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NAG Toolbox: nag_specfun_bessel_k1_scaled_vector (s18cr)
Purpose
nag_specfun_bessel_k1_scaled_vector (s18cr) returns an array of values of the scaled modified Bessel function .
Syntax
Description
nag_specfun_bessel_k1_scaled_vector (s18cr) evaluates an approximation to , where is a modified Bessel function of the second kind for an array of arguments , for . The scaling factor removes most of the variation in .
The function uses the same Chebyshev expansions as
nag_specfun_bessel_k1_real_vector (s18ar), which returns an array of the unscaled values of
.
References
Abramowitz M and Stegun I A (1972) Handbook of Mathematical Functions (3rd Edition) Dover Publications
Parameters
Compulsory Input Parameters
- 1:
– double array
-
The argument of the function, for .
Constraint:
, for .
Optional Input Parameters
- 1:
– int64int32nag_int scalar
-
Default:
the dimension of the array
x.
, the number of points.
Constraint:
.
Output Parameters
- 1:
– double array
-
, the function values.
- 2:
– int64int32nag_int array
-
contains the error code for
, for
.
- No error.
On entry, | , is undefined. contains . |
- is too close to zero, as determined by the value of the safe-range parameter nag_machine_real_safe (x02am): there is a danger of causing overflow. contains the reciprocal of the safe-range parameter.
- 3:
– 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:
Cases prefixed with W are classified as warnings and
do not generate an error of type NAG:error_n. See nag_issue_warnings.
- W
-
On entry, at least one value of
x was invalid.
Check
ivalid for more information.
-
-
Constraint: .
-
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
Relative errors in the argument are attenuated when propagated into the function value. When the accuracy of the argument is essentially limited by the
machine precision, the accuracy of the function value will be similarly limited by at most a small multiple of the
machine precision.
Further Comments
None.
Example
This example reads values of
x from a file, evaluates the function at each value of
and prints the results.
Open in the MATLAB editor:
s18cr_example
function s18cr_example
fprintf('s18cr example results\n\n');
x = [0.4; 0.6; 1.4; 2.5; 10; 1000];
[f, ivalid, ifail] = s18cr(x);
fprintf(' x e^xK_1(x) ivalid\n');
for i=1:numel(x)
fprintf('%12.3e%12.3e%5d\n', x(i), f(i), ivalid(i));
end
s18cr example results
x e^xK_1(x) ivalid
4.000e-01 3.259e+00 0
6.000e-01 2.374e+00 0
1.400e+00 1.301e+00 0
2.500e+00 9.002e-01 0
1.000e+01 4.108e-01 0
1.000e+03 3.965e-02 0
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