nag_1d_ratnl_interp (e01rac) produces, from a set of function values and corresponding abscissae, the coefficients of an interpolating rational function expressed in continued fraction form.
nag_1d_ratnl_interp (e01rac) produces the parameters of a rational function
which assumes prescribed values
at prescribed values
of the independent variable
, for
. More specifically, nag_1d_ratnl_interp (e01rac) determines the parameters
, for
and
, for
, in the continued fraction
where
and
such that
, for
. The value of
in
(1) is determined by the function; normally
. The values of
form a reordered subset of the values of
and their ordering is designed to ensure that a representation of the form
(1) is determined whenever one exists.
The subsequent evaluation of
(1) for given values of
can be carried out using
nag_1d_ratnl_eval (e01rbc).
The computational method employed in nag_1d_ratnl_interp (e01rac) is the modification of the Thacher–Tukey algorithm described in
Graves–Morris and Hopkins (1981).
Usually, it is not the accuracy of the coefficients produced by this function which is of prime interest, but rather the accuracy of the value of
that is produced by the associated function
nag_1d_ratnl_eval (e01rbc) when subsequently it evaluates the continued fraction
(1) for a given value of
. This final accuracy will depend mainly on the nature of the interpolation being performed. If interpolation of a ‘well-behaved smooth’ function is attempted (and provided the data adequately represents the function), high accuracy will normally ensue, but, if the function is not so ‘smooth’ or extrapolation is being attempted, high accuracy is much less likely. Indeed, in extreme cases, results can be highly inaccurate.
There is no built-in test of accuracy but several courses are open to you to prevent the production or the acceptance of inaccurate results.
1. |
If the origin of a variable is well outside the range of its data values, the origin should be shifted to correct this; and, if the new data values are still excessively large or small, scaling to make the largest value of the order of unity is recommended. Thus, normalization to the range to is ideal. This applies particularly to the independent variable; for the dependent variable, the removal of leading figures which are common to all the data values will usually suffice. |
2. |
To check the effect of rounding errors engendered in the functions themselves, nag_1d_ratnl_interp (e01rac) should be re-entered with interchanged with and with , . This will produce a completely different vector and a reordered vector , but any change in the value of subsequently produced by nag_1d_ratnl_eval (e01rbc) will be due solely to rounding error. |
3. |
Even if the data consist of calculated values of a formal mathematical function, it is only in exceptional circumstances that bounds for the interpolation error (the difference between the true value of the function underlying the data and the value which would be produced by the two functions if exact arithmetic were used) can be derived that are sufficiently precise to be of practical use. Consequently, you are recommended to rely on comparison checks: if extra data points are available, the calculation may be repeated with one or more data pairs added or exchanged, or alternatively, one of the original data pairs may be omitted. If the algorithms are being used for extrapolation, the calculations should be performed repeatedly with the nearest points until, hopefully, successive values of for the given agree to the required accuracy. |
nag_1d_ratnl_interp (e01rac) is not threaded in any implementation.
The time taken by nag_1d_ratnl_interp (e01rac) is approximately proportional to .
The continued fraction
(1) when expanded produces a rational function in
, the degree of whose numerator is either equal to or exceeds by unity that of the denominator. Only if this rather special form of interpolatory rational function is needed explicitly, would this function be used without subsequent entry (or entries) to
nag_1d_ratnl_eval (e01rbc).