NAG Library Function Document

nag_bessel_i0 (s18aec)

+− Contents

1 Purpose

2 Specification

3 Description

4 References

5 Arguments

6 Error Indicators and Warnings

7 Accuracy

8 Parallelism and Performance

9 Further Comments

+− 10 Example

10.1 Program Text

10.2 Program Data

10.3 Program Results

1 Purpose

nag_bessel_i0 (s18aec) returns the value of the modified Bessel function

I_{0} (x)

2 Specification

#include <nag.h>

#include <nags.h>

double

nag_bessel_i0 (double x, NagError *fail)

3 Description

nag_bessel_i0 (s18aec) evaluates an approximation to the modified Bessel function of the first kind

I_{0} (x)

Note:

I_{0} (- x) = I_{0} (x)

, so the approximation need only consider

x \geq 0

The function is based on three Chebyshev expansions:

For

0 < x \leq 4

I_{0} (x) = e^{x} \underset{r = 0}{\sum^{'}} a_{r} T_{r} (t),   where ​ t = 2 (\frac{x}{4}) - 1 .

For

4 < x \leq 12

I_{0} (x) = e^{x} \underset{r = 0}{\sum^{'}} b_{r} T_{r} (t),   where ​ t = \frac{x - 8}{4} .

For

x > 12

I_{0} (x) = \frac{e^{x}}{\sqrt{x}} \underset{r = 0}{\sum^{'}} c_{r} T_{r} (t),   where ​ t = 2 (\frac{12}{x}) - 1 .

For small

x

I_{0} (x) ≃ 1

. This approximation is used when

x

is sufficiently small for the result to be correct to machine precision.

For large

x

, the function must fail because of the danger of overflow in calculating

e^{x}

4 References

Abramowitz M and Stegun I A (1972) Handbook of Mathematical Functions (3rd Edition) Dover Publications

5 Arguments

1: x – doubleInput: On entry: the argument $x$ of the function.
2: fail – NagError *Input/Output: The NAG error argument (see Section 3.6 in the Essential Introduction).

6 Error Indicators and Warnings

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.
NE_REAL_ARG_GT: On entry, $x = ⟨value⟩$ .
Constraint: $|x| \leq ⟨value⟩$ .
$|x|$ is too large and the function returns the approximate value of $I_{0} (x)$ at the nearest valid argument.

7 Accuracy

Let

δ

and

ε

be the relative errors in the argument and result respectively.

δ

is somewhat larger than the machine precision (i.e., if

δ

is due to data errors etc.), then

ε

and

δ

are approximately related by:

ε ≃ |\frac{x I_{1} (x)}{I_{0} (x)}| δ .

Figure 1 shows the behaviour of the error amplification factor

|\frac{x I_{1} (x)}{I_{0} (x)}| .

Figure 1

However if

δ

is of the same order as machine precision, then rounding errors could make

ε

slightly larger than the above relation predicts.

For small

x

the amplification factor is approximately

\frac{x^{2}}{2}

, which implies strong attenuation of the error, but in general

ε

can never be less than the machine precision.

For large

x

ε ≃ x δ

and we have strong amplification of errors. However the function must fail for quite moderate values of

x

, because

I_{0} (x)

would overflow; hence in practice the loss of accuracy for large

x

is not excessive. Note that for large

x

the errors will be dominated by those of the standard function exp.

8 Parallelism and Performance

Not applicable.

9 Further Comments

None.

10 Example

This example reads values of the argument

x

from a file, evaluates the function at each value of

x

and prints the results.

NAG Library Function Documentnag_bessel_i0 (s18aec)