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NAG Toolbox: nag_specfun_kelvin_kei (s19ad)
Purpose
nag_specfun_kelvin_kei (s19ad) returns a value for the Kelvin function via the function name.
Syntax
Description
nag_specfun_kelvin_kei (s19ad) evaluates an approximation to the Kelvin function .
Note: for the function is undefined, so we need only consider .
The function is based on several Chebyshev expansions:
For
,
where
,
and
are expansions in the variable
;
For
,
where
is an expansion in the variable
;
For
,
where
, and
and
are expansions in the variable
.
For , the function is undefined, and hence the function fails and returns zero.
When
is sufficiently close to zero, the result is computed as
and when
is even closer to zero simply as
For large
,
is asymptotically given by
and this becomes so small that it cannot be computed without underflow and the function fails.
References
Abramowitz M and Stegun I A (1972) Handbook of Mathematical Functions (3rd Edition) Dover Publications
Parameters
Compulsory Input Parameters
- 1:
– double scalar
-
The argument of the function.
Constraint:
.
Optional Input Parameters
None.
Output Parameters
- 1:
– double scalar
The result of the function.
- 2:
– int64int32nag_int scalar
unless the function detects an error (see
Error Indicators and Warnings).
Error Indicators and Warnings
Errors or warnings detected by the function:
-
-
On entry,
x is too large: the result underflows. On soft failure, the function returns zero.
-
-
On entry, : the function is undefined. On soft failure the function returns zero.
-
An unexpected error has been triggered by this routine. Please
contact
NAG.
-
Your licence key may have expired or may not have been installed correctly.
-
Dynamic memory allocation failed.
Accuracy
Let
be the absolute error in the result, and
be the relative error in the argument. If
is somewhat larger than the machine representation error, then we have:
For small
, errors are attenuated by the function and hence are limited by the
machine precision.
For medium and large , the error behaviour, like the function itself, is oscillatory and hence only absolute accuracy of the function can be maintained. For this range of , the amplitude of the absolute error decays like , which implies a strong attenuation of error. Eventually, , which is asymptotically given by ,becomes so small that it cannot be calculated without causing underflow and therefore the function returns zero. Note that for large , the errors are dominated by those of the standard function exp.
Further Comments
Underflow may occur for a few values of close to the zeros of , below the limit which causes a failure with .
Example
This example reads values of the argument from a file, evaluates the function at each value of and prints the results.
Open in the MATLAB editor:
s19ad_example
function s19ad_example
fprintf('s19ad example results\n\n');
x = [0.1 1 2.5 5 10 15];
n = size(x,2);
result = x;
for j=1:n
[result(j), ifail] = s19ad(x(j));
end
disp(' x kei(x)');
fprintf('%12.3e%12.3e\n',[x; result]);
s19ad example results
x kei(x)
1.000e-01 -7.769e-01
1.000e+00 -4.950e-01
2.500e+00 -1.107e-01
5.000e+00 1.119e-02
1.000e+01 -3.075e-04
1.500e+01 7.963e-06
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