The function may be called by the names: s19apc, nag_specfun_kelvin_bei_vector or nag_kelvin_bei_vector.
3Description
s19apc evaluates an approximation to the Kelvin function for an array of arguments , for .
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.
is too large for an accurate result to be returned. contains zero. The threshold value is the same as for NE_REAL_ARG_GT in s19abc
, as defined in the the Users' Note for your implementation.
5: – NagError *Input/Output
The NAG error argument (see Section 7 in the Introduction to the NAG Library CL Interface).
6Error Indicators and Warnings
NE_ALLOC_FAIL
Dynamic memory allocation failed.
See Section 3.1.2 in the Introduction to the NAG Library CL Interface for further information.
NE_BAD_PARAM
On entry, argument had an illegal value.
NE_INT
On entry, .
Constraint: .
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.
See Section 7.5 in the Introduction to the NAG Library CL Interface for further information.
NE_NO_LICENCE
Your licence key may have expired or may not have been installed correctly.
See Section 8 in the Introduction to the NAG Library CL Interface for further information.
NW_IVALID
On entry, at least one value of x was invalid.
Check ivalid for more information.
7Accuracy
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.
8Parallelism and Performance
s19apc is not threaded in any implementation.
9Further Comments
None.
10Example
This example reads values of x from a file, evaluates the function at each value of and prints the results.