Shanks transformation


In numerical analysis, the Shanks transformation is a non-linear series acceleration method to increase the rate of convergence of a sequence. This method is named after Daniel Shanks, who rediscovered this sequence transformation in 1955. It was first derived and published by R. Schmidt in 1941.

Formulation

For a sequence the series
is to be determined. First, the partial sum is defined as:
and forms a new sequence. Provided the series converges, will also approach the limit as
The Shanks transformation of the sequence is the new sequence defined by
where this sequence often converges more rapidly than the sequence
Further speed-up may be obtained by repeated use of the Shanks transformation, by computing etc.
Note that the non-linear transformation as used in the Shanks transformation is essentially the same as used in Aitken's delta-squared process so that as with Aitken's method, the right-most expression in 's definition is more numerically stable than the expression to its left. Both Aitken's method and the Shanks transformation operate on a sequence, but the sequence the Shanks transformation operates on is usually thought of as being a sequence of partial sums, although any sequence may be viewed as a sequence of partial sums.

Example

As an example, consider the slowly convergent series
which has the exact sum π ≈ 3.14159265. The partial sum has only one digit accuracy, while six-figure accuracy requires summing about 400,000 terms.
In the table below, the partial sums, the Shanks transformation on them, as well as the repeated Shanks transformations and are given for up to 12. The figure to the right shows the absolute error for the partial sums and Shanks transformation results, clearly showing the improved accuracy and convergence rate.
04.00000000
12.666666673.16666667
23.466666673.133333333.14210526
32.895238103.145238103.141450223.14159936
43.339682543.139682543.141643323.14159086
52.976046183.142712843.141571293.14159323
63.283738483.140881343.141602843.14159244
73.017071823.142071823.141587323.14159274
83.252365933.141254823.141595663.14159261
93.041839623.141839623.141590863.14159267
103.232315813.141406723.141593773.14159264
113.058402773.141736103.141591923.14159266
123.218402773.141479693.141593143.14159265

The Shanks transformation already has two-digit accuracy, while the original partial sums only establish the same accuracy at Remarkably, has six digits accuracy, obtained from repeated Shank transformations applied to the first seven terms As said before, only obtains 6-digit accuracy after about summing 400,000 terms.

Motivation

The Shanks transformation is motivated by the observation that — for larger — the partial sum quite often behaves approximately as
with so that the sequence converges transiently to the series result for
So for and the respective partial sums are:
These three equations contain three unknowns: and Solving for gives
In the case that the denominator is equal to zero: then for all

Generalized Shanks transformation

The generalized kth-order Shanks transformation is given as the ratio of the determinants:
with It is the solution of a model for the convergence behaviour of the partial sums with distinct transients:
This model for the convergence behaviour contains unknowns. By evaluating the above equation at the elements and solving for the above expression for the kth-order Shanks transformation is obtained. The first-order generalized Shanks transformation is equal to the ordinary Shanks transformation:
The generalized Shanks transformation is closely related to Padé approximants and Padé tables.