]](nevillealgorithm/NevilleAlgorithmMod/Images/NevilleAlgorithmMod_gr_199.gif)
Mathematica Subroutine (Aitken Polynomials).
Example
2. Given
and
the nodes
compute the entries in Aitken's tableau and Neville's tableau for
evaluating
at
Show the details for the computations.
Example
3. Given
and
the nodes
compute the entries in Aitken's tableau and Neville's tableau for
evaluating
at
Use the recursive subroutines.
Example
4. Given
and
the nodes
compute the entries in Aitken's tableau and Neville's tableau for
evaluating
at
Use the recursive subroutines.
The Rearranged Nodes
Aitken's and Neville's methods agree on the
diagonal, and one usually tests for convergence of these
values. If
is
to be approximated at
then
one improvement that can be made is to rearrange the nodes so that
they are "closer to
"
in the sense that is explained in the following
result.
Theorem(Rearrangement of
Nodes). Given the
function
, and
the set of
distinct nodes
. If
is
to be approximated at the point
, then let
be the rearrangement of
such that
is an increasing sequence. Then the diagonal
terms
will converge to
faster
than any other rearrangement of the nodes.
Example
5. Given
and
the nodes
compute the entries in Aitken's tableau and Neville's tableau for
evaluating
at
Use the rearrangement of the nodes
and the recursive subroutines.
The Improved Interpolation
Tableau
The tables for Aitken's and Neville's methods
can be stored in a two-dimensional array and do not need long
subscript lists as shown in the following tables.
Neville's
Method. In
each new elements is computed using the element in the {same row,
preceding column} and {preceding row, preceding column}.
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Aitken's
Method. In
each new elements is computed using the element in the {same row,
preceding column} and {top row, preceding column}.
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Computer Programs Aitken's and Neville's Interpolation Methods
Mathematica Subroutine (Neville Interpolation).
![[Graphics:Images/NevilleAlgorithmMod_gr_493.gif]](nevillealgorithm/NevilleAlgorithmMod/Images/NevilleAlgorithmMod_gr_493.gif)
Mathematica Subroutine (Aitken Interpolation).
Example
6. Given
and
the nodes
compute the entries in Aitken's tableau and Neville's tableau for
evaluating
at
Use the improved interpolation subroutines.
The Improved Subroutines using
Matrices
The subroutines for Aitken's and Neville's
methods can be modified to use matrices, this is the final
improvement.
Algorithm (Neville
Interpolation). Given the nodes
the Neville interpolation at
is
where we compute:
Computer Programs Neville Interpolation
Mathematica Subroutine (Neville Interpolation).
![[Graphics:Images/NevilleAlgorithmMod_gr_509.gif]](nevillealgorithm/NevilleAlgorithmMod/Images/NevilleAlgorithmMod_gr_509.gif)
Algorithm (Aitken
Interpolation). Given the nodes
the Aitken interpolation at
is
where we compute:
Computer Programs Aitken Interpolation
Mathematica Subroutine (Aitken Interpolation).
Example
7. Given
and
the nodes
compute the entries in Aitken's tableau and Neville's tableau for
evaluating
at
Use the improved interpolation subroutines with matrices.
Research Experience for Undergraduates
Aitken's and Neville's Methods Internet hyperlinks to web sites and a bibliography of articles.
Download this Mathematica Notebook Aitken's and Neville's Methods
(c) John H. Mathews 2005