NAG Library Function Document
nag_kelvin_bei (s19abc)
1 Purpose
nag_kelvin_bei (s19abc) returns a value for the Kelvin function .
2 Specification
#include <nag.h> |
#include <nags.h> |
double |
nag_kelvin_bei (double x,
NagError *fail) |
|
3 Description
nag_kelvin_bei (s19abc) evaluates an approximation to the Kelvin function .
Note: , so the approximation need only consider .
The function is based on several Chebyshev expansions:
For
,
For
,
where
,
,
and , , , and are expansions in the variable .
When is sufficiently close to zero, the result is computed as . If this result would underflow, the result returned is .
For large , there is a danger of the result being totally inaccurate, as the error amplification factor grows in an essentially exponential manner; therefore the function must fail.
4 References
Abramowitz M and Stegun I A (1972) Handbook of Mathematical Functions (3rd Edition) Dover Publications
5 Arguments
- 1:
– doubleInput
-
On entry: the argument of the function.
- 2:
– NagError *Input/Output
-
The NAG error argument (see
Section 3.6 in the Essential Introduction).
6 Error Indicators and Warnings
- NE_ALLOC_FAIL
-
Dynamic memory allocation failed.
See
Section 3.2.1.2 in the Essential Introduction for further information.
- NE_INTERNAL_ERROR
-
An internal error has occurred in this function. Check the function call and any array sizes. If the call is correct then please contact
NAG for assistance.
An unexpected error has been triggered by this function. Please contact
NAG.
See
Section 3.6.6 in the Essential Introduction for further information.
- NE_NO_LICENCE
-
Your licence key may have expired or may not have been installed correctly.
See
Section 3.6.5 in the Essential Introduction for further information.
- NE_REAL_ARG_GT
-
On entry, .
Constraint: .
is too large for an accurate result to be returned and the function returns zero.
7 Accuracy
Since the function is oscillatory, the absolute error rather than the relative error is important. Let
be the absolute error in the function, and
be the relative error in the argument. If
is somewhat larger than the
machine precision, then we have:
(provided
is within machine bounds).
For small the error amplification is insignificant and thus the absolute error is effectively bounded by the machine precision.
For medium and large , the error behaviour is oscillatory and its amplitude grows like . Therefore it is impossible to calculate the functions with any accuracy when . Note that this value of is much smaller than the minimum value of for which the function overflows.
8 Parallelism and Performance
Not applicable.
None.
10 Example
This example reads values of the argument from a file, evaluates the function at each value of and prints the results.
10.1 Program Text
Program Text (s19abce.c)
10.2 Program Data
Program Data (s19abce.d)
10.3 Program Results
Program Results (s19abce.r)